Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

PubMed Central

Attique, Muhammad; Gilanie, Ghulam; Hafeez-Ullah; Mehmood, Malik S.; Naweed, Muhammad S.; Ikram, Masroor; Kamran, Javed A.; Vitkin, Alex

2012-01-01

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described. PMID:22479421

An improved driving waveform reference grayscale of electrophoretic displays

NASA Astrophysics Data System (ADS)

Wang, Li; Yi, Zichuan; Peng, Bao; Zhou, Guofu

2015-10-01

Driving waveform is an important component for gray scale display on the electrophoretic display (EPD). In the traditional driving waveform, a white reference gray scale is formed before writing a new image. However, the reflectance value can not reach agreement in each gray scale transformation. In this paper, a new driving waveform, which has a short waiting time after the formation of reference gray scale, is proposed to improve the consistency of reference gray scale. Firstly, the property of the particles in the microcapsule is analyzed and the change of the EPD reflectance after the white reference gray scale formation is studied. Secondly, the reflectance change curve is fitted by using polynomial and the duration of the waiting time is determined. Thirdly, a set of the new driving waveform is designed by using the rule of DC balance and some real E-ink commercial EPDs are used to test the performance. Experimental results show that the effect of the new driving waveform has a better performance than traditional waveforms.

Image matching for digital close-range stereo photogrammetry based on constraints of Delaunay triangulated network and epipolar-line

NASA Astrophysics Data System (ADS)

Zhang, K.; Sheng, Y. H.; Li, Y. Q.; Han, B.; Liang, Ch.; Sha, W.

2006-10-01

In the field of digital photogrammetry and computer vision, the determination of conjugate points in a stereo image pair, referred to as "image matching," is the critical step to realize automatic surveying and recognition. Traditional matching methods encounter some problems in the digital close-range stereo photogrammetry, because the change of gray-scale or texture is not obvious in the close-range stereo images. The main shortcoming of traditional matching methods is that geometric information of matching points is not fully used, which will lead to wrong matching results in regions with poor texture. To fully use the geometry and gray-scale information, a new stereo image matching algorithm is proposed in this paper considering the characteristics of digital close-range photogrammetry. Compared with the traditional matching method, the new algorithm has three improvements on image matching. Firstly, shape factor, fuzzy maths and gray-scale projection are introduced into the design of synthetical matching measure. Secondly, the topology connecting relations of matching points in Delaunay triangulated network and epipolar-line are used to decide matching order and narrow the searching scope of conjugate point of the matching point. Lastly, the theory of parameter adjustment with constraint is introduced into least square image matching to carry out subpixel level matching under epipolar-line constraint. The new algorithm is applied to actual stereo images of a building taken by digital close-range photogrammetric system. The experimental result shows that the algorithm has a higher matching speed and matching accuracy than pyramid image matching algorithm based on gray-scale correlation.

Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

NASA Astrophysics Data System (ADS)

Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

2018-02-01

Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

Real-time gray-scale photolithography for fabrication of continuous microstructure

NASA Astrophysics Data System (ADS)

Peng, Qinjun; Guo, Yongkang; Liu, Shijie; Cui, Zheng

2002-10-01

A novel real-time gray-scale photolithography technique for the fabrication of continuous microstructures that uses a LCD panel as a real-time gray-scale mask is presented. The principle of design of the technique is explained, and computer simulation results based on partially coherent imaging theory are given for the patterning of a microlens array and a zigzag grating. An experiment is set up, and a microlens array and a zigzag grating on panchromatic silver halide sensitized gelatin with trypsinase etching are obtained.

Graphical user interface to optimize image contrast parameters used in object segmentation - biomed 2009.

PubMed

Anderson, Jeffrey R; Barrett, Steven F

2009-01-01

Image segmentation is the process of isolating distinct objects within an image. Computer algorithms have been developed to aid in the process of object segmentation, but a completely autonomous segmentation algorithm has yet to be developed [1]. This is because computers do not have the capability to understand images and recognize complex objects within the image. However, computer segmentation methods [2], requiring user input, have been developed to quickly segment objects in serial sectioned images, such as magnetic resonance images (MRI) and confocal laser scanning microscope (CLSM) images. In these cases, the segmentation process becomes a powerful tool in visualizing the 3D nature of an object. The user input is an important part of improving the performance of many segmentation methods. A double threshold segmentation method has been investigated [3] to separate objects in gray scaled images, where the gray level of the object is among the gray levels of the background. In order to best determine the threshold values for this segmentation method the image must be manipulated for optimal contrast. The same is true of other segmentation and edge detection methods as well. Typically, the better the image contrast, the better the segmentation results. This paper describes a graphical user interface (GUI) that allows the user to easily change image contrast parameters that will optimize the performance of subsequent object segmentation. This approach makes use of the fact that the human brain is extremely effective in object recognition and understanding. The GUI provides the user with the ability to define the gray scale range of the object of interest. These lower and upper bounds of this range are used in a histogram stretching process to improve image contrast. Also, the user can interactively modify the gamma correction factor that provides a non-linear distribution of gray scale values, while observing the corresponding changes to the image. This interactive approach gives the user the power to make optimal choices in the contrast enhancement parameters.

Least-squares model-based halftoning

NASA Astrophysics Data System (ADS)

Pappas, Thrasyvoulos N.; Neuhoff, David L.

1992-08-01

A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach permits the halftoner to be tuned to the individual printer, whose characteristics may vary considerably from those of other printers, for example, write-black vs. write-white laser printers.

QR code based noise-free optical encryption and decryption of a gray scale image

NASA Astrophysics Data System (ADS)

Jiao, Shuming; Zou, Wenbin; Li, Xia

2017-03-01

In optical encryption systems, speckle noise is one major challenge in obtaining high quality decrypted images. This problem can be addressed by employing a QR code based noise-free scheme. Previous works have been conducted for optically encrypting a few characters or a short expression employing QR codes. This paper proposes a practical scheme for optically encrypting and decrypting a gray-scale image based on QR codes for the first time. The proposed scheme is compatible with common QR code generators and readers. Numerical simulation results reveal the proposed method can encrypt and decrypt an input image correctly.

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

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

Bradley, J.N.; Brislawn, C.M.; Hopper, T.

1993-05-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI`s Integrated Automated Fingerprint Identification System.

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

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

Bradley, J.N.; Brislawn, C.M.; Hopper, T.

1993-01-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI's Integrated Automated Fingerprint Identification System.

A survey of quality measures for gray-scale image compression

NASA Technical Reports Server (NTRS)

Eskicioglu, Ahmet M.; Fisher, Paul S.

1993-01-01

Although a variety of techniques are available today for gray-scale image compression, a complete evaluation of these techniques cannot be made as there is no single reliable objective criterion for measuring the error in compressed images. The traditional subjective criteria are burdensome, and usually inaccurate or inconsistent. On the other hand, being the most common objective criterion, the mean square error (MSE) does not have a good correlation with the viewer's response. It is now understood that in order to have a reliable quality measure, a representative model of the complex human visual system is required. In this paper, we survey and give a classification of the criteria for the evaluation of monochrome image quality.

Effect of color visualization and display hardware on the visual assessment of pseudocolor medical images

PubMed Central

Zabala-Travers, Silvina; Choi, Mina; Cheng, Wei-Chung

2015-01-01

Purpose: Even though the use of color in the interpretation of medical images has increased significantly in recent years, the ad hoc manner in which color is handled and the lack of standard approaches have been associated with suboptimal and inconsistent diagnostic decisions with a negative impact on patient treatment and prognosis. The purpose of this study is to determine if the choice of color scale and display device hardware affects the visual assessment of patterns that have the characteristics of functional medical images. Methods: Perfusion magnetic resonance imaging (MRI) was the basis for designing and performing experiments. Synthetic images resembling brain dynamic-contrast enhanced MRI consisting of scaled mixtures of white, lumpy, and clustered backgrounds were used to assess the performance of a rainbow (“jet”), a heated black-body (“hot”), and a gray (“gray”) color scale with display devices of different quality on the detection of small changes in color intensity. The authors used a two-alternative, forced-choice design where readers were presented with 600 pairs of images. Each pair consisted of two images of the same pattern flipped along the vertical axis with a small difference in intensity. Readers were asked to select the image with the highest intensity. Three differences in intensity were tested on four display devices: a medical-grade three-million-pixel display, a consumer-grade monitor, a tablet device, and a phone. Results: The estimates of percent correct show that jet outperformed hot and gray in the high and low range of the color scales for all devices with a maximum difference in performance of 18% (confidence intervals: 6%, 30%). Performance with hot was different for high and low intensity, comparable to jet for the high range, and worse than gray for lower intensity values. Similar performance was seen between devices using jet and hot, while gray performance was better for handheld devices. Time of performance was shorter with jet. Conclusions: Our findings demonstrate that the choice of color scale and display hardware affects the visual comparative analysis of pseudocolor images. Follow-up studies in clinical settings are being considered to confirm the results with patient images. PMID:26127048

Example-Based Image Colorization Using Locality Consistent Sparse Representation.

PubMed

Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

2017-11-01

Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

Generalized image contrast enhancement technique based on Heinemann contrast discrimination model

NASA Astrophysics Data System (ADS)

Liu, Hong; Nodine, Calvin F.

1994-03-01

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

A psychophysical comparison of two methods for adaptive histogram equalization.

PubMed

Zimmerman, J B; Cousins, S B; Hartzell, K M; Frisse, M E; Kahn, M G

1989-05-01

Adaptive histogram equalization (AHE) is a method for adaptive contrast enhancement of digital images. It is an automatic, reproducible method for the simultaneous viewing of contrast within a digital image with a large dynamic range. Recent experiments have shown that in specific cases, there is no significant difference in the ability of AHE and linear intensity windowing to display gray-scale contrast. More recently, a variant of AHE which limits the allowed contrast enhancement of the image has been proposed. This contrast-limited adaptive histogram equalization (CLAHE) produces images in which the noise content of an image is not excessively enhanced, but in which sufficient contrast is provided for the visualization of structures within the image. Images processed with CLAHE have a more natural appearance and facilitate the comparison of different areas of an image. However, the reduced contrast enhancement of CLAHE may hinder the ability of an observer to detect the presence of some significant gray-scale contrast. In this report, a psychophysical observer experiment was performed to determine if there is a significant difference in the ability of AHE and CLAHE to depict gray-scale contrast. Observers were presented with computed tomography (CT) images of the chest processed with AHE and CLAHE. Subtle artificial lesions were introduced into some images. The observers were asked to rate their confidence regarding the presence of the lesions; this rating-scale data was analyzed using receiver operating characteristic (ROC) curve techniques. These ROC curves were compared for significant differences in the observers' performances. In this report, no difference was found in the abilities of AHE and CLAHE to depict contrast information.

Autographic theme extraction

USGS Publications Warehouse

Edson, D.; Colvocoresses, Alden P.

1973-01-01

Remote-sensor images, including aerial and space photographs, are generally recorded on film, where the differences in density create the image of the scene. With panchromatic and multiband systems the density differences are recorded in shades of gray. On color or color infrared film, with the emulsion containing dyes sensitive to different wavelengths, a color image is created by a combination of color densities. The colors, however, can be separated by filtering or other techniques, and the color image reduced to monochromatic images in which each of the separated bands is recorded as a function of the gray scale.

An improved quantum watermarking scheme using small-scale quantum circuits and color scrambling

NASA Astrophysics Data System (ADS)

Li, Panchi; Zhao, Ya; Xiao, Hong; Cao, Maojun

2017-05-01

In order to solve the problem of embedding the watermark into the quantum color image, in this paper, an improved scheme of using small-scale quantum circuits and color scrambling is proposed. Both color carrier image and color watermark image are represented using novel enhanced quantum representation. The image sizes for carrier and watermark are assumed to be 2^{n+1}× 2^{n+2} and 2n× 2n, respectively. At first, the color of pixels in watermark image is scrambled using the controlled rotation gates, and then, the scrambled watermark with 2^n× 2^n image size and 24-qubit gray scale is expanded to an image with 2^{n+1}× 2^{n+2} image size and 3-qubit gray scale. Finally, the expanded watermark image is embedded into the carrier image by the controlled-NOT gates. The extraction of watermark is the reverse process of embedding it into carrier image, which is achieved by applying operations in the reverse order. Simulation-based experimental results show that the proposed scheme is superior to other similar algorithms in terms of three items, visual quality, scrambling effect of watermark image, and noise resistibility.

Cellular automata rule characterization and classification using texture descriptors

NASA Astrophysics Data System (ADS)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

Mapping gray-scale image to 3D surface scanning data by ray tracing

NASA Astrophysics Data System (ADS)

Li, Peng; Jones, Peter R. M.

1997-03-01

The extraction and location of feature points from range imaging is an important but difficult task in machine vision based measurement systems. There exist some feature points which are not able to be detected from pure geometric characteristics, particularly in those measurement tasks related to the human body. The Loughborough Anthropometric Shadow Scanner (LASS) is a whole body surface scanner based on structured light technique. Certain applications of LASS require accurate location of anthropometric landmarks from the scanned data. This is sometimes impossible from existing raw data because some landmarks do not appear in the scanned data. Identification of these landmarks has to resort to surface texture of the scanned object. Modifications to LASS were made to allow gray-scale images to be captured before or after the object was scanned. Two-dimensional gray-scale image must be mapped to the scanned data to acquire the 3D coordinates of a landmark. The method to map 2D images to the scanned data is based on the colinearity conditions and ray-tracing method. If the camera center and image coordinates are known, the corresponding object point must lie on a ray starting from the camera center and connecting to the image coordinate. By intersecting the ray with the scanned surface of the object, the 3D coordinates of a point can be solved. Experimentation has demonstrated the feasibility of the method.

Multi-sensor image registration based on algebraic projective invariants.

PubMed

Li, Bin; Wang, Wei; Ye, Hao

2013-04-22

A new automatic feature-based registration algorithm is presented for multi-sensor images with projective deformation. Contours are firstly extracted from both reference and sensed images as basic features in the proposed method. Since it is difficult to design a projective-invariant descriptor from the contour information directly, a new feature named Five Sequential Corners (FSC) is constructed based on the corners detected from the extracted contours. By introducing algebraic projective invariants, we design a descriptor for each FSC that is ensured to be robust against projective deformation. Further, no gray scale related information is required in calculating the descriptor, thus it is also robust against the gray scale discrepancy between the multi-sensor image pairs. Experimental results utilizing real image pairs are presented to show the merits of the proposed registration method.

Image smoothing and enhancement via min/max curvature flow

NASA Astrophysics Data System (ADS)

Malladi, Ravikanth; Sethian, James A.

1996-03-01

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

Computer-aided mass detection in mammography: False positive reduction via gray-scale invariant ranklet texture features

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

Masotti, Matteo; Lanconelli, Nico; Campanini, Renato

In this work, gray-scale invariant ranklet texture features are proposed for false positive reduction (FPR) in computer-aided detection (CAD) of breast masses. Two main considerations are at the basis of this proposal. First, false positive (FP) marks surviving our previous CAD system seem to be characterized by specific texture properties that can be used to discriminate them from masses. Second, our previous CAD system achieves invariance to linear/nonlinear monotonic gray-scale transformations by encoding regions of interest into ranklet images through the ranklet transform, an image transformation similar to the wavelet transform, yet dealing with pixels' ranks rather than with theirmore » gray-scale values. Therefore, the new FPR approach proposed herein defines a set of texture features which are calculated directly from the ranklet images corresponding to the regions of interest surviving our previous CAD system, hence, ranklet texture features; then, a support vector machine (SVM) classifier is used for discrimination. As a result of this approach, texture-based information is used to discriminate FP marks surviving our previous CAD system; at the same time, invariance to linear/nonlinear monotonic gray-scale transformations of the new CAD system is guaranteed, as ranklet texture features are calculated from ranklet images that have this property themselves by construction. To emphasize the gray-scale invariance of both the previous and new CAD systems, training and testing are carried out without any in-between parameters' adjustment on mammograms having different gray-scale dynamics; in particular, training is carried out on analog digitized mammograms taken from a publicly available digital database, whereas testing is performed on full-field digital mammograms taken from an in-house database. Free-response receiver operating characteristic (FROC) curve analysis of the two CAD systems demonstrates that the new approach achieves a higher reduction of FP marks when compared to the previous one. Specifically, at 60%, 65%, and 70% per-mammogram sensitivity, the new CAD system achieves 0.50, 0.68, and 0.92 FP marks per mammogram, whereas at 70%, 75%, and 80% per-case sensitivity it achieves 0.37, 0.48, and 0.71 FP marks per mammogram, respectively. Conversely, at the same sensitivities, the previous CAD system reached 0.71, 0.87, and 1.15 FP marks per mammogram, and 0.57, 0.73, and 0.92 FPs per mammogram. Also, statistical significance of the difference between the two per-mammogram and per-case FROC curves is demonstrated by the p-value<0.001 returned by jackknife FROC analysis performed on the two CAD systems.« less

Doppler color imaging. Principles and instrumentation.

PubMed

Kremkau, F W

1992-01-01

DCI acquires Doppler-shifted echoes from a cross-section of tissue scanned by an ultrasound beam. These echoes are then presented in color and superimposed on the gray-scale anatomic image of non-Doppler-shifted echoes received during the scan. The flow echoes are assigned colors according to the color map chosen. Usually red, yellow, or white indicates positive Doppler shifts (approaching flow) and blue, cyan, or white indicates negative shifts (receding flow). Green is added to indicate variance (disturbed or turbulent flow). Several pulses (the number is called the ensemble length) are needed to generate a color scan line. Linear, convex, phased, and annular arrays are used to acquire the gray-scale and color-flow information. Doppler color-flow instruments are pulsed-Doppler instruments and are subject to the same limitations, such as Doppler angle dependence and aliasing, as other Doppler instruments. Color controls include gain, TGC, map selection, variance on/off, persistence, ensemble length, color/gray priority. Nyquist limit (PRF), baseline shift, wall filter, and color window angle, location, and size. Doppler color-flow instruments generally have output intensities intermediate between those of gray-scale imaging and pulsed-Doppler duplex instruments. Although there is no known risk with the use of color-flow instruments, prudent practice dictates that they be used for medical indications and with the minimum exposure time and instrument output required to obtain the needed diagnostic information.

Overview of the physics of US.

PubMed

Goldstein, A

1993-05-01

In ultrasonography (US), high-frequency sound waves are transmitted through the body by a transducer. When a transmitted ultrasound pulse encounters a tissue target, some of its energy is deflected back to the transducer. The time of flight of this ultrasound echo is used to calculate depth of the target in the transducer beam. The pulse-echo parameters used in the formation of images include echo amplitude, target spatial position, and frequency shift between the transmitted pulse and the received echo. The first two are displayed in gray-scale images and all three in color flow images. In gray-scale US, echo amplitude is encoded into shades of gray, with the lighter shades representing higher amplitude echoes. In color flow US, velocity of moving blood is usually presented in blue for motion toward the transducer and in red for motion away from it. A Doppler spectrum depicts changing blood velocity as a function of time. US has become more clinically valuable due to its ability to demonstrate soft-tissue structures, real-time imaging capability, relative safety, portability, and cost-effectiveness.

Spinal Cord Gray Matter Atrophy in Amyotrophic Lateral Sclerosis.

PubMed

Paquin, M-Ê; El Mendili, M M; Gros, C; Dupont, S M; Cohen-Adad, J; Pradat, P-F

2018-01-01

There is an emerging need for biomarkers to better categorize clinical phenotypes and predict progression in amyotrophic lateral sclerosis. This study aimed to quantify cervical spinal gray matter atrophy in amyotrophic lateral sclerosis and investigate its association with clinical disability at baseline and after 1 year. Twenty-nine patients with amyotrophic lateral sclerosis and 22 healthy controls were scanned with 3T MR imaging. Standard functional scale was recorded at the time of MR imaging and after 1 year. MR imaging data were processed automatically to measure the spinal cord, gray matter, and white matter cross-sectional areas. A statistical analysis assessed the difference in cross-sectional areas between patients with amyotrophic lateral sclerosis and controls, correlations between spinal cord and gray matter atrophy to clinical disability at baseline and at 1 year, and prediction of clinical disability at 1 year. Gray matter atrophy was more sensitive to discriminate patients with amyotrophic lateral sclerosis from controls ( P = .004) compared with spinal cord atrophy ( P = .02). Gray matter and spinal cord cross-sectional areas showed good correlations with clinical scores at baseline ( R = 0.56 for gray matter and R = 0.55 for spinal cord; P < .01). Prediction at 1 year with clinical scores ( R 2 = 0.54) was improved when including a combination of gray matter and white matter cross-sectional areas ( R 2 = 0.74). Although improvements over spinal cord cross-sectional areas were modest, this study suggests the potential use of gray matter cross-sectional areas as an MR imaging structural biomarker to monitor the evolution of amyotrophic lateral sclerosis. © 2018 by American Journal of Neuroradiology.

Prostate: techniques, results, and potential applications of color Doppler US scanning.

PubMed

Rifkin, M D; Sudakoff, G S; Alexander, A A

1993-02-01

Color Doppler ultrasound (US) scanning and conventional endorectal gray-scale US of the prostate were performed in 619 patients. Pathologic correlation was available in all cases after US-guided transrectal biopsy. There were 132 cancers in 121 men, 13 foci of atypia in 10 men, 33 foci of inflammation in 31 men, and 469 benign lesions in 457 men. Two hundred seventy patients with abnormal areas of flow identified at color Doppler scanning also underwent spectral waveform analysis of the area of potential concern. No statistical difference in the mean resistive indexes was identified in any patient (P = .25; Scheffe F test, analysis of variance). All malignant lesions had abnormalities demonstrated at gray-scale US and/or focal or diffuse abnormal flow demonstrated at color Doppler scanning. Of the 132 cancers, 123 (93%) had corresponding gray-scale abnormalities and 114 (86%) demonstrated abnormal flow at color Doppler imaging. Nine of the 132 cancers (7%) had no obviously identifiable abnormality at gray-scale scanning but had distinctly abnormal flow at color Doppler scanning. Abnormal findings at color scanning without abnormal findings at gray-scale scanning occurred in eight of the 33 cases of inflammatory foci (24%) and in 24 of the 469 (5%) benign lesions.

SU-E-I-100: Heterogeneity Studying for Primary and Lymphoma Tumors by Using Multi-Scale Image Texture Analysis with PET-CT Images

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

Li, Dengwang; Wang, Qinfen; Li, H

Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contourmore » structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity differences between primary and lymphoma tumor by multi-scale image texture analysis. This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)« less

Wavelet/scalar quantization compression standard for fingerprint images

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

Brislawn, C.M.

1996-06-12

US Federal Bureau of Investigation (FBI) has recently formulated a national standard for digitization and compression of gray-scale fingerprint images. Fingerprints are scanned at a spatial resolution of 500 dots per inch, with 8 bits of gray-scale resolution. The compression algorithm for the resulting digital images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition (wavelet/scalar quantization method). The FBI standard produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. The compression standard specifies a class ofmore » potential encoders and a universal decoder with sufficient generality to reconstruct compressed images produced by any compliant encoder, allowing flexibility for future improvements in encoder technology. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.« less

A New Quantum Gray-Scale Image Encoding Scheme

NASA Astrophysics Data System (ADS)

Naseri, Mosayeb; Abdolmaleky, Mona; Parandin, Fariborz; Fatahi, Negin; Farouk, Ahmed; Nazari, Reza

2018-02-01

In this paper, a new quantum images encoding scheme is proposed. The proposed scheme mainly consists of four different encoding algorithms. The idea behind of the scheme is a binary key generated randomly for each pixel of the original image. Afterwards, the employed encoding algorithm is selected corresponding to the qubit pair of the generated randomized binary key. The security analysis of the proposed scheme proved its enhancement through both randomization of the generated binary image key and altering the gray-scale value of the image pixels using the qubits of randomized binary key. The simulation of the proposed scheme assures that the final encoded image could not be recognized visually. Moreover, the histogram diagram of encoded image is flatter than the original one. The Shannon entropies of the final encoded images are significantly higher than the original one, which indicates that the attacker can not gain any information about the encoded images. Supported by Kermanshah Branch, Islamic Azad University, Kermanshah, IRAN

Opto-acoustic breast imaging with co-registered ultrasound

NASA Astrophysics Data System (ADS)

Zalev, Jason; Clingman, Bryan; Herzog, Don; Miller, Tom; Stavros, A. Thomas; Oraevsky, Alexander; Kist, Kenneth; Dornbluth, N. Carol; Otto, Pamela

2014-03-01

We present results from a recent study involving the ImagioTM breast imaging system, which produces fused real-time two-dimensional color-coded opto-acoustic (OA) images that are co-registered and temporally inter- leaved with real-time gray scale ultrasound using a specialized duplex handheld probe. The use of dual optical wavelengths provides functional blood map images of breast tissue and tumors displayed with high contrast based on total hemoglobin and oxygen saturation of the blood. This provides functional diagnostic information pertaining to tumor metabolism. OA also shows morphologic information about tumor neo-vascularity that is complementary to the morphological information obtained with conventional gray scale ultrasound. This fusion technology conveniently enables real-time analysis of the functional opto-acoustic features of lesions detected by readers familiar with anatomical gray scale ultrasound. We demonstrate co-registered opto-acoustic and ultrasonic images of malignant and benign tumors from a recent clinical study that provide new insight into the function of tumors in-vivo. Results from the Feasibility Study show preliminary evidence that the technology may have the capability to improve characterization of benign and malignant breast masses over conventional diagnostic breast ultrasound alone and to improve overall accuracy of breast mass diagnosis. In particular, OA improved speci city over that of conventional diagnostic ultrasound, which could potentially reduce the number of negative biopsies performed without missing cancers.

New MR imaging assessment tool to define brain abnormalities in very preterm infants at term.

PubMed

Kidokoro, H; Neil, J J; Inder, T E

2013-01-01

WM injury is the dominant form of injury in preterm infants. However, other cerebral structures, including the deep gray matter and the cerebellum, can also be affected by injury and/or impaired growth. Current MR imaging injury assessment scales are subjective and are challenging to apply. Thus, we developed a new assessment tool and applied it to MR imaging studies obtained from very preterm infants at term age. MR imaging scans from 97 very preterm infants (< 30 weeks' gestation) and 22 healthy term-born infants were evaluated retrospectively. The severity of brain injury (defined by signal abnormalities) and impaired brain growth (defined with biometrics) was scored in the WM, cortical gray matter, deep gray matter, and cerebellum. Perinatal variables for clinical risks were collected. In very preterm infants, brain injury was observed in the WM (n=23), deep GM (n=5), and cerebellum (n=23). Combining measures of injury and impaired growth showed moderate to severe abnormalities most commonly in the WM (n=38) and cerebellum (n=32) but still notable in the cortical gray matter (n=16) and deep gray matter (n=11). WM signal abnormalities were associated with a reduced deep gray matter area but not with cerebellar abnormality. Intraventricular and/or parenchymal hemorrhage was associated with cerebellar signal abnormality and volume reduction. Multiple clinical risk factors, including prolonged intubation, prolonged parenteral nutrition, postnatal corticosteroid use, and postnatal sepsis, were associated with increased global abnormality on MR imaging. Very preterm infants demonstrate a high prevalence of injury and growth impairment in both the WM and gray matter. This MR imaging scoring system provides a more comprehensive and objective classification of the nature and extent of abnormalities than existing measures.

Digital shaded relief image of a carbonate platform (northern Great Bahama Bank): Scenery seen and unseen

NASA Astrophysics Data System (ADS)

Boss, Stephen K.

1996-11-01

A mosaic image of the northern Great Bahama Bank was created from separate gray-scale Landsat images using photo-editing and image analysis software that is commercially available for desktop computers. Measurements of pixel gray levels (relative scale from 0 to 255 referred to as digital number, DN) on the mosaic image were compared to bank-top bathymetry (determined from a network of single-channel, high-resolution seismic profiles), bottom type (coarse sand, sandy mud, barren rock, or reef determined from seismic profiles and diver observations), and vegetative cover (presence and/or absence and relative density of the marine angiosperm Thalassia testudinum determined from diver observations). Results of these analyses indicate that bank-top bathymetry is a primary control on observed pixel DN, bottom type is a secondary control on pixel DN, and vegetative cover is a tertiary influence on pixel DN. Consequently, processing of the gray-scale Landsat mosaic with a directional gradient edge-detection filter generated a physiographic shaded relief image resembling bank-top bathymetric patterns related to submerged physiographic features across the platform. The visibility of submerged karst landforms, Pleistocene eolianite ridges, islands, and possible paleo-drainage patterns created during sea-level lowstands is significantly enhanced on processed images relative to the original mosaic. Bank-margin ooid shoals, platform interior sand bodies, reef edifices, and bidirectional sand waves are features resulting from Holocene carbonate deposition that are also more clearly visible on the new physiographic images. Combined with observational data (single-channel, high-resolution seismic profiles, bottom observations by SCUBA divers, sediment and rock cores) across the northern Great Bahama Bank, these physiographic images facilitate comprehension of areal relations among antecedent platform topography, physical processes, and ensuing depositional patterns during sea-level rise.

Gray scale enhances display readability of bitmapped documents

NASA Astrophysics Data System (ADS)

Ostberg, Olov; Disfors, Dennis; Feng, Yingduo

1994-05-01

Bitmapped images of high resolution, say 300 dpi rastered documents, stored in the memory of a PC are at best only borderline readable on the PC's display screen (say a 72 dpi VGA monitor). Results from a series of exploratory psycho-physical experiments, using the Adobe PhotoshopR software, show that the readability can be significantly enhanced by making use of the monitor's capability to display shades of gray. It is suggested that such a gray scale adaptation module should be bundled to all software products for electronic document management. In fact, fax modems are already available in which this principle is employed, hereby making it possible to read incoming fax documents directly on the screen.

Dark and Bright Terrains of Pluto

NASA Image and Video Library

2015-07-10

These circular maps shows the distribution of Pluto's dark and bright terrains as revealed by NASA's New Horizons mission prior to July 4, 2015. Each map is an azimuthal equidistant projection centered on the north pole, with latitude and longitude indicated. Both a gray-scale and color version are shown. The gray-scale version is based on 7 days of panchromatic imaging from the Long Range Reconnaissance Imager (LORRI), whereas the color version uses the gray-scale base and incorporates lower-resolution color information from the Multi-spectral Visible Imaging Camera (MVIC), part of the Ralph instrument. The color version is also shown in a simple cylindrical projection in PIA19700. In these maps, the polar bright terrain is surrounded by a somewhat darker polar fringe, one whose latitudinal position varies strongly with longitude. Especially striking are the much darker regions along the equator. A broad dark swath ("the whale") stretches along the equator from approximately 20 to 160 degrees of longitude. Several dark patches appear in a regular sequence centered near 345 degrees of longitude. A spectacular bright region occupies Pluto's mid-latitudes near 180 degrees of longitude, and stretches southward over the equator. New Horizons' closest approach to Pluto will occur near this longitude, which will permit high-resolution visible imaging and compositional mapping of these various regions. http://photojournal.jpl.nasa.gov/catalog/PIA19706

Effect of resin infiltration on white spot lesions after debonding orthodontic brackets.

PubMed

Hammad, Shaza M; El Banna, Mai; El Zayat, Inas; Mohsen, Mohamed Abdel

2012-02-01

To evaluate the effect of application of a resin infiltration material on masking the white spot lesions (WSLs) after bracket removal. 18 patients participated in this study and were divided into two groups of nine patients each; by a visual score based on the extent of demineralization, according to the classification of the WSLs. Group 1: Visible WSLs without surface disruption and Group 2: WSLs showed a roughened surface but not requiring restoration. Three successive photographs were taken for every patient; immediately after bracket removal, 1 week after oral hygiene measures and after Icon material application. The JPEG images were imported into image analysis software (Image J version 1.33u for Windows XP, US National Institutes of Health) which presented the images into histograms of gray scale from (0 to 255). Initial and final images were compared for percentage of WSLs masking area. For both groups, a statistically significant difference at P<0.05 was obtained as follows; for WSLs in Group 1, the means at gray scale for the initial and the final photographs were 126.091 +/- 13.452 and 221.268 +/- 9.350 respectively and they revealed significance by Wilcoxon's signed rank test = 0.038, P<0.05. For WSLs in Group 2, the means at gray scale for the initial and the final photographs were 95.585 +/- 20.973 and 155.612 +/- 31.203 respectively and they revealed significance by Wilcoxon's signed rank test = 0.029, P<0.05.

Clinical feasibility study of combined opto-acoustic and ultrasonic imaging modality providing coregistered functional and anatomical maps of breast tumors

NASA Astrophysics Data System (ADS)

Zalev, Jason; Clingman, Bryan; Smith, Remie J.; Herzog, Don; Miller, Tom; Stavros, A. Thomas; Ermilov, Sergey; Conjusteau, André; Tsyboulski, Dmitri; Oraevsky, Alexander A.; Kist, Kenneth; Dornbluth, N. C.; Otto, Pamela

2013-03-01

We report on findings from the clinical feasibility study of the ImagioTM. Breast Imaging System, which acquires two-dimensional opto-acoustic (OA) images co-registered with conventional ultrasound using a specialized duplex hand-held probe. Dual-wavelength opto-acoustic technology is used to generate parametric maps based upon total hemoglobin and its oxygen saturation in breast tissues. This may provide functional diagnostic information pertaining to tumor metabolism and microvasculature, which is complementary to morphological information obtained with conventional gray-scale ultrasound. We present co-registered opto-acoustic and ultrasonic images of malignant and benign tumors from a recent clinical feasibility study. The clinical results illustrate that the technology may have the capability to improve the efficacy of breast tumor diagnosis. In doing so, it may have the potential to reduce biopsies and to characterize cancers that were not seen well with conventional gray-scale ultrasound alone.

Multi-image encryption based on synchronization of chaotic lasers and iris authentication

NASA Astrophysics Data System (ADS)

Banerjee, Santo; Mukhopadhyay, Sumona; Rondoni, Lamberto

2012-07-01

A new technique of transmitting encrypted combinations of gray scaled and chromatic images using chaotic lasers derived from Maxwell-Bloch's equations has been proposed. This novel scheme utilizes the general method of solution of a set of linear equations to transmit similar sized heterogeneous images which are a combination of monochrome and chromatic images. The chaos encrypted gray scaled images are concatenated along the three color planes resulting in color images. These are then transmitted over a secure channel along with a cover image which is an iris scan. The entire cryptology is augmented with an iris-based authentication scheme. The secret messages are retrieved once the authentication is successful. The objective of our work is briefly outlined as (a) the biometric information is the iris which is encrypted before transmission, (b) the iris is used for personal identification and verifying for message integrity, (c) the information is transmitted securely which are colored images resulting from a combination of gray images, (d) each of the images transmitted are encrypted through chaos based cryptography, (e) these encrypted multiple images are then coupled with the iris through linear combination of images before being communicated over the network. The several layers of encryption together with the ergodicity and randomness of chaos render enough confusion and diffusion properties which guarantee a fool-proof approach in achieving secure communication as demonstrated by exhaustive statistical methods. The result is vital from the perspective of opening a fundamental new dimension in multiplexing and simultaneous transmission of several monochromatic and chromatic images along with biometry based authentication and cryptography.

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Tate, Lanetra C.; Wright, M. Clara; Caraccio, Anne

2013-01-01

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

Automatic Brain Portion Segmentation From Magnetic Resonance Images of Head Scans Using Gray Scale Transformation and Morphological Operations.

PubMed

Somasundaram, Karuppanagounder; Ezhilarasan, Kamalanathan

2015-01-01

To develop an automatic skull stripping method for magnetic resonance imaging (MRI) of human head scans. The proposed method is based on gray scale transformation and morphological operations. The proposed method has been tested with 20 volumes of normal T1-weighted images taken from Internet Brain Segmentation Repository. Experimental results show that the proposed method gives better results than the popular skull stripping methods Brain Extraction Tool and Brain Surface Extractor. The average value of Jaccard and Dice coefficients are 0.93 and 0.962 respectively. In this article, we have proposed a novel skull stripping method using intensity transformation and morphological operations. This is a low computational complexity method but gives competitive or better results than that of the popular skull stripping methods Brain Surface Extractor and Brain Extraction Tool.

Binarization of Gray-Scaled Digital Images Via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Klinko, Steve; Voska, Ned (Technical Monitor)

2002-01-01

A new fast-computational technique based on fuzzy entropy measure has been developed to find an optimal binary image threshold. In this method, the image pixel membership functions are dependent on the threshold value and reflect the distribution of pixel values in two classes; thus, this technique minimizes the classification error. This new method is compared with two of the best-known threshold selection techniques, Otsu and Huang-Wang. The performance of the proposed method supersedes the performance of Huang- Wang and Otsu methods when the image consists of textured background and poor printing quality. The three methods perform well but yield different binarization approaches if the background and foreground of the image have well-separated gray-level ranges.

Binarization of Gray-Scaled Digital Images Via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Klinko, Steve; Voska, Ned (Technical Monitor)

2002-01-01

A new fast-computational technique based on fuzzy entropy measure has been developed to find an optimal binary image threshold. In this method, the image pixel membership functions are dependent on the threshold value and reflect the distribution of pixel values in two classes; thus, this technique minimizes the classification error. This new method is compared with two of the best-known threshold selection techniques, Otsu and Huang-Wang. The performance of the proposed method supersedes the performance of Huang-Wang and Otsu methods when the image consists of textured background and poor printing quality. The three methods perform well but yield different binarization approaches if the background and foreground of the image have well-separated gray-level ranges.

CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

NASA Astrophysics Data System (ADS)

Gong, Qian; Qu, Zhiyi; Hao, Kun

2017-07-01

Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

A Large Scale (N=400) Investigation of Gray Matter Differences in Schizophrenia Using Optimized Voxel-based Morphometry

PubMed Central

Meda, Shashwath A.; Giuliani, Nicole R.; Calhoun, Vince D.; Jagannathan, Kanchana; Schretlen, David J.; Pulver, Anne; Cascella, Nicola; Keshavan, Matcheri; Kates, Wendy; Buchanan, Robert; Sharma, Tonmoy; Pearlson, Godfrey D.

2008-01-01

Background Many studies have employed voxel-based morphometry (VBM) of MRI images as an automated method of investigating cortical gray matter differences in schizophrenia. However, results from these studies vary widely, likely due to different methodological or statistical approaches. Objective To use VBM to investigate gray matter differences in schizophrenia in a sample significantly larger than any published to date, and to increase statistical power sufficiently to reveal differences missed in smaller analyses. Methods Magnetic resonance whole brain images were acquired from four geographic sites, all using the same model 1.5T scanner and software version, and combined to form a sample of 200 patients with both first episode and chronic schizophrenia and 200 healthy controls, matched for age, gender and scanner location. Gray matter concentration was assessed and compared using optimized VBM. Results Compared to the healthy controls, schizophrenia patients showed significantly less gray matter concentration in multiple cortical and subcortical regions, some previously unreported. Overall, we found lower concentrations of gray matter in regions identified in prior studies, most of which reported only subsets of the affected areas. Conclusions Gray matter differences in schizophrenia are most comprehensively elucidated using a large, diverse and representative sample. PMID:18378428

[A voxel-based morphometric analysis of brain gray matter in online game addicts].

PubMed

Weng, Chuan-bo; Qian, Ruo-bing; Fu, Xian-ming; Lin, Bin; Ji, Xue-bing; Niu, Chao-shi; Wang, Ye-han

2012-12-04

To explore the possible brain mechanism of online game addiction (OGA) in terms of brain morphology through voxel-based morphometric (VBM) analysis. Seventeen subjects with OGA and 17 age- and gender-matched healthy controls (HC group) were recruited from Department of Psychology at our hospital during February-December 2011. The internet addiction scale (IAS) was used to measure the degree of OGA tendency. Magnetic resonance imaging (MRI) scans were performed to acquire 3-dimensional T1-weighted images. And FSL 4.1 software was employed to confirm regional gray matter volume changes. For the regions where OGA subjects showed significantly different gray matter volumes from the controls, the gray matter volumes of these areas were extracted, averaged and regressed against the scores of IAS. The OGA group had lower gray matter volume in left orbitofrontal cortex (OFC), left medial prefrontal cortex (mPFC), bilateral insula (INS), left posterior cingulate cortex (PCC) and left supplementary motor area (SMA). Gray matter volumes of left OFC and bilateral INS showed a negative correlation with the scores of IAS (r = -0.65, r = -0.78, P < 0.05). Gray matter volume changes are present in online game addicts and they may be correlated with the occurrence and maintenance of OGA.

Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter.

PubMed

Dupont, Sara M; De Leener, Benjamin; Taso, Manuel; Le Troter, Arnaud; Nadeau, Sylvie; Stikov, Nikola; Callot, Virginie; Cohen-Adad, Julien

2017-04-15

The spinal cord white and gray matter can be affected by various pathologies such as multiple sclerosis, amyotrophic lateral sclerosis or trauma. Being able to precisely segment the white and gray matter could help with MR image analysis and hence be useful in further understanding these pathologies, and helping with diagnosis/prognosis and drug development. Up to date, white/gray matter segmentation has mostly been done manually, which is time consuming, induces a bias related to the rater and prevents large-scale multi-center studies. Recently, few methods have been proposed to automatically segment the spinal cord white and gray matter. However, no single method exists that combines the following criteria: (i) fully automatic, (ii) works on various MRI contrasts, (iii) robust towards pathology and (iv) freely available and open source. In this study we propose a multi-atlas based method for the segmentation of the spinal cord white and gray matter that addresses the previous limitations. Moreover, to study the spinal cord morphology, atlas-based approaches are increasingly used. These approaches rely on the registration of a spinal cord template to an MR image, however the registration usually doesn't take into account the spinal cord internal structure and thus lacks accuracy. In this study, we propose a new template registration framework that integrates the white and gray matter segmentation to account for the specific gray matter shape of each individual subject. Validation of segmentation was performed in 24 healthy subjects using T 2 * -weighted images, in 8 healthy subjects using diffusion weighted images (exhibiting inverted white-to-gray matter contrast compared to T 2 *-weighted), and in 5 patients with spinal cord injury. The template registration was validated in 24 subjects using T 2 *-weighted data. Results of automatic segmentation on T 2 *-weighted images was in close correspondence with the manual segmentation (Dice coefficient in the white/gray matter of 0.91/0.71 respectively). Similarly, good results were obtained in data with inverted contrast (diffusion-weighted image) and in patients. When compared to the classical template registration framework, the proposed framework that accounts for gray matter shape significantly improved the quality of the registration (comparing Dice coefficient in gray matter: p=9.5×10 -6 ). While further validation is needed to show the benefits of the new registration framework in large cohorts and in a variety of patients, this study provides a fully-integrated tool for quantitative assessment of white/gray matter morphometry and template-based analysis. All the proposed methods are implemented in the Spinal Cord Toolbox (SCT), an open-source software for processing spinal cord multi-parametric MRI data. Copyright © 2017 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Liu, Hong; Nodine, Calvin F.

1996-07-01

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

Recall of patterns using binary and gray-scale autoassociative morphological memories

NASA Astrophysics Data System (ADS)

Sussner, Peter

2005-08-01

Morphological associative memories (MAM's) belong to a class of artificial neural networks that perform the operations erosion or dilation of mathematical morphology at each node. Therefore we speak of morphological neural networks. Alternatively, the total input effect on a morphological neuron can be expressed in terms of lattice induced matrix operations in the mathematical theory of minimax algebra. Neural models of associative memories are usually concerned with the storage and the retrieval of binary or bipolar patterns. Thus far, the emphasis in research on morphological associative memory systems has been on binary models, although a number of notable features of autoassociative morphological memories (AMM's) such as optimal absolute storage capacity and one-step convergence have been shown to hold in the general, gray-scale setting. In previous papers, we gained valuable insight into the storage and recall phases of AMM's by analyzing their fixed points and basins of attraction. We have shown in particular that the fixed points of binary AMM's correspond to the lattice polynomials in the original patterns. This paper extends these results in the following ways. In the first place, we provide an exact characterization of the fixed points of gray-scale AMM's in terms of combinations of the original patterns. Secondly, we present an exact expression for the fixed point attractor that represents the output of either a binary or a gray-scale AMM upon presentation of a certain input. The results of this paper are confirmed in several experiments using binary patterns and gray-scale images.

Comparison between a new computer program and the reference software for gray-scale median analysis of atherosclerotic carotid plaques.

PubMed

Casella, Ivan Benaduce; Fukushima, Rodrigo Bono; Marques, Anita Battistini de Azevedo; Cury, Marcus Vinícius Martins; Presti, Calógero

2015-03-01

To compare a new dedicated software program and Adobe Photoshop for gray-scale median (GSM) analysis of B-mode images of carotid plaques. A series of 42 carotid plaques generating ≥50% diameter stenosis was evaluated by a single observer. The best segment for visualization of internal carotid artery plaque was identified on a single longitudinal view and images were recorded in JPEG format. Plaque analysis was performed by both programs. After normalization of image intensity (blood = 0, adventitial layer = 190), histograms were obtained after manual delineation of plaque. Results were compared with nonparametric Wilcoxon signed rank test and Kendall tau-b correlation analysis. GSM ranged from 00 to 100 with Adobe Photoshop and from 00 to 96 with IMTPC, with a high grade of similarity between image pairs, and a highly significant correlation (R = 0.94, p < .0001). IMTPC software appears suitable for the GSM analysis of carotid plaques. © 2014 Wiley Periodicals, Inc.

Watermarking scheme based on singular value decomposition and homomorphic transform

NASA Astrophysics Data System (ADS)

Verma, Deval; Aggarwal, A. K.; Agarwal, Himanshu

2017-10-01

A semi-blind watermarking scheme based on singular-value-decomposition (SVD) and homomorphic transform is pro-posed. This scheme ensures the digital security of an eight bit gray scale image by inserting an invisible eight bit gray scale wa-termark into it. The key approach of the scheme is to apply the homomorphic transform on the host image to obtain its reflectance component. The watermark is embedded into the singular values that are obtained by applying the singular value decomposition on the reflectance component. Peak-signal-to-noise-ratio (PSNR), normalized-correlation-coefficient (NCC) and mean-structural-similarity-index-measure (MSSIM) are used to evaluate the performance of the scheme. Invisibility of watermark is ensured by visual inspection and high value of PSNR of watermarked images. Presence of watermark is ensured by visual inspection and high values of NCC and MSSIM of extracted watermarks. Robustness of the scheme is verified by high values of NCC and MSSIM for attacked watermarked images.

Correlation among body height, intelligence, and brain gray matter volume in healthy children.

PubMed

Taki, Yasuyuki; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Asano, Michiko; Asano, Kohei; Kotozaki, Yuka; Nouchi, Rui; Wu, Kai; Fukuda, Hiroshi; Kawashima, Ryuta

2012-01-16

A significant positive correlation between height and intelligence has been demonstrated in children. Additionally, intelligence has been associated with the volume of gray matter in the brains of children. Based on these correlations, we analyzed the correlation among height, full-scale intelligence quotient (IQ) and gray matter volume applying voxel-based morphometry using data from the brain magnetic resonance images of 160 healthy children aged 5-18 years of age. As a result, body height was significantly positively correlated with brain gray matter volume. Additionally, the regional gray matter volume of several regions such as the bilateral prefrontal cortices, temporoparietal region, and cerebellum was significantly positively correlated with body height and that the gray matter volume of several of these regions was also significantly positively correlated with full-scale intelligence quotient (IQ) scores after adjusting for age, sex, and socioeconomic status. Our results demonstrate that gray and white matter volume may mediate the correlation between body height and intelligence in healthy children. Additionally, the correlations among gray and white matter volume, height, and intelligence may be at least partially explained by the effect of insulin-like growth factor-1 and growth hormones. Given the importance of the effect of environmental factors, especially nutrition, on height, IQ, and gray matter volume, the present results stress the importance of nutrition during childhood for the healthy maturation of body and brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

NASA Astrophysics Data System (ADS)

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system.

PubMed

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Near-Infrared Coloring via a Contrast-Preserving Mapping Model.

PubMed

Chang-Hwan Son; Xiao-Ping Zhang

2017-11-01

Near-infrared gray images captured along with corresponding visible color images have recently proven useful for image restoration and classification. This paper introduces a new coloring method to add colors to near-infrared gray images based on a contrast-preserving mapping model. A naive coloring method directly adds the colors from the visible color image to the near-infrared gray image. However, this method results in an unrealistic image because of the discrepancies in the brightness and image structure between the captured near-infrared gray image and the visible color image. To solve the discrepancy problem, first, we present a new contrast-preserving mapping model to create a new near-infrared gray image with a similar appearance in the luminance plane to the visible color image, while preserving the contrast and details of the captured near-infrared gray image. Then, we develop a method to derive realistic colors that can be added to the newly created near-infrared gray image based on the proposed contrast-preserving mapping model. Experimental results show that the proposed new method not only preserves the local contrast and details of the captured near-infrared gray image, but also transfers the realistic colors from the visible color image to the newly created near-infrared gray image. It is also shown that the proposed near-infrared coloring can be used effectively for noise and haze removal, as well as local contrast enhancement.

Histogram and gray level co-occurrence matrix on gray-scale ultrasound images for diagnosing lymphocytic thyroiditis.

PubMed

Shin, Young Gyung; Yoo, Jaeheung; Kwon, Hyeong Ju; Hong, Jung Hwa; Lee, Hye Sun; Yoon, Jung Hyun; Kim, Eun-Kyung; Moon, Hee Jung; Han, Kyunghwa; Kwak, Jin Young

2016-08-01

The objective of the study was to evaluate whether texture analysis using histogram and gray level co-occurrence matrix (GLCM) parameters can help clinicians diagnose lymphocytic thyroiditis (LT) and differentiate LT according to pathologic grade. The background thyroid pathology of 441 patients was classified into no evidence of LT, chronic LT (CLT), and Hashimoto's thyroiditis (HT). Histogram and GLCM parameters were extracted from the regions of interest on ultrasound. The diagnostic performances of the parameters for diagnosing and differentiating LT were calculated. Of the histogram and GLCM parameters, the mean on histogram had the highest Az (0.63) and VUS (0.303). As the degrees of LT increased, the mean decreased and the standard deviation and entropy increased. The mean on histogram from gray-scale ultrasound showed the best diagnostic performance as a single parameter in differentiating LT according to pathologic grade as well as in diagnosing LT. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative analysis of brain magnetic resonance imaging for hepatic encephalopathy

NASA Astrophysics Data System (ADS)

Syh, Hon-Wei; Chu, Wei-Kom; Ong, Chin-Sing

1992-06-01

High intensity lesions around ventricles have recently been observed in T1-weighted brain magnetic resonance images for patients suffering hepatic encephalopathy. The exact etiology that causes magnetic resonance imaging (MRI) gray scale changes has not been totally understood. The objective of our study was to investigate, through quantitative means, (1) the amount of changes to brain white matter due to the disease process, and (2) the extent and distribution of these high intensity lesions, since it is believed that the abnormality may not be entirely limited to the white matter only. Eleven patients with proven haptic encephalopathy and three normal persons without any evidence of liver abnormality constituted our current data base. Trans-axial, sagittal, and coronal brain MRI were obtained on a 1.5 Tesla scanner. All processing was carried out on a microcomputer-based image analysis system in an off-line manner. Histograms were decomposed into regular brain tissues and lesions. Gray scale ranges coded as lesion were then brought back to original images to identify distribution of abnormality. Our results indicated the disease process involved pallidus, mesencephalon, and subthalamic regions.

Automatic crack detection and classification method for subway tunnel safety monitoring.

PubMed

Zhang, Wenyu; Zhang, Zhenjiang; Qi, Dapeng; Liu, Yun

2014-10-16

Cracks are an important indicator reflecting the safety status of infrastructures. This paper presents an automatic crack detection and classification methodology for subway tunnel safety monitoring. With the application of high-speed complementary metal-oxide-semiconductor (CMOS) industrial cameras, the tunnel surface can be captured and stored in digital images. In a next step, the local dark regions with potential crack defects are segmented from the original gray-scale images by utilizing morphological image processing techniques and thresholding operations. In the feature extraction process, we present a distance histogram based shape descriptor that effectively describes the spatial shape difference between cracks and other irrelevant objects. Along with other features, the classification results successfully remove over 90% misidentified objects. Also, compared with the original gray-scale images, over 90% of the crack length is preserved in the last output binary images. The proposed approach was tested on the safety monitoring for Beijing Subway Line 1. The experimental results revealed the rules of parameter settings and also proved that the proposed approach is effective and efficient for automatic crack detection and classification.

Automatic Crack Detection and Classification Method for Subway Tunnel Safety Monitoring

PubMed Central

Zhang, Wenyu; Zhang, Zhenjiang; Qi, Dapeng; Liu, Yun

2014-01-01

Cracks are an important indicator reflecting the safety status of infrastructures. This paper presents an automatic crack detection and classification methodology for subway tunnel safety monitoring. With the application of high-speed complementary metal-oxide-semiconductor (CMOS) industrial cameras, the tunnel surface can be captured and stored in digital images. In a next step, the local dark regions with potential crack defects are segmented from the original gray-scale images by utilizing morphological image processing techniques and thresholding operations. In the feature extraction process, we present a distance histogram based shape descriptor that effectively describes the spatial shape difference between cracks and other irrelevant objects. Along with other features, the classification results successfully remove over 90% misidentified objects. Also, compared with the original gray-scale images, over 90% of the crack length is preserved in the last output binary images. The proposed approach was tested on the safety monitoring for Beijing Subway Line 1. The experimental results revealed the rules of parameter settings and also proved that the proposed approach is effective and efficient for automatic crack detection and classification. PMID:25325337

Prospective evaluation of Doppler sonography to detect the twinkling artifact versus unenhanced computed tomography for identifying urinary tract calculi.

PubMed

Kielar, Ania Z; Shabana, Wael; Vakili, Maryam; Rubin, Jonathan

2012-10-01

The twinkling artifact is an emerging tool for identifying urinary tract calculi. The purpose of this prospective study was to evaluate the diagnostic accuracy of the twinkling artifact compared to unenhanced computed tomography in detecting urolithasis. After Research Ethics Board approval, 51 patients with flank pain from the emergency department were enrolled between November 2009 and September 2010. Patients received an unenhanced computed tomographic scan with 1.25-mm raw data and reformatted 5-mm axial and 2-mm coronal images. Blinded assessment of the urinary tract was performed with gray-scale and color Doppler interrogation. The number of calculi, location, size, kidney distance from the skin, body mass index of the patient, and sonographic image parameters were recorded. There were 35 right-sided and 38 left-sided renal calculi, 14 right-sided and 21 left-sided ureteric calculi, and 6 bladder calculi (total, 114 calculi). Thirteen patients had no calculi. The average calculus size was 2.6 mm (range, 1-9 mm). There were 6 false-positive and 22 false-negative instances of twinkling artifacts. On gray-scale evaluation looking for an echogenic focus with shadowing, there were 8 false-positive and 40 false-negative findings. The positive predictive value (PPV) of the twinkling artifact for identifying calculi was 94%, and the sensitivity was 83%. The PPV of gray-scale sonographic shadowing was only 64.9%, and the sensitivity was 80.2%. The twinkling artifact has a high PPV for detecting renal and urinary tract calculi. Evaluation for the twinkling artifact is a complementary technique to standard gray-scale shadowing of calculi and improves detection of urolithiasis on sonography.

The BMPix and PEAK Tools: New Methods for Automated Laminae Recognition and Counting - Application to Glacial Varves From Antarctic Marine Sediment

NASA Astrophysics Data System (ADS)

Weber, M. E.; Reichelt, L.; Kuhn, G.; Thurow, J. W.; Ricken, W.

2009-12-01

We present software-based tools for rapid and quantitative detection of sediment lamination. The BMPix tool extracts color and gray-scale curves from images at ultrahigh (pixel) resolution. The PEAK tool uses the gray-scale curve and performs, for the first time, fully automated counting of laminae based on three methods. The maximum count algorithm counts every bright peak of a couplet of two laminae (annual resolution) in a Gaussian smoothed gray-scale curve. The zero-crossing algorithm counts every positive and negative halfway-passage of the gray-scale curve through a wide moving average. Hence, the record is separated into bright and dark intervals (seasonal resolution). The same is true for the frequency truncation method, which uses Fourier transformation to decompose the gray-scale curve into its frequency components, before positive and negative passages are count. We applied the new methods successfully to tree rings and to well-dated and already manually counted marine varves from Saanich Inlet before we adopted the tools to rather complex marine laminae from the Antarctic continental margin. In combination with AMS14C dating, we found convincing evidence that the laminations from three Weddell Sea sites represent true varves that were deposited on sediment ridges over several millennia during the last glacial maximum (LGM). There are apparently two seasonal layers of terrigenous composition, a coarser-grained bright layer, and a finer-grained dark layer. The new tools offer several advantages over previous tools. The counting procedures are based on a moving average generated from gray-scale curves instead of manual counting. Hence, results are highly objective and rely on reproducible mathematical criteria. Since PEAK associates counts with a specific depth, the thickness of each year or each season is also measured which is an important prerequisite for later spectral analysis. Since all information required to conduct the analysis is displayed graphically, interactive optimization of the counting algorithms can be achieved quickly and conveniently.

A comparison of methods to evaluate gray scale response of tomosynthesis systems using a software breast phantom

NASA Astrophysics Data System (ADS)

Sousa, Maria A. Z.; Bakic, Predrag R.; Schiabel, Homero; Maidment, Andrew D. A.

2017-03-01

Digital breast tomosynthesis (DBT) has been shown to be an effective imaging tool for breast cancer diagnosis as it provides three-dimensional images of the breast with minimal tissue overlap. The quality of the reconstructed image depends on many factors that can be assessed using uniform or realistic phantoms. In this paper, we created four models of phantoms using an anthropomorphic software breast phantom and compared four methods to evaluate the gray scale response in terms of the contrast, noise and detectability of adipose and glandular tissues binarized according to phantom ground truth. For each method, circular regions of interest (ROIs) were selected with various sizes, quantity and positions inside a square area in the phantom. We also estimated the percent density of the simulated breast and the capability of distinguishing both tissues by receiver operating characteristic (ROC) analysis. Results shows a sensitivity of the methods to the ROI size, placement and to the slices considered.

The AAPM/RSNA physics tutorial for residents: digital fluoroscopy.

PubMed

Pooley, R A; McKinney, J M; Miller, D A

2001-01-01

A digital fluoroscopy system is most commonly configured as a conventional fluoroscopy system (tube, table, image intensifier, video system) in which the analog video signal is converted to and stored as digital data. Other methods of acquiring the digital data (eg, digital or charge-coupled device video and flat-panel detectors) will become more prevalent in the future. Fundamental concepts related to digital imaging in general include binary numbers, pixels, and gray levels. Digital image data allow the convenient use of several image processing techniques including last image hold, gray-scale processing, temporal frame averaging, and edge enhancement. Real-time subtraction of digital fluoroscopic images after injection of contrast material has led to widespread use of digital subtraction angiography (DSA). Additional image processing techniques used with DSA include road mapping, image fade, mask pixel shift, frame summation, and vessel size measurement. Peripheral angiography performed with an automatic moving table allows imaging of the peripheral vasculature with a single contrast material injection.

Video rate morphological processor based on a redundant number representation

NASA Astrophysics Data System (ADS)

Kuczborski, Wojciech; Attikiouzel, Yianni; Crebbin, Gregory A.

1992-03-01

This paper presents a video rate morphological processor for automated visual inspection of printed circuit boards, integrated circuit masks, and other complex objects. Inspection algorithms are based on gray-scale mathematical morphology. Hardware complexity of the known methods of real-time implementation of gray-scale morphology--the umbra transform and the threshold decomposition--has prompted us to propose a novel technique which applied an arithmetic system without carrying propagation. After considering several arithmetic systems, a redundant number representation has been selected for implementation. Two options are analyzed here. The first is a pure signed digit number representation (SDNR) with the base of 4. The second option is a combination of the base-2 SDNR (to represent gray levels of images) and the conventional twos complement code (to represent gray levels of structuring elements). Operation principle of the morphological processor is based on the concept of the digit level systolic array. Individual processing units and small memory elements create a pipeline. The memory elements store current image windows (kernels). All operation primitives of processing units apply a unified direction of digit processing: most significant digit first (MSDF). The implementation technology is based on the field programmable gate arrays by Xilinx. This paper justified the rationality of a new approach to logic design, which is the decomposition of Boolean functions instead of Boolean minimization.

Automatic vehicle counting using background subtraction method on gray scale images and morphology operation

NASA Astrophysics Data System (ADS)

Adi, K.; Widodo, A. P.; Widodo, C. E.; Pamungkas, A.; Putranto, A. B.

2018-05-01

Traffic monitoring on road needs to be done, the counting of the number of vehicles passing the road is necessary. It is more emphasized for highway transportation management in order to prevent efforts. Therefore, it is necessary to develop a system that is able to counting the number of vehicles automatically. Video processing method is able to counting the number of vehicles automatically. This research has development a system of vehicle counting on toll road. This system includes processes of video acquisition, frame extraction, and image processing for each frame. Video acquisition is conducted in the morning, at noon, in the afternoon, and in the evening. This system employs of background subtraction and morphology methods on gray scale images for vehicle counting. The best vehicle counting results were obtained in the morning with a counting accuracy of 86.36 %, whereas the lowest accuracy was in the evening, at 21.43 %. Differences in morning and evening results are caused by different illumination in the morning and evening. This will cause the values in the image pixels to be different.

The crack detection algorithm of pavement image based on edge information

NASA Astrophysics Data System (ADS)

Yang, Chunde; Geng, Mingyue

2018-05-01

As the images of pavement cracks are affected by a large amount of complicated noises, such as uneven illumination and water stains, the detected cracks are discontinuous and the main body information at the edge of the cracks is easily lost. In order to solve the problem, a crack detection algorithm in pavement image based on edge information is proposed. Firstly, the image is pre-processed by the nonlinear gray-scale transform function and reconstruction filter to enhance the linear characteristic of the crack. At the same time, an adaptive thresholding method is designed to coarsely extract the cracks edge according to the gray-scale gradient feature and obtain the crack gradient information map. Secondly, the candidate edge points are obtained according to the gradient information, and the edge is detected based on the single pixel percolation processing, which is improved by using the local difference between pixels in the fixed region. Finally, complete crack is obtained by filling the crack edge. Experimental results show that the proposed method can accurately detect pavement cracks and preserve edge information.

Pixel-based image fusion with false color mapping

NASA Astrophysics Data System (ADS)

Zhao, Wei; Mao, Shiyi

2003-06-01

In this paper, we propose a pixel-based image fusion algorithm that combines the gray-level image fusion method with the false color mapping. This algorithm integrates two gray-level images presenting different sensor modalities or at different frequencies and produces a fused false-color image. The resulting image has higher information content than each of the original images. The objects in the fused color image are easy to be recognized. This algorithm has three steps: first, obtaining the fused gray-level image of two original images; second, giving the generalized high-boost filtering images between fused gray-level image and two source images respectively; third, generating the fused false-color image. We use the hybrid averaging and selection fusion method to obtain the fused gray-level image. The fused gray-level image will provide better details than two original images and reduce noise at the same time. But the fused gray-level image can't contain all detail information in two source images. At the same time, the details in gray-level image cannot be discerned as easy as in a color image. So a color fused image is necessary. In order to create color variation and enhance details in the final fusion image, we produce three generalized high-boost filtering images. These three images are displayed through red, green and blue channel respectively. A fused color image is produced finally. This method is used to fuse two SAR images acquired on the San Francisco area (California, USA). The result shows that fused false-color image enhances the visibility of certain details. The resolution of the final false-color image is the same as the resolution of the input images.

Efficacy of Strain Elastography in Diagnosis and Staging of Acute Appendicitis in Pediatric Patients.

PubMed

Arslan, Harun; Akdemir, Zülküf; Yavuz, Alpaslan; Gökçal, Fahri; Parlakgümüş, Cemal; İslamoglu, Necat; Akdeniz, Hüseyin

2018-02-11

BACKGROUND In the present study, the role and efficiency of strain elastography (SE) were evaluated in diagnosis and staging of acute appendicitis in pediatric patients. MATERIAL AND METHODS We enrolled 225 pediatric patients with suspected clinical and laboratory findings of acute appendicitis. Gray-scale sonographic findings were recorded and staging was made by the colorization method of SE imaging. Appendectomy was performed in all patients and the results of the surgical pathology were compared with the imaging findings. The sensitivity, specificity, and accuracy of SE imaging were determined in terms of evaluating the "acute appendicitis". RESULTS Sonographic evaluation revealed acute appendicitis in 100 patients. Regarding the SE analysis, cases with appendicitis were classified into 3 groups as: mild (n=17), moderate (n=39), and severe (n=44). The pathological evaluation revealed 95 different stages of appendicitis and normal appendix in 5 cases: acute focal (n=10), acute suppurative (n=46), phlegmonous (n=27), and perforated (n=12), regarding the results of surgical pathology. Five patients with pathologically proven "normal" appendix were noted as "mild stage appendicitis" based on gray scale and SE analysis. In total, when gray-scale and SE results were compared with pathology results regardless of the stage of appendicitis, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy rates were 96%, 96%, 95%, 96.8%, and 96%, respectively. No statistically significant difference was detected between other groups (P<0.05). CONCLUSIONS In acute appendicitis, the use of SE imaging as a supportive method for the clinical approach can be useful in diagnosis, and its results are closely correlated with the histopathologic stage of appendix inflammation.

Comparative analysis of renal flow using contrast power Doppler and gray-scale ultrasound

NASA Astrophysics Data System (ADS)

Sehgal, Chandra M.; Arger, Peter H.; Bovee, Kenneth C.; Pugh, Charles; Kirchhofer, Justin I.

1997-05-01

Our previous studies have shown that renal perfusion can be visualized by imaging the transit of a contrast agent through the parenchyma of the organ using gray scale (GS) and power Doppler (PD) ultrasound.However, the relative merits and the sensitivities of the two imaging methods are not known. This study compares the effectiveness of the two modes in visualizing kidney perfusion at the clinical dose of contrast agents. GS and PD images of the dog kidneys were recorded using a clinical ultrasound scanner at 4-7 MHz. A fixed longitudinal plane of the kidney was imaged by mounting the transducer on the animal with a specially designed holder. A dose of 0.1 m1/kg of Echogen was injected intravenously and GS and PD images were recorded simultaneously on two separate time-encoded video tapes during the passage of the contrast agent through the kidneys. The enhancement of GS and PD images was assessed qualitatively by three radiologists. The quantitative assessment was made by measuring the regional and global enhancements of digitized B-scan and PS images. Regional measurements were made by comparing brightness of the post contrast images with that of a pre-contrast reference image pixel by pixel. Student t-test was used to determine the statistical significance of the change. The regions representing statistically significant differences were encoded on the image in color with brightness proportional to the magnitude of change. The regions with no significant change were represented in GS. This generated a series of new images, referred to as StatMap, with color representing regions of perfusion. Changes in power Doppler images were visually detectable with high confidence in all five dogs by al three radiologists. There was no perceptible changes in B-scans. Computer analysis of PD images yielded characteristic indicator dilution curves in all five dogs with an initial rise time of 2-5 sec and a peak at 7-20 sec. The enhancement in PD lasted for 97-400 seconds. The peak to pre-injection Doppler power ratio was 2.41 +/- 0.85. There were not detectable changes in gray scale images except in one dog which exhibited a small change. The StatMap images of PD exhibited perfusion over the entire kidney, whereas the GS images showed perfusion to be sparsely distributed.

Sonoelastography in the Evaluation of Plantar Fasciitis Treatment: 3-Month Follow-Up After Collagen Injection.

PubMed

Kim, Minchul; Choi, Yun Sun; You, Myung-Won; Kim, Jin Su; Young, Ki Won

2016-12-01

The aim of this study was to investigate whether ultrasound elastography can demonstrate the outcome of the treatment in comparison with gray-scale imaging. Sixteen patients (mean age, 46.9 years) with plantar fasciitis were prospectively enrolled after unsuccessful conservative treatment. Individuals graded their heel pain on a 100-mm visual analogue scale (VAS) and underwent gray-scale ultrasonography and sonoelastography. Collagen was injected in the heels. Fascial thickness and hypoechogenicity, perifascial edema, and plantar fascial elasticity were evaluated. Follow-up sonoelastography and VAS grading were done 3 months after the injection. Statistical analyses were performed by the paired t test and the Fisher exact test. A P < 0.05 was considered statistically significant. Mean plantar fascial thickness showed insignificant decrease on follow-up (from 4.30 [1.37] to 4.23 [1.15] mm, P = 0.662). Fascial hypoechogenicity and perifascial edema did not change significantly after treatment. The mean strain ratio of the plantar fascia was significantly increased (from 0.71 [0.24] to 1.66 [0.72], P = 0.001). Softening of the plantar fascia decreased significantly after injection (from 12 to 3 ft, P = 0.004). Twelve (75%) of 16 patients showed significant VAS improvement at the follow-up. Sonoelastography revealed a hardening of the plantar fascia after collagen injection treatment and could aid in monitoring the improvement of the symptoms of plantar fasciitis, in cases where gray-scale imaging is inconclusive.

[Digital processing and evaluation of ultrasound images].

PubMed

Borchers, J; Klews, P M

1993-10-01

With the help of workstations and PCs, on-site image processing has become possible. If the images are not available in digital form the video signal has to be A/D converted. In the case of colour images the colour channels R (red), G (green) and B (blue) have to be digitized separately. "Truecolour" imaging calls for an 8 bit resolution per channel, leading to 24 bits per pixel. Out of a pool of 2(24) possible values only the relevant 128 gray values and 64 shades of red and blue respectively needed for a colour-coded ultrasound image have to be isolated. Digital images can be changed and evaluated with the help of readily available image evaluation programmes. It is mandatory that during image manipulation the gray scale and colour pixels and LUTs (Look-Up-Table) must be worked on separately. Using relatively simple LUT manipulations astonishing image improvements are possible. Application of simple mathematical operations can lead to completely new clinical results. For example, by subtracting two consecutive colour flow images in time and special LUT operations, local acceleration of blood flow can be visualized (Colour Acceleration Imaging).

Neurilemmoma of the glans penis: ultrasonography and magnetic resonance imaging findings.

PubMed

Jung, Dae Chul; Hwang, Sung Il; Jung, Sung Il; Kim, Sun Ho; Kim, Seung Hyup

2006-01-01

Neurilemmoma of the glans penis is rare, and no imaging findings have been reported. A case of neurilemmoma of the glans penis is presented. Ultrasonography (US) and magnetic resonance imaging revealed a well-defined small mass in the glans penis. The mass appeared hypoechoic on gray-scale US and hypervascular on color Doppler US. Magnetic resonance imaging revealed high signal intensity of the mass on a T2-weighted image and strong enhancement on a contrast-enhanced T1-weighted image.

Assessing the activity of perianal Crohn's disease: comparison of clinical indices and computer-assisted anal ultrasound.

PubMed

Losco, Alessandra; Viganò, Chiara; Conte, Dario; Cesana, Bruno Mario; Basilisco, Guido

2009-05-01

Assessing perianal disease activity is important for the treatment and prognosis of Crohn's disease (CD) patients, but the diagnostic accuracy of the activity indices has not yet been established. The aim of this study was to determine the accuracy and agreement of the Fistula Drainage Assessment (FDA), Perianal Disease Activity Index (PDAI), and computer-assisted anal ultrasound imaging (AUS). Sixty-two consecutive patients with CD and perianal fistulae underwent clinical, FDA, PDAI, and AUS evaluation. Perianal disease was considered active in the presence of visible fistula drainage and/or signs of local inflammation (induration and pain at digital compression) upon clinical examination. The AUS images were analyzed by calculating the mean gray-scale tone of the lesion. The PDAI and gray-scale tone values discriminating active and inactive perianal disease were defined using receiver operating characteristics statistics. Perianal disease was active in 46 patients. The accuracy of the FDA was 87% (confidence interval [CI]: 76%-94%). A PDAI of >4 and a mean gray-scale tone value of 117 maximized sensitivity and specificity; their diagnostic accuracy was, respectively, 87% (CI: 76%-94%) and 81% (CI: 69%-90%). The agreement of the 3 evaluations was fair to moderate. The addition of AUS to the PDAI or FDA increased their diagnostic accuracy to respectively 95% and 98%. The diagnostic accuracy of the FDA, PDAI, and computer-assisted AUS imaging was good in assessing perianal disease activity in patients with CD. The agreement between the techniques was fair to moderate. Overall accuracy can be increased by combining the FDA or PDAI with AUS.

A New Scrambling Evaluation Scheme Based on Spatial Distribution Entropy and Centroid Difference of Bit-Plane

NASA Astrophysics Data System (ADS)

Zhao, Liang; Adhikari, Avishek; Sakurai, Kouichi

Watermarking is one of the most effective techniques for copyright protection and information hiding. It can be applied in many fields of our society. Nowadays, some image scrambling schemes are used as one part of the watermarking algorithm to enhance the security. Therefore, how to select an image scrambling scheme and what kind of the image scrambling scheme may be used for watermarking are the key problems. Evaluation method of the image scrambling schemes can be seen as a useful test tool for showing the property or flaw of the image scrambling method. In this paper, a new scrambling evaluation system based on spatial distribution entropy and centroid difference of bit-plane is presented to obtain the scrambling degree of image scrambling schemes. Our scheme is illustrated and justified through computer simulations. The experimental results show (in Figs. 6 and 7) that for the general gray-scale image, the evaluation degree of the corresponding cipher image for the first 4 significant bit-planes selection is nearly the same as that for the 8 bit-planes selection. That is why, instead of taking 8 bit-planes of a gray-scale image, it is sufficient to take only the first 4 significant bit-planes for the experiment to find the scrambling degree. This 50% reduction in the computational cost makes our scheme efficient.

Voxel-Based Morphometry and fMRI Revealed Differences in Brain Gray Matter in Breastfed and Milk Formula-Fed Children.

PubMed

Ou, X; Andres, A; Pivik, R T; Cleves, M A; Snow, J H; Ding, Z; Badger, T M

2016-04-01

Infant diets may have significant impact on brain development in children. The aim of this study was to evaluate brain gray matter structure and function in 8-year-old children who were predominantly breastfed or fed cow's milk formula as infants. Forty-two healthy children (breastfed: n = 22, 10 boys and 12 girls; cow's milk formula: n = 20, 10 boys and 10 girls) were studied by using structural MR imaging (3D T1-weighted imaging) and blood oxygen level-dependent fMRI (while performing tasks involving visual perception and language functions). They were also administered standardized tests evaluating intelligence (Reynolds Intellectual Assessment Scales) and language skills (Clinical Evaluation of Language Fundamentals). Total brain gray matter volume did not differ between the breastfed and cow's milk formula groups. However, breastfed children had significantly higher (P < .05, corrected) regional gray matter volume measured by voxel-based morphometry in the left inferior temporal lobe and left superior parietal lobe compared with cow's milk formula-fed children. Breastfed children showed significantly more brain activation in the right frontal and left/right temporal lobes on fMRI when processing the perception task and in the left temporal/occipital lobe when processing the visual language task than cow's milk formula-fed children. The imaging findings were associated with significantly better performance for breastfed than cow's milk formula-fed children on both tasks. Our findings indicated greater regional gray matter development and better regional gray matter function in breastfed than cow's milk formula-fed children at 8 years of age and suggested that infant diets may have long-term influences on brain development in children. © 2016 by American Journal of Neuroradiology.

Voxel-based morphometry and automated lobar volumetry: The trade-off between spatial scale and statistical correction

PubMed Central

Voormolen, Eduard H.J.; Wei, Corie; Chow, Eva W.C.; Bassett, Anne S.; Mikulis, David J.; Crawley, Adrian P.

2011-01-01

Voxel-based morphometry (VBM) and automated lobar region of interest (ROI) volumetry are comprehensive and fast methods to detect differences in overall brain anatomy on magnetic resonance images. However, VBM and automated lobar ROI volumetry have detected dissimilar gray matter differences within identical image sets in our own experience and in previous reports. To gain more insight into how diverging results arise and to attempt to establish whether one method is superior to the other, we investigated how differences in spatial scale and in the need to statistically correct for multiple spatial comparisons influence the relative sensitivity of either technique to group differences in gray matter volumes. We assessed the performance of both techniques on a small dataset containing simulated gray matter deficits and additionally on a dataset of 22q11-deletion syndrome patients with schizophrenia (22q11DS-SZ) vs. matched controls. VBM was more sensitive to simulated focal deficits compared to automated ROI volumetry, and could detect global cortical deficits equally well. Moreover, theoretical calculations of VBM and ROI detection sensitivities to focal deficits showed that at increasing ROI size, ROI volumetry suffers more from loss in sensitivity than VBM. Furthermore, VBM and automated ROI found corresponding GM deficits in 22q11DS-SZ patients, except in the parietal lobe. Here, automated lobar ROI volumetry found a significant deficit only after a smaller subregion of interest was employed. Thus, sensitivity to focal differences is impaired relatively more by averaging over larger volumes in automated ROI methods than by the correction for multiple comparisons in VBM. These findings indicate that VBM is to be preferred over automated lobar-scale ROI volumetry for assessing gray matter volume differences between groups. PMID:19619660

Compressed/reconstructed test images for CRAF/Cassini

NASA Technical Reports Server (NTRS)

Dolinar, S.; Cheung, K.-M.; Onyszchuk, I.; Pollara, F.; Arnold, S.

1991-01-01

A set of compressed, then reconstructed, test images submitted to the Comet Rendezvous Asteroid Flyby (CRAF)/Cassini project is presented as part of its evaluation of near lossless high compression algorithms for representing image data. A total of seven test image files were provided by the project. The seven test images were compressed, then reconstructed with high quality (root mean square error of approximately one or two gray levels on an 8 bit gray scale), using discrete cosine transforms or Hadamard transforms and efficient entropy coders. The resulting compression ratios varied from about 2:1 to about 10:1, depending on the activity or randomness in the source image. This was accomplished without any special effort to optimize the quantizer or to introduce special postprocessing to filter the reconstruction errors. A more complete set of measurements, showing the relative performance of the compression algorithms over a wide range of compression ratios and reconstruction errors, shows that additional compression is possible at a small sacrifice in fidelity.

The wavelet/scalar quantization compression standard for digital fingerprint images

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

Bradley, J.N.; Brislawn, C.M.

1994-04-01

A new digital image compression standard has been adopted by the US Federal Bureau of Investigation for use on digitized gray-scale fingerprint images. The algorithm is based on adaptive uniform scalar quantization of a discrete wavelet transform image decomposition and is referred to as the wavelet/scalar quantization standard. The standard produces archival quality images at compression ratios of around 20:1 and will allow the FBI to replace their current database of paper fingerprint cards with digital imagery.

Hijacking User Uploads to Online Persistent Data Repositories for Covert Data Exfiltration

DTIC Science & Technology

2010-09-01

Detecting LSB Steganography in Color, and Gray-scale Images . Multimedia, IEEE, 8(4):22 –28, Oct.-Dec. 2001. [Fli10] Flickr. Camera finder...in images is known as Least Significant Bit ( LSB ) manipulation. This technique requires an individual to alter each pixel in an image just slightly...the human eye. It is this property of images that LSB manipulation relies on. When a user creates a piece of data they wish to hide in an image , they

Document image binarization using "multi-scale" predefined filters

NASA Astrophysics Data System (ADS)

Saabni, Raid M.

2018-04-01

Reading text or searching for key words within a historical document is a very challenging task. one of the first steps of the complete task is binarization, where we separate foreground such as text, figures and drawings from the background. Successful results of this important step in many cases can determine next steps to success or failure, therefore it is very vital to the success of the complete task of reading and analyzing the content of a document image. Generally, historical documents images are of poor quality due to their storage condition and degradation over time, which mostly cause to varying contrasts, stains, dirt and seeping ink from reverse side. In this paper, we use banks of anisotropic predefined filters in different scales and orientations to develop a binarization method for degraded documents and manuscripts. Using the fact, that handwritten strokes may follow different scales and orientations, we use predefined sets of filter banks having various scales, weights, and orientations to seek a compact set of filters and weights in order to generate diffrent layers of foregrounds and background. Results of convolving these fiters on the gray level image locally, weighted and accumulated to enhance the original image. Based on the different layers, seeds of components in the gray level image and a learning process, we present an improved binarization algorithm to separate the background from layers of foreground. Different layers of foreground which may be caused by seeping ink, degradation or other factors are also separated from the real foreground in a second phase. Promising experimental results were obtained on the DIBCO2011 , DIBCO2013 and H-DIBCO2016 data sets and a collection of images taken from real historical documents.

Normal gray and white matter volume after weight restoration in adolescents with anorexia nervosa.

PubMed

Lázaro, Luisa; Andrés, Susana; Calvo, Anna; Cullell, Clàudia; Moreno, Elena; Plana, M Teresa; Falcón, Carles; Bargalló, Núria; Castro-Fornieles, Josefina

2013-12-01

The aim of this study was to determine whether treated, weight-stabilized adolescents with anorexia nervosa (AN) present brain volume differences in comparison with healthy controls. Thirty-five adolescents with weight-recovered AN and 17 healthy controls were assessed by means of psychopathology scales and magnetic resonance imaging. Axial three-dimensional T1-weighted images were obtained in a 1.5 Tesla scanner and analyzed using optimized voxel-based morphometry (VBM). There were no significant differences between controls and weight-stabilized AN patients with regard to global volumes of either gray or white brain matter, or in the regional VBM study. Differences were not significant between patients with psychopharmacological treatment and without, between those with amenorrhea and without, as well as between patients with restrictive versus purgative AN. The present findings reveal no global or regional gray or white matter abnormalities in this sample of adolescents following weight restoration. Copyright © 2013 Wiley Periodicals, Inc.

Regional gray matter volume in the posterior precuneus is associated with general self-efficacy.

PubMed

Sugiura, Ayaka; Aoki, Ryuta; Murayama, Kou; Yomogida, Yukihito; Haji, Tomoki; Saito, Atsuko; Hasegawa, Toshikazu; Matsumoto, Kenji

2016-12-14

Motivation in doing a task is influenced not only by the expected outcome of the task but also by the belief that one has in successfully executing the task. Over time, individuals accumulate experiences that contribute toward a general belief in one's overall ability to successfully perform tasks, which is called general self-efficacy (GSE). We investigated the relationship between regional gray matter volume and individual differences in GSE. Brain anatomy was analyzed using magnetic resonance images obtained from 64 healthy right-handed participants who had completed Sherer's GSE scale. After controlling for other factors related to motivation, age, sex, and total gray matter volume of each participant, results showed that regional gray matter volume in the posterior part of the precuneus significantly and positively correlated with the GSE score. These results suggest that one's accumulated experiences of success and failure, which contribute toward GSE, also influence the anatomical characteristics of the precuneus.

A combination chaotic system and application in color image encryption

NASA Astrophysics Data System (ADS)

Parvaz, R.; Zarebnia, M.

2018-05-01

In this paper, by using Logistic, Sine and Tent systems we define a combination chaotic system. Some properties of the chaotic system are studied by using figures and numerical results. A color image encryption algorithm is introduced based on new chaotic system. Also this encryption algorithm can be used for gray scale or binary images. The experimental results of the encryption algorithm show that the encryption algorithm is secure and practical.

General Approach for Rock Classification Based on Digital Image Analysis of Electrical Borehole Wall Images

NASA Astrophysics Data System (ADS)

Linek, M.; Jungmann, M.; Berlage, T.; Clauser, C.

2005-12-01

Within the Ocean Drilling Program (ODP), image logging tools have been routinely deployed such as the Formation MicroScanner (FMS) or the Resistivity-At-Bit (RAB) tools. Both logging methods are based on resistivity measurements at the borehole wall and therefore are sensitive to conductivity contrasts, which are mapped in color scale images. These images are commonly used to study the structure of the sedimentary rocks and the oceanic crust (petrologic fabric, fractures, veins, etc.). So far, mapping of lithology from electrical images is purely based on visual inspection and subjective interpretation. We apply digital image analysis on electrical borehole wall images in order to develop a method, which augments objective rock identification. We focus on supervised textural pattern recognition which studies the spatial gray level distribution with respect to certain rock types. FMS image intervals of rock classes known from core data are taken in order to train textural characteristics for each class. A so-called gray level co-occurrence matrix is computed by counting the occurrence of a pair of gray levels that are a certain distant apart. Once the matrix for an image interval is computed, we calculate the image contrast, homogeneity, energy, and entropy. We assign characteristic textural features to different rock types by reducing the image information into a small set of descriptive features. Once a discriminating set of texture features for each rock type is found, we are able to discriminate the entire FMS images regarding the trained rock type classification. A rock classification based on texture features enables quantitative lithology mapping and is characterized by a high repeatability, in contrast to a purely visual subjective image interpretation. We show examples for the rock classification between breccias, pillows, massive units, and horizontally bedded tuffs based on ODP image data.

Evaluation of carotid plaque echogenicity based on the integral of the cumulative probability distribution using gray-scale ultrasound images.

PubMed

Huang, Xiaowei; Zhang, Yanling; Meng, Long; Abbott, Derek; Qian, Ming; Wong, Kelvin K L; Zheng, Rongqing; Zheng, Hairong; Niu, Lili

2017-01-01

Carotid plaque echogenicity is associated with the risk of cardiovascular events. Gray-scale median (GSM) of the ultrasound image of carotid plaques has been widely used as an objective method for evaluation of plaque echogenicity in patients with atherosclerosis. We proposed a computer-aided method to evaluate plaque echogenicity and compared its efficiency with GSM. One hundred and twenty-five carotid plaques (43 echo-rich, 35 intermediate, 47 echolucent) were collected from 72 patients in this study. The cumulative probability distribution curves were obtained based on statistics of the pixels in the gray-level images of plaques. The area under the cumulative probability distribution curve (AUCPDC) was calculated as its integral value to evaluate plaque echogenicity. The classification accuracy for three types of plaques is 78.4% (kappa value, κ = 0.673), when the AUCPDC is used for classifier training, whereas GSM is 64.8% (κ = 0.460). The receiver operating characteristic curves were produced to test the effectiveness of AUCPDC and GSM for the identification of echolucent plaques. The area under the curve (AUC) was 0.817 when AUCPDC was used for training the classifier, which is higher than that achieved using GSM (AUC = 0.746). Compared with GSM, the AUCPDC showed a borderline association with coronary heart disease (Spearman r = 0.234, p = 0.050). Our experimental results suggest that AUCPDC analysis is a promising method for evaluation of plaque echogenicity and predicting cardiovascular events in patients with plaques.

Digital enhancement of computerized axial tomograms

NASA Technical Reports Server (NTRS)

Roberts, E., Jr.

1978-01-01

A systematic evaluation was conducted of certain digital image enhancement techniques performed in image space. Three types of images were used, computer generated phantoms, tomograms of a synthetic phantom, and axial tomograms of human anatomy containing images of lesions, artificially introduced into the tomograms. Several types of smoothing, sharpening, and histogram modification were explored. It was concluded that the most useful enhancement techniques are a selective smoothing of singular picture elements, combined with contrast manipulation. The most useful tool in applying these techniques is the gray-scale histogram.

Morphological filtering and multiresolution fusion for mammographic microcalcification detection

NASA Astrophysics Data System (ADS)

Chen, Lulin; Chen, Chang W.; Parker, Kevin J.

1997-04-01

Mammographic images are often of relatively low contrast and poor sharpness with non-stationary background or clutter and are usually corrupted by noise. In this paper, we propose a new method for microcalcification detection using gray scale morphological filtering followed by multiresolution fusion and present a unified general filtering form called the local operating transformation for whitening filtering and adaptive thresholding. The gray scale morphological filters are used to remove all large areas that are considered as non-stationary background or clutter variations, i.e., to prewhiten images. The multiresolution fusion decision is based on matched filter theory. In addition to the normal matched filter, the Laplacian matched filter which is directly related through the wavelet transforms to multiresolution analysis is exploited for microcalcification feature detection. At the multiresolution fusion stage, the region growing techniques are used in each resolution level. The parent-child relations between resolution levels are adopted to make final detection decision. FROC is computed from test on the Nijmegen database.

The Engineer Topographic Laboratories /ETL/ hybrid optical/digital image processor

NASA Astrophysics Data System (ADS)

Benton, J. R.; Corbett, F.; Tuft, R.

1980-01-01

An optical-digital processor for generalized image enhancement and filtering is described. The optical subsystem is a two-PROM Fourier filter processor. Input imagery is isolated, scaled, and imaged onto the first PROM; this input plane acts like a liquid gate and serves as an incoherent-to-coherent converter. The image is transformed onto a second PROM which also serves as a filter medium; filters are written onto the second PROM with a laser scanner in real time. A solid state CCTV camera records the filtered image, which is then digitized and stored in a digital image processor. The operator can then manipulate the filtered image using the gray scale and color remapping capabilities of the video processor as well as the digital processing capabilities of the minicomputer.

ENSO-Type Signals Recorded in the Late Cretaceous Laminated Sediments of Songliao Basin, Northeast China

NASA Astrophysics Data System (ADS)

Yu, E.; Wang, C.; Hinnov, L. A.; Wu, H.

2014-12-01

The quasi-periodic, ca. 2-7 year El Niño Southern Oscillation (ENSO) phenomenon globally influences the inter-annual variability of temperature and precipitation. Global warming may increase the frequency of extreme ENSO events. Although the Cretaceous plate tectonic configuration was different from today, the sedimentary record suggests that ENSO-type oscillations had existed at the time of Cretaceous greenhouse conditions. Cored Cretaceous lacustrine sediments from the Songliao Basin in Northeast China (SK-1 cores from the International Continental Drilling Program) potentially offer a partially varved record of Cretaceous paleoclimate. Fourteen polished thin sections from the depth interval 1096.12-1096.53 m with an age of 84.4 Ma were analyzed by optical and scanning electron microscopy (SEM). ImageJ software was applied to extract gray scale curves from optical images at pixel resolution. We tracked minimum values of the gray scale curves to estimate the thickness of each lamina. Five sedimentary structures were recognized: flaser bedding, wavy bedding, lenticular bedding, horizontal bedding, and massive layers. The mean layer thicknesses with different sedimentary structures range from 116 to 162mm, very close to the mean sedimentation rate estimated for this sampled interval, 135mm/year, indicating that the layers bounded by pure clay lamina with the minimum gray values are varves. SEM images indicate that a varve is composed, in succession, of one lamina rich in coarse silt, one lamina rich in fine silt, one clay-rich lamina with some silt, and one clay-rich lamina. This suggests that a Cretaceous year featured four distinct depositional seasons, two of which were rainy and the others were lacking precipitation. Spectral analysis of extended intervals of the tuned gray scale curve indicates the presence of inter-annual periodicities of 2.2-2.7 yr, 3.5-6.1 year, and 10.1-14.5 year consistent with those of modern ENSO cycles and solar cycles, as well as those recognized in the Cretaceous Arctic and Marca Shale of California.

Decreased gray matter volume in the left hippocampus and bilateral calcarine cortex in coal mine flood disaster survivors with recent onset PTSD.

PubMed

Zhang, Jian; Tan, Qingrong; Yin, Hong; Zhang, Xiaoliang; Huan, Yi; Tang, Lihua; Wang, Huaihai; Xu, Junqing; Li, Lingjiang

2011-05-31

Although limbic structure changes have been found in chronic and recent onset post-traumatic stress disorder (PTSD) patients, there are few studies about brain structure changes in recent onset PTSD patients after a single extreme and prolonged trauma. In the current study, 20 coal mine flood disaster survivors underwent magnetic resonance imaging (MRI). Voxel-based morphometry (VBM) and region of interest (ROI) techniques were used to detect the gray matter and white matter volume changes in 10 survivors with recent onset PTSD and 10 survivors without PTSD. The correlation between the Clinician-Administered PTSD Scale (CAPS) and gray matter density in the ROI was also studied. Compared with survivors without PTSD, survivors with PTSD had significantly decreased gray matter volume and density in left anterior hippocampus, left parahippocampal gyrus, and bilateral calcarine cortex. The CAPS score correlated negatively with the gray matter density in bilateral calcarine cortex and left hippocampus in coal mine disaster survivors. Our study suggests that the gray matter volume and density of limbic structure decreased in recent onset PTSD patients who were exposed to extreme trauma. PTSD symptom severity was associated with gray matter density in calcarine cortex and hippocampus. 2010 Elsevier Ireland Ltd. All rights reserved.

Alexithymia in Neurodegenerative Disease

PubMed Central

Sturm, Virginia E.; Levenson, Robert W.

2012-01-01

We investigated alexithymia, a deficit in the ability to identify and describe one’s emotions, in a sample that included patients with neurodegenerative disease and healthy controls. In addition, we investigated the relationship that alexithymia has with behavioral disturbance and with regional gray matter volumes. Alexithymia was examined with the Toronto Alexithymia Scale-20, behavioral disturbance was assessed with the Neuropsychiatric Inventory, and regional gray matter volumes were obtained from structural magnetic resonance images. Group analyses revealed higher levels of alexithymia in patients than controls. Alexithymia scores were positively correlated with behavioral disturbance (apathy and informant distress, in particular) and negatively correlated with the gray matter volume of the right pregenual anterior cingulate cortex, a region of the brain that is thought to play an important role in self and emotion processing. PMID:21432723

Diffusion Tensor Imaging of Heterotopia: Changes of Fractional Anisotropy during Radial Migration of Neurons

PubMed Central

Kim, Jinna

2010-01-01

Purpose Diffusion tensor imaging provides better understanding of pathophysiology of congenital anomalies, involving central nervous system. This study was aimed to specify the pathogenetic mechanism of heterotopia, proved by diffusion tensor imaging, and establish new findings of heterotopia on fractional anisotropy maps. Materials and Methods Diffusion-weighted imaging data from 11 patients (M : F = 7 : 4, aged from 1 to 22 years, mean = 12.3 years) who visited the epilepsy clinic and received a routine seizure protocol MRI exam were retrospectively analyzed. Fractional anisotropy (FA) maps were generated from diffusion tensor imaging of 11 patients with heterotopia. Regions of interests (ROI) were placed in cerebral cortex, heterotopic gray matter and deep gray matter, including putamen. ANOVA analysis was performed for comparison of different gray matter tissues. Results Heterotopic gray matter showed signal intensities similar to normal gray matter on T1 and T2 weighted MRI. The measured FA of heterotopic gray matter was higher than that of cortical gray matter (0.236 ± 0.011 vs. 0.169 ± 0.015, p < 0.01, one way ANOVA), and slightly lower than that of deep gray matter (0.236 ± 0.011 vs. 0.259 ± 0.016, p < 0.01). Conclusion Increased FA of heterotopic gray matter suggests arrested neuron during radial migration and provides better understanding of neurodevelopment. PMID:20499428

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Combining Segmented Grey and White Matter Images Improves Voxel-based Morphometry for the Case of Dilated Lateral Ventricles.

PubMed

Goto, Masami; Abe, Osamu; Aoki, Shigeki; Kamagata, Koji; Hori, Masaaki; Miyati, Tosiaki; Gomi, Tsutomu; Takeda, Tohoru

2018-01-18

To evaluate the error in segmented tissue images and to show the usefulness of the brain image in voxel-based morphometry (VBM) using Statistical Parametric Mapping (SPM) 12 software and 3D T 1 -weighted magnetic resonance images (3D-T 1 WIs) processed to simulate idiopathic normal pressure hydrocephalus (iNPH). VBM analysis was performed on sagittal 3D-T 1 WIs obtained in 22 healthy volunteers using a 1.5T MR scanner. Regions of interest for the lateral ventricles of all subjects were carefully outlined on the original 3D-T 1 WIs, and two types of simulated 3D-T 1 WI were also prepared (non-dilated 3D-T 1 WI as normal control and dilated 3D-T 1 WI to simulate iNPH). All simulated 3D-T 1 WIs were segmented into gray matter, white matter, and cerebrospinal fluid images, and normalized to standard space. A brain image was made by adding the gray and white matter images. After smoothing with a 6-mm isotropic Gaussian kernel, group comparisons (dilated vs non-dilated) were made for gray and white matter, cerebrospinal fluid, and brain images using a paired t-test. In evaluation of tissue volume, estimation error was larger using gray or white matter images than using the brain image, and estimation errors in gray and white matter volume change were found for the brain surface. To our knowledge, this is the first VBM study to show the possibility that VBM of gray and white matter volume on the brain surface may be more affected by individual differences in the level of dilation of the lateral ventricles than by individual differences in gray and white matter volumes. We recommend that VBM evaluation in patients with iNPH should be performed using the brain image rather than the gray and white matter images.

Einstein Observations of Galactic supernova remnants

NASA Technical Reports Server (NTRS)

Seward, Frederick D.

1990-01-01

This paper summarizes the observations of Galactic supernova remnants with the imaging detectors of the Einstein Observatory. X-ray surface brightness contours of 47 remnants are shown together with gray-scale pictures. Count rates for these remnants have been derived and are listed for the HRI, IPC, and MPC detectors.

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor.

PubMed

Liu, Zhenwang; Xu, Jiangtao; Wang, Xinlei; Nie, Kaiming; Jin, Weimin

2015-09-16

In order to eliminate the fixed-pattern noise (FPN) in the output image of time-delay-integration CMOS image sensor (TDI-CIS), a FPN correction method based on gray value compensation is proposed. One hundred images are first captured under uniform illumination. Then, row FPN (RFPN) and column FPN (CFPN) are estimated based on the row-mean vector and column-mean vector of all collected images, respectively. Finally, RFPN are corrected by adding the estimated RFPN gray value to the original gray values of pixels in the corresponding row, and CFPN are corrected by subtracting the estimated CFPN gray value from the original gray values of pixels in the corresponding column. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination with the proposed method, the standard-deviation of row-mean vector decreases from 5.6798 to 0.4214 LSB, and the standard-deviation of column-mean vector decreases from 15.2080 to 13.4623 LSB. Both kinds of FPN in the real images captured by TDI-CIS are eliminated effectively with the proposed method.

How Do Statistical Detection Methods Compare to Entropy Measures

DTIC Science & Technology

2012-08-28

October 2001. It is known as RS attack or “Reliable Detection of LSB Steganography in Grayscale and color images ”. The algorithm they use is very...precise for the detection of pseudo-aleatory LSB steganography . Its precision varies with the image but, its referential value is a 0.005 bits by...Jessica Fridrich, Miroslav Goljan, Rui Du, "Detecting LSB Steganography in Color and Gray-Scale Images ," IEEE Multimedia, vol. 8, no. 4, pp. 22-28, Oct

Digital enhancement of computerized axial tomograms

NASA Technical Reports Server (NTRS)

Roberts, E., Jr.

1978-01-01

A systematic evaluation has been conducted of certain digital image enhancement techniques performed in image space. Three types of images have been used, computer generated phantoms, tomograms of a synthetic phantom, and axial tomograms of human anatomy containing images of lesions, artificially introduced into the tomograms. Several types of smoothing, sharpening, and histogram modification have been explored. It has been concluded that the most useful enhancement techniques are a selective smoothing of singular picture elements, combined with contrast manipulation. The most useful tool in applying these techniques is the gray-scale histogram.

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

PubMed

Shu, Ting; Zhang, Bob; Yan Tang, Yuan

2017-04-01

Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors. The eight methods are from four texture feature families: (1) statistical texture feature family: Image Gray-scale Histogram, Gray-level Co-occurance Matrix, and Local Binary Pattern, (2) structural texture feature family: Voronoi Tessellation, (3) signal processing based texture feature family: Gaussian, Steerable, and Gabor filters, and (4) model based texture feature family: Markov Random Field. In order to determine the most appropriate extractor with optimal parameter(s), various parameter(s) of each extractor are experimented. For each extractor, the same dataset (284 Diabetes Mellitus and 231 Healthy samples), classifiers (k-Nearest Neighbors and Support Vector Machines), and validation method (10-fold cross validation) are used. According to the experiments, the first and third families achieved a better outcome at detecting Diabetes Mellitus than the other two. The best texture feature extractor for Diabetes Mellitus detection is the Image Gray-scale Histogram with bin number=256, obtaining an accuracy of 99.02%, a sensitivity of 99.64%, and a specificity of 98.26% by using SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

Single-faced GRAYQB™: a radiation mapping device

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

Mayer, J.; Farfan, E.; Immel, D.

2013-12-12

GrayQb{trademark} is a novel technology that has the potential to characterize radioactively contaminated areas such as hot cells, gloveboxes, small and large rooms, hallways, and waste tanks. The goal of GrayQb{trademark} is to speed the process of decontaminating these areas, which reduces worker exposures and promotes ALARA considerations. The device employs Phosphorous Storage Plate (PSP) technology as its primary detector material. PSPs, commonly used for medical applications and non-destructive testing, can be read using a commercially available scanner. The goal of GrayQb{trademark} technology is to locate, quantify, and identify the sources of contamination. The purpose of the work documented inmore » this report was to better characterize the performance of GrayQb{trademark} in its ability to present overlay images of the PSP image and the associated visual image of the location being surveyed. The results presented in this report are overlay images identifying the location of hot spots in both controlled and field environments. The GrayQb{trademark} technology has been mainly tested in a controlled environment with known distances and source characteristics such as specific known radionuclides, dose rates, and strength. The original concept for the GrayQb{trademark} device involved utilizing the six faces of a cube configuration and was designed to be positioned in the center of a contaminated area for 3D mapping. A smaller single-faced GrayQb{trademark}, dubbed GrayQb SF, was designed for the purpose of conducting the characterization testing documented in this report. This lighter 2D version is ideal for applications where entry ports are too small for a deployment of the original GrayQb™ version or where only a single surface is of interest. The shape, size, and weight of these two designs have been carefully modeled to account for most limitations encountered in hot cells, gloveboxes, and contaminated areas. GrayQb{trademark} and GrayQb{trademark} SF share the same fundamental detection system design (e.g., pinhole and PSPs). Therefore, performance tests completed on the single face GrayQB in this report is also applicable to the six- faced GrayQB (e.g., ambient light sensitivity and PSP response). This report details the characterization of the GrayQb{trademark} SF in both an uncontrolled environment; specifically, the Savannah River Site (SRS) Plutonium Fuel Form Facility in Building 235-F (Metallurgical Building) and controlled testing at SRS’s Health Physics Instrument Calibration Facility and SRS’s R&D Engineering Imaging and Radiation Systems Building. In this report, the resulting images from the Calibration Facility were obtained by overlaying the PSP and visual images manually using ImageJ. The resulting images from the Building 235-F tests presented in this report were produced using ImageJ and applying response trends developed from controlled testing results. The GrayQb{trademark} technology has been developed in two main stages at Savannah River National Laboratory (SRNL): 1) the GrayQb{trademark} development was supported by SRNL’s Laboratory Directed Research and Development Program and 2) the GrayQb{trademark} SF development and its testing in Building 235-F were supported by the Office of Deactivation and Decommissioning and Facility Engineering (EM-13), U.S. Department of Energy – Office of Environmental Management.« less

Integrated clinical workstations for image and text data capture, display, and teleconsultation.

PubMed

Dayhoff, R; Kuzmak, P M; Kirin, G

1994-01-01

The Department of Veterans Affairs (VA) DHCP Imaging System digitally records clinically significant diagnostic images selected by medical specialists in a variety of hospital departments, including radiology, cardiology, gastroenterology, pathology, dermatology, hematology, surgery, podiatry, dental clinic, and emergency room. These images, which include true color and gray scale images, scanned documents, and electrocardiogram waveforms, are stored on network file servers and displayed on workstations located throughout a medical center. All images are managed by the VA's hospital information system (HIS), allowing integrated displays of text and image data from all medical specialties. Two VA medical centers currently have DHCP Imaging Systems installed, and other installations are underway.

A fast color image enhancement algorithm based on Max Intensity Channel

PubMed Central

Sun, Wei; Han, Long; Guo, Baolong; Jia, Wenyan; Sun, Mingui

2014-01-01

In this paper, we extend image enhancement techniques based on the retinex theory imitating human visual perception of scenes containing high illumination variations. This extension achieves simultaneous dynamic range modification, color consistency, and lightness rendition without multi-scale Gaussian filtering which has a certain halo effect. The reflection component is analyzed based on the illumination and reflection imaging model. A new prior named Max Intensity Channel (MIC) is implemented assuming that the reflections of some points in the scene are very high in at least one color channel. Using this prior, the illumination of the scene is obtained directly by performing a gray-scale closing operation and a fast cross-bilateral filtering on the MIC of the input color image. Consequently, the reflection component of each RGB color channel can be determined from the illumination and reflection imaging model. The proposed algorithm estimates the illumination component which is relatively smooth and maintains the edge details in different regions. A satisfactory color rendition is achieved for a class of images that do not satisfy the gray-world assumption implicit to the theoretical foundation of the retinex. Experiments are carried out to compare the new method with several spatial and transform domain methods. Our results indicate that the new method is superior in enhancement applications, improves computation speed, and performs well for images with high illumination variations than other methods. Further comparisons of images from National Aeronautics and Space Administration and a wearable camera eButton have shown a high performance of the new method with better color restoration and preservation of image details. PMID:25110395

A fast color image enhancement algorithm based on Max Intensity Channel.

PubMed

Sun, Wei; Han, Long; Guo, Baolong; Jia, Wenyan; Sun, Mingui

2014-03-30

In this paper, we extend image enhancement techniques based on the retinex theory imitating human visual perception of scenes containing high illumination variations. This extension achieves simultaneous dynamic range modification, color consistency, and lightness rendition without multi-scale Gaussian filtering which has a certain halo effect. The reflection component is analyzed based on the illumination and reflection imaging model. A new prior named Max Intensity Channel (MIC) is implemented assuming that the reflections of some points in the scene are very high in at least one color channel. Using this prior, the illumination of the scene is obtained directly by performing a gray-scale closing operation and a fast cross-bilateral filtering on the MIC of the input color image. Consequently, the reflection component of each RGB color channel can be determined from the illumination and reflection imaging model. The proposed algorithm estimates the illumination component which is relatively smooth and maintains the edge details in different regions. A satisfactory color rendition is achieved for a class of images that do not satisfy the gray-world assumption implicit to the theoretical foundation of the retinex. Experiments are carried out to compare the new method with several spatial and transform domain methods. Our results indicate that the new method is superior in enhancement applications, improves computation speed, and performs well for images with high illumination variations than other methods. Further comparisons of images from National Aeronautics and Space Administration and a wearable camera eButton have shown a high performance of the new method with better color restoration and preservation of image details.

A fast color image enhancement algorithm based on Max Intensity Channel

NASA Astrophysics Data System (ADS)

Sun, Wei; Han, Long; Guo, Baolong; Jia, Wenyan; Sun, Mingui

2014-03-01

In this paper, we extend image enhancement techniques based on the retinex theory imitating human visual perception of scenes containing high illumination variations. This extension achieves simultaneous dynamic range modification, color consistency, and lightness rendition without multi-scale Gaussian filtering which has a certain halo effect. The reflection component is analyzed based on the illumination and reflection imaging model. A new prior named Max Intensity Channel (MIC) is implemented assuming that the reflections of some points in the scene are very high in at least one color channel. Using this prior, the illumination of the scene is obtained directly by performing a gray-scale closing operation and a fast cross-bilateral filtering on the MIC of the input color image. Consequently, the reflection component of each RGB color channel can be determined from the illumination and reflection imaging model. The proposed algorithm estimates the illumination component which is relatively smooth and maintains the edge details in different regions. A satisfactory color rendition is achieved for a class of images that do not satisfy the gray-world assumption implicit to the theoretical foundation of the retinex. Experiments are carried out to compare the new method with several spatial and transform domain methods. Our results indicate that the new method is superior in enhancement applications, improves computation speed, and performs well for images with high illumination variations than other methods. Further comparisons of images from National Aeronautics and Space Administration and a wearable camera eButton have shown a high performance of the new method with better color restoration and preservation of image details.

Ladar range image denoising by a nonlocal probability statistics algorithm

NASA Astrophysics Data System (ADS)

Xia, Zhi-Wei; Li, Qi; Xiong, Zhi-Peng; Wang, Qi

2013-01-01

According to the characteristic of range images of coherent ladar and the basis of nonlocal means (NLM), a nonlocal probability statistics (NLPS) algorithm is proposed in this paper. The difference is that NLM performs denoising using the mean of the conditional probability distribution function (PDF) while NLPS using the maximum of the marginal PDF. In the algorithm, similar blocks are found out by the operation of block matching and form a group. Pixels in the group are analyzed by probability statistics and the gray value with maximum probability is used as the estimated value of the current pixel. The simulated range images of coherent ladar with different carrier-to-noise ratio and real range image of coherent ladar with 8 gray-scales are denoised by this algorithm, and the results are compared with those of median filter, multitemplate order mean filter, NLM, median nonlocal mean filter and its incorporation of anatomical side information, and unsupervised information-theoretic adaptive filter. The range abnormality noise and Gaussian noise in range image of coherent ladar are effectively suppressed by NLPS.

The faintest speck of dirt: disgust enhances the detection of impurity.

PubMed

Sherman, Gary D; Haidt, Jonathan; Clore, Gerald L

2012-12-01

Purity is commonly regarded as being physically embodied in the color white, with even trivial deviations from whiteness indicating a loss of purity. In three studies, we explored the implications of this "white = pure" association for disgust, an emotion that motivates the detection and avoidance of impurities that threaten purity and cleanliness. We hypothesized that disgust tunes perception to prioritize the light end of the light-dark spectrum, which results in a relative hypersensitivity to changes in lightness in this range. In studies 1 and 2, greater sensitivity to disgusting stimuli was associated with greater ability to make subtle gray-scale discriminations (e.g., detecting a faint gray stimulus against a white background) at the light end of the spectrum relative to ability to make subtle gray-scale discriminations at the dark end of the spectrum. In study 3, after viewing disgusting images, disgust-sensitive individuals demonstrated a heightened ability to detect deviations from white. These findings suggest that disgust not only motivates people to avoid impurities, but actually makes them better able to see them.

Rotation And Scale Invariant Object Recognition Using A Distributed Associative Memory

NASA Astrophysics Data System (ADS)

Wechsler, Harry; Zimmerman, George Lee

1988-04-01

This paper describes an approach to 2-dimensional object recognition. Complex-log conformal mapping is combined with a distributed associative memory to create a system which recognizes objects regardless of changes in rotation or scale. Recalled information from the memorized database is used to classify an object, reconstruct the memorized version of the object, and estimate the magnitude of changes in scale or rotation. The system response is resistant to moderate amounts of noise and occlusion. Several experiments, using real, gray scale images, are presented to show the feasibility of our approach.

Reproducibility of sonographic measurement of thickness and echogenicity of the plantar fascia.

PubMed

Cheng, Ju-Wen; Tsai, Wen-Chung; Yu, Tung-Yang; Huang, Kuo-Yao

2012-01-01

To evaluate the intra- and interrater reliability of ultrasonographic measurements of the thickness and echogenicity of the plantar fascia. Eleven patients (20 feet), who complained of inferior heel pain, and 26 volunteers (52 feet) were enrolled. Two sonographers independently imaged the plantar fascia in both longitudinal and transverse planes. Volunteers were assessed twice to evaluate intrarater reliability. Quantitative evaluation of the echogenicity of the plantar fascia was performed by measuring the mean gray level of the region of interest using Digital Imaging and Communications in Medicine viewer software. Sonographic evaluation of the thickness of the plantar fascia showed high reliability. Sonographic evaluations of the presence or absence of hypoechoic change in the plantar fascia showed surprisingly low agreement. The reliability of gray-scale evaluations appears to be much better than subjective judgments in the evaluation of echogenicity. Transverse scanning did not show any advantage in sonographic evaluation of the plantar fascia. The reliability of sonographic examination of the thickness of the plantar fascia is high. Mean gray-level analysis of quantitative sonography can be used for the evaluation of echogenicity, which could reduce discrepancies in the interpretation of echogenicity by different sonographers. Longitudinal instead of transverse scanning is recommended for imaging the plantar fascia. Copyright © 2011 Wiley Periodicals, Inc.

A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners.

PubMed

Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

2013-01-01

Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.

Computed gray levels in multislice and cone-beam computed tomography.

PubMed

Azeredo, Fabiane; de Menezes, Luciane Macedo; Enciso, Reyes; Weissheimer, Andre; de Oliveira, Rogério Belle

2013-07-01

Gray level is the range of shades of gray in the pixels, representing the x-ray attenuation coefficient that allows for tissue density assessments in computed tomography (CT). An in-vitro study was performed to investigate the relationship between computed gray levels in 3 cone-beam CT (CBCT) scanners and 1 multislice spiral CT device using 5 software programs. Six materials (air, water, wax, acrylic, plaster, and gutta-percha) were scanned with the CBCT and CT scanners, and the computed gray levels for each material at predetermined points were measured with OsiriX Medical Imaging software (Geneva, Switzerland), OnDemand3D (CyberMed International, Seoul, Korea), E-Film (Merge Healthcare, Milwaukee, Wis), Dolphin Imaging (Dolphin Imaging & Management Solutions, Chatsworth, Calif), and InVivo Dental Software (Anatomage, San Jose, Calif). The repeatability of these measurements was calculated with intraclass correlation coefficients, and the gray levels were averaged to represent each material. Repeated analysis of variance tests were used to assess the differences in gray levels among scanners and materials. There were no differences in mean gray levels with the different software programs. There were significant differences in gray levels between scanners for each material evaluated (P <0.001). The software programs were reliable and had no influence on the CT and CBCT gray level measurements. However, the gray levels might have discrepancies when different CT and CBCT scanners are used. Therefore, caution is essential when interpreting or evaluating CBCT images because of the significant differences in gray levels between different CBCT scanners, and between CBCT and CT values. Copyright © 2013 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

RATIO_TOOL - SOFTWARE FOR COMPUTING IMAGE RATIOS

NASA Technical Reports Server (NTRS)

Yates, G. L.

1994-01-01

Geological studies analyze spectral data in order to gain information on surface materials. RATIO_TOOL is an interactive program for viewing and analyzing large multispectral image data sets that have been created by an imaging spectrometer. While the standard approach to classification of multispectral data is to match the spectrum for each input pixel against a library of known mineral spectra, RATIO_TOOL uses ratios of spectral bands in order to spot significant areas of interest within a multispectral image. Each image band can be viewed iteratively, or a selected image band of the data set can be requested and displayed. When the image ratios are computed, the result is displayed as a gray scale image. At this point a histogram option helps in viewing the distribution of values. A thresholding option can then be used to segment the ratio image result into two to four classes. The segmented image is then color coded to indicate threshold classes and displayed alongside the gray scale image. RATIO_TOOL is written in C language for Sun series computers running SunOS 4.0 and later. It requires the XView toolkit and the OpenWindows window manager (version 2.0 or 3.0). The XView toolkit is distributed with Open Windows. A color monitor is also required. The standard distribution medium for RATIO_TOOL is a .25 inch streaming magnetic tape cartridge in UNIX tar format. An electronic copy of the documentation is included on the program media. RATIO_TOOL was developed in 1992 and is a copyrighted work with all copyright vested in NASA. Sun, SunOS, and OpenWindows are trademarks of Sun Microsystems, Inc. UNIX is a registered trademark of AT&T Bell Laboratories.

Automatic counting and classification of bacterial colonies using hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Detection and counting of bacterial colonies on agar plates is a routine microbiology practice to get a rough estimate of the number of viable cells in a sample. There have been a variety of different automatic colony counting systems and software algorithms mainly based on color or gray-scale pictu...

Theoretical foundations of spatially-variant mathematical morphology part ii: gray-level images.

PubMed

Bouaynaya, Nidhal; Schonfeld, Dan

2008-05-01

In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the Euclidean space. The proposed theory preserves the geometrical concept of the structuring function, which provides the foundation of classical morphology and is essential in signal and image processing applications. We define the basic SV gray-level morphological operators (i.e., SV gray-level erosion, dilation, opening, and closing) and investigate their properties. We demonstrate the ubiquity of SV gray-level morphological systems by deriving a kernel representation for a large class of systems, called V-systems, in terms of the basic SV graylevel morphological operators. A V-system is defined to be a gray-level operator, which is invariant under gray-level (vertical) translations. Particular attention is focused on the class of SV flat gray-level operators. The kernel representation for increasing V-systems is a generalization of Maragos' kernel representation for increasing and translation-invariant function-processing systems. A representation of V-systems in terms of their kernel elements is established for increasing and upper-semi-continuous V-systems. This representation unifies a large class of spatially-variant linear and non-linear systems under the same mathematical framework. Finally, simulation results show the potential power of the general theory of gray-level spatially-variant mathematical morphology in several image analysis and computer vision applications.

GRAY: a program to calculate gray-body radiation heat-transfer view factors from black-body view factors

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

Wong, R. L.

1976-06-14

Program GRAY is written to perform the matrix manipulations necessary to convert black-body radiation heat-transfer view factors to gray-body view factors as required by thermal analyzer codes. The black-body view factors contain only geometric relationships. Program GRAY allows the effects of multiple gray-body reflections to be included. The resulting effective gray-body factors can then be used with the corresponding fourth-power temperature differences to obtain the net radiative heat flux. The program is written to accept a matrix input or the card image output generated by the black-body view factor program CNVUFAC. The resulting card image output generated by GRAY ismore » in a form usable by the TRUMP thermal analyzer.« less

Automatic image equalization and contrast enhancement using Gaussian mixture modeling.

PubMed

Celik, Turgay; Tjahjadi, Tardi

2012-01-01

In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution, and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equalized image is generated by transforming the pixels' gray levels in each input interval to the appropriate output gray-level interval according to the dominant Gaussian component and the cumulative distribution function of the input interval. To take account of the hypothesis that homogeneous regions in the image represent homogeneous silences (or set of Gaussian components) in the image histogram, the Gaussian components with small variances are weighted with smaller values than the Gaussian components with larger variances, and the gray-level distribution is also used to weight the components in the mapping of the input interval to the output interval. Experimental results show that the proposed algorithm produces better or comparable enhanced images than several state-of-the-art algorithms. Unlike the other algorithms, the proposed algorithm is free of parameter setting for a given dynamic range of the enhanced image and can be applied to a wide range of image types.

Differentiating the grades of thymic epithelial tumor malignancy using textural features of intratumoral heterogeneity via (18)F-FDG PET/CT.

PubMed

Lee, Hyo Sang; Oh, Jungsu S; Park, Young Soo; Jang, Se Jin; Choi, Ik Soo; Ryu, Jin-Sook

2016-05-01

We aimed to explore the ability of textural heterogeneity indices determined by (18)F-FDG PET/CT for grading the malignancy of thymic epithelial tumors (TETs). We retrospectively enrolled 47 patients with pathologically proven TETs who underwent pre-treatment (18)F-FDG PET/CT. TETs were classified by pathological results into three subgroups with increasing grades of malignancy: low-risk thymoma (LRT; WHO classification A, AB and B1), high-risk thymoma (B2 and B3), and thymic carcinoma (TC). Using (18)F-FDG PET/CT, we obtained conventional imaging indices including SUVmax and 20 intratumoral heterogeneity indices: i.e., four local-scale indices derived from the neighborhood gray-tone difference matrix (NGTDM), eight regional-scale indices from the gray-level run-length matrix (GLRLM), and eight regional-scale indices from the gray-level size zone matrix (GLSZM). Area under the receiver operating characteristic curve (AUC) was used to demonstrate the abilities of the imaging indices for differentiating subgroups. Multivariable logistic regression analysis was performed to show the independent significance of the textural indices. Combined criteria using optimal cutoff values of the SUVmax and a best-performing heterogeneity index were applied to investigate whether they improved differentiation between the subgroups. Most of the GLRLM and GLSZM indices and the SUVmax showed good or fair discrimination (AUC >0.7) with best performance for some of the GLRLM indices and the SUVmax, whereas the NGTDM indices showed relatively inferior performance. The discriminative ability of some of the GLSZM indices was independent from that of SUVmax in multivariate analysis. Combined use of the SUVmax and a GLSZM index improved positive predictive values for LRT and TC. Texture analysis of (18)F-FDG PET/CT scans has the potential to differentiate between TET tumor grades; regional-scale indices from GLRLM and GLSZM perform better than local-scale indices from the NGTDM. The SUVmax and heterogeneity indices may have complementary value in differentiating TET subgroups.

A method for evaluating image quality of monochrome and color displays based on luminance by use of a commercially available color digital camera

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

Tokurei, Shogo, E-mail: shogo.tokurei@gmail.com, E-mail: junjim@med.kyushu-u.ac.jp; Morishita, Junji, E-mail: shogo.tokurei@gmail.com, E-mail: junjim@med.kyushu-u.ac.jp

Purpose: The aim of this study is to propose a method for the quantitative evaluation of image quality of both monochrome and color liquid-crystal displays (LCDs) using a commercially available color digital camera. Methods: The intensities of the unprocessed red (R), green (G), and blue (B) signals of a camera vary depending on the spectral sensitivity of the image sensor used in the camera. For consistent evaluation of image quality for both monochrome and color LCDs, the unprocessed RGB signals of the camera were converted into gray scale signals that corresponded to the luminance of the LCD. Gray scale signalsmore » for the monochrome LCD were evaluated by using only the green channel signals of the camera. For the color LCD, the RGB signals of the camera were converted into gray scale signals by employing weighting factors (WFs) for each RGB channel. A line image displayed on the color LCD was simulated on the monochrome LCD by using a software application for subpixel driving in order to verify the WF-based conversion method. Furthermore, the results obtained by different types of commercially available color cameras and a photometric camera were compared to examine the consistency of the authors’ method. Finally, image quality for both the monochrome and color LCDs was assessed by measuring modulation transfer functions (MTFs) and Wiener spectra (WS). Results: The authors’ results demonstrated that the proposed method for calibrating the spectral sensitivity of the camera resulted in a consistent and reliable evaluation of the luminance of monochrome and color LCDs. The MTFs and WS showed different characteristics for the two LCD types owing to difference in the subpixel structure. The MTF in the vertical direction of the color LCD was superior to that of the monochrome LCD, although the WS in the vertical direction of the color LCD was inferior to that of the monochrome LCD as a result of luminance fluctuations in RGB subpixels. Conclusions: The authors’ method based on the use of a commercially available color camera is useful to evaluate and understand the display performances of both monochrome and color LCDs in radiology departments.« less

Changes in Fundus Autofluorescence after Anti-vascular Endothelial Growth Factor According to the Type of Choroidal Neovascularization in Age-related Macular Degeneration.

PubMed

Lee, Ji Young; Chung, Hyewon; Kim, Hyung Chan

2016-02-01

To describe the changes of fundus autofluorescence (FAF) in patients with age-related macular degeneration before and after intravitreal injection of anti-vascular endothelial growth factor according to the type of choroidal neovascularization (CNV) and to evaluate the correlation of FAF with spectral domain optical coherence tomography (SD-OCT) parameters and vision. This was a retrospective study. Twenty-one treatment-naïve patients with neovascular age-related macular degeneration were included. Study eyes were divided into two groups according to the type of CNV. Fourteen eyes were type 1 CNV and seven eyes were type 2 CNV. All eyes underwent a complete ophthalmologic examination, including an assessment of best-corrected visual acuity, SD-OCT, fluorescein angiography, and FAF imaging, before and 3 months after intravitreal anti-vascular endothelial growth factor injection. Gray scales of FAF image for CNV areas, delineated as in fluorescein angiography, were analyzed using the ImageJ program, which were adjusted by comparison with normal background areas. Correlation of changes in FAF with changes in SD-OCT parameters, including CNV thickness, photoreceptor inner and outer segment junction disruption length, external limiting membrane disruption length, central macular thickness, subretinal fluid, and intraretinal fluid were analyzed. Eyes with both type 1 and type 2 CNV showed reduced FAF before treatment. The mean gray scales (%) of type 1 and type 2 CNV were 52.20% and 42.55%, respectively. The background values were 106.72 and 96.86. After treatment, the mean gray scales (%) of type 1 CNV and type 2 CNV were changed to 57.61% (p = 0.005) and 57.93% (p = 0.008), respectively. After treatment, CNV thickness, central macular thickness, and inner and outer segment junction disruption length were decreased while FAF increased. FAF was noted to be reduced in eyes with newly diagnosed wet age-related macular degeneration, but increased after anti-vascular endothelial growth factor therapy regardless of CNV lesion type.

Correlations among Brain Gray Matter Volumes, Age, Gender, and Hemisphere in Healthy Individuals

PubMed Central

Taki, Yasuyuki; Thyreau, Benjamin; Kinomura, Shigeo; Sato, Kazunori; Goto, Ryoi; Kawashima, Ryuta; Fukuda, Hiroshi

2011-01-01

To determine the relationship between age and gray matter structure and how interactions between gender and hemisphere impact this relationship, we examined correlations between global or regional gray matter volume and age, including interactions of gender and hemisphere, using a general linear model with voxel-based and region-of-interest analyses. Brain magnetic resonance images were collected from 1460 healthy individuals aged 20–69 years; the images were linearly normalized and segmented and restored to native space for analysis of global gray matter volume. Linearly normalized images were then non-linearly normalized and smoothed for analysis of regional gray matter volume. Analysis of global gray matter volume revealed a significant negative correlation between gray matter ratio (gray matter volume divided by intracranial volume) and age in both genders, and a significant interaction effect of age × gender on the gray matter ratio. In analyzing regional gray matter volume, the gray matter volume of all regions showed significant main effects of age, and most regions, with the exception of several including the inferior parietal lobule, showed a significant age × gender interaction. Additionally, the inferior temporal gyrus showed a significant age × gender × hemisphere interaction. No regional volumes showed significant age × hemisphere interactions. Our study may contribute to clarifying the mechanism(s) of normal brain aging in each brain region. PMID:21818377

3M's Dry Silver technology: an ideal media for electronic imaging

NASA Astrophysics Data System (ADS)

Morgan, David A.

1991-08-01

In recent years there has been great interest and growth in the ability to create images electronically. This trend has been driven by the lower cost of computing and storing data, and the speed in which this can be accomplished. The ability to scan, create, and transmit color images is possible even with the enormous amount of data needed to create color images with gray scale and high resolution. In the past, there has not been a great demand for color copiers because few color images were in existence. The above-mentioned trend is changing this, and in addition scanners can quickly translate color graphics into electronic forms at affordable costs. The replacement of black and white televisions and monitors with color was rapid and nearly 100% once the technology was available at a reasonable cost. It is felt by some equipment manufacturers that soft copy will replace hard copy and there will be a diminishing need for imaging media. The author believes, however, that the need for hard copy will continue, and in fact may increase, but with new technology. To create black and white or color hard copy from electronically generated data, some essential characteristics are needed. They are: (1) total dryness, (2) rapid access, (3) gray scale, (4) high resolution, (5) good image quality, and (6) easy to use, low-cost, reliable equipment. Some of the leading technologies for this are electrostatic, thermal dye transfer, ink jet, instant silver photography, and 3M's Dry Silver. This paper gives a general overview of these technologies, but its main emphasis is 3M's Dry Silver approach.

Snakeskin Terrain

NASA Image and Video Library

2015-09-24

In this extended color image of Pluto taken by NASA New Horizons spacecraft, rounded and bizarrely textured mountains, informally named the Tartarus Dorsa, rise up along Pluto's day-night terminator and show intricate but puzzling patterns of blue-gray ridges and reddish material in between. This view, roughly 330 miles (530 kilometers) across, combines blue, red and infrared images taken by the Ralph/Multispectral Visual Imaging Camera (MVIC) on July 14, 2015, and resolves details and colors on scales as small as 0.8 miles (1.3 kilometers). http://photojournal.jpl.nasa.gov/catalog/PIA19957

Role of "the frame cycle time" in portal dose imaging using an aS500-II EPID.

PubMed

Al Kattar Elbalaa, Zeina; Foulquier, Jean Noel; Orthuon, Alexandre; Elbalaa, Hanna; Touboul, Emmanuel

2009-09-01

This paper evaluates the role of an acquisition parameter, the frame cycle time "FCT", in the performance of an aS500-II EPID. The work presented rests on the study of the Varian EPID aS500-II and the image acquisition system 3 (IAS3). We are interested in integrated acquisition using asynchronous mode. For better understanding the image acquisition operation, we investigated the influence of the "frame cycle time" on the speed of acquisition, the pixel value of the averaged gray-scale frame and the noise, using 6 and 15MV X-ray beams and dose rates of 1-6Gy/min on 2100 C/D Linacs. In the integrated mode not synchronized to beam pulses, only one parameter the frame cycle time "FCT" influences the pixel value. The pixel value of the averaged gray-scale frame is proportional to this parameter. When the FCT <55ms (speed of acquisition V(f/s)>18 frames/s), the speed of acquisition becomes unstable and leads to a fluctuation of the portal dose response. A timing instability and saturation are detected when the dose per frame exceeds 1.53MU/frame. Rules were deduced to avoid saturation and to optimize this dosimetric mode. The choice of the acquisition parameter is essential for the accurate portal dose imaging.

Estimated spectrum adaptive postfilter and the iterative prepost filtering algirighms

NASA Technical Reports Server (NTRS)

Linares, Irving (Inventor)

2004-01-01

The invention presents The Estimated Spectrum Adaptive Postfilter (ESAP) and the Iterative Prepost Filter (IPF) algorithms. These algorithms model a number of image-adaptive post-filtering and pre-post filtering methods. They are designed to minimize Discrete Cosine Transform (DCT) blocking distortion caused when images are highly compressed with the Joint Photographic Expert Group (JPEG) standard. The ESAP and the IPF techniques of the present invention minimize the mean square error (MSE) to improve the objective and subjective quality of low-bit-rate JPEG gray-scale images while simultaneously enhancing perceptual visual quality with respect to baseline JPEG images.

Integrated clinical workstations for image and text data capture, display, and teleconsultation.

PubMed Central

Dayhoff, R.; Kuzmak, P. M.; Kirin, G.

1994-01-01

The Department of Veterans Affairs (VA) DHCP Imaging System digitally records clinically significant diagnostic images selected by medical specialists in a variety of hospital departments, including radiology, cardiology, gastroenterology, pathology, dermatology, hematology, surgery, podiatry, dental clinic, and emergency room. These images, which include true color and gray scale images, scanned documents, and electrocardiogram waveforms, are stored on network file servers and displayed on workstations located throughout a medical center. All images are managed by the VA's hospital information system (HIS), allowing integrated displays of text and image data from all medical specialties. Two VA medical centers currently have DHCP Imaging Systems installed, and other installations are underway. PMID:7949899

Statistical-techniques-based computer-aided diagnosis (CAD) using texture feature analysis: application in computed tomography (CT) imaging to fatty liver disease

NASA Astrophysics Data System (ADS)

Chung, Woon-Kwan; Park, Hyong-Hu; Im, In-Chul; Lee, Jae-Seung; Goo, Eun-Hoe; Dong, Kyung-Rae

2012-09-01

This paper proposes a computer-aided diagnosis (CAD) system based on texture feature analysis and statistical wavelet transformation technology to diagnose fatty liver disease with computed tomography (CT) imaging. In the target image, a wavelet transformation was performed for each lesion area to set the region of analysis (ROA, window size: 50 × 50 pixels) and define the texture feature of a pixel. Based on the extracted texture feature values, six parameters (average gray level, average contrast, relative smoothness, skewness, uniformity, and entropy) were determined to calculate the recognition rate for a fatty liver. In addition, a multivariate analysis of the variance (MANOVA) method was used to perform a discriminant analysis to verify the significance of the extracted texture feature values and the recognition rate for a fatty liver. According to the results, each texture feature value was significant for a comparison of the recognition rate for a fatty liver ( p < 0.05). Furthermore, the F-value, which was used as a scale for the difference in recognition rates, was highest in the average gray level, relatively high in the skewness and the entropy, and relatively low in the uniformity, the relative smoothness and the average contrast. The recognition rate for a fatty liver had the same scale as that for the F-value, showing 100% (average gray level) at the maximum and 80% (average contrast) at the minimum. Therefore, the recognition rate is believed to be a useful clinical value for the automatic detection and computer-aided diagnosis (CAD) using the texture feature value. Nevertheless, further study on various diseases and singular diseases will be needed in the future.

Imaging Findings Associated with Cognitive Performance in Primary Lateral Sclerosis and Amyotrophic Lateral Sclerosis

PubMed Central

Meoded, Avner; Kwan, Justin Y.; Peters, Tracy L.; Huey, Edward D.; Danielian, Laura E.; Wiggs, Edythe; Morrissette, Arthur; Wu, Tianxia; Russell, James W.; Bayat, Elham; Grafman, Jordan; Floeter, Mary Kay

2013-01-01

Introduction Executive dysfunction occurs in many patients with amyotrophic lateral sclerosis (ALS), but it has not been well studied in primary lateral sclerosis (PLS). The aims of this study were to (1) compare cognitive function in PLS to that in ALS patients, (2) explore the relationship between performance on specific cognitive tests and diffusion tensor imaging (DTI) metrics of white matter tracts and gray matter volumes, and (3) compare DTI metrics in patients with and without cognitive and behavioral changes. Methods The Delis-Kaplan Executive Function System (D-KEFS), the Mattis Dementia Rating Scale (DRS-2), and other behavior and mood scales were administered to 25 ALS patients and 25 PLS patients. Seventeen of the PLS patients, 13 of the ALS patients, and 17 healthy controls underwent structural magnetic resonance imaging (MRI) and DTI. Atlas-based analysis using MRI Studio software was used to measure fractional anisotropy, and axial and radial diffusivity of selected white matter tracts. Voxel-based morphometry was used to assess gray matter volumes. The relationship between diffusion properties of selected association and commissural white matter and performance on executive function and memory tests was explored using a linear regression model. Results More ALS than PLS patients had abnormal scores on the DRS-2. DRS-2 and D-KEFS scores were related to DTI metrics in several long association tracts and the callosum. Reduced gray matter volumes in motor and perirolandic areas were not associated with cognitive scores. Conclusion The changes in diffusion metrics of white matter long association tracts suggest that the loss of integrity of the networks connecting fronto-temporal areas to parietal and occipital areas contributes to cognitive impairment. PMID:24052798

DISRUPTION OF LARGE-SCALE NEURAL NETWORKS IN NON-FLUENT/AGRAMMATIC VARIANT PRIMARY PROGRESSIVE APHASIA ASSOCIATED WITH FRONTOTEMPORAL DEGENERATION PATHOLOGY

PubMed Central

Grossman, Murray; Powers, John; Ash, Sherry; McMillan, Corey; Burkholder, Lisa; Irwin, David; Trojanowski, John Q.

2012-01-01

Non-fluent/agrammatic primary progressive aphasia (naPPA) is a progressive neurodegenerative condition most prominently associated with slowed, effortful speech. A clinical imaging marker of naPPA is disease centered in the left inferior frontal lobe. We used multimodal imaging to assess large-scale neural networks underlying effortful expression in 15 patients with sporadic naPPA due to frontotemporal lobar degeneration (FTLD) spectrum pathology. Effortful speech in these patients is related in part to impaired grammatical processing, and to phonologic speech errors. Gray matter (GM) imaging shows frontal and anterior-superior temporal atrophy, most prominently in the left hemisphere. Diffusion tensor imaging reveals reduced fractional anisotropy in several white matter (WM) tracts mediating projections between left frontal and other GM regions. Regression analyses suggest disruption of three large-scale GM-WM neural networks in naPPA that support fluent, grammatical expression. These findings emphasize the role of large-scale neural networks in language, and demonstrate associated language deficits in naPPA. PMID:23218686

Recognition of Roasted Coffee Bean Levels using Image Processing and Neural Network

NASA Astrophysics Data System (ADS)

Nasution, T. H.; Andayani, U.

2017-03-01

The coffee beans roast levels have some characteristics. However, some people cannot recognize the coffee beans roast level. In this research, we propose to design a method to recognize the coffee beans roast level of images digital by processing the image and classifying with backpropagation neural network. The steps consist of how to collect the images data with image acquisition, pre-processing, feature extraction using Gray Level Co-occurrence Matrix (GLCM) method and finally normalization of data extraction using decimal scaling features. The values of decimal scaling features become an input of classifying in backpropagation neural network. We use the method of backpropagation to recognize the coffee beans roast levels. The results showed that the proposed method is able to identify the coffee roasts beans level with an accuracy of 97.5%.

Investigation of varying gray scale levels for remote manipulation

NASA Technical Reports Server (NTRS)

Bierschwale, John M.; Stuart, Mark A.; Sampaio, Carlos E.

1991-01-01

A study was conducted to investigate the effects of variant monitor gray scale levels and workplace illumination levels on operators' ability to discriminate between different colors on a monochrome monitor. It was determined that 8-gray scale viewing resulted in significantly worse discrimination performance compared to 16- and 32-gray scale viewing and that there was only a negligible difference found between 16 and 32 shades of gray. Therefore, it is recommended that monitors used while performing remote manipulation tasks have 16 or above shades of gray since this evaluation has found levels lower than this to be unacceptable for color discrimination task. There was no significant performance difference found between a high and a low workplace illumination condition. Further analysis was conducted to determine which specific combinations of colors can be used in conjunction with each other to ensure errorfree color coding/brightness discrimination performance while viewing a monochrome monitor. It was found that 92 three-color combination and 9 four-color combinations could be used with 100 percent accuracy. The results can help to determine which gray scale levels should be provided on monochrome monitors as well as which colors to use to ensure the maximal performance of remotely-viewed color discrimination/coding tasks.

Comparing features sets for content-based image retrieval in a medical-case database

NASA Astrophysics Data System (ADS)

Muller, Henning; Rosset, Antoine; Vallee, Jean-Paul; Geissbuhler, Antoine

2004-04-01

Content-based image retrieval systems (CBIRSs) have frequently been proposed for the use in medical image databases and PACS. Still, only few systems were developed and used in a real clinical environment. It rather seems that medical professionals define their needs and computer scientists develop systems based on data sets they receive with little or no interaction between the two groups. A first study on the diagnostic use of medical image retrieval also shows an improvement in diagnostics when using CBIRSs which underlines the potential importance of this technique. This article explains the use of an open source image retrieval system (GIFT - GNU Image Finding Tool) for the retrieval of medical images in the medical case database system CasImage that is used in daily, clinical routine in the university hospitals of Geneva. Although the base system of GIFT shows an unsatisfactory performance, already little changes in the feature space show to significantly improve the retrieval results. The performance of variations in feature space with respect to color (gray level) quantizations and changes in texture analysis (Gabor filters) is compared. Whereas stock photography relies mainly on colors for retrieval, medical images need a large number of gray levels for successful retrieval, especially when executing feedback queries. The results also show that a too fine granularity in the gray levels lowers the retrieval quality, especially with single-image queries. For the evaluation of the retrieval peformance, a subset of the entire case database of more than 40,000 images is taken with a total of 3752 images. Ground truth was generated by a user who defined the expected query result of a perfect system by selecting images relevant to a given query image. The results show that a smaller number of gray levels (32 - 64) leads to a better retrieval performance, especially when using relevance feedback. The use of more scales and directions for the Gabor filters in the texture analysis also leads to improved results but response time is going up equally due to the larger feature space. CBIRSs can be of great use in managing large medical image databases. They allow to find images that might otherwise be lost for research and publications. They also give students students the possibility to navigate within large image repositories. In the future, CBIR might also become more important in case-based reasoning and evidence-based medicine to support the diagnostics because first studies show good results.

Self-calibration of a noisy multiple-sensor system with genetic algorithms

NASA Astrophysics Data System (ADS)

Brooks, Richard R.; Iyengar, S. Sitharama; Chen, Jianhua

1996-01-01

This paper explores an image processing application of optimization techniques which entails interpreting noisy sensor data. The application is a generalization of image correlation; we attempt to find the optimal gruence which matches two overlapping gray-scale images corrupted with noise. Both taboo search and genetic algorithms are used to find the parameters which match the two images. A genetic algorithm approach using an elitist reproduction scheme is found to provide significantly superior results. The presentation includes a graphic presentation of the paths taken by tabu search and genetic algorithms when trying to find the best possible match between two corrupted images.

Adaptive histogram equalization in digital radiography of destructive skeletal lesions.

PubMed

Braunstein, E M; Capek, P; Buckwalter, K; Bland, P; Meyer, C R

1988-03-01

Adaptive histogram equalization, an image-processing technique that distributes pixel values of an image uniformly throughout the gray scale, was applied to 28 plain radiographs of bone lesions, after they had been digitized. The non-equalized and equalized digital images were compared by two skeletal radiologists with respect to lesion margins, internal matrix, soft-tissue mass, cortical breakthrough, and periosteal reaction. Receiver operating characteristic (ROC) curves were constructed on the basis of the responses. Equalized images were superior to nonequalized images in determination of cortical breakthrough and presence or absence of periosteal reaction. ROC analysis showed no significant difference in determination of margins, matrix, or soft-tissue masses.

Ultrasound artifacts: classification, applied physics with illustrations, and imaging appearances.

PubMed

Prabhu, Somnath J; Kanal, Kalpana; Bhargava, Puneet; Vaidya, Sandeep; Dighe, Manjiri K

2014-06-01

Ultrasound has become a widely used diagnostic imaging modality in medicine because of its safety and portability. Because of rapid advances in technology, in recent years, sonographic imaging quality has significantly increased. Despite these advances, the potential to encounter artifacts while imaging remains.This article classifies both common and uncommon gray-scale and Doppler ultrasound artifacts into those resulting from physiology and those caused by hardware. A brief applied-physics explanation for each artifact is listed along with an illustrated diagram. The imaging appearance of artifacts is presented in case examples, along with strategies to minimize the artifacts in real time or use them for clinical advantage where applicable.

Interface control document between the NASA Goddard Space Flight Center (GSFC) and Department of Interior EROS Data Center (EDC) for LANDSAT-D. Thematic mapper high resolution 241 mm film

NASA Technical Reports Server (NTRS)

1982-01-01

The 241 mm photographic product produced by the Goddard Space Flight Center Data Management System for LANDSAT-D is described. Film type and format, image dimensions, frame ID, gray scale, resolution patterns, registration marks, etc. are addressed.

A modular approach to detection and identification of defects in rough lumber

Treesearch

Sang Mook Lee; A. Lynn Abbott; Daniel L. Schmoldt

2001-01-01

This paper describes a prototype scanning system that can automatically identify several important defects on rough hardwood lumber. The scanning system utilizes 3 laser sources and an embedded-processor camera to capture and analyze profile and gray-scale images. The modular approach combines the detection of wane (the curved sides of a board, possibly containing...

Gray-level transformations for interactive image enhancement. M.S. Thesis. Final Technical Report

NASA Technical Reports Server (NTRS)

Fittes, B. A.

1975-01-01

A gray-level transformation method suitable for interactive image enhancement was presented. It is shown that the well-known histogram equalization approach is a special case of this method. A technique for improving the uniformity of a histogram is also developed. Experimental results which illustrate the capabilities of both algorithms are described. Two proposals for implementing gray-level transformations in a real-time interactive image enhancement system are also presented.

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

Performance assessment of methods for estimation of fractal dimension from scanning electron microscope images.

PubMed

Risović, Dubravko; Pavlović, Zivko

2013-01-01

Processing of gray scale images in order to determine the corresponding fractal dimension is very important due to widespread use of imaging technologies and application of fractal analysis in many areas of science, technology, and medicine. To this end, many methods for estimation of fractal dimension from gray scale images have been developed and routinely used. Unfortunately different methods (dimension estimators) often yield significantly different results in a manner that makes interpretation difficult. Here, we report results of comparative assessment of performance of several most frequently used algorithms/methods for estimation of fractal dimension. To that purpose, we have used scanning electron microscope images of aluminum oxide surfaces with different fractal dimensions. The performance of algorithms/methods was evaluated using the statistical Z-score approach. The differences between performances of six various methods are discussed and further compared with results obtained by electrochemical impedance spectroscopy on the same samples. The analysis of results shows that the performance of investigated algorithms varies considerably and that systematically erroneous fractal dimensions could be estimated using certain methods. The differential cube counting, triangulation, and box counting algorithms showed satisfactory performance in the whole investigated range of fractal dimensions. Difference statistic is proved to be less reliable generating 4% of unsatisfactory results. The performances of the Power spectrum, Partitioning and EIS were unsatisfactory in 29%, 38%, and 75% of estimations, respectively. The results of this study should be useful and provide guidelines to researchers using/attempting fractal analysis of images obtained by scanning microscopy or atomic force microscopy. © Wiley Periodicals, Inc.

Quantitative evaluation of low-cost frame-grabber boards for personal computers.

PubMed

Kofler, J M; Gray, J E; Fuelberth, J T; Taubel, J P

1995-11-01

Nine moderately priced frame-grabber boards for both Macintosh (Apple Computers, Cupertino, CA) and IBM-compatible computers were evaluated using a Society of Motion Pictures and Television Engineers (SMPTE) pattern and a video signal generator for dynamic range, gray-scale reproducibility, and spatial integrity of the captured image. The degradation of the video information ranged from minor to severe. Some boards are of reasonable quality for applications in diagnostic imaging and education. However, price and quality are not necessarily directly related.

State-of-the-art for large area high resolution gray scale and full color AC plasma flat panel displays

NASA Technical Reports Server (NTRS)

Stoller, Ray A.; Wedding, Donald K.; Friedman, Peter S.

1993-01-01

A development status evaluation is presented for gas plasma display technology, noting how tradeoffs among the parameters of size, resolution, speed, portability, color, and image quality can yield cost-effective solutions for medical imaging, CAD, teleconferencing, multimedia, and both civil and military applications. Attention is given to plasma-based large-area displays' suitability for radar, sonar, and IR, due to their lack of EM susceptibility. Both monochrome and color displays are available.

Comparison of gray matter volume and thickness for analysis of cortical changes in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Liu, Jiachao; Li, Ziyi; Chen, Kewei; Yao, Li; Wang, Zhiqun; Li, Kunchen; Guo, Xiaojuan

2011-03-01

Gray matter volume and cortical thickness are two indices of concern in brain structure magnetic resonance imaging research. Gray matter volume reflects mixed-measurement information of cerebral cortex, while cortical thickness reflects only the information of distance between inner surface and outer surface of cerebral cortex. Using Scaled Subprofile Modeling based on Principal Component Analysis (SSM_PCA) and Pearson's Correlation Analysis, this study further provided quantitative comparisons and depicted both global relevance and local relevance to comprehensively investigate morphometrical abnormalities in cerebral cortex in Alzheimer's disease (AD). Thirteen patients with AD and thirteen age- and gender-matched healthy controls were included in this study. Results showed that factor scores from the first 8 principal components accounted for ~53.38% of the total variance for gray matter volume, and ~50.18% for cortical thickness. Factor scores from the fifth principal component showed significant correlation. In addition, gray matter voxel-based volume was closely related to cortical thickness alterations in most cortical cortex, especially, in some typical abnormal brain regions such as insula and the parahippocampal gyrus in AD. These findings suggest that these two measurements are effective indices for understanding the neuropathology in AD. Studies using both gray matter volume and cortical thickness can separate the causes of the discrepancy, provide complementary information and carry out a comprehensive description of the morphological changes of brain structure.

Segmentation of white rat sperm image

NASA Astrophysics Data System (ADS)

Bai, Weiguo; Liu, Jianguo; Chen, Guoyuan

2011-11-01

The segmentation of sperm image exerts a profound influence in the analysis of sperm morphology, which plays a significant role in the research of animals' infertility and reproduction. To overcome the microscope image's properties of low contrast and highly polluted noise, and to get better segmentation results of sperm image, this paper presents a multi-scale gradient operator combined with a multi-structuring element for the micro-spermatozoa image of white rat, as the multi-scale gradient operator can smooth the noise of an image, while the multi-structuring element can retain more shape details of the sperms. Then, we use the Otsu method to segment the modified gradient image whose gray scale processed is strong in sperms and weak in the background, converting it into a binary sperm image. As the obtained binary image owns impurities that are not similar with sperms in the shape, we choose a form factor to filter those objects whose form factor value is larger than the select critical value, and retain those objects whose not. And then, we can get the final binary image of the segmented sperms. The experiment shows this method's great advantage in the segmentation of the micro-spermatozoa image.

Occulting focal plane masks for Terrestrial Planet Finder Coronagraph: design, fabrication, simulations and test results

NASA Technical Reports Server (NTRS)

Balasubramanian, Kunjithapatham; Hoppe, Daniel J.; Halverson, Peter G.; Wilson, Daniel W.; Echternach, Pierre M.; Shi, Fang; Lowman, Andrew E.; Niessner, Albert F.; Trauger, John T.; Shaklan, Stuart B.

2005-01-01

Occulting focal plane masks for the Terrestrial Planet Finder Coronagraph (TPF-C) could be designed with continuous gray scale profile of the occulting pattern such as 1-sinc2 on a suitable material or with micron-scale binary transparent and opaque structures of metallic pattern on glass. We have designed, fabricated and tested both kinds of masks. The fundamental characteristics of such masks and initial test results from the High Contrast Imaging Test bed (HCIT) at JPL are presented.

Wavelet Transforms in Parallel Image Processing

DTIC Science & Technology

1994-01-27

NUMBER OF PAGES Object Segmentation, Texture Segmentation, Image Compression, Image 137 Halftoning , Neural Network, Parallel Algorithms, 2D and 3D...Vector Quantization of Wavelet Transform Coefficients ........ ............................. 57 B.1.f Adaptive Image Halftoning based on Wavelet...application has been directed to the adaptive image halftoning . The gray information at a pixel, including its gray value and gradient, is represented by

Histological Underpinnings of Grey Matter Changes in Fibromyalgia Investigated Using Multimodal Brain Imaging.

PubMed

Pomares, Florence B; Funck, Thomas; Feier, Natasha A; Roy, Steven; Daigle-Martel, Alexandre; Ceko, Marta; Narayanan, Sridar; Araujo, David; Thiel, Alexander; Stikov, Nikola; Fitzcharles, Mary-Ann; Schweinhardt, Petra

2017-02-01

Chronic pain patients present with cortical gray matter alterations, observed with anatomical magnetic resonance (MR) imaging. Reduced regional gray matter volumes are often interpreted to reflect neurodegeneration, but studies investigating the cellular origin of gray matter changes are lacking. We used multimodal imaging to compare 26 postmenopausal women with fibromyalgia with 25 healthy controls (age range: 50-75 years) to test whether regional gray matter volume decreases in chronic pain are associated with compromised neuronal integrity. Regional gray matter decreases were largely explained by T1 relaxation times in gray matter, a surrogate measure of water content, and not to any substantial degree by GABA A receptor concentration, an indirect marker of neuronal integrity measured with [ 18 F] flumazenil PET. In addition, the MR spectroscopy marker of neuronal viability, N-acetylaspartate, did not differ between patients and controls. These findings suggest that decreased gray matter volumes are not explained by compromised neuronal integrity. Alternatively, a decrease in neuronal matter could be compensated for by an upregulation of GABA A receptors. The relation between regional gray matter and T1 relaxation times suggests decreased tissue water content underlying regional gray matter decreases. In contrast, regional gray matter increases were explained by GABA A receptor concentration in addition to T1 relaxation times, indicating perhaps increased neuronal matter or GABA A receptor upregulation and inflammatory edema. By providing information on the histological origins of cerebral gray matter alterations in fibromyalgia, this study advances the understanding of the neurobiology of chronic widespread pain. Regional gray matter alterations in chronic pain, as detected with voxel-based morphometry of anatomical magnetic resonance images, are commonly interpreted to reflect neurodegeneration, but this assumption has not been tested. We found decreased gray matter in fibromyalgia to be associated with T1 relaxation times, a surrogate marker of water content, but not with GABA A receptor concentration, a surrogate of neuronal integrity. In contrast, regional gray matter increases were partly explained by GABA A receptor concentration, indicating some form of neuronal plasticity. The study emphasizes that voxel-based morphometry is an exploratory measure, demonstrating the need to investigate the histological origin of gray matter alterations for every distinct clinical entity, and advances the understanding of the neurobiology of chronic (widespread) pain. Copyright © 2017 the authors 0270-6474/17/371091-12$15.00/0.

Color segmentation in the HSI color space using the K-means algorithm

NASA Astrophysics Data System (ADS)

Weeks, Arthur R.; Hague, G. Eric

1997-04-01

Segmentation of images is an important aspect of image recognition. While grayscale image segmentation has become quite a mature field, much less work has been done with regard to color image segmentation. Until recently, this was predominantly due to the lack of available computing power and color display hardware that is required to manipulate true color images (24-bit). TOday, it is not uncommon to find a standard desktop computer system with a true-color 24-bit display, at least 8 million bytes of memory, and 2 gigabytes of hard disk storage. Segmentation of color images is not as simple as segmenting each of the three RGB color components separately. The difficulty of using the RGB color space is that it doesn't closely model the psychological understanding of color. A better color model, which closely follows that of human visual perception is the hue, saturation, intensity model. This color model separates the color components in terms of chromatic and achromatic information. Strickland et al. was able to show the importance of color in the extraction of edge features form an image. His method enhances the edges that are detectable in the luminance image with information from the saturation image. Segmentation of both the saturation and intensity components is easily accomplished with any gray scale segmentation algorithm, since these spaces are linear. The modulus 2(pi) nature of the hue color component makes its segmentation difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Instead of applying separate image segmentation to each of the hue, saturation, and intensity components, a better method is to segment the chromatic component separately from the intensity component because of the importance that the chromatic information plays in the segmentation of color images. This paper presents a method of using the gray scale K-means algorithm to segment 24-bit color images. Additionally, this paper will show the importance the hue component plays in the segmentation of color images.

The Research of Feature Extraction Method of Liver Pathological Image Based on Multispatial Mapping and Statistical Properties

PubMed Central

Liu, Huiling; Xia, Bingbing; Yi, Dehui

2016-01-01

We propose a new feature extraction method of liver pathological image based on multispatial mapping and statistical properties. For liver pathological images of Hematein Eosin staining, the image of R and B channels can reflect the sensitivity of liver pathological images better, while the entropy space and Local Binary Pattern (LBP) space can reflect the texture features of the image better. To obtain the more comprehensive information, we map liver pathological images to the entropy space, LBP space, R space, and B space. The traditional Higher Order Local Autocorrelation Coefficients (HLAC) cannot reflect the overall information of the image, so we propose an average correction HLAC feature. We calculate the statistical properties and the average gray value of pathological images and then update the current pixel value as the absolute value of the difference between the current pixel gray value and the average gray value, which can be more sensitive to the gray value changes of pathological images. Lastly the HLAC template is used to calculate the features of the updated image. The experiment results show that the improved features of the multispatial mapping have the better classification performance for the liver cancer. PMID:27022407

Image Description with Local Patterns: An Application to Face Recognition

NASA Astrophysics Data System (ADS)

Zhou, Wei; Ahrary, Alireza; Kamata, Sei-Ichiro

In this paper, we propose a novel approach for presenting the local features of digital image using 1D Local Patterns by Multi-Scans (1DLPMS). We also consider the extentions and simplifications of the proposed approach into facial images analysis. The proposed approach consists of three steps. At the first step, the gray values of pixels in image are represented as a vector giving the local neighborhood intensity distrubutions of the pixels. Then, multi-scans are applied to capture different spatial information on the image with advantage of less computation than other traditional ways, such as Local Binary Patterns (LBP). The second step is encoding the local features based on different encoding rules using 1D local patterns. This transformation is expected to be less sensitive to illumination variations besides preserving the appearance of images embedded in the original gray scale. At the final step, Grouped 1D Local Patterns by Multi-Scans (G1DLPMS) is applied to make the proposed approach computationally simpler and easy to extend. Next, we further formulate boosted algorithm to extract the most discriminant local features. The evaluated results demonstrate that the proposed approach outperforms the conventional approaches in terms of accuracy in applications of face recognition, gender estimation and facial expression.

Low-Speed Fingerprint Image Capture System User`s Guide, June 1, 1993

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

Whitus, B.R.; Goddard, J.S.; Jatko, W.B.

1993-06-01

The Low-Speed Fingerprint Image Capture System (LS-FICS) uses a Sun workstation controlling a Lenzar ElectroOptics Opacity 1000 imaging system to digitize fingerprint card images to support the Federal Bureau of Investigation`s (FBI`s) Automated Fingerprint Identification System (AFIS) program. The system also supports the operations performed by the Oak Ridge National Laboratory- (ORNL-) developed Image Transmission Network (ITN) prototype card scanning system. The input to the system is a single FBI fingerprint card of the agreed-upon standard format and a user-specified identification number. The output is a file formatted to be compatible with the National Institute of Standards and Technology (NIST)more » draft standard for fingerprint data exchange dated June 10, 1992. These NIST compatible files contain the required print and text images. The LS-FICS is designed to provide the FBI with the capability of scanning fingerprint cards into a digital format. The FBI will replicate the system to generate a data base of test images. The Host Workstation contains the image data paths and the compression algorithm. A local area network interface, disk storage, and tape drive are used for the image storage and retrieval, and the Lenzar Opacity 1000 scanner is used to acquire the image. The scanner is capable of resolving 500 pixels/in. in both x and y directions. The print images are maintained in full 8-bit gray scale and compressed with an FBI-approved wavelet-based compression algorithm. The text fields are downsampled to 250 pixels/in. and 2-bit gray scale. The text images are then compressed using a lossless Huffman coding scheme. The text fields retrieved from the output files are easily interpreted when displayed on the screen. Detailed procedures are provided for system calibration and operation. Software tools are provided to verify proper system operation.« less

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

PubMed

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

2017-04-01

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

A cross-sectional and follow-up voxel-based morphometric MRI study in adolescent anorexia nervosa.

PubMed

Castro-Fornieles, Josefina; Bargalló, Nuria; Lázaro, Luisa; Andrés, Susana; Falcon, Carles; Plana, Maria Teresa; Junqué, Carme

2009-01-01

The objective was to examine whether cerebral volumes are reduced, and in what regions, in adolescents with anorexia nervosa and to study changes after nutritional recovery. Twelve anorexia nervosa (DSM-IV) patients aged 11-17 consecutively admitted to an Eating Disorders Unit were assessed by means of psychopathological scales, neuropsychological battery and voxel-based morphometric (VBM) magnetic resonance imaging at admission and after 7 months' follow-up. Nine control subjects of similar age, gender and estimated intelligence level were also studied. The two groups showed differences in gray matter (F=22.2; p<0.001) and cerebrospinal fluid (CSF) (F=21.2; p<0.001) but not in white matter volumes. In anorexic patients, gray matter volume correlated negatively with the copy time from the Rey Complex Figure Test. In the regional VBM study several temporal and parietal gray matter regions were reduced. During follow-up there was a greater global increase in gray matter (F=10.7; p=0.004) and decrease in CSF (F=22.1; p=0.001) in anorexic patients. The increase in gray matter correlated with a decrease in cortisol (Spearman correlation=-0.73; p=0.017). At follow-up there were no differences in global gray matter (F=2.1; p=0.165), white matter (F=0.02, p=0.965) or CSF (F=1.8; p=0.113) volumes between both groups. There were still some smaller areas, in the right temporal and both supplementary motor area, showing differences between them in the regional VBM study. In conclusion, in adolescent anorexic patients gray matter is more affected than white matter and mainly involves the posterior regions of the brain. Overall gray matter alterations are reversible after nutritional recovery.

Texture classification using non-Euclidean Minkowski dilation

NASA Astrophysics Data System (ADS)

Florindo, Joao B.; Bruno, Odemir M.

2018-03-01

This study presents a new method to extract meaningful descriptors of gray-scale texture images using Minkowski morphological dilation based on the Lp metric. The proposed approach is motivated by the success previously achieved by Bouligand-Minkowski fractal descriptors on texture classification. In essence, such descriptors are directly derived from the morphological dilation of a three-dimensional representation of the gray-level pixels using the classical Euclidean metric. In this way, we generalize the dilation for different values of p in the Lp metric (Euclidean is a particular case when p = 2) and obtain the descriptors from the cumulated distribution of the distance transform computed over the texture image. The proposed method is compared to other state-of-the-art approaches (such as local binary patterns and textons for example) in the classification of two benchmark data sets (UIUC and Outex). The proposed descriptors outperformed all the other approaches in terms of rate of images correctly classified. The interesting results suggest the potential of these descriptors in this type of task, with a wide range of possible applications to real-world problems.

Three-dimensional contour edge detection algorithm

NASA Astrophysics Data System (ADS)

Wang, Yizhou; Ong, Sim Heng; Kassim, Ashraf A.; Foong, Kelvin W. C.

2000-06-01

This paper presents a novel algorithm for automatically extracting 3D contour edges, which are points of maximum surface curvature in a surface range image. The 3D image data are represented as a surface polygon mesh. The algorithm transforms the range data, obtained by scanning a dental plaster cast, into a 2D gray scale image by linearly converting the z-value of each vertex to a gray value. The Canny operator is applied to the median-filtered image to obtain the edge pixels and their orientations. A vertex in the 3D object corresponding to the detected edge pixel and its neighbors in the direction of the edge gradient are further analyzed with respect to their n-curvatures to extract the real 3D contour edges. This algorithm provides a fast method of reducing and sorting the unwieldy data inherent in the surface mesh representation. It employs powerful 2D algorithms to extract features from the transformed 3D models and refers to the 3D model for further analysis of selected data. This approach substantially reduces the computational burden without losing accuracy. It is also easily extended to detect 3D landmarks and other geometrical features, thus making it applicable to a wide range of applications.

The method for detecting small lesions in medical image based on sliding window

NASA Astrophysics Data System (ADS)

Han, Guilai; Jiao, Yuan

2016-10-01

At present, the research on computer-aided diagnosis includes the sample image segmentation, extracting visual features, generating the classification model by learning, and according to the model generated to classify and judge the inspected images. However, this method has a large scale of calculation and speed is slow. And because medical images are usually low contrast, when the traditional image segmentation method is applied to the medical image, there is a complete failure. As soon as possible to find the region of interest, improve detection speed, this topic attempts to introduce the current popular visual attention model into small lesions detection. However, Itti model is mainly for natural images. But the effect is not ideal when it is used to medical images which usually are gray images. Especially in the early stages of some cancers, the focus of a disease in the whole image is not the most significant region and sometimes is very difficult to be found. But these lesions are prominent in the local areas. This paper proposes a visual attention mechanism based on sliding window, and use sliding window to calculate the significance of a local area. Combined with the characteristics of the lesion, select the features of gray, entropy, corner and edge to generate a saliency map. Then the significant region is segmented and distinguished. This method reduces the difficulty of image segmentation, and improves the detection accuracy of small lesions, and it has great significance to early discovery, early diagnosis and treatment of cancers.

Scanning Probe Platform | Materials Science | NREL

Science.gov Websites

level; this image obtained using a scanning tunneling microscope shows gray and white clusters of produce high-resolution color images or maps like this one obtained using scanning tunneling luminescence gray clusters. Gold substrate: (Left) STM image reveals the terraces of the H2 flamed substrate. (Right

Differences in quantitative assessment of myocardial scar and gray zone by LGE-CMR imaging using established gray zone protocols.

PubMed

Mesubi, Olurotimi; Ego-Osuala, Kelechi; Jeudy, Jean; Purtilo, James; Synowski, Stephen; Abutaleb, Ameer; Niekoop, Michelle; Abdulghani, Mohammed; Asoglu, Ramazan; See, Vincent; Saliaris, Anastasios; Shorofsky, Stephen; Dickfeld, Timm

2015-02-01

Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging is the gold standard for myocardial scar evaluation. Heterogeneous areas of scar ('gray zone'), may serve as arrhythmogenic substrate. Various gray zone protocols have been correlated to clinical outcomes and ventricular tachycardia channels. This study assessed the quantitative differences in gray zone and scar core sizes as defined by previously validated signal intensity (SI) threshold algorithms. High quality LGE-CMR images performed in 41 cardiomyopathy patients [ischemic (33) or non-ischemic (8)] were analyzed using previously validated SI threshold methods [Full Width at Half Maximum (FWHM), n-standard deviation (NSD) and modified-FWHM]. Myocardial scar was defined as scar core and gray zone using SI thresholds based on these methods. Scar core, gray zone and total scar sizes were then computed and compared among these models. The median gray zone mass was 2-3 times larger with FWHM (15 g, IQR: 8-26 g) compared to NSD or modified-FWHM (5 g, IQR: 3-9 g; and 8 g. IQR: 6-12 g respectively, p < 0.001). Conversely, infarct core mass was 2.3 times larger with NSD (30 g, IQR: 17-53 g) versus FWHM and modified-FWHM (13 g, IQR: 7-23 g, p < 0.001). The gray zone extent (percentage of total scar that was gray zone) also varied significantly among the three methods, 51 % (IQR: 42-61 %), 17 % (IQR: 11-21 %) versus 38 % (IQR: 33-43 %) for FWHM, NSD and modified-FWHM respectively (p < 0.001). Considerable variability exists among the current methods for MRI defined gray zone and scar core. Infarct core and total myocardial scar mass also differ using these methods. Further evaluation of the most accurate quantification method is needed.

Differential microstructural and morphological abnormalities in mild cognitive impairment and Alzheimer's disease: Evidence from cortical and deep gray matter.

PubMed

Gong, Nan-Jie; Chan, Chun-Chung; Leung, Lam-Ming; Wong, Chun-Sing; Dibb, Russell; Liu, Chunlei

2017-05-01

One aim of this study is to use non-Gaussian diffusion kurtosis imaging (DKI) for capturing microstructural abnormalities in gray matter of Alzheimer's disease (AD). The other aim is to compare DKI metrics against thickness of cortical gray matter and volume of deep gray matter, respectively. A cohort of 18 patients with AD, 18 patients with amnestic mild cognitive impairment (MCI), and 18 normal controls underwent morphological and DKI MR imaging. Images were investigated using regions-of-interest-based analyses for deep gray matter and vertex-wise analyses for cortical gray matter. In deep gray matter, more regions showed DKI parametric abnormalities than atrophies at the early MCI stage. Mean kurtosis (MK) exhibited the largest number of significant abnormalities among all DKI metrics. At the later AD stage, diffusional abnormalities were observed in fewer regions than atrophies. In cortical gray matter, abnormalities in thickness were mainly in the medial and lateral temporal lobes, which fit the locations of known early pathological changes. Microstructural abnormalities were predominantly in the parietal and even frontal lobes, which fit the locations of known late pathological changes. In conclusion, MK can complement conventional diffusion metrics for detecting microstructural changes, especially in deep gray matter. This study also provides evidence supporting the notion that microstructural changes predate morphological changes. Hum Brain Mapp 38:2495-2508, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

F3D Image Processing and Analysis for Many - and Multi-core Platforms

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

F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expeditesmore » any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.« less

Multiport Multiplex Program

DTIC Science & Technology

1975-02-01

UNCLASSIFIED AD NUMBER LIMITATION CHANGES TO: FROM: AUTHORITY THIS PAGE IS UNCLASSIFIED ADB013811 Approved for public release; distribution is...of Changing Sampling Frequency and Bits/Sample 13 Image Coding Methods 63 Basic Dual-Mode Coder Code Assignment 73 Oversampled Dual...results from the threshold at which a 1 bit will oe trans- mitted. The threshold corresponds to a finite change on the gray scale or resolution of the

Quantification technology study on flaws in steam-filled pipelines based on image processing

NASA Astrophysics Data System (ADS)

Sun, Lina; Yuan, Peixin

2009-07-01

Starting from exploiting the applied detection system of gas transmission pipeline, a set of X-ray image processing methods and pipeline flaw quantificational evaluation methods are proposed. Defective and non-defective strings and rows in gray image were extracted and oscillogram was obtained. We can distinguish defects in contrast with two gray images division. According to the gray value of defects with different thicknesses, the gray level depth curve is founded. Through exponential and polynomial fitting way to obtain the attenuation mathematical model which the beam penetrates pipeline, thus attain flaw deep dimension. This paper tests on the PPR pipe in the production of simulated holes flaw and cracks flaw, 135KV used the X-ray source on the testing. Test results show that X-ray image processing method, which meet the needs of high efficient flaw detection and provide quality safeguard for thick oil recovery, can be used successfully in detecting corrosion of insulated pipe.

Quantification technology study on flaws in steam-filled pipelines based on image processing

NASA Astrophysics Data System (ADS)

Yuan, Pei-xin; Cong, Jia-hui; Chen, Bo

2008-03-01

Starting from exploiting the applied detection system of gas transmission pipeline, a set of X-ray image processing methods and pipeline flaw quantificational evaluation methods are proposed. Defective and non-defective strings and rows in gray image were extracted and oscillogram was obtained. We can distinguish defects in contrast with two gray images division. According to the gray value of defects with different thicknesses, the gray level depth curve is founded. Through exponential and polynomial fitting way to obtain the attenuation mathematical model which the beam penetrates pipeline, thus attain flaw deep dimension. This paper tests on the PPR pipe in the production of simulated holes flaw and cracks flaw. The X-ray source tube voltage was selected as 130kv and valve current was 1.5mA.Test results show that X-ray image processing methods, which meet the needs of high efficient flaw detection and provide quality safeguard for thick oil recovery, can be used successfully in detecting corrosion of insulated pipe.

Gray matter and white matter abnormalities in online game addiction.

PubMed

Weng, Chuan-Bo; Qian, Ruo-Bing; Fu, Xian-Ming; Lin, Bin; Han, Xiao-Peng; Niu, Chao-Shi; Wang, Ye-Han

2013-08-01

Online game addiction (OGA) has attracted greater attention as a serious public mental health issue. However, there are only a few brain magnetic resonance imaging studies on brain structure about OGA. In the current study, we used voxel-based morphometry (VBM) analysis and tract-based spatial statistics (TBSS) to investigate the microstructural changes in OGA and assessed the relationship between these morphology changes and the Young's Internet Addiction Scale (YIAS) scores within the OGA group. Compared with healthy subjects, OGA individuals showed significant gray matter atrophy in the right orbitofrontal cortex, bilateral insula, and right supplementary motor area. According to TBSS analysis, OGA subjects had significantly reduced FA in the right genu of corpus callosum, bilateral frontal lobe white matter, and right external capsule. Gray matter volumes (GMV) of the right orbitofrontal cortex, bilateral insula and FA values of the right external capsule were significantly positively correlated with the YIAS scores in the OGA subjects. Our findings suggested that microstructure abnormalities of gray and white matter were present in OGA subjects. This finding may provide more insights into the understanding of the underlying neural mechanisms of OGA. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

In vitro and clinical evaluation of optical coherence tomography for the detection of subgingival calculus and root cementum.

PubMed

Tsubokawa, Masaki; Aoki, Akira; Kakizaki, Sho; Taniguchi, Yoichi; Ejiri, Kenichiro; Mizutani, Koji; Koshy, Geena; Akizuki, Tatsuya; Oda, Shigeru; Sumi, Yasunori; Izumi, Yuichi

2018-05-24

This study evaluated the effectiveness of swept-source optical coherence tomography (ss-OCT) for detecting calculus and root cementum during periodontal therapy. Optical coherence tomography (OCT) images were taken before and after removal of subgingival calculus from extracted teeth and compared with non-decalcified histological sections. Porcine gingival sheets of various thicknesses were applied to the root surfaces of extracted teeth with calculus and OCT images were taken. OCT images were also taken before and after scaling and root planing (SRP) in human patients. In vitro, calculus was clearly detected as a white-gray amorphous structure on the root surface, which disappeared after removal. Cementum was identified as a thin, dark-gray layer. The calculus could not be clearly observed when soft tissues were present on the root surface. Clinically, supragingival calculus and cementum could be detected clearly with OCT, and subgingival calculus in the buccal cervical area of the anterior and premolar teeth was identified, which disappeared after SRP. Digital processing of the original OCT images was useful for clarifying the calculus. In conclusion, ss-OCT showed potential as a periodontal diagnostic tool for detecting cementum and subgingival calculus, although the practical applications of subgingival imaging remain limited.

Coprates Chasma

NASA Technical Reports Server (NTRS)

1998-01-01

Mars Orbiter Camera (MOC) image of a 10 km by 12 km area of Coprates Chasma (14.7 degrees S, 55.8 degrees W), a ridge with a flat upper surface in the center of Coprates Chasma, which is part of the 6000-km-long Valles Marineris. Rock layers are visible just below the ridge. The gray scale (4.8 m/pixel) MOC image was combined with a Viking Orbiter color view of the same area. The faults of a graben offset beds on the slope to the left.

Figure caption from Science Magazine

Alexithymia is related to differences in gray matter volume: a voxel-based morphometry study.

PubMed

Ihme, Klas; Dannlowski, Udo; Lichev, Vladimir; Stuhrmann, Anja; Grotegerd, Dominik; Rosenberg, Nicole; Kugel, Harald; Heindel, Walter; Arolt, Volker; Kersting, Anette; Suslow, Thomas

2013-01-23

Alexithymia has been characterized as the inability to identify and describe feelings. Functional imaging studies have revealed that alexithymia is linked to reactivity changes in emotion- and face-processing-relevant brain areas. In this respect, anterior cingulate cortex (ACC), amygdala, anterior insula and fusiform gyrus (FFG) have been consistently reported. However, it remains to be clarified whether alexithymia is also associated with structural differences. Voxel-based morphometry on T1-weighted magnetic resonance images was used to investigate gray matter volume in 17 high alexithymics (HA) and 17 gender-matched low alexithymics (LA), which were selected from a sample of 161 healthy volunteers on basis of the 20-item Toronto Alexithymia Scale. Data were analyzed as statistic parametric maps for the comparisons LA>HA and HA>LA in a priori determined regions of interests (ROIs), i.e., ACC, amygdala, anterior insula and FFG. Moreover, an exploratory whole brain analysis was accomplished. For the contrast LA>HA, significant clusters were detected in the ACC, left amygdala and left anterior insula. Additionally, the whole brain analysis revealed volume differences in the left middle temporal gyrus. No significant differences were found for the comparison HA>LA. Our findings suggest that high compared to low alexithymics show less gray matter volume in several emotion-relevant brain areas. These structural differences might contribute to the functional alterations found in previous imaging studies in alexithymia. Copyright © 2012 Elsevier B.V. All rights reserved.

Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

PubMed

Calhoun, V D; Adali, T; Giuliani, N R; Pekar, J J; Kiehl, K A; Pearlson, G D

2006-01-01

The acquisition of both structural MRI (sMRI) and functional MRI (fMRI) data for a given study is a very common practice. However, these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform independent component analysis across image modalities, specifically, gray matter images and fMRI activation images as well as a joint histogram visualization technique. Joint independent component analysis (jICA) is used to decompose a matrix with a given row consisting of an fMRI activation image resulting from auditory oddball target stimuli and an sMRI gray matter segmentation image, collected from the same individual. We analyzed data collected on a group of schizophrenia patients and healthy controls using the jICA approach. Spatially independent joint-components are estimated and resulting components were further analyzed only if they showed a significant difference between patients and controls. The main finding was that group differences in bilateral parietal and frontal as well as posterior temporal regions in gray matter were associated with bilateral temporal regions activated by the auditory oddball target stimuli. A finding of less patient gray matter and less hemodynamic activity for target detection in these bilateral anterior temporal lobe regions was consistent with previous work. An unexpected corollary to this finding was that, in the regions showing the largest group differences, gray matter concentrations were larger in patients vs. controls, suggesting that more gray matter may be related to less functional connectivity in the auditory oddball fMRI task. Hum Brain Mapp, 2005. (c) 2005 Wiley-Liss, Inc.

Images as embedding maps and minimal surfaces: Movies, color, and volumetric medical images

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

Kimmel, R.; Malladi, R.; Sochen, N.

A general geometrical framework for image processing is presented. The authors consider intensity images as surfaces in the (x,I) space. The image is thereby a two dimensional surface in three dimensional space for gray level images. The new formulation unifies many classical schemes, algorithms, and measures via choices of parameters in a {open_quote}master{close_quotes} geometrical measure. More important, it is a simple and efficient tool for the design of natural schemes for image enhancement, segmentation, and scale space. Here the authors give the basic motivation and apply the scheme to enhance images. They present the concept of an image as amore » surface in dimensions higher than the three dimensional intuitive space. This will help them handle movies, color, and volumetric medical images.« less

Exploring the role of testosterone in the cerebellum link to neuroticism: From adolescence to early adulthood.

PubMed

Schutter, Dennis J L G; Meuwese, Rosa; Bos, Marieke G N; Crone, Eveline A; Peper, Jiska S

2017-04-01

Previous research has found an association between a smaller cerebellar volume and higher levels of neuroticism. The steroid hormone testosterone reduces stress responses and the susceptibility to negative mood. Together with in vitro studies showing a positive effect of testosterone on cerebellar gray matter volumes, we set out to explore the role of testosterone in the relation between cerebellar gray matter and neuroticism. Structural magnetic resonance imaging scans were acquired, and indices of neurotic personality traits were assessed by administering the depression and anxiety scale of the revised NEO personality inventory and Gray's behavioural avoidance in one hundred and forty-nine healthy volunteers between 12 and 27 years of age. Results demonstrated an inverse relation between total brain corrected cerebellar volumes and neurotic personality traits in adolescents and young adults. In males, higher endogenous testosterone levels were associated with lower scores on neurotic personality traits and larger cerebellar gray matter volumes. No such relations were observed in the female participants. Analyses showed that testosterone significantly mediated the relation between male cerebellar gray matter and measures of neuroticism. Our findings on the interrelations between endogenous testosterone, neuroticism and cerebellar morphology provide a cerebellum-oriented framework for the susceptibility to experience negative emotions and mood in adolescence and early adulthood. Copyright © 2017 Elsevier Ltd. All rights reserved.

A-law/Mu-law Dynamic Range Compression Deconvolution (Preprint)

DTIC Science & Technology

2008-02-04

noise filtering via the spectrum proportionality filter, and second the signal deblurring via the inverse filter. In this process for regions when...is the joint image of motion impulse response and the noisy blurred image with signal to noise ratio 5, 6(A’) is the gray level recovered image...joint image of motion impulse response and the noisy blurred image with signal to noise ratio 5, (A’) the gray level recovered image using the A-law

An adaptive enhancement algorithm for infrared video based on modified k-means clustering

NASA Astrophysics Data System (ADS)

Zhang, Linze; Wang, Jingqi; Wu, Wen

2016-09-01

In this paper, we have proposed a video enhancement algorithm to improve the output video of the infrared camera. Sometimes the video obtained by infrared camera is very dark since there is no clear target. In this case, infrared video should be divided into frame images by frame extraction, in order to carry out the image enhancement. For the first frame image, which can be divided into k sub images by using K-means clustering according to the gray interval it occupies before k sub images' histogram equalization according to the amount of information per sub image, we used a method to solve a problem that final cluster centers close to each other in some cases; and for the other frame images, their initial cluster centers can be determined by the final clustering centers of the previous ones, and the histogram equalization of each sub image will be carried out after image segmentation based on K-means clustering. The histogram equalization can make the gray value of the image to the whole gray level, and the gray level of each sub image is determined by the ratio of pixels to a frame image. Experimental results show that this algorithm can improve the contrast of infrared video where night target is not obvious which lead to a dim scene, and reduce the negative effect given by the overexposed pixels adaptively in a certain range.

NASA Spacecraft Images Texas Wildfire

NASA Image and Video Library

2011-09-13

The tri-county Riley Road wildfire burning in Texas north of Houston was 85 percent contained when NASA Terra spacecraft acquired this image on Sept. 12, 2011. Burned areas are dark gray and black; vegetation red; and bare ground and roads light gray.

Brain changes in children and adolescents with obsessive-compulsive disorder before and after treatment: a voxel-based morphometric MRI study.

PubMed

Lázaro, Luisa; Bargalló, Nuria; Castro-Fornieles, Josefina; Falcón, Carles; Andrés, Susana; Calvo, Rosa; Junqué, Carme

2009-05-15

The aim of this study is to determine whether children and adolescents with treatment-naïve obsessive-compulsive disorder (OCD) present brain structure differences in comparison with healthy subjects, and to evaluate brain changes after treatment and clinical improvement. Initial and 6 months' follow-up evaluations were performed in 15 children and adolescents (age range=9-17 years, mean=13.7, S.D.=2.5; 8 male, 7 female) with DSM-IV OCD and 15 healthy subjects matched for age, sex and estimated intellectual level. An evaluation with psychopathological scales and magnetic resonance imaging (MRI) was carried out at admission and after 6 months' follow-up. Axial three-dimensional T1-weighted images were obtained in a 1.5 T scanner and analysed using optimized voxel-based morphometry (VBM) and longitudinal VBM approaches. Compared with controls, OCD patients presented significantly less gray matter volume bilaterally in right and left parietal lobes and right parietal white matter (P=0.001 FWE corrected) at baseline evaluation. After 6 months of treatment, and with a clear clinical improvement, the differences between OCD patients and controls in the parietal lobes in gray and white matter were no longer statistically significant. During follow-up in the longitudinal study, an increase in gray matter volume in the right striatum of OCD patients was observed, though the difference was not statistically significant. Children and adolescents with untreated OCD present gray and white matter decreases in lateral parietal cortices, but this abnormality is reversible after clinical improvement.

Opto-acoustic image fusion technology for diagnostic breast imaging in a feasibility study

NASA Astrophysics Data System (ADS)

Zalev, Jason; Clingman, Bryan; Herzog, Don; Miller, Tom; Ulissey, Michael; Stavros, A. T.; Oraevsky, Alexander; Lavin, Philip; Kist, Kenneth; Dornbluth, N. C.; Otto, Pamela

2015-03-01

Functional opto-acoustic (OA) imaging was fused with gray-scale ultrasound acquired using a specialized duplex handheld probe. Feasibility Study findings indicated the potential to more accurately characterize breast masses for cancer than conventional diagnostic ultrasound (CDU). The Feasibility Study included OA imagery of 74 breast masses that were collected using the investigational Imagio® breast imaging system. Superior specificity and equal sensitivity to CDU was demonstrated, suggesting that OA fusion imaging may potentially obviate the need for negative biopsies without missing cancers in a certain percentage of breast masses. Preliminary results from a 100 subject Pilot Study are also discussed. A larger Pivotal Study (n=2,097 subjects) is underway to confirm the Feasibility Study and Pilot Study findings.

The FBI compression standard for digitized fingerprint images

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

Brislawn, C.M.; Bradley, J.N.; Onyshczak, R.J.

1996-10-01

The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the currentmore » status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.« less

FBI compression standard for digitized fingerprint images

NASA Astrophysics Data System (ADS)

Brislawn, Christopher M.; Bradley, Jonathan N.; Onyshczak, Remigius J.; Hopper, Thomas

1996-11-01

The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the current status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.

MRI intensity nonuniformity correction using simultaneously spatial and gray-level histogram information.

PubMed

Milles, Julien; Zhu, Yue Min; Gimenez, Gérard; Guttmann, Charles R G; Magnin, Isabelle E

2007-03-01

A novel approach for correcting intensity nonuniformity in magnetic resonance imaging (MRI) is presented. This approach is based on the simultaneous use of spatial and gray-level histogram information. Spatial information about intensity nonuniformity is obtained using cubic B-spline smoothing. Gray-level histogram information of the image corrupted by intensity nonuniformity is exploited from a frequential point of view. The proposed correction method is illustrated using both physical phantom and human brain images. The results are consistent with theoretical prediction, and demonstrate a new way of dealing with intensity nonuniformity problems. They are all the more significant as the ground truth on intensity nonuniformity is unknown in clinical images.

Integral-geometry characterization of photobiomodulation effects on retinal vessel morphology

PubMed Central

Barbosa, Marconi; Natoli, Riccardo; Valter, Kriztina; Provis, Jan; Maddess, Ted

2014-01-01

The morphological characterization of quasi-planar structures represented by gray-scale images is challenging when object identification is sub-optimal due to registration artifacts. We propose two alternative procedures that enhances object identification in the integral-geometry morphological image analysis (MIA) framework. The first variant streamlines the framework by introducing an active contours segmentation process whose time step is recycled as a multi-scale parameter. In the second variant, we used the refined object identification produced in the first variant to perform the standard MIA with exact dilation radius as multi-scale parameter. Using this enhanced MIA we quantify the extent of vaso-obliteration in oxygen-induced retinopathic vascular growth, the preventative effect (by photobiomodulation) of exposure during tissue development to near-infrared light (NIR, 670 nm), and the lack of adverse effects due to exposure to NIR light. PMID:25071966

The effects of adjunctive intranasal oxytocin in patients with schizophrenia.

PubMed

Ota, Miho; Yoshida, Sumiko; Nakata, Masanori; Yada, Toshihiko; Kunugi, Hiroshi

2018-01-01

Both human and animal studies have suggested that oxytocin may have therapeutic potential in the treatment of schizophrenia. We evaluated the effects of intranasal oxytocin on cognition and its predictive factors in Japanese patients with schizophrenia. Subjects were 16 chronic schizophrenia patients who underwent intranasal oxytocin treatment for 3 months and were assessed for changes in severity of clinical symptoms and cognitions. Fifteen of the 16 subjects underwent 3-Tesla magnetic resonance imaging. Oxytocin significantly reduced scores on the positive and negative syndrome scale, especially on the negative symptoms. As for cognition, there was an improvement of the verbal fluency. Furthermore, the change of the negative score in positive and negative syndrome scale showed a negative correlation with the gray matter volumes of the right insula and left cingulate cortex. Our results indicate that daily administration of intranasal oxytocin may be effective for ameliorating clinical symptoms and cognitive functions in chronic schizophrenia patients, and this improvement may be related to the gray matter volume of the right insula and left cingulate cortex.

Prostate ultrasound--for urologists only?

PubMed

Frauscher, Ferdinand; Gradl, Johann; Pallwein, Leo

2005-11-23

The value of ultrasound (US) in the diagnosis of prostate cancer has dramatically increased in the past decade. This is mainly related to the increasing incidence of prostate cancer, the most common cancer in men and one of the most important causes of death from cancer in men. The value of conventional gray-scale US for prostate cancer detection has been extensively investigated, and has shown a low sensitivity and specificity. Therefore conventional gray-scale US is mainly used by urologists for guiding systematic prostate biopsies. With the development of new US techniques, such as color and power Doppler US, and the introduction of US contrast agents, the role of US for prostate cancer detection has dramatically changed. Advances in US techniques were introduced to further increase the value of US contrast agents. Although most of these developments in US techniques, which use the interaction of the contrast agent with the transmitted US waves, are very sensitive for the detection of microbubbles, they are mostly unexplored, in particular for prostate applications. Early reports of contrast-enhanced US investigations of blood flow of the prostate have shown that contrast-enhanced US adds important information to the conventional gray-scale US technique. Furthermore, elastography or 'strain imaging' seems to have great potential in prostate cancer detection. Since these new advances in US are very sophisticated and need a long learning curve, radiologists, who are overall better trained with these new US techniques, will play a more important role in prostate cancer diagnosis. Current trends show that these new US techniques may allow for targeted biopsies and therefore replace the current 'gold standard' for prostate cancer detection--the systematic biopsy. Consequently the use of these new US techniques for the detection and clinical staging of prostate cancer is promising. However, future clinical trials will be needed to determine if the promise of these new US advances of the prostate evolves into clinical application. International Cancer Imaging Society.

Optical classification for quality and defect analysis of train brakes

NASA Astrophysics Data System (ADS)

Glock, Stefan; Hausmann, Stefan; Gerke, Sebastian; Warok, Alexander; Spiess, Peter; Witte, Stefan; Lohweg, Volker

2009-06-01

In this paper we present an optical measurement system approach for quality analysis of brakes which are used in high-speed trains. The brakes consist of the so called brake discs and pads. In a deceleration process the discs will be heated up to 500°C. The quality measure is based on the fact that the heated brake discs should not generate hot spots inside the brake material. Instead, the brake disc should be heated homogeneously by the deceleration. Therefore, it makes sense to analyze the number of hot spots and their relative gradients to create a quality measure for train brakes. In this contribution we present a new approach for a quality measurement system which is based on an image analysis and classification of infra-red based heat images. Brake images which are represented in pseudo-color are first transformed in a linear grayscale space by a hue-saturation-intensity (HSI) space. This transform is necessary for the following gradient analysis which is based on gray scale gradient filters. Furthermore, different features based on Haralick's measures are generated from the gray scale and gradient images. A following Fuzzy-Pattern-Classifier is used for the classification of good and bad brakes. It has to be pointed out that the classifier returns a score value for each brake which is between 0 and 100% good quality. This fact guarantees that not only good and bad bakes can be distinguished, but also their quality can be labeled. The results show that all critical thermal patterns of train brakes can be sensed and verified.

Correlation between white matter damage and gray matter lesions in multiple sclerosis patients.

PubMed

Han, Xue-Mei; Tian, Hong-Ji; Han, Zheng; Zhang, Ce; Liu, Ying; Gu, Jie-Bing; Bakshi, Rohit; Cao, Xia

2017-05-01

We observed the characteristics of white matter fibers and gray matter in multiple sclerosis patients, to identify changes in diffusion tensor imaging fractional anisotropy values following white matter fiber injury. We analyzed the correlation between fractional anisotropy values and changes in whole-brain gray matter volume. The participants included 20 patients with relapsing-remitting multiple sclerosis and 20 healthy volunteers as controls. All subjects underwent head magnetic resonance imaging and diffusion tensor imaging. Our results revealed that fractional anisotropy values decreased and gray matter volumes were reduced in the genu and splenium of corpus callosum, left anterior thalamic radiation, hippocampus, uncinate fasciculus, right corticospinal tract, bilateral cingulate gyri, and inferior longitudinal fasciculus in multiple sclerosis patients. Gray matter volumes were significantly different between the two groups in the right frontal lobe (superior frontal, middle frontal, precentral, and orbital gyri), right parietal lobe (postcentral and inferior parietal gyri), right temporal lobe (caudate nucleus), right occipital lobe (middle occipital gyrus), right insula, right parahippocampal gyrus, and left cingulate gyrus. The voxel sizes of atrophic gray matter positively correlated with fractional anisotropy values in white matter association fibers in the patient group. These findings suggest that white matter fiber bundles are extensively injured in multiple sclerosis patients. The main areas of gray matter atrophy in multiple sclerosis are the frontal lobe, parietal lobe, caudate nucleus, parahippocampal gyrus, and cingulate gyrus. Gray matter atrophy is strongly associated with white matter injury in multiple sclerosis patients, particularly with injury to association fibers.

Fuzzy control system for a remote focusing microscope

NASA Astrophysics Data System (ADS)

Weiss, Jonathan J.; Tran, Luc P.

1992-01-01

Space Station Crew Health Care System procedures require the use of an on-board microscope whose slide images will be transmitted for analysis by ground-based microbiologists. Focusing of microscope slides is low on the list of crew priorities, so NASA is investigating the option of telerobotic focusing controlled by the microbiologist on the ground, using continuous video feedback. However, even at Space Station distances, the transmission time lag may disrupt the focusing process, severely limiting the number of slides that can be analyzed within a given bandwidth allocation. Substantial time could be saved if on-board automation could pre-focus each slide before transmission. The authors demonstrate the feasibility of on-board automatic focusing using a fuzzy logic ruled-based system to bring the slide image into focus. The original prototype system was produced in under two months and at low cost. Slide images are captured by a video camera, then digitized by gray-scale value. A software function calculates an index of 'sharpness' based on gray-scale contrasts. The fuzzy logic rule-based system uses feedback to set the microscope's focusing control in an attempt to maximize sharpness. The systems as currently implemented performs satisfactorily in focusing a variety of slide types at magnification levels ranging from 10 to 1000x. Although feasibility has been demonstrated, the system's performance and usability could be improved substantially in four ways: by upgrading the quality and resolution of the video imaging system (including the use of full color); by empirically defining and calibrating the index of image sharpness; by letting the overall focusing strategy vary depending on user-specified parameters; and by fine-tuning the fuzzy rules, set definitions, and procedures used.

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Real-time single image dehazing based on dark channel prior theory and guided filtering

NASA Astrophysics Data System (ADS)

Zhang, Zan

2017-10-01

Images and videos taken outside the foggy day are serious degraded. In order to restore degraded image taken in foggy day and overcome traditional Dark Channel prior algorithms problems of remnant fog in edge, we propose a new dehazing method.We first find the fog area in the dark primary color map to obtain the estimated value of the transmittance using quadratic tree. Then we regard the gray-scale image after guided filtering as atmospheric light map and remove haze based on it. Box processing and image down sampling technology are also used to improve the processing speed. Finally, the atmospheric light scattering model is used to restore the image. A plenty of experiments show that algorithm is effective, efficient and has a wide range of application.

Subpixel resolution from multiple images

NASA Technical Reports Server (NTRS)

Cheeseman, Peter; Kanefsky, Rob; Stutz, John; Kraft, Richard

1994-01-01

Multiple images taken from similar locations and under similar lighting conditions contain similar, but not identical, information. Slight differences in instrument orientation and position produces mismatches between the projected pixel grids. These mismatches ensure that any point on the ground is sampled differently in each image. If all the images can be registered with respect to each other to a small fraction of a pixel accuracy, then the information from the multiple images can be combined to increase linear resolution by roughly the square root of the number of images. In addition, the gray-scale resolution of the composite image is also improved. We describe methods for multiple image registration and combination, and discuss some of the problems encountered in developing and extending them. We display test results with 8:1 resolution enhancement, and Viking Orbiter imagery with 2:1 and 4:1 enhancements.

Quantification of dental prostheses on cone‐beam CT images by the Taguchi method

PubMed Central

Kuo, Rong‐Fu; Fang, Kwang‐Ming; TY, Wong

2016-01-01

The gray values accuracy of dental cone‐beam computed tomography (CBCT) is affected by dental metal prostheses. The distortion of dental CBCT gray values could lead to inaccuracies of orthodontic and implant treatment. The aim of this study was to quantify the effect of scanning parameters and dental metal prostheses on the accuracy of dental cone‐beam computed tomography (CBCT) gray values using the Taguchi method. Eight dental model casts of an upper jaw including prostheses, and a ninth prosthesis‐free dental model cast, were scanned by two dental CBCT devices. The mean gray value of the selected circular regions of interest (ROIs) were measured using dental CBCT images of eight dental model casts and were compared with those measured from CBCT images of the prosthesis‐free dental model cast. For each image set, four consecutive slices of gingiva were selected. The seven factors (CBCTs, occlusal plane canting, implant connection, prosthesis position, coping material, coping thickness, and types of dental restoration) were used to evaluate scanning parameter and dental prostheses effects. Statistical methods of signal to noise ratio (S/N) and analysis of variance (ANOVA) with 95% confidence were applied to quantify the effects of scanning parameters and dental prostheses on dental CBCT gray values accuracy. For ROIs surrounding dental prostheses, the accuracy of CBCT gray values were affected primarily by implant connection (42%), followed by type of restoration (29%), prostheses position (19%), coping material (4%), and coping thickness (4%). For a single crown prosthesis (without support of implants) placed in dental model casts, gray value differences for ROIs 1–9 were below 12% and gray value differences for ROIs 13–18 away from prostheses were below 10%. We found the gray value differences set to be between 7% and 8% for regions next to a single implant‐supported titanium prosthesis, and between 46% and 59% for regions between double implant‐supported, nickel‐chromium alloys (Ni‐Cr) prostheses. Quantification of the effect of prostheses and scanning parameters on dental CBCT gray values was assessed. PACS numbers: 87.59.bd, 87.57Q PMID:26894354

Image quality and radiation dose of brain computed tomography in children: effects of decreasing tube voltage from 120 kVp to 80 kVp.

PubMed

Park, Ji Eun; Choi, Young Hun; Cheon, Jung-Eun; Kim, Woo Sun; Kim, In-One; Cho, Hyun Suk; Ryu, Young Jin; Kim, Yu Jin

2017-05-01

Computed tomography (CT) has generated public concern associated with radiation exposure, especially for children. Lowering the tube voltage is one strategy to reduce radiation dose. To assess the image quality and radiation dose of non-enhanced brain CT scans acquired at 80 kilo-voltage peak (kVp) compared to those at 120 kVp in children. Thirty children who had undergone both 80- and 120-kVp non-enhanced brain CT were enrolled. For quantitative analysis, the mean attenuation of white and gray matter, attenuation difference, noise, signal-to-noise ratio, contrast-to-noise ratio and posterior fossa artifact index were measured. For qualitative analysis, noise, gray-white matter differentiation, artifact and overall image quality were scored. Radiation doses were evaluated by CT dose index, dose-length product and effective dose. The mean attenuations of gray and white matter and contrast-to-noise ratio were significantly increased at 80 kVp, while parameters related to image noise, i.e. noise, signal-to-noise ratio and posterior fossa artifact index were higher at 80 kVp than at 120 kVp. In qualitative analysis, 80-kVp images showed improved gray-white differentiation but more artifacts compared to 120-kVp images. Subjective image noise and overall image quality scores were similar between the two scans. Radiation dose parameters were significantly lower at 80 kVp than at 120 kVp. In pediatric non-enhanced brain CT scans, a decrease in tube voltage from 120 kVp to 80 kVp resulted in improved gray-white matter contrast, comparable image quality and decreased radiation dose.

MIA - A free and open source software for gray scale medical image analysis

PubMed Central

2013-01-01

Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers. One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development. Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don’t provide an clear approach when one wants to shape a new command line tool from a prototype shell script. Results The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. Conclusion In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed. PMID:24119305

MIA - A free and open source software for gray scale medical image analysis.

PubMed

Wollny, Gert; Kellman, Peter; Ledesma-Carbayo, María-Jesus; Skinner, Matthew M; Hublin, Jean-Jaques; Hierl, Thomas

2013-10-11

Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large.Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers.One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development.Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don't provide an clear approach when one wants to shape a new command line tool from a prototype shell script. The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed.

Validation of an MRI Brain Injury and Growth Scoring System in Very Preterm Infants Scanned at 29- to 35-Week Postmenstrual Age.

PubMed

George, J M; Fiori, S; Fripp, J; Pannek, K; Bursle, J; Moldrich, R X; Guzzetta, A; Coulthard, A; Ware, R S; Rose, S E; Colditz, P B; Boyd, R N

2017-07-01

The diagnostic and prognostic potential of brain MR imaging before term-equivalent age is limited until valid MR imaging scoring systems are available. This study aimed to validate an MR imaging scoring system of brain injury and impaired growth for use at 29 to 35 weeks postmenstrual age in infants born at <31 weeks gestational age. Eighty-three infants in a prospective cohort study underwent early 3T MR imaging between 29 and 35 weeks' postmenstrual age (mean, 32 +2 ± 1 +3 weeks; 49 males, born at median gestation of 28 +4 weeks; range, 23 +6 -30 +6 weeks; mean birthweight, 1068 ± 312 g). Seventy-seven infants had a second MR scan at term-equivalent age (mean, 40 +6 ± 1 +3 weeks). Structural images were scored using a modified scoring system which generated WM, cortical gray matter, deep gray matter, cerebellar, and global scores. Outcome at 12-months corrected age (mean, 12 months 4 days ± 1 +2 weeks) consisted of the Bayley Scales of Infant and Toddler Development, 3rd ed. (Bayley III), and the Neuro-Sensory Motor Developmental Assessment. Early MR imaging global, WM, and deep gray matter scores were negatively associated with Bayley III motor (regression coefficient for global score β = -1.31; 95% CI, -2.39 to -0.23; P = .02), cognitive (β = -1.52; 95% CI, -2.39 to -0.65; P < .01) and the Neuro-Sensory Motor Developmental Assessment outcomes (β = -1.73; 95% CI, -3.19 to -0.28; P = .02). Early MR imaging cerebellar scores were negatively associated with the Neuro-Sensory Motor Developmental Assessment (β = -5.99; 95% CI, -11.82 to -0.16; P = .04). Results were reconfirmed at term-equivalent-age MR imaging. This clinically accessible MR imaging scoring system is valid for use at 29 to 35 weeks postmenstrual age in infants born very preterm. It enables identification of infants at risk of adverse outcomes before the current standard of term-equivalent age. © 2017 by American Journal of Neuroradiology.

Syntactic Approach To Geometric Surface Shell Determination

NASA Astrophysics Data System (ADS)

DeGryse, Donald G.; Panton, Dale J.

1980-12-01

Autonomous terminal homing of a smart missile requires a stored reference scene of the target for which the missle is destined. The reference scene is produced from stereo source imagery by deriving a three-dimensional model containing cultural structures such as buildings, towers, bridges, and tanks. This model is obtained by the precise matching of cultural features from one image of the stereo pair to the other. In the past, this stereo matching process has relied heavily on local edge operators and a gray scale matching metric. The processing is performed line by line over the imagery and the amount of geometric control is minimal. As a result, the gross structure of the scene is determined but the derived three-dimensional data is noisy, oscillatory, and at times significantly inaccurate. This paper discusses new concepts that are currently being developed to stabilize this geometric reference preparation process. The new concepts involve the use of a structural syntax which will be used as a geometric constraint on automatic stereo matching. The syntax arises from the stereo configuration of the imaging platforms at the time of exposure and the knowledge of how various cultural structures are constructed. The syntax is used to parse a scene in terms of its cultural surfaces and to dictate to the matching process the allowable relative positions and orientations of surface edges in the image planes. Using the syntax, extensive searches using a gray scale matching metric are reduced.

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

PubMed

Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

2018-09-01

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

Erratum: ``Structure and Colors of Diffuse Emission in the Spitzer Galactic First Look Survey'' (ApJS, 154, 281 [2004])

NASA Astrophysics Data System (ADS)

Ingalls, James G.; Miville-Deschênes, M.-A.; Reach, William T.; Noriega-Crespo, A.; Carey, Sean J.; Boulanger, F.; Stolovy, S. R.; Padgett, Deborah L.; Burgdorf, M. J.; Fajardo-Acosta, S. B.; Glaccum, W. J.; Helou, G.; Hoard, D. W.; Karr, J.; O'Linger, J.; Rebull, L. M.; Rho, J.; Stauffer, J. R.; Wachter, S.

2006-05-01

We have discovered an error in the scaling of our IRAC 8 μm and MIPS 70 μm data, which affected the caption for Figure 1 and the vertical axis scales for Figure 2. The original units in the images displayed in Figure 1 were MJy sr-1 for 8 μm and μJy arcsec-2 for MIPS 24 and 70 μm. We incorrectly multiplied our IRAC data by 0.0425 (the conversion from μJy arcsec-2 to MJy sr-1), but neglected to multiply our MIPS 70 μm data by that factor. (MIPS 24 μm data were scaled correctly.) Thus, contrary to the caption of Figure 1, the gray levels for panels (a) and (b) actually range from 6.7 to 7.8 MJy sr-1, and the gray levels for panels (e) and (f) actually range from 0.85 to 20.8 MJy sr-1. The power spectra in Figure 2 should have been normalized such that the integral over the spectrum equals the mean square image surface brightness. In the original paper, however, the IRAC power spectrum was incorrectly multiplied by (0.0425)2, whereas the MIPS 70 μm spectrum should have been multiplied by this factor but was not. We correct this in a revised version of Figure 2 included here. We thank Rick Arendt for calling our attention to this error.

New algorithm for detecting smaller retinal blood vessels in fundus images

NASA Astrophysics Data System (ADS)

LeAnder, Robert; Bidari, Praveen I.; Mohammed, Tauseef A.; Das, Moumita; Umbaugh, Scott E.

2010-03-01

About 4.1 million Americans suffer from diabetic retinopathy. To help automatically diagnose various stages of the disease, a new blood-vessel-segmentation algorithm based on spatial high-pass filtering was developed to automatically segment blood vessels, including the smaller ones, with low noise. Methods: Image database: Forty, 584 x 565-pixel images were collected from the DRIVE image database. Preprocessing: Green-band extraction was used to obtain better contrast, which facilitated better visualization of retinal blood vessels. A spatial highpass filter of mask-size 11 was applied. A histogram stretch was performed to enhance contrast. A median filter was applied to mitigate noise. At this point, the gray-scale image was converted to a binary image using a binary thresholding operation. Then, a NOT operation was performed by gray-level value inversion between 0 and 255. Postprocessing: The resulting image was AND-ed with its corresponding ring mask to remove the outer-ring (lens-edge) artifact. At this point, the above algorithm steps had extracted most of the major and minor vessels, with some intersections and bifurcations missing. Vessel segments were reintegrated using the Hough transform. Results: After applying the Hough transform, both the average peak SNR and the RMS error improved by 10%. Pratt's Figure of Merit (PFM) was decreased by 6%. Those averages were better than [1] by 10-30%. Conclusions: The new algorithm successfully preserved the details of smaller blood vessels and should prove successful as a segmentation step for automatically identifying diseases that affect retinal blood vessels.

Adaptive Electronic Camouflage Using Texture Synthesis

DTIC Science & Technology

2012-04-01

algorithm begins by computing the GLCMs, GIN and GOUT , of the input image (e.g., image of local environment) and output image (randomly generated...respectively. The algorithm randomly selects a pixel from the output image and cycles its gray-level through all values. For each value, GOUT is updated...The value of the selected pixel is permanently changed to the gray-level value that minimizes the error between GIN and GOUT . Without selecting a

Threshold secret sharing scheme based on phase-shifting interferometry.

PubMed

Deng, Xiaopeng; Shi, Zhengang; Wen, Wei

2016-11-01

We propose a new method for secret image sharing with the (3,N) threshold scheme based on phase-shifting interferometry. The secret image, which is multiplied with an encryption key in advance, is first encrypted by using Fourier transformation. Then, the encoded image is shared into N shadow images based on the recording principle of phase-shifting interferometry. Based on the reconstruction principle of phase-shifting interferometry, any three or more shadow images can retrieve the secret image, while any two or fewer shadow images cannot obtain any information of the secret image. Thus, a (3,N) threshold secret sharing scheme can be implemented. Compared with our previously reported method, the algorithm of this paper is suited for not only a binary image but also a gray-scale image. Moreover, the proposed algorithm can obtain a larger threshold value t. Simulation results are presented to demonstrate the feasibility of the proposed method.

Cerebral Perfusion and Gray Matter Changes Associated With Chemotherapy-Induced Peripheral Neuropathy.

PubMed

Nudelman, Kelly N H; McDonald, Brenna C; Wang, Yang; Smith, Dori J; West, John D; O'Neill, Darren P; Zanville, Noah R; Champion, Victoria L; Schneider, Bryan P; Saykin, Andrew J

2016-03-01

To investigate the longitudinal relationship between chemotherapy-induced peripheral neuropathy (CIPN) symptoms (sx) and brain perfusion changes in patients with breast cancer. Interaction of CIPN-sx perfusion effects with known chemotherapy-associated gray matter density decrease was also assessed to elucidate the relationship between CIPN and previously reported cancer treatment-related brain structural changes. Patients with breast cancer treated with (n = 24) or without (n = 23) chemotherapy underwent clinical examination and brain magnetic resonance imaging at the following three time points: before treatment (baseline), 1 month after treatment completion, and 1 year after the 1-month assessment. CIPN-sx were evaluated with the self-reported Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity four-item sensory-specific scale. Perfusion and gray matter density were assessed using voxel-based pulsed arterial spin labeling and morphometric analyses and tested for association with CIPN-sx in the patients who received chemotherapy. Patients who received chemotherapy reported significantly increased CIPN-sx from baseline to 1 month, with partial recovery by 1 year (P < .001). CIPN-sx increase from baseline to 1 month was significantly greater for patients who received chemotherapy compared with those who did not (P = .001). At 1 month, neuroimaging showed that for the group that received chemotherapy, CIPN-sx were positively associated with cerebral perfusion in the right superior frontal gyrus and cingulate gyrus, regions associated with pain processing (P < .001). Longitudinal magnetic resonance imaging analysis in the group receiving chemotherapy indicated that CIPN-sx and associated perfusion changes from baseline to 1 month were also positively correlated with gray matter density change (P < .005). Peripheral neuropathy symptoms after systemic chemotherapy for breast cancer are associated with changes in cerebral perfusion and gray matter. The specific mechanisms warrant further investigation given the potential diagnostic and therapeutic implications. © 2015 by American Society of Clinical Oncology.

Cerebral Perfusion and Gray Matter Changes Associated With Chemotherapy-Induced Peripheral Neuropathy

PubMed Central

Nudelman, Kelly N.H.; McDonald, Brenna C.; Wang, Yang; Smith, Dori J.; West, John D.; O'Neill, Darren P.; Zanville, Noah R.; Champion, Victoria L.; Schneider, Bryan P.

2016-01-01

Purpose To investigate the longitudinal relationship between chemotherapy-induced peripheral neuropathy (CIPN) symptoms (sx) and brain perfusion changes in patients with breast cancer. Interaction of CIPN-sx perfusion effects with known chemotherapy-associated gray matter density decrease was also assessed to elucidate the relationship between CIPN and previously reported cancer treatment–related brain structural changes. Methods Patients with breast cancer treated with (n = 24) or without (n = 23) chemotherapy underwent clinical examination and brain magnetic resonance imaging at the following three time points: before treatment (baseline), 1 month after treatment completion, and 1 year after the 1-month assessment. CIPN-sx were evaluated with the self-reported Functional Assessment of Cancer Therapy/Gynecologic Oncology Group–Neurotoxicity four-item sensory-specific scale. Perfusion and gray matter density were assessed using voxel-based pulsed arterial spin labeling and morphometric analyses and tested for association with CIPN-sx in the patients who received chemotherapy. Results Patients who received chemotherapy reported significantly increased CIPN-sx from baseline to 1 month, with partial recovery by 1 year (P < .001). CIPN-sx increase from baseline to 1 month was significantly greater for patients who received chemotherapy compared with those who did not (P = .001). At 1 month, neuroimaging showed that for the group that received chemotherapy, CIPN-sx were positively associated with cerebral perfusion in the right superior frontal gyrus and cingulate gyrus, regions associated with pain processing (P < .001). Longitudinal magnetic resonance imaging analysis in the group receiving chemotherapy indicated that CIPN-sx and associated perfusion changes from baseline to 1 month were also positively correlated with gray matter density change (P < .005). Conclusion Peripheral neuropathy symptoms after systemic chemotherapy for breast cancer are associated with changes in cerebral perfusion and gray matter. The specific mechanisms warrant further investigation given the potential diagnostic and therapeutic implications. PMID:26527786

Mated Fingerprint Card Pairs (Volumes 1-5)

National Institute of Standards and Technology Data Gateway

NIST Mated Fingerprint Card Pairs (Volumes 1-5) (Web, free access)   The NIST database of mated fingerprint card pairs (Special Database 9) consists of multiple volumes. Currently five volumes have been released. Each volume will be a 3-disk set with each CD-ROM containing 90 mated card pairs of segmented 8-bit gray scale fingerprint images (900 fingerprint image pairs per CD-ROM). A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

[Research on non-rigid registration of multi-modal medical image based on Demons algorithm].

PubMed

Hao, Peibo; Chen, Zhen; Jiang, Shaofeng; Wang, Yang

2014-02-01

Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large de formation and multi-modal three-dimensional medical image registration had good effects.

A scalable method to improve gray matter segmentation at ultra high field MRI.

PubMed

Gulban, Omer Faruk; Schneider, Marian; Marquardt, Ingo; Haast, Roy A M; De Martino, Federico

2018-01-01

High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data.

A scalable method to improve gray matter segmentation at ultra high field MRI

PubMed Central

De Martino, Federico

2018-01-01

High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data. PMID:29874295

Added value of high-b-value (b = 3000 s/mm2) diffusion-weighted imaging at 3 T in relation to fluid-attenuated inversion recovery images for the evaluation of cortical lesions in inflammatory brain diseases.

PubMed

Iwashita, Koya; Hirai, Toshinori; Kitajima, Mika; Shigematsu, Yoshinori; Uetani, Hiroyuki; Iryo, Yasuhiko; Azuma, Minako; Hayashida, Eri; Ando, Yukio; Murakami, Ryuji; Yamashita, Yasuyuki

2013-01-01

The purpose of this study was to determine how the gray-to-white matter contrast in healthy subjects changes on high-b-value diffusion-weighted imaging (DWI) acquired at 3 T and evaluate whether high-b-value DWI at 3 T is useful for the detection of cortical lesions in inflammatory brain diseases. Ten healthy volunteers underwent DWI at b = 1000, 2000, 3000, 4000, and 5000 s/mm(2) on a 3-T MRI unit. On DW images, 1 radiologist performed region-of-interest measurements of the signal intensity of 8 gray matter structures. The gray-to-white matter contrast ratio (GWCR) was calculated. Ten patients with inflammatory cortical lesions were also included. All patients underwent conventional MRI and DWI at b = 1000 and 3000 s/mm(2). Using a 4-point grading system, 2 radiologists independently assessed the presence of additional information on DW images compared with fluid-attenuated inversion recovery images. Interobserver agreement was assessed by κ statistics. In the healthy subjects, the b value increased as the GWCR decreased in all evaluated gray matter structures. On DW images acquired at b = 3000 s/mm(2), mean GWCR was less than 1.0 in 7 of 8 structures. For both reviewers, DWI at b = 3000 s/mm(2) yielded significantly more additional information than did DWI at b = 1000 s/mm(2) (P < 0.05). Interobserver agreement for DWI at b = 1000 s/mm(2) and b = 3000 s/mm(2) was fair (κ = 0.35) and excellent (κ = 1.0), respectively. At 3-T DWI, the gray-to-white matter contrast in most gray matter structures reverses at b = 3000 s/mm. In the evaluation of cortical lesions in patients with inflammatory brain diseases, 3-T DWI at b = 3000 s/mm was more useful than b = 1000 s/mm(2).

Three-dimensional volumetric gray-scale uterine cervix histogram prediction of days to delivery in full term pregnancy.

PubMed

Kim, Ji Youn; Kim, Hai-Joong; Hahn, Meong Hi; Jeon, Hye Jin; Cho, Geum Joon; Hong, Sun Chul; Oh, Min Jeong

2013-09-01

Our aim was to figure out whether volumetric gray-scale histogram difference between anterior and posterior cervix can indicate the extent of cervical consistency. We collected data of 95 patients who were appropriate for vaginal delivery with 36th to 37th weeks of gestational age from September 2010 to October 2011 in the Department of Obstetrics and Gynecology, Korea University Ansan Hospital. Patients were excluded who had one of the followings: Cesarean section, labor induction, premature rupture of membrane. Thirty-four patients were finally enrolled. The patients underwent evaluation of the cervix through Bishop score, cervical length, cervical volume, three-dimensional (3D) cervical volumetric gray-scale histogram. The interval days from the cervix evaluation to the delivery day were counted. We compared to 3D cervical volumetric gray-scale histogram, Bishop score, cervical length, cervical volume with interval days from the evaluation of the cervix to the delivery. Gray-scale histogram difference between anterior and posterior cervix was significantly correlated to days to delivery. Its correlation coefficient (R) was 0.500 (P = 0.003). The cervical length was significantly related to the days to delivery. The correlation coefficient (R) and P-value between them were 0.421 and 0.013. However, anterior lip histogram, posterior lip histogram, total cervical volume, Bishop score were not associated with days to delivery (P >0.05). By using gray-scale histogram difference between anterior and posterior cervix and cervical length correlated with the days to delivery. These methods can be utilized to better help predict a cervical consistency.

Colorizing SENTINEL-1 SAR Images Using a Variational Autoencoder Conditioned on SENTINEL-2 Imagery

NASA Astrophysics Data System (ADS)

Schmitt, M.; Hughes, L. H.; Körner, M.; Zhu, X. X.

2018-05-01

In this paper, we have shown an approach for the automatic colorization of SAR backscatter images, which are usually provided in the form of single-channel gray-scale imagery. Using a deep generative model proposed for the purpose of photograph colorization and a Lab-space-based SAR-optical image fusion formulation, we are able to predict artificial color SAR images, which disclose much more information to the human interpreter than the original SAR data. Future work will aim at further adaption of the employed procedure to our special case of multi-sensor remote sensing imagery. Furthermore, we will investigate if the low-level representations learned intrinsically by the deep network can be used for SAR image interpretation in an end-to-end manner.

(In) Sensitivity to spatial distortion in natural scenes

PubMed Central

Bex, Peter J.

2010-01-01

The perception of object structure in the natural environment is remarkably stable under large variation in image size and projection, especially given our insensitivity to spatial position outside the fovea. Sensitivity to periodic spatial distortions that were introduced into one quadrant of gray-scale natural images was measured in a 4AFC task. Observers were able to detect the presence of distortions in unfamiliar images even though they did not significantly affect the amplitude spectrum. Sensitivity depended on the spatial period of the distortion and on the image structure at the location of the distortion. The results suggest that the detection of distortion involves decisions made in the late stages of image perception and is based on an expectation of the typical structure of natural scenes. PMID:20462324

Acute Disseminated Encephalomyelitis: A Gray Distinction.

PubMed

Abu Libdeh, Amal; Goodkin, Howard P; Ramirez-Montealegre, Denia; Brenton, J Nicholas

2017-03-01

Acute disseminated encephalomyelitis (ADEM) is an immune-mediated, inflammatory acquired demyelinating syndrome predominantly affecting the white matter of the central nervous system. We describe a three-year-old boy whose clinical presentation was suspicious for ADEM but whose initial imaging abnormalities were confined to the deep gray matter (without evidence of white matter involvement). His clinical course was fluctuating and repeat imaging one week after presentation demonstrated interval development of characteristic white matter lesions. Treatment with adjunctive intravenous immunoglobulin and high-dose corticosteroids resulted in significant clinical improvement. Isolated deep gray matter involvement can precede the appearance of white matter abnormalities of ADEM, suggesting that repeat imaging is indicated in individuals whose findings are clinically suspicious for ADEM but who lack characteristic imaging findings. Copyright © 2017 Elsevier Inc. All rights reserved.

Using Correlative Properties of Neighboring Pixels to Enhance Contrast-to-Noise Ratio of Abnormal Hippocampus in Patients With Intractable Epilepsy and Mesial Temporal Sclerosis.

PubMed

Parsons, Matthew S; Sharma, Aseem; Hildebolt, Charles

2018-06-12

To test whether an image-processing algorithm can aid in visualization of mesial temporal sclerosis on magnetic resonance imaging by selectively increasing contrast-to-noise ratio (CNR) between abnormal hippocampus and normal brain. In this Institutional Review Board-approved and Health Insurance Portability and Accountability Act-compliant study, baseline coronal fluid-attenuated inversion recovery images of 18 adults (10 females, eight males; mean age 41.2 years) with proven mesial temporal sclerosis were processed using a custom algorithm to produce corresponding enhanced images. Average (Hmean) and maximum (Hmax) CNR for abnormal hippocampus were calculated relative to normal ipsilateral white matter. CNR values for normal gray matter (GM) were similarly calculated using ipsilateral cingulate gyrus as the internal control. To evaluate effect of image processing on visual conspicuity of hippocampal signal alteration, a neuroradiologist masked to the side of hippocampal abnormality rated signal intensity (SI) of hippocampi on baseline and enhanced images using a five-point scale (definitely abnormal to definitely normal). Differences in Hmean, Hmax, GM, and SI ratings for abnormal hippocampi on baseline and enhanced images were assessed for statistical significance. Both Hmean and Hmax were significantly higher in enhanced images as compared to baseline images (p < 0.0001 for both). There was no significant difference in the GM between baseline and enhanced images (p = 0.9375). SI ratings showed a more confident identification of abnormality on enhanced images (p = 0.0001). Image-processing resulted in increased CNR of abnormal hippocampus without affecting the CNR of normal gray matter. This selective increase in conspicuity of abnormal hippocampus was associated with more confident identification of hippocampal signal alteration. Copyright © 2018 Academic Radiology. Published by Elsevier Inc. All rights reserved.

Gray Matter Is Targeted in First-Attack Multiple Sclerosis

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

Schutzer, Steven E.; Angel, Thomas E.; Liu, Tao

The cause of multiple sclerosis (MS), its driving pathogenesis at the earliest stages, and what factors allow the first clinical attack to manifest remain unknown. Some imaging studies suggest gray rather than white matter may be involved early, and some postulate this may be predictive of developing MS. Other imaging studies are in conflict. To determine if there was objective molecular evidence of gray matter involvement in early MS we used high-resolution mass spectrometry to identify proteins in the cerebrospinal fluid (CSF) of first-attack MS patients (two independent groups) compared to established relapsing remitting (RR) MS and controls. We foundmore » that the CSF proteins in first-attack patients were differentially enriched for gray matter components (axon, neuron, synapse). Myelin components did not distinguish these groups. The results support that gray matter dysfunction is involved early in MS, and also may be integral for the initial clinical presentation.« less

Simmering Vanuatu Volcano Imaged by NASA Satellite

NASA Image and Video Library

2017-10-06

On Sept. 28, 2017, Manaro Voui volcano on Ambae island in Vanuatu began spewing ash in a moderate eruption, prompting authorities to order the evacuation of all 11,000 residents. This nighttime thermal infrared image from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), acquired on Oct. 7, shows a hot spot (white) on the volcano's summit crater, but no large eruption. Cold clouds are dark gray, the warmer island is gray, and the ocean, (warmer than the island), is light gray. The image covers an area of 17 by 26 miles (27 by 42.4 kilometers), and is centered at 15.4 degrees south, 167.8 degrees east. https://photojournal.jpl.nasa.gov/catalog/PIA22045

An FPGA-based heterogeneous image fusion system design method

NASA Astrophysics Data System (ADS)

Song, Le; Lin, Yu-chi; Chen, Yan-hua; Zhao, Mei-rong

2011-08-01

Taking the advantages of FPGA's low cost and compact structure, an FPGA-based heterogeneous image fusion platform is established in this study. Altera's Cyclone IV series FPGA is adopted as the core processor of the platform, and the visible light CCD camera and infrared thermal imager are used as the image-capturing device in order to obtain dualchannel heterogeneous video images. Tailor-made image fusion algorithms such as gray-scale weighted averaging, maximum selection and minimum selection methods are analyzed and compared. VHDL language and the synchronous design method are utilized to perform a reliable RTL-level description. Altera's Quartus II 9.0 software is applied to simulate and implement the algorithm modules. The contrast experiments of various fusion algorithms show that, preferably image quality of the heterogeneous image fusion can be obtained on top of the proposed system. The applied range of the different fusion algorithms is also discussed.

Seed viability detection using computerized false-color radiographic image enhancement

NASA Technical Reports Server (NTRS)

Vozzo, J. A.; Marko, Michael

1994-01-01

Seed radiographs are divided into density zones which are related to seed germination. The seeds which germinate have densities relating to false-color red. In turn, a seed sorter may be designed which rejects those seeds not having sufficient red to activate a gate along a moving belt containing the seed source. This results in separating only seeds with the preselected densities representing biological viability lending to germination. These selected seeds demand a higher market value. Actual false-coloring isn't required for a computer to distinguish the significant gray-zone range. This range can be predetermined and screened without the necessity of red imaging. Applying false-color enhancement is a means of emphasizing differences in densities of gray within any subject from photographic, radiographic, or video imaging. Within the 0-255 range of gray levels, colors can be assigned to any single level or group of gray levels. Densitometric values then become easily recognized colors which relate to the image density. Choosing a color to identify any given density allows separation by morphology or composition (form or function). Additionally, relative areas of each color are readily available for determining distribution of that density by comparison with other densities within the image.

A difference tracking algorithm based on discrete sine transform

NASA Astrophysics Data System (ADS)

Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

2018-04-01

Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

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.

SU-E-J-248: Comparative Study of Two Image Registration for Image-Guided Radiation Therapy in Esophageal Cancer

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

Shang, K; Wang, J; Liu, D

2014-06-01

Purpose: Image-guided radiation therapy (IGRT) is one of the major treatment of esophageal cancer. Gray value registration and bone registration are two kinds of image registration, the purpose of this work is to compare which one is more suitable for esophageal cancer patients. Methods: Twenty three esophageal patients were treated by Elekta Synergy, CBCT images were acquired and automatically registered to planning kilovoltage CT scans according to gray value or bone registration. The setup errors were measured in the X, Y and Z axis, respectively. Two kinds of setup errors were analysed by matching T test statistical method. Results: Fourmore » hundred and five groups of CBCT images were available and the systematic and random setup errors (cm) in X, Y, Z directions were 0.35, 0.63, 0.29 and 0.31, 0.53, 0.21 with gray value registration, while 0.37, 0.64, 0.26 and 0.32, 0.55, 0.20 with bone registration, respectively. Compared with bone registration and gray value registration, the setup errors in X and Z axis have significant differences. In Y axis, both measurement comparison results of T value is 0.256 (P value > 0.05); In X axis, the T value is 5.287(P value < 0.05); In Z axis, the T value is −5.138 (P value < 0.05). Conclusion: Gray value registration is recommended in image-guided radiotherapy for esophageal cancer and the other thoracic tumors. Manual registration could be applied when it is necessary. Bone registration is more suitable for the head tumor and pelvic tumor department where composed of redundant interconnected and immobile bone tissue.« less

Experiments in encoding multilevel images as quadtrees

NASA Technical Reports Server (NTRS)

Lansing, Donald L.

1987-01-01

Image storage requirements for several encoding methods are investigated and the use of quadtrees with multigray level or multicolor images are explored. The results of encoding a variety of images having up to 256 gray levels using three schemes (full raster, runlength and quadtree) are presented. Although there is considerable literature on the use of quadtrees to store and manipulate binary images, their application to multilevel images is relatively undeveloped. The potential advantage of quadtree encoding is that an entire area with a uniform gray level may be encoded as a unit. A pointerless quadtree encoding scheme is described. Data are presented on the size of the quadtree required to encode selected images and on the relative storage requirements of the three encoding schemes. A segmentation scheme based on the statistical variation of gray levels within a quadtree quadrant is described. This parametric scheme may be used to control the storage required by an encoded image and to preprocess a scene for feature identification. Several sets of black and white and pseudocolor images obtained by varying the segmentation parameter are shown.

3D shape recovery from image focus using gray level co-occurrence matrix

NASA Astrophysics Data System (ADS)

Mahmood, Fahad; Munir, Umair; Mehmood, Fahad; Iqbal, Javaid

2018-04-01

Recovering a precise and accurate 3-D shape of the target object utilizing robust 3-D shape recovery algorithm is an ultimate objective of computer vision community. Focus measure algorithm plays an important role in this architecture which convert the color values of each pixel of the acquired 2-D image dataset into corresponding focus values. After convolving the focus measure filter with the input 2-D image dataset, a 3-D shape recovery approach is applied which will recover the depth map. In this document, we are concerned with proposing Gray Level Co-occurrence Matrix along with its statistical features for computing the focus information of the image dataset. The Gray Level Co-occurrence Matrix quantifies the texture present in the image using statistical features and then applies joint probability distributive function of the gray level pairs of the input image. Finally, we quantify the focus value of the input image using Gaussian Mixture Model. Due to its little computational complexity, sharp focus measure curve, robust to random noise sources and accuracy, it is considered as superior alternative to most of recently proposed 3-D shape recovery approaches. This algorithm is deeply investigated on real image sequences and synthetic image dataset. The efficiency of the proposed scheme is also compared with the state of art 3-D shape recovery approaches. Finally, by means of two global statistical measures, root mean square error and correlation, we claim that this approach -in spite of simplicity generates accurate results.

Application of gray level mapping in computed tomographic colonography: a pilot study to compare with traditional surface rendering method for identification and differentiation of endoluminal lesions

PubMed Central

Chen, Lih-Shyang; Hsu, Ta-Wen; Chang, Shu-Han; Lin, Chih-Wen; Chen, Yu-Ruei; Hsieh, Chin-Chiang; Han, Shu-Chen; Chang, Ku-Yaw; Hou, Chun-Ju

2017-01-01

Objective: In traditional surface rendering (SR) computed tomographic endoscopy, only the shape of endoluminal lesion is depicted without gray-level information unless the volume rendering technique is used. However, volume rendering technique is relatively slow and complex in terms of computation time and parameter setting. We use computed tomographic colonography (CTC) images as examples and report a new visualization technique by three-dimensional gray level mapping (GM) to better identify and differentiate endoluminal lesions. Methods: There are 33 various endoluminal cases from 30 patients evaluated in this clinical study. These cases were segmented using gray-level threshold. The marching cube algorithm was used to detect isosurfaces in volumetric data sets. GM is applied using the surface gray level of CTC. Radiologists conducted the clinical evaluation of the SR and GM images. The Wilcoxon signed-rank test was used for data analysis. Results: Clinical evaluation confirms GM is significantly superior to SR in terms of gray-level pattern and spatial shape presentation of endoluminal cases (p < 0.01) and improves the confidence of identification and clinical classification of endoluminal lesions significantly (p < 0.01). The specificity and diagnostic accuracy of GM is significantly better than those of SR in diagnostic performance evaluation (p < 0.01). Conclusion: GM can reduce confusion in three-dimensional CTC and well correlate CTC with sectional images by the location as well as gray-level value. Hence, GM increases identification and differentiation of endoluminal lesions, and facilitates diagnostic process. Advances in knowledge: GM significantly improves the traditional SR method by providing reliable gray-level information for the surface points and is helpful in identification and differentiation of endoluminal lesions according to their shape and density. PMID:27925483

Gray matter segmentation of the spinal cord with active contours in MR images.

PubMed

Datta, Esha; Papinutto, Nico; Schlaeger, Regina; Zhu, Alyssa; Carballido-Gamio, Julio; Henry, Roland G

2017-02-15

Fully or partially automated spinal cord gray matter segmentation techniques for spinal cord gray matter segmentation will allow for pivotal spinal cord gray matter measurements in the study of various neurological disorders. The objective of this work was multi-fold: (1) to develop a gray matter segmentation technique that uses registration methods with an existing delineation of the cord edge along with Morphological Geodesic Active Contour (MGAC) models; (2) to assess the accuracy and reproducibility of the newly developed technique on 2D PSIR T1 weighted images; (3) to test how the algorithm performs on different resolutions and other contrasts; (4) to demonstrate how the algorithm can be extended to 3D scans; and (5) to show the clinical potential for multiple sclerosis patients. The MGAC algorithm was developed using a publicly available implementation of a morphological geodesic active contour model and the spinal cord segmentation tool of the software Jim (Xinapse Systems) for initial estimate of the cord boundary. The MGAC algorithm was demonstrated on 2D PSIR images of the C2/C3 level with two different resolutions, 2D T2* weighted images of the C2/C3 level, and a 3D PSIR image. These images were acquired from 45 healthy controls and 58 multiple sclerosis patients selected for the absence of evident lesions at the C2/C3 level. Accuracy was assessed though visual assessment, Hausdorff distances, and Dice similarity coefficients. Reproducibility was assessed through interclass correlation coefficients. Validity was assessed through comparison of segmented gray matter areas in images with different resolution for both manual and MGAC segmentations. Between MGAC and manual segmentations in healthy controls, the mean Dice similarity coefficient was 0.88 (0.82-0.93) and the mean Hausdorff distance was 0.61 (0.46-0.76) mm. The interclass correlation coefficient from test and retest scans of healthy controls was 0.88. The percent change between the manual segmentations from high and low-resolution images was 25%, while the percent change between the MGAC segmentations from high and low resolution images was 13%. Between MGAC and manual segmentations in MS patients, the average Dice similarity coefficient was 0.86 (0.8-0.92) and the average Hausdorff distance was 0.83 (0.29-1.37) mm. We demonstrate that an automatic segmentation technique, based on a morphometric geodesic active contours algorithm, can provide accurate and precise spinal cord gray matter segmentations on 2D PSIR images. We have also shown how this automated technique can potentially be extended to other imaging protocols. Copyright © 2016 Elsevier Inc. All rights reserved.

Robust image watermarking using DWT and SVD for copyright protection

NASA Astrophysics Data System (ADS)

Harjito, Bambang; Suryani, Esti

2017-02-01

The Objective of this paper is proposed a robust combined Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The RGB image is called a cover medium, and watermark image is converted into gray scale. Then, they are transformed using DWT so that they can be split into several subbands, namely sub-band LL2, LH2, HL2. The watermark image embeds into the cover medium on sub-band LL2. This scheme aims to obtain the higher robustness level than the previous method which performs of SVD matrix factorization image for copyright protection. The experiment results show that the proposed method has robustness against several image processing attacks such as Gaussian, Poisson and Salt and Pepper Noise. In these attacks, noise has average Normalized Correlation (NC) values of 0.574863 0.889784, 0.889782 respectively. The watermark image can be detected and extracted.

Locoregional spread of cutaneous melanoma: sonography findings.

PubMed

Catalano, Orlando; Caracò, Corrado; Mozzillo, Nicola; Siani, Alfredo

2010-03-01

This article reviews various aspects of locoregional spread of malignant cutaneous melanoma, as imaged with gray-scale sonography and Doppler techniques. The scenarios illustrated include disease staging (primary melanoma, satellite metastasis, in-transit metastasis, and lymphadenopathies), sentinel lymph node biopsy procedure, patient follow-up, recurrence detection, cutaneous metastasis, and sonographically guided intervention. High-resolution sonography allows recognition of small, clinically-occult melanomatous foci. It plays a major role in locoregional staging and follow-up of patients with cutaneous melanoma.

Computer-Assisted Visual Search/Decision Aids as a Training Tool for Mammography

DTIC Science & Technology

1999-07-01

display of a digital mammogram that compensates for the display brightness, the ambient light and the useful range of pixel intensities in the image...described here extends the work of Liu and Nodine (7) to include adjusting the gray-scale transform for ambient illumination and adjusting the mammogram...visible" disk in each band. The observer’s responses are affected by the display contrast and the ambient room lighting. The contrast of each indicated

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images.

PubMed

Wang, Wensheng; Nie, Ting; Fu, Tianjiao; Ren, Jianyue; Jin, Longxu

2017-05-06

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu's algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape.

Mapping Gray Matter Development: Implications for Typical Development and Vulnerability to Psychopathology

ERIC Educational Resources Information Center

Gogtay, Nitin; Thompson, Paul M.

2010-01-01

Recent studies with brain magnetic resonance imaging (MRI) have scanned large numbers of children and adolescents repeatedly over time, as their brains develop, tracking volumetric changes in gray and white matter in remarkable detail. Focusing on gray matter changes specifically, here we explain how earlier studies using lobar volumes of specific…

The correlation between emotional intelligence and gray matter volume in university students.

PubMed

Tan, Yafei; Zhang, Qinglin; Li, Wenfu; Wei, Dongtao; Qiao, Lei; Qiu, Jiang; Hitchman, Glenn; Liu, Yijun

2014-11-01

A number of recent studies have investigated the neurological substrates of emotional intelligence (EI), but none of them have considered the neural correlates of EI that are measured using the Schutte Self-Report Emotional Intelligence Scale (SSREIS). This scale was developed based on the EI model of Salovey and Mayer (1990). In the present study, SSREIS was adopted to estimate EI. Meanwhile, magnetic resonance imaging (MRI) and voxel-based morphometry (VBM) were used to evaluate the gray matter volume (GMV) of 328 university students. Results found positive correlations between Monitor of Emotions and VBM measurements in the insula and orbitofrontal cortex. In addition, Utilization of Emotions was positively correlated with the GMV in the parahippocampal gyrus, but was negatively correlated with the VBM measurements in the fusiform gyrus and middle temporal gyrus. Furthermore, Social Ability had volume correlates in the vermis. These findings indicate that the neural correlates of the EI model, which primarily focuses on the abilities of individuals to appraise and express emotions, can also regulate and utilize emotions to solve problems. Copyright © 2014 Elsevier Inc. All rights reserved.

Dissociating prefrontal circuitry in intelligence and memory: neuropsychological correlates of magnetic resonance and diffusion tensor imaging.

PubMed

Nestor, Paul G; Ohtani, Toshiyuki; Bouix, Sylvain; Hosokawa, Taiga; Saito, Yukiko; Newell, Dominick T; Kubicki, Marek

2015-12-01

We examined intelligence and memory in 25 healthy participants who had both prior magnetic resonance imaging (MRI) of gray matter volumes of medial orbital frontal cortex (mOFC) and rostral anterior cingulate cortex (rACC), along with diffusion tensor imaging (DTI) of posterior and anterior mOFC-rACC white matter microstructure, as assessed by fractional anisotropy (FA). Results showed distinct relationships between these basic structural brain parameters and higher cognition, highlighted by a highly significant correlation of left rACC gray matter volume with memory, and to a lesser extent, though still statistically significant, correlation of left posterior mOFC-rACC FA with intelligence. Regression analyses showed that left posterior mOFC-rACC connections and left rACC gray matter volume each contributed to intelligence, with left posterior mOFC-rACC FA uniquely accounting for between 20.43 and 24.99% of the variance in intelligence, in comparison to 13.54 to 17.98% uniquely explained by left rACC gray matter volume. For memory, only left rACC gray matter volume explained neuropsychological performance, uniquely accounting for a remarkably high portion of individual variation, ranging from 73.61 to 79.21%. These results pointed to differential contributions of white mater microstructure connections and gray matter volumes to individual differences in intelligence and memory, respectively.

Optical image security using Stokes polarimetry of spatially variant polarized beam

NASA Astrophysics Data System (ADS)

Fatima, Areeba; Nishchal, Naveen K.

2018-06-01

We propose a novel security scheme that uses vector beam characterized by the spatially variant polarization distribution. A vector beam is so generated that its helical components carry tailored phases corresponding to the image/images that is/are to be encrypted. The tailoring of phase has been done by employing the modified Gerchberg-Saxton algorithm for phase retrieval. Stokes parameters for the final vector beam is evaluated and is used to construct the ciphertext and one of the keys. The advantage of the proposed scheme is that it generates real ciphertext and keys which are easier to transmit and store than complex quantities. Moreover, the known plaintext attack is not applicable to this system. As a proof-of-concept, simulation results have been presented for securing single and double gray-scale images.

Information extraction from multivariate images

NASA Technical Reports Server (NTRS)

Park, S. K.; Kegley, K. A.; Schiess, J. R.

1986-01-01

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Ex-vivo quantitative susceptibility mapping of human brain hemispheres

PubMed Central

Kotrotsou, Aikaterini; Tamhane, Ashish A.; Dawe, Robert J.; Kapasi, Alifiya; Leurgans, Sue E.; Schneider, Julie A.; Bennett, David A.; Arfanakis, Konstantinos

2017-01-01

Ex-vivo brain quantitative susceptibility mapping (QSM) allows investigation of brain characteristics at essentially the same point in time as histopathologic examination, and therefore has the potential to become an important tool for determining the role of QSM as a diagnostic and monitoring tool of age-related neuropathologies. In order to be able to translate the ex-vivo QSM findings to in-vivo, it is crucial to understand the effects of death and chemical fixation on brain magnetic susceptibility measurements collected ex-vivo. Thus, the objective of this work was twofold: a) to assess the behavior of magnetic susceptibility in both gray and white matter of human brain hemispheres as a function of time postmortem, and b) to establish the relationship between in-vivo and ex-vivo gray matter susceptibility measurements on the same hemispheres. Five brain hemispheres from community-dwelling older adults were imaged ex-vivo with QSM on a weekly basis for six weeks postmortem, and the longitudinal behavior of ex-vivo magnetic susceptibility in both gray and white matter was assessed. The relationship between in-vivo and ex-vivo gray matter susceptibility measurements was investigated using QSM data from eleven older adults imaged both antemortem and postmortem. No systematic change in ex-vivo magnetic susceptibility of gray or white matter was observed over time postmortem. Additionally, it was demonstrated that, gray matter magnetic susceptibility measured ex-vivo may be well modeled as a linear function of susceptibility measured in-vivo. In conclusion, magnetic susceptibility in gray and white matter measured ex-vivo with QSM does not systematically change in the first six weeks after death. This information is important for future cross-sectional ex-vivo QSM studies of hemispheres imaged at different postmortem intervals. Furthermore, the linear relationship between in-vivo and ex-vivo gray matter magnetic susceptibility suggests that ex-vivo QSM captures information linked to antemortem gray matter magnetic susceptibility, which is important for translation of ex-vivo QSM findings to in-vivo. PMID:29261693

Optical Coherence Tomography for Brain Imaging

NASA Astrophysics Data System (ADS)

Liu, Gangjun; Chen, Zhongping

Recently, there has been growing interest in using OCT for brain imaging. A feasibility study of OCT for guiding deep brain probes has found that OCT can differentiate the white matter and gray matter because the white matter tends to have a higher peak reflectivity and steeper attenuation rate compared to gray matter. In vivo 3D visualization of the layered organization of a rat olfactory bulb with OCT has been demonstrated. OCT has been used for single myelin fiber imaging in living rodents without labeling. The refractive index in the rat somatosensory cortex has also been measured with OCT. In addition, functional extension of OCT, such as Doppler-OCT (D-OCT), polarization sensitive-OCT (PS-OCT), and phase-resolved-OCT (PR-OCT), can image and quantify physiological parameters in addition to the morphological structure image. Based on the scattering changes during neural activity, OCT has been used to measure the functional activation in neuronal tissues. PS-OCT, which combines polarization sensitive detection with OCT to determine tissue birefringence, has been used for the localization of nerve fiber bundles and the mapping of micrometer-scale fiber pathways in the brain. D-OCT, also named optical Doppler tomography (ODT), combines the Doppler principle with OCT to obtain high resolution tomographic images of moving constituents in highly scattering biological tissues. D-OCT has been successfully used to image cortical blood flow and map the blood vessel network for brain research. In this chapter, the principle and technology of OCT and D-OCT are reviewed and examples of potential applications are described.

Synergistic Effects of Age on Patterns of White and Gray Matter Volume across Childhood and Adolescence1,2,3

PubMed Central

Krongold, Mark; Cooper, Cassandra; Lebel, Catherine

2015-01-01

Abstract The human brain develops with a nonlinear contraction of gray matter across late childhood and adolescence with a concomitant increase in white matter volume. Across the adult population, properties of cortical gray matter covary within networks that may represent organizational units for development and degeneration. Although gray matter covariance may be strongest within structurally connected networks, the relationship to volume changes in white matter remains poorly characterized. In the present study we examined age-related trends in white and gray matter volume using T1-weighted MR images from 360 human participants from the NIH MRI study of Normal Brain Development. Images were processed through a voxel-based morphometry pipeline. Linear effects of age on white and gray matter volume were modeled within four age bins, spanning 4-18 years, each including 90 participants (45 male). White and gray matter age-slope maps were separately entered into k-means clustering to identify regions with similar age-related variability across the four age bins. Four white matter clusters were identified, each with a dominant direction of underlying fibers: anterior–posterior, left–right, and two clusters with superior–inferior directions. Corresponding, spatially proximal, gray matter clusters encompassed largely cerebellar, fronto-insular, posterior, and sensorimotor regions, respectively. Pairs of gray and white matter clusters followed parallel slope trajectories, with white matter changes generally positive from 8 years onward (indicating volume increases) and gray matter negative (decreases). As developmental disorders likely target networks rather than individual regions, characterizing typical coordination of white and gray matter development can provide a normative benchmark for understanding atypical development. PMID:26464999

Grayscale inhomogeneity correction method for multiple mosaicked electron microscope images

NASA Astrophysics Data System (ADS)

Zhou, Fangxu; Chen, Xi; Sun, Rong; Han, Hua

2018-04-01

Electron microscope image stitching is highly desired to acquire microscopic resolution images of large target scenes in neuroscience. However, the result of multiple Mosaicked electron microscope images may exist severe gray scale inhomogeneity due to the instability of the electron microscope system and registration errors, which degrade the visual effect of the mosaicked EM images and aggravate the difficulty of follow-up treatment, such as automatic object recognition. Consequently, the grayscale correction method for multiple mosaicked electron microscope images is indispensable in these areas. Different from most previous grayscale correction methods, this paper designs a grayscale correction process for multiple EM images which tackles the difficulty of the multiple images monochrome correction and achieves the consistency of grayscale in the overlap regions. We adjust overall grayscale of the mosaicked images with the location and grayscale information of manual selected seed images, and then fuse local overlap regions between adjacent images using Poisson image editing. Experimental result demonstrates the effectiveness of our proposed method.

Perceptual distortion analysis of color image VQ-based coding

NASA Astrophysics Data System (ADS)

Charrier, Christophe; Knoblauch, Kenneth; Cherifi, Hocine

1997-04-01

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

Examining the effect of psychopathic traits on gray matter volume in a community substance abuse sample.

PubMed

Cope, Lora M; Shane, Matthew S; Segall, Judith M; Nyalakanti, Prashanth K; Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D; Kiehl, Kent A

2012-11-30

Psychopathy is believed to be associated with brain abnormalities in both paralimbic (i.e., orbitofrontal cortex, insula, temporal pole, parahippocampal gyrus, posterior cingulate) and limbic (i.e., amygdala, hippocampus, anterior cingulate) regions. Recent structural imaging studies in both community and prison samples are beginning to support this view. Sixty-six participants, recruited from community corrections centers, were administered the Hare psychopathy checklist-revised (PCL-R), and underwent magnetic resonance imaging (MRI). Voxel-based morphometry was used to test the hypothesis that psychopathic traits would be associated with gray matter reductions in limbic and paralimbic regions. Effects of lifetime drug and alcohol use on gray matter volume were covaried. Psychopathic traits were negatively associated with gray matter volumes in right insula and right hippocampus. Additionally, psychopathic traits were positively associated with gray matter volumes in bilateral orbital frontal cortex and right anterior cingulate. Exploratory regression analyses indicated that gray matter volumes within right hippocampus and left orbital frontal cortex combined to explain 21.8% of the variance in psychopathy scores. These results support the notion that psychopathic traits are associated with abnormal limbic and paralimbic gray matter volume. Furthermore, gray matter increases in areas shown to be functionally impaired suggest that the structure-function relationship may be more nuanced than previously thought. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Prostate segmentation in MR images using discriminant boundary features.

PubMed

Yang, Meijuan; Li, Xuelong; Turkbey, Baris; Choyke, Peter L; Yan, Pingkun

2013-02-01

Segmentation of the prostate in magnetic resonance image has become more in need for its assistance to diagnosis and surgical planning of prostate carcinoma. Due to the natural variability of anatomical structures, statistical shape model has been widely applied in medical image segmentation. Robust and distinctive local features are critical for statistical shape model to achieve accurate segmentation results. The scale invariant feature transformation (SIFT) has been employed to capture the information of the local patch surrounding the boundary. However, when SIFT feature being used for segmentation, the scale and variance are not specified with the location of the point of interest. To deal with it, the discriminant analysis in machine learning is introduced to measure the distinctiveness of the learned SIFT features for each landmark directly and to make the scale and variance adaptive to the locations. As the gray values and gradients vary significantly over the boundary of the prostate, separate appearance descriptors are built for each landmark and then optimized. After that, a two stage coarse-to-fine segmentation approach is carried out by incorporating the local shape variations. Finally, the experiments on prostate segmentation from MR image are conducted to verify the efficiency of the proposed algorithms.

Fast hierarchical knowledge-based approach for human face detection in color images

NASA Astrophysics Data System (ADS)

Jiang, Jun; Gong, Jie; Zhang, Guilin; Hu, Ruolan

2001-09-01

This paper presents a fast hierarchical knowledge-based approach for automatically detecting multi-scale upright faces in still color images. The approach consists of three levels. At the highest level, skin-like regions are determinated by skin model, which is based on the color attributes hue and saturation in HSV color space, as well color attributes red and green in normalized color space. In level 2, a new eye model is devised to select human face candidates in segmented skin-like regions. An important feature of the eye model is that it is independent of the scale of human face. So it is possible for finding human faces in different scale with scanning image only once, and it leads to reduction the computation time of face detection greatly. In level 3, a human face mosaic image model, which is consistent with physical structure features of human face well, is applied to judge whether there are face detects in human face candidate regions. This model includes edge and gray rules. Experiment results show that the approach has high robustness and fast speed. It has wide application perspective at human-computer interactions and visual telephone etc.

A novel method for retinal optic disc detection using bat meta-heuristic algorithm.

PubMed

Abdullah, Ahmad S; Özok, Yasa Ekşioğlu; Rahebi, Javad

2018-05-09

Normally, the optic disc detection of retinal images is useful during the treatment of glaucoma and diabetic retinopathy. In this paper, the novel preprocessing of a retinal image with a bat algorithm (BA) optimization is proposed to detect the optic disc of the retinal image. As the optic disk is a bright area and the vessels that emerge from it are dark, these facts lead to the selected segments being regions with a great diversity of intensity, which does not usually happen in pathological regions. First, in the preprocessing stage, the image is fully converted into a gray image using a gray scale conversion, and then morphological operations are implemented in order to remove dark elements such as blood vessels, from the images. In the next stage, a bat algorithm (BA) is used to find the optimum threshold value for the optic disc location. In order to improve the accuracy and to obtain the best result for the segmented optic disc, the ellipse fitting approach was used in the last stage to enhance and smooth the segmented optic disc boundary region. The ellipse fitting is carried out using the least square distance approach. The efficiency of the proposed method was tested on six publicly available datasets, MESSIDOR, DRIVE, DIARETDB1, DIARETDB0, STARE, and DRIONS-DB. The optic disc segmentation average overlaps and accuracy was in the range of 78.5-88.2% and 96.6-99.91% in these six databases. The optic disk of the retinal images was segmented in less than 2.1 s per image. The use of the proposed method improved the optic disc segmentation results for healthy and pathological retinal images in a low computation time. Graphical abstract ᅟ.

An effective and robust method for tracking multiple fish in video image based on fish head detection.

PubMed

Qian, Zhi-Ming; Wang, Shuo Hong; Cheng, Xi En; Chen, Yan Qiu

2016-06-23

Fish tracking is an important step for video based analysis of fish behavior. Due to severe body deformation and mutual occlusion of multiple swimming fish, accurate and robust fish tracking from video image sequence is a highly challenging problem. The current tracking methods based on motion information are not accurate and robust enough to track the waving body and handle occlusion. In order to better overcome these problems, we propose a multiple fish tracking method based on fish head detection. The shape and gray scale characteristics of the fish image are employed to locate the fish head position. For each detected fish head, we utilize the gray distribution of the head region to estimate the fish head direction. Both the position and direction information from fish detection are then combined to build a cost function of fish swimming. Based on the cost function, global optimization method can be applied to associate the target between consecutive frames. Results show that our method can accurately detect the position and direction information of fish head, and has a good tracking performance for dozens of fish. The proposed method can successfully obtain the motion trajectories for dozens of fish so as to provide more precise data to accommodate systematic analysis of fish behavior.

New contrasts for x-ray imaging and synergy with optical imaging

NASA Astrophysics Data System (ADS)

Wang, Ge

2017-02-01

Due to its penetrating power, fine resolution, unique contrast, high-speed, and cost-effectiveness, x-ray imaging is one of the earliest and most popular imaging modalities in biomedical applications. Current x-ray radiographs and CT images are mostly on gray-scale, since they reflect overall energy attenuation. Recent advances in x-ray detection, contrast agent, and image reconstruction technologies have changed our perception and expectation of x-ray imaging capabilities, and generated an increasing interest in imaging biological soft tissues in terms of energy-sensitive material decomposition, phase-contrast, small angle scattering (also referred to as dark-field), x-ray fluorescence and luminescence properties. These are especially relevant to preclinical and mesoscopic studies, and potentially mendable for hybridization with optical molecular tomography. In this article, we review new x-ray imaging techniques as related to optical imaging, suggest some combined x-ray and optical imaging schemes, and discuss our ideas on micro-modulated x-ray luminescence tomography (MXLT) and x-ray modulated opto-genetics (X-Optogenetics).

Facial recognition using simulated prosthetic pixelized vision.

PubMed

Thompson, Robert W; Barnett, G David; Humayun, Mark S; Dagnelie, Gislin

2003-11-01

To evaluate a model of simulated pixelized prosthetic vision using noncontiguous circular phosphenes, to test the effects of phosphene and grid parameters on facial recognition. A video headset was used to view a reference set of four faces, followed by a partially averted image of one of those faces viewed through a square pixelizing grid that contained 10x10 to 32x32 dots separated by gaps. The grid size, dot size, gap width, dot dropout rate, and gray-scale resolution were varied separately about a standard test condition, for a total of 16 conditions. All tests were first performed at 99% contrast and then repeated at 12.5% contrast. Discrimination speed and performance were influenced by all stimulus parameters. The subjects achieved highly significant facial recognition accuracy for all high-contrast tests except for grids with 70% random dot dropout and two gray levels. In low-contrast tests, significant facial recognition accuracy was achieved for all but the most adverse grid parameters: total grid area less than 17% of the target image, 70% dropout, four or fewer gray levels, and a gap of 40.5 arcmin. For difficult test conditions, a pronounced learning effect was noticed during high-contrast trials, and a more subtle practice effect on timing was evident during subsequent low-contrast trials. These findings suggest that reliable face recognition with crude pixelized grids can be learned and may be possible, even with a crude visual prosthesis.

Regional Gray Matter Volume Deficits in Adolescents with First-Episode Psychosis

ERIC Educational Resources Information Center

Janssen, Joost; Parellada, Mara; Moreno, Dolores; Graell, Montserrat; Fraguas, David; Zabala, Arantzazu; Vazquez, Veronica Garcia; Desco, Manuel; Arango, Celso

2008-01-01

The regional gray matter volumes of adolescents with first-episode psychosis are compared with those of a control group. Magnetic resonance imaging was conducted on 70 patients with early onset FEP and on 51 individuals without FEP. Findings revealed that volume deficits in the left medial frontal gray matter were common in individuals with…

Ultrathin Nonlinear Metasurface for Optical Image Encoding.

PubMed

Walter, Felicitas; Li, Guixin; Meier, Cedrik; Zhang, Shuang; Zentgraf, Thomas

2017-05-10

Security of optical information is of great importance in modern society. Many cryptography techniques based on classical and quantum optics have been widely explored in the linear optical regime. Nonlinear optical encryption in which encoding and decoding involve nonlinear frequency conversions represents a new strategy for securing optical information. Here, we demonstrate that an ultrathin nonlinear photonic metasurface, consisting of meta-atoms with 3-fold rotational symmetry, can be used to hide optical images under illumination with a fundamental wave. However, the hidden image can be read out from second harmonic generation (SHG) waves. This is achieved by controlling the destructive and constructive interferences of SHG waves from two neighboring meta-atoms. In addition, we apply this concept to obtain gray scale SHG imaging. Nonlinear metasurfaces based on space variant optical interference open new avenues for multilevel image encryption, anticounterfeiting, and background free image reconstruction.

A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

PubMed Central

Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao

2017-01-01

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181

Color image processing and vision system for an automated laser paint-stripping system

NASA Astrophysics Data System (ADS)

Hickey, John M., III; Hise, Lawson

1994-10-01

Color image processing in machine vision systems has not gained general acceptance. Most machine vision systems use images that are shades of gray. The Laser Automated Decoating System (LADS) required a vision system which could discriminate between substrates of various colors and textures and paints ranging from semi-gloss grays to high gloss red, white and blue (Air Force Thunderbirds). The changing lighting levels produced by the pulsed CO2 laser mandated a vision system that did not require a constant color temperature lighting for reliable image analysis.

Divergent regional patterns of cerebral hypoperfusion and gray matter atrophy in mild cognitive impairment patients.

PubMed

Wirth, Miranka; Pichet Binette, Alexa; Brunecker, Peter; Köbe, Theresa; Witte, A Veronica; Flöel, Agnes

2017-03-01

Reductions of cerebral blood flow and gray matter structure have been implicated in early pathogenesis of Alzheimer's disease, potentially providing complementary information. The present study evaluated regional patterns of cerebral hypoperfusion and atrophy in patients with mild cognitive impairment and healthy older adults. In each participant, cerebral perfusion and gray matter structure were extracted within selected brain regions vulnerable to Alzheimer's disease using magnetic resonance imaging. Measures were compared between diagnostic groups with/without adjustment for covariates. In mild cognitive impairment patients, cerebral blood flow was significantly reduced in comparison with healthy controls in temporo-parietal regions and the basal ganglia in the absence of local gray matter atrophy. By contrast, gray matter structure was significantly reduced in the hippocampus in the absence of local hypoperfusion. Both, cerebral perfusion and gray matter structure were significantly reduced in the entorhinal and isthmus cingulate cortex in mild cognitive impairment patients compared with healthy older adults. Our results demonstrated partly divergent patterns of temporo-parietal hypoperfusion and medial-temporal atrophy in mild cognitive impairment patients, potentially indicating biomarker sensitivity to dissociable pathological mechanisms. The findings support applicability of cerebral perfusion and gray matter structure as complementary magnetic resonance imaging-based biomarkers in early Alzheimer's disease detection, a hypothesis to be further evaluated in longitudinal studies.

Correlation estimation and performance optimization for distributed image compression

NASA Astrophysics Data System (ADS)

He, Zhihai; Cao, Lei; Cheng, Hui

2006-01-01

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

Associations between IQ, total and regional brain volumes, and demography in a large normative sample of healthy children and adolescents.

PubMed

Lange, Nicholas; Froimowitz, Michael P; Bigler, Erin D; Lainhart, Janet E

2010-01-01

In the course of efforts to establish quantitative norms for healthy brain development by magnetic resonance imaging (MRI) (Brain Development Cooperative Group, 2006), previously unreported associations of parental education and temporal and frontal lobe volumes with full scale IQ and its verbal and performance subscales were discovered. Our findings were derived from the largest, most representative MRI sample to date of healthy children and adolescents, ages 4 years 10 months to 18 years 4 months. We first find that parental education has a strong association with IQ in children that is not mediated by total or regional brain volumes. Second, we find that our observed correlations between temporal gray matter, temporal white matter and frontal white matter volumes with full scale IQ, between 0.14 to 0.27 in children and adolescents, are due in large part to their correlations with performance IQ and not verbal IQ. The volumes of other lobar gray and white matter, subcortical gray matter (thalamus, caudate nucleus, putamen, and globus pallidus), cerebellum, and brainstem do not contribute significantly to IQ variation. Third, we find that head circumference is an insufficient index of cerebral volume in typically developing older children and adolescents. The relations between total and regional brain volumes and IQ can best be discerned when additional variables known to be associated with IQ, especially parental education and other demographic measures, are considered concurrently.

BMPix and PEAK tools: New methods for automated laminae recognition and counting—Application to glacial varves from Antarctic marine sediment

NASA Astrophysics Data System (ADS)

Weber, M. E.; Reichelt, L.; Kuhn, G.; Pfeiffer, M.; Korff, B.; Thurow, J.; Ricken, W.

2010-03-01

We present tools for rapid and quantitative detection of sediment lamination. The BMPix tool extracts color and gray scale curves from images at pixel resolution. The PEAK tool uses the gray scale curve and performs, for the first time, fully automated counting of laminae based on three methods. The maximum count algorithm counts every bright peak of a couplet of two laminae (annual resolution) in a smoothed curve. The zero-crossing algorithm counts every positive and negative halfway passage of the curve through a wide moving average, separating the record into bright and dark intervals (seasonal resolution). The same is true for the frequency truncation method, which uses Fourier transformation to decompose the curve into its frequency components before counting positive and negative passages. The algorithms are available at doi:10.1594/PANGAEA.729700. We applied the new methods successfully to tree rings, to well-dated and already manually counted marine varves from Saanich Inlet, and to marine laminae from the Antarctic continental margin. In combination with AMS14C dating, we found convincing evidence that laminations in Weddell Sea sites represent varves, deposited continuously over several millennia during the last glacial maximum. The new tools offer several advantages over previous methods. The counting procedures are based on a moving average generated from gray scale curves instead of manual counting. Hence, results are highly objective and rely on reproducible mathematical criteria. Also, the PEAK tool measures the thickness of each year or season. Since all information required is displayed graphically, interactive optimization of the counting algorithms can be achieved quickly and conveniently.

Normalization of similarity-based individual brain networks from gray matter MRI and its association with neurodevelopment in infants with intrauterine growth restriction.

PubMed

Batalle, Dafnis; Muñoz-Moreno, Emma; Figueras, Francesc; Bargallo, Nuria; Eixarch, Elisenda; Gratacos, Eduard

2013-12-01

Obtaining individual biomarkers for the prediction of altered neurological outcome is a challenge of modern medicine and neuroscience. Connectomics based on magnetic resonance imaging (MRI) stands as a good candidate to exhaustively extract information from MRI by integrating the information obtained in a few network features that can be used as individual biomarkers of neurological outcome. However, this approach typically requires the use of diffusion and/or functional MRI to extract individual brain networks, which require high acquisition times and present an extreme sensitivity to motion artifacts, critical problems when scanning fetuses and infants. Extraction of individual networks based on morphological similarity from gray matter is a new approach that benefits from the power of graph theory analysis to describe gray matter morphology as a large-scale morphological network from a typical clinical anatomic acquisition such as T1-weighted MRI. In the present paper we propose a methodology to normalize these large-scale morphological networks to a brain network with standardized size based on a parcellation scheme. The proposed methodology was applied to reconstruct individual brain networks of 63 one-year-old infants, 41 infants with intrauterine growth restriction (IUGR) and 22 controls, showing altered network features in the IUGR group, and their association with neurodevelopmental outcome at two years of age by means of ordinal regression analysis of the network features obtained with Bayley Scale for Infant and Toddler Development, third edition. Although it must be more widely assessed, this methodology stands as a good candidate for the development of biomarkers for altered neurodevelopment in the pediatric population. © 2013 Elsevier Inc. All rights reserved.

Feature extraction using gray-level co-occurrence matrix of wavelet coefficients and texture matching for batik motif recognition

NASA Astrophysics Data System (ADS)

Suciati, Nanik; Herumurti, Darlis; Wijaya, Arya Yudhi

2017-02-01

Batik is one of Indonesian's traditional cloth. Motif or pattern drawn on a piece of batik fabric has a specific name and philosopy. Although batik cloths are widely used in everyday life, but only few people understand its motif and philosophy. This research is intended to develop a batik motif recognition system which can be used to identify motif of Batik image automatically. First, a batik image is decomposed into sub-images using wavelet transform. Six texture descriptors, i.e. max probability, correlation, contrast, uniformity, homogenity and entropy, are extracted from gray-level co-occurrence matrix of each sub-image. The texture features are then matched to the template features using canberra distance. The experiment is performed on Batik Dataset consisting of 1088 batik images grouped into seven motifs. The best recognition rate, that is 92,1%, is achieved using feature extraction process with 5 level wavelet decomposition and 4 directional gray-level co-occurrence matrix.

A novel quantum LSB-based steganography method using the Gray code for colored quantum images

NASA Astrophysics Data System (ADS)

Heidari, Shahrokh; Farzadnia, Ehsan

2017-10-01

As one of the prevalent data-hiding techniques, steganography is defined as the act of concealing secret information in a cover multimedia encompassing text, image, video and audio, imperceptibly, in order to perform interaction between the sender and the receiver in which nobody except the receiver can figure out the secret data. In this approach a quantum LSB-based steganography method utilizing the Gray code for quantum RGB images is investigated. This method uses the Gray code to accommodate two secret qubits in 3 LSBs of each pixel simultaneously according to reference tables. Experimental consequences which are analyzed in MATLAB environment, exhibit that the present schema shows good performance and also it is more secure and applicable than the previous one currently found in the literature.

Gray Matter Increase in Motor Cortex in Pediatric ADHD: A Voxel-Based Morphometry Study.

PubMed

Sutcubasi Kaya, Bernis; Metin, Baris; Tas, Zeynep Cubukcuoglu; Buyukaslan, Ayse; Soysal, Aysegul; Hatiloglu, Deniz; Tarhan, Nevzat

2018-05-01

Several studies report that ADHD is associated with reduced gray matter (GM), whereas others report no differences in GM volume between ADHD patients and controls, and some even report more GM volume in individuals with ADHD. These conflicting findings suggest that reduced GM is not a universal finding in ADHD, and that more research is needed to delineate with greater accuracy the range of GM alterations. The present study aimed to identify GM alterations in ADHD using pediatric templates. 19 drug-naïve ADHD patients and 18 controls, all aged 7 to 14 years, were scanned using magnetic resonance imaging. Relative to the controls, the ADHD patients had more GM, predominantly in the precentral and supplementary motor areas. Moreover, there were positive correlations between GM volume in these areas and ADHD scale scores. The clinical and pathophysiological significance of increased GM in the motor areas remains to be elucidated by additional research.

Heterotopic gray matter. Neuroradiological aspects and clinical correlations.

PubMed

Canapicchi, R; Padolecchia, R; Puglioli, M; Collavoli, P; Marcella, F; Valleriani, A M

1990-01-01

Anomalies of cell migration manifest themselves in many ways with various clinical and morphological aspects. Among these, heterotopic gray matter, especially when isolated, is characterized by slighter symptoms and later onset. In this paper eight cases of gray matter heterotopia are presented which have been studied over a two-year period. Magnetic Resonance imaging is emphasised for a correct diagnosis.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

Spectral mixture modeling - A new analysis of rock and soil types at the Viking Lander 1 site. [on Mars

NASA Technical Reports Server (NTRS)

Adams, J. B.; Smith, M. O.; Johnson, P. E.

1986-01-01

A Viking Lander 1 image was modeled as mixtures of reflectance spectra of palagonite dust, gray andesitelike rock, and a coarse rocklike soil. The rocks are covered to varying degrees by dust but otherwise appear unweathered. Rocklike soil occurs as lag deposits in deflation zones around stones and on top of a drift and as a layer in a trench dug by the lander. This soil probably is derived from the rocks by wind abrasion and/or spallation. Dust is the major component of the soil and covers most of the surface. The dust is unrelated spectrally to the rock but is equivalent to the global-scale dust observed telescopically. A new method was developed to model a multispectral image as mixtures of end-member spectra and to compare image spectra directly with laboratory reference spectra. The method for the first time uses shade and secondary illumination effects as spectral end-members; thus the effects of topography and illumination on all scales can be isolated or removed. The image was calibrated absolutely from the laboratory spectra, in close agreement with direct calibrations. The method has broad applications to interpreting multispectral images, including satellite images.

Comparison of fundamental and wideband harmonic contrast imaging of liver tumors.

PubMed

Forsberg, F; Liu, J B; Chiou, H J; Rawool, N M; Parker, L; Goldberg, B B

2000-03-01

Wideband harmonic imaging (with phase inversion for improved tissue suppression) was compared to fundamental imaging in vivo. Four woodchucks with naturally occurring liver tumors were injected with Imagent (Alliance Pharmaceutical Corp., San Diego, CA). Randomized combinations of dose (0.05, 0.2 and 0.4 ml/kg) and acoustic output power (AO; 5, 25 and 63% or MI < or = 0.9) were imaged in gray scale using a Sonoline Elegra scanner (Siemens Medical Systems, Issaquah, WA). Tumor vascularity, conspicuity and contrast enhancement were rated by three independent observers. Imagent produced marked tumor enhancement and improved depiction of neovascularity at all dosages and AO settings in both modes. Tumor vascularity and enhancement correlated with mode, dose and AO (P < 0.002). Fundamental imaging produced more enhancement (P < 0.05), but tumor vascularity and conspicuity were best appreciated in harmonic mode (P < 0.05). Under the conditions studied here, the best approach was wideband harmonic imaging with 0.2 ml/kg of Imagent at an AO of 25%.

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.

PubMed

Zhang, Weilong; Guo, Bingxuan; Li, Ming; Liao, Xuan; Li, Wenzhuo

2018-04-16

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

Cognitive Implications of Deep Gray Matter Iron in Multiple Sclerosis.

PubMed

Fujiwara, E; Kmech, J A; Cobzas, D; Sun, H; Seres, P; Blevins, G; Wilman, A H

2017-05-01

Deep gray matter iron accumulation is increasingly recognized in association with multiple sclerosis and can be measured in vivo with MR imaging. The cognitive implications of this pathology are not well-understood, especially vis-à-vis deep gray matter atrophy. Our aim was to investigate the relationships between cognition and deep gray matter iron in MS by using 2 MR imaging-based iron-susceptibility measures. Forty patients with multiple sclerosis (relapsing-remitting, n = 16; progressive, n = 24) and 27 healthy controls were imaged at 4.7T by using the transverse relaxation rate and quantitative susceptibility mapping. The transverse relaxation rate and quantitative susceptibility mapping values and volumes (atrophy) of the caudate, putamen, globus pallidus, and thalamus were determined by multiatlas segmentation. Cognition was assessed with the Brief Repeatable Battery of Neuropsychological Tests. Relationships between cognition and deep gray matter iron were examined by hierarchic regressions. Compared with controls, patients showed reduced memory ( P < .001) and processing speed ( P = .02) and smaller putamen ( P < .001), globus pallidus ( P = .002), and thalamic volumes ( P < .001). Quantitative susceptibility mapping values were increased in patients compared with controls in the putamen ( P = .003) and globus pallidus ( P = .003). In patients only, thalamus ( P < .001) and putamen ( P = .04) volumes were related to cognitive performance. After we controlled for volume effects, quantitative susceptibility mapping values in the globus pallidus ( P = .03; trend for transverse relaxation rate, P = .10) were still related to cognition. Quantitative susceptibility mapping was more sensitive compared with the transverse relaxation rate in detecting deep gray matter iron accumulation in the current multiple sclerosis cohort. Atrophy and iron accumulation in deep gray matter both have negative but separable relationships to cognition in multiple sclerosis. © 2017 by American Journal of Neuroradiology.

LSB-based Steganography Using Reflected Gray Code for Color Quantum Images

NASA Astrophysics Data System (ADS)

Li, Panchi; Lu, Aiping

2018-02-01

At present, the classical least-significant-bit (LSB) based image steganography has been extended to quantum image processing. For the existing LSB-based quantum image steganography schemes, the embedding capacity is no more than 3 bits per pixel. Therefore, it is meaningful to study how to improve the embedding capacity of quantum image steganography. This work presents a novel LSB-based steganography using reflected Gray code for colored quantum images, and the embedding capacity of this scheme is up to 4 bits per pixel. In proposed scheme, the secret qubit sequence is considered as a sequence of 4-bit segments. For the four bits in each segment, the first bit is embedded in the second LSB of B channel of the cover image, and and the remaining three bits are embedded in LSB of RGB channels of each color pixel simultaneously using reflected-Gray code to determine the embedded bit from secret information. Following the transforming rule, the LSB of stego-image are not always same as the secret bits and the differences are up to almost 50%. Experimental results confirm that the proposed scheme shows good performance and outperforms the previous ones currently found in the literature in terms of embedding capacity.

Studies in optical parallel processing. [All optical and electro-optic approaches

NASA Technical Reports Server (NTRS)

Lee, S. H.

1978-01-01

Threshold and A/D devices for converting a gray scale image into a binary one were investigated for all-optical and opto-electronic approaches to parallel processing. Integrated optical logic circuits (IOC) and optical parallel logic devices (OPA) were studied as an approach to processing optical binary signals. In the IOC logic scheme, a single row of an optical image is coupled into the IOC substrate at a time through an array of optical fibers. Parallel processing is carried out out, on each image element of these rows, in the IOC substrate and the resulting output exits via a second array of optical fibers. The OPAL system for parallel processing which uses a Fabry-Perot interferometer for image thresholding and analog-to-digital conversion, achieves a higher degree of parallel processing than is possible with IOC.

Median Hetero-Associative Memories Applied to the Categorization of True-Color Patterns

NASA Astrophysics Data System (ADS)

Vázquez, Roberto A.; Sossa, Humberto

Median associative memories (MED-AMs) are a special type of associative memory based on the median operator. This type of associative model has been applied to the restoration of gray scale images and provides better performance than other models, such as morphological associative memories, when the patterns are altered with mixed noise. Despite of his power, MED-AMs have not been applied in problems involving true-color patterns. In this paper we describe how a median hetero-associative memory (MED-HAM) could be applied in problems that involve true-color patterns. A complete study of the behavior of this associative model in the restoration of true-color images is performed using a benchmark of 14400 images altered by different type of noises. Furthermore, we describe how this model can be applied to an image categorization problem.

A Simple Encryption Algorithm for Quantum Color Image

NASA Astrophysics Data System (ADS)

Li, Panchi; Zhao, Ya

2017-06-01

In this paper, a simple encryption scheme for quantum color image is proposed. Firstly, a color image is transformed into a quantum superposition state by employing NEQR (novel enhanced quantum representation), where the R,G,B values of every pixel in a 24-bit RGB true color image are represented by 24 single-qubit basic states, and each value has 8 qubits. Then, these 24 qubits are respectively transformed from a basic state into a balanced superposition state by employed the controlled rotation gates. At this time, the gray-scale values of R, G, B of every pixel are in a balanced superposition of 224 multi-qubits basic states. After measuring, the whole image is an uniform white noise, which does not provide any information. Decryption is the reverse process of encryption. The experimental results on the classical computer show that the proposed encryption scheme has better security.

A pilot study using an infrared imaging system in prevention of post-endoscopic submucosal dissection ulcer bleeding.

PubMed

Yoshida, Yukinaga; Matsuda, Koji; Tamai, Naoto; Yoshizawa, Kai; Nikami, Toshiki; Ishiguro, Haruya; Tajiri, Hisao

2014-01-01

Endoscopic submucosal dissection (ESD) for superficial gastric neoplasm is a curative method. The aim of this study was to detect potential nonbleeding visible vessels (NBVVs) by using an infrared imaging (IRI) system. A total of 24 patients (25 lesions) were consecutively enrolled between March 2010 and December 2010. The day after ESD, endoscopist A (K.M.), who was blinded to the actual procedure of ESD, performed esophagogastroduodenoscopy (EGD) of the post-ESD ulcer base using the IRI system. Endoscopist A marked gray/blue points in the hard-copy images with the IRI system. After the first procedure, endoscopist B (Y.Y.), who was blinded to the results recorded by endoscopist A, performed a second EGD with white light endoscopy and administered water-jet pressure with the maximum level of an Olympus flushing pump onto the post-ESD ulcer base. This test can cause iatrogenic bleeding via application of pressure to NBVV in the post-ESD ulcer. The IRI system detected 58 gray points and 71 blue points. The post-ESD ulcer was divided into the central area and the peripheral area. There were 14 gray points (24 %) in the central area and 44 gray points (76 %) in the peripheral area. There were 19 blue points (27 %) in the central area and 52 blue points (73 %) in the peripheral area. There was no significant difference when comparing the distribution of gray points and blue points. Bleeding occurred with a water-jet pressure in 11 of 58 gray points and in none of the blue points (P = 0.000478). Among the gray points, bleeding in response to a water-jet pressure occurred in 2 points in the central area and in 9 points in the peripheral area. The IRI system detects visible vessels (VVs) that are in no need of coagulation as blue points, and VVs have a potential risk of bleeding as gray points.

Emerging factors associated with the decline of a gray fox population and multi-scale land cover associations of mesopredators in the Chicago metropolitan area.

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

Willingham, Alison N.; /Ohio State U.

Statewide surveys of furbearers in Illinois indicate gray (Urocyon cinereoargenteus) and red (Vulpes vulpes) foxes have experienced substantial declines in relative abundance, whereas other species such as raccoons (Procyon lotor) and coyotes (Canis latrans) have exhibited dramatic increases during the same time period. The cause of the declines of gray and red foxes has not been identified, and the current status of gray foxes remains uncertain. Therefore, I conducted a large-scale predator survey and tracked radiocollared gray foxes from 2004 to 2007 in order to determine the distribution, survival, cause-specific mortality sources and land cover associations of gray foxes inmore » an urbanized region of northeastern Illinois, and examined the relationships between the occurrence of gray fox and the presence other species of mesopredators, specifically coyotes and raccoons. Although generalist mesopredators are common and can reach high densities in many urban areas their urban ecology is poorly understood due to their secretive nature and wariness of humans. Understanding how mesopredators utilize urbanized landscapes can be useful in the management and control of disease outbreaks, mitigation of nuisance wildlife issues, and gaining insight into how mesopredators shape wildlife communities in highly fragmented areas. I examined habitat associations of raccoons, opossums (Didelphis virginiana), domestic cats (Felis catus), coyotes, foxes (gray and red), and striped skunks (Mephitis mephitis) at multiple spatial scales in an urban environment. Gray fox occurrence was rare and widely dispersed, and survival estimates were similar to other studies. Gray fox occurrence was negatively associated with natural and semi-natural land cover types. Fox home range size increased with increasing urban development suggesting that foxes may be negatively influenced by urbanization. Gray fox occurrence was not associated with coyote or raccoon presence. However, spatial avoidance and mortality due to coyote predation was documented and disease was a major mortality source for foxes. The declining relative abundance of gray fox in Illinois is likely a result of a combination of factors. Assessment of habitat associations indicated that urban mesopredators, particularly coyotes and foxes, perceived the landscape as relatively homogeneous and that urban mesopredators interacted with the environment at scales larger than that accommodated by remnant habitat patches. Coyote and fox presence was found to be associated with a high degree of urban development at large and intermediate spatial scales. However, at a small spatial scale fox presence was associated with high density urban land cover whereas coyote presence was associated with urban development with increased forest cover. Urban habitats can offer a diversity of prey items and anthropogenic resources and natural land cover could offer coyotes daytime resting opportunities in urban areas where they may not be as tolerated as smaller foxes. Raccoons and opossums were found to utilize moderately developed landscapes with interspersed natural and semi-natural land covers at a large spatial scale, which may facilitate dispersal movements. At intermediate and small spatial scales, both species were found to utilize areas that were moderately developed and included forested land cover. These results indicated that raccoons and opossums used natural areas in proximity to anthropogenic resources. At a large spatial scale, skunk presence was associated with highly developed landscapes with interspersed natural and semi-natural land covers. This may indicate that skunks perceived the urban matrix as more homogeneous than raccoons or opossums. At an intermediate spatial scale skunks were associated with moderate levels of development and increased forest cover, which indicated that they might utilize natural land cover in proximity to human-dominated land cover. At the smallest spatial scale skunk presence was associated with forested land cover surrounded by a suburban matrix. Compared to raccoons and opossums, skunks may not be tolerated in close proximity to human development in urban areas. Domestic cat presence was positively associated with increasingly urbanized and less diverse landscapes with decreased amounts of forest and urban open space at the largest spatial scale. At an intermediate spatial scale, cat presence was associated with a moderate degree of urban development characterized by increased forest cover, and at a small spatial scale cat presence was associated with a high degree of urbanization. Free-ranging domestic cats are often associated with human-dominated landscapes and likely utilize remnant natural habitat patches for hunting purposes, which may have implications for native predator and prey species existing in fragmented habitat patches in proximity to human development.« less

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

NASA Technical Reports Server (NTRS)

Anderson, J. H. (Principal Investigator)

1972-01-01

The author has identified the following significant results. A reconstituted color infrared image covering the western Seward Peninsula was used for identifying vegetation types by simple visual examination. The image was taken by ERTS-1 approximately 1120 hours on August 1, 1972. Seven major colors were identified. Four of these were matched with four units on existing vegetation maps: bright red - shrub thicket; light gray-red - upland tundra; medium gray-red - coastal wet tundra; gray - alpine barrens. In the bright red color, two phases, violet and orange, were recognized and tentatively ascribed to differences in species composition in the shrub thicket type. The three colors which had no map unit equivalents were interpreted as follows: pink - grassland tundra; dark gray-red - burn scars; light orange-red - senescent vegetation. It was concluded that the image provides a considerable amount of information regarding the distribution of vegetation types, even at so simple a leval of analysis. It was also concluded that sequential imagery of this type could provide useful information on vegetation fires and phenologic events.

A new vegetation map of the western Seward Peninsula, Alaska, based on ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Anderson, J. H.; Belon, A. E. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A reconstituted, simulated color-infrared ERTS-1 image covering the western Seward Peninsula was prepared and it is used for identifying and mapping vegetation types by direct visual examination. The image, NASA ERTS E-1009-22095, was obtained approximately at 1110 hours, 165 degrees WMT on August 1, 1972. Seven major colors are identified. Four of these are matched with units on existing vegetation maps: bright red - shrub thicket; light gray-red - upland tundra; medium gray-red - coastal coastal wet tundra; gray - alpine barrens. The three colors having no map equivalents are tentatively interpreted as follows: pink - grassland tundra; dark gray-red - burn scars; light orange-red - senescent vegetation. A vegetation map, drawn by tracing on an acetate overlay of the image is presented. Significantly more information is depicted than on existing maps with regards to vegetation types and their areal distribution. Furthermore the preparation of the new map from ERTS-1 imagery required little time relative to conventional methods and extent of areal coverage.

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

PubMed

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

NASA Astrophysics Data System (ADS)

Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

2017-08-01

Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

Integration of medical imaging into a multi-institutional hospital information system structure.

PubMed

Dayhoff, R E

1995-01-01

The Department of Veterans Affairs (VA) is providing integrated text and image data to its clinical users at its Washington and Baltimore medical centers and, soon, at nine other medical centers. The DHCP Imaging System records clinically significant diagnostic images selected by medical specialists in a variety of departments, including cardiology, gastroenterology, pathology, dermatology, surgery, radiology, podiatry, dentistry, and emergency medicine. These images, which include color and gray scale images, and electrocardiogram waveforms, are displayed on workstations located throughout the medical centers. Integration of clinical images with the VA's electronic mail system allows transfer of data from one medical center to another. The ability to incorporate transmitted text and image data into on-line patient records at the collaborating sites is an important aspect of professional consultation. In order to achieve the maximum benefits from an integrated patient record system, a critical mass of information must be available for clinicians. When there is also seamless support for administration, it becomes possible to re-engineer the processes involved in providing medical care.

Image Edge Extraction via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A. (Inventor); Klinko, Steve (Inventor)

2008-01-01

A computer-based technique for detecting edges in gray level digital images employs fuzzy reasoning to analyze whether each pixel in an image is likely on an edge. The image is analyzed on a pixel-by-pixel basis by analyzing gradient levels of pixels in a square window surrounding the pixel being analyzed. An edge path passing through the pixel having the greatest intensity gradient is used as input to a fuzzy membership function, which employs fuzzy singletons and inference rules to assigns a new gray level value to the pixel that is related to the pixel's edginess degree.

Converging evidence for abnormalities of the prefrontal cortex and evaluation of midsagittal structures in pediatric PTSD: an MRI study

PubMed Central

Carrion, Victor G.; Weems, Carl F.; Watson, Christa; Eliez, Stephan; Menon, Vinod; Reiss, Allan L.

2009-01-01

Objective Volumetric imaging research has shown abnormal brain morphology in posttraumatic stress disorder (PTSD) when compared to controls. We present results on a study of brain morphology in the prefrontal cortex (PFC) and midline structures, via indices of gray matter volume and density, in pediatric PTSD. We hypothesized that both methods would demonstrate aberrant morphology in the PFC. Further, we hypothesized aberrant brainstem anatomy and reduced corpus collosum volume in children with PTSD. Methods Twenty-four children (aged 7-14) with history of interpersonal trauma and 24 age, and gender matched controls underwent structural magnetic resonance imaging. Images of the PFC and midline brain structures were first analyzed using volumetric image analysis. The PFC data were then compared with whole-brain voxel-based techniques using statistical parametric mapping (SPM). Results The PTSD group showed significant increased gray matter volume in the right and left inferior and superior quadrants of the prefrontal cortex and smaller gray matter volume in pons, and posterior vermis areas by volumetric image analysis. The voxel-byvoxel group comparisons demonstrated increased gray matter density mostly localized to ventral PFC as compared to the control group. Conclusions Abnormal frontal lobe morphology, as revealed by separate-complementary image analysis methods, and reduced pons and posterior vermis areas are associated with pediatric PTSD. Voxel-based morphometry may help to corroborate and further localize data obtained by volume of interest methods in PTSD. PMID:19349151

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

PubMed

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

2012-07-01

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

Early changes in brain structure correlate with language outcomes in children with neonatal encephalopathy.

PubMed

Shapiro, Kevin A; Kim, Hosung; Mandelli, Maria Luisa; Rogers, Elizabeth E; Gano, Dawn; Ferriero, Donna M; Barkovich, A James; Gorno-Tempini, Maria Luisa; Glass, Hannah C; Xu, Duan

2017-01-01

Global patterns of brain injury correlate with motor, cognitive, and language outcomes in survivors of neonatal encephalopathy (NE). However, it is still unclear whether local changes in brain structure predict specific deficits. We therefore examined whether differences in brain structure at 6 months of age are associated with neurodevelopmental outcomes in this population. We enrolled 32 children with NE, performed structural brain MR imaging at 6 months, and assessed neurodevelopmental outcomes at 30 months. All subjects underwent T1-weighted imaging at 3 T using a 3D IR-SPGR sequence. Images were normalized in intensity and nonlinearly registered to a template constructed specifically for this population, creating a deformation field map. We then used deformation based morphometry (DBM) to correlate variation in the local volume of gray and white matter with composite scores on the Bayley Scales of Infant and Toddler Development (Bayley-III) at 30 months. Our general linear model included gestational age, sex, birth weight, and treatment with hypothermia as covariates. Regional brain volume was significantly associated with language scores, particularly in perisylvian cortical regions including the left supramarginal gyrus, posterior superior and middle temporal gyri, and right insula, as well as inferior frontoparietal subcortical white matter. We did not find significant correlations between regional brain volume and motor or cognitive scale scores. We conclude that, in children with a history of NE, local changes in the volume of perisylvian gray and white matter at 6 months are correlated with language outcome at 30 months. Quantitative measures of brain volume on early MRI may help identify infants at risk for poor language outcomes.

Spirit Scans Winter Haven

NASA Image and Video Library

2006-04-24

This approximately true-color image shows paper-thin layers of light-toned, jagged-edged rocks; a light gray rock with smooth, rounded edges atop and drifts; and several dark gray to black, angular rocks with vesicles typical of hardened lava

[Imaging Observation of Scalp Acupuncture on Brain Gray Matter Injury in Stroke Patients with Cerebral Infarction].

PubMed

Lang, Yi; Cui, Fang-yuan; Li, Kuang-shi; Tan, Zhong-jian; Zou, Yi-huai

2016-03-01

To study features of brain gray matter injury in cerebral infarction patients and intervention of scalp acupuncture by using voxel-based morphology. A total of 16 cerebral infarction patients were recruited in this study, and assigned to the scalp acupuncture group and the control group, 8 in each group. Another 16 healthy volunteers were recruited as a normal group. All patients received scanning of T1 structure. Images were managed using VBM8 Software package. Difference of the gray matter structure was compared among the scalp acupuncture group, the control group, and the healthy volunteers. Compared with healthy volunteers, gray matter injury of cerebral infarction patients mainly occurred in 14 brain regions such as cingulate gyrus, precuneus, cuneus, anterior central gyrus, insular lobe, and so on. They were mainly distributed in affected side. Two weeks after treatment when compared with healthy volunteers, gray matter injury of cerebral infarction patients in the scalp acupuncture group still existed in 8 brain regions such as bilateral lingual gyrus, posterior cingulate gyrus, left cuneus, right precuneus, and so on. New gray matter injury occurred in lingual gyrus and posterior cingulate gyrus. Two weeks after treatment when compared with healthy volunteers, gray matter injury of cerebral infarction patients in the control group existed in 23 brain regions: bilateral anterior cingulum, caudate nucleus, cuneate lobe, insular lobe, inferior frontal gyrus, medial frontal gyrus, precuneus, paracentral lobule, superior temporal gyrus, middle temporal gyrus, lingual gyrus, right postcentral gyrus, posterior cingulate gyrus, precentral gyrus, middle frontal gyrus, and so on. New gray matter injury still existed in 9 cerebral regions such as lingual gyrus, posterior cingulate gyrus, postcentral gyrus, and so on. Brain gray matter structure is widely injured after cerebral infarction. Brain gray matter volume gradually decreased as time went by. Combined use of scalp acupuncture might inhibit the progression of gray matter injury more effectively.

Contrast-enhanced color Doppler ultrasonography increases diagnostic accuracy for soft tissue tumors.

PubMed

Oebisu, Naoto; Hoshi, Manabu; Ieguchi, Makoto; Takada, Jun; Iwai, Tadashi; Ohsawa, Masahiko; Nakamura, Hiroaki

2014-10-01

Resolution of ultrasonography (US) has undergone marked development. Additionally, a new-generation contrast medium (Sonazoid) used for US is newly available. Contrast-enhanced US has been widely used for evaluating several types of cancer. In the present study, we evaluated the ability of color Doppler US (CDUS) and Sonazoid to differentiate between benign and malignant soft tissue tumors. A total of 180 patients (87 male, 93 female) were enrolled in the present study. The patient ages ranged from 1 to 91 years (mean 58.1±20.0 years). The maximum size, depth, tumor margins, shape, echogenicity and textural pattern were measured on gray-scale images. CDUS was used to evaluate the intratumoral blood flow with and without Sonazoid. Peak systolic flow velocity (Vp), mean flow velocity (Vm), resistivity index (RI) and pulsatility index (PI) of each detected intratumoral artery were automatically calculated with power Doppler US (PDUS). The present study included 118 benign and 62 malignant tumors. Statistical significances were found in size, depth, tumor margin and textural pattern but not in shape or echogenicity on gray-scale images. Before Sonazoid injection, CDUS findings showed 55% sensitivity, 77% specificity and 69% accuracy, whereas contrast-enhanced CDUS showed 87% sensitivity, 68% specificity and 74% accuracy. There were no statistically significant differences between malignant and benign tumors regarding the mean Vp, Vm, RI and PI values determined on PDUS. In conclusion, contrast-enhanced CDUS proved to be a reliable diagnostic tool for detecting malignant potential in soft tissue tumors.

A Novel Method of Aircraft Detection Based on High-Resolution Panchromatic Optical Remote Sensing Images

PubMed Central

Wang, Wensheng; Nie, Ting; Fu, Tianjiao; Ren, Jianyue; Jin, Longxu

2017-01-01

In target detection of optical remote sensing images, two main obstacles for aircraft target detection are how to extract the candidates in complex gray-scale-multi background and how to confirm the targets in case the target shapes are deformed, irregular or asymmetric, such as that caused by natural conditions (low signal-to-noise ratio, illumination condition or swaying photographing) and occlusion by surrounding objects (boarding bridge, equipment). To solve these issues, an improved active contours algorithm, namely region-scalable fitting energy based threshold (TRSF), and a corner-convex hull based segmentation algorithm (CCHS) are proposed in this paper. Firstly, the maximal variance between-cluster algorithm (Otsu’s algorithm) and region-scalable fitting energy (RSF) algorithm are combined to solve the difficulty of targets extraction in complex and gray-scale-multi backgrounds. Secondly, based on inherent shapes and prominent corners, aircrafts are divided into five fragments by utilizing convex hulls and Harris corner points. Furthermore, a series of new structure features, which describe the proportion of targets part in the fragment to the whole fragment and the proportion of fragment to the whole hull, are identified to judge whether the targets are true or not. Experimental results show that TRSF algorithm could improve extraction accuracy in complex background, and that it is faster than some traditional active contours algorithms. The CCHS is effective to suppress the detection difficulties caused by the irregular shape. PMID:28481260

Prefrontal gray matter volume mediates genetic risks for obesity.

PubMed

Opel, N; Redlich, R; Kaehler, C; Grotegerd, D; Dohm, K; Heindel, W; Kugel, H; Thalamuthu, A; Koutsouleris, N; Arolt, V; Teuber, A; Wersching, H; Baune, B T; Berger, K; Dannlowski, U

2017-05-01

Genetic and neuroimaging research has identified neurobiological correlates of obesity. However, evidence for an integrated model of genetic risk and brain structural alterations in the pathophysiology of obesity is still absent. Here we investigated the relationship between polygenic risk for obesity, gray matter structure and body mass index (BMI) by the use of univariate and multivariate analyses in two large, independent cohorts (n=330 and n=347). Higher BMI and higher polygenic risk for obesity were significantly associated with medial prefrontal gray matter decrease, and prefrontal gray matter was further shown to significantly mediate the effect of polygenic risk for obesity on BMI in both samples. Building on this, the successful individualized prediction of BMI by means of multivariate pattern classification algorithms trained on whole-brain imaging data and external validations in the second cohort points to potential clinical applications of this imaging trait marker.

An Adaptive Immune Genetic Algorithm for Edge Detection

NASA Astrophysics Data System (ADS)

Li, Ying; Bai, Bendu; Zhang, Yanning

An adaptive immune genetic algorithm (AIGA) based on cost minimization technique method for edge detection is proposed. The proposed AIGA recommends the use of adaptive probabilities of crossover, mutation and immune operation, and a geometric annealing schedule in immune operator to realize the twin goals of maintaining diversity in the population and sustaining the fast convergence rate in solving the complex problems such as edge detection. Furthermore, AIGA can effectively exploit some prior knowledge and information of the local edge structure in the edge image to make vaccines, which results in much better local search ability of AIGA than that of the canonical genetic algorithm. Experimental results on gray-scale images show the proposed algorithm perform well in terms of quality of the final edge image, rate of convergence and robustness to noise.

Calibration Methods for a 3D Triangulation Based Camera

NASA Astrophysics Data System (ADS)

Schulz, Ulrike; Böhnke, Kay

A sensor in a camera takes a gray level image (1536 x 512 pixels), which is reflected by a reference body. The reference body is illuminated by a linear laser line. This gray level image can be used for a 3D calibration. The following paper describes how a calibration program calculates the calibration factors. The calibration factors serve to determine the size of an unknown reference body.

Brain MR image segmentation using NAMS in pseudo-color.

PubMed

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

Blood Pressure Control in Aging Predicts Cerebral Atrophy Related to Small-Vessel White Matter Lesions.

PubMed

Kern, Kyle C; Wright, Clinton B; Bergfield, Kaitlin L; Fitzhugh, Megan C; Chen, Kewei; Moeller, James R; Nabizadeh, Nooshin; Elkind, Mitchell S V; Sacco, Ralph L; Stern, Yaakov; DeCarli, Charles S; Alexander, Gene E

2017-01-01

Cerebral small-vessel damage manifests as white matter hyperintensities and cerebral atrophy on brain MRI and is associated with aging, cognitive decline and dementia. We sought to examine the interrelationship of these imaging biomarkers and the influence of hypertension in older individuals. We used a multivariate spatial covariance neuroimaging technique to localize the effects of white matter lesion load on regional gray matter volume and assessed the role of blood pressure control, age and education on this relationship. Using a case-control design matching for age, gender, and educational attainment we selected 64 participants with normal blood pressure, controlled hypertension or uncontrolled hypertension from the Northern Manhattan Study cohort. We applied gray matter voxel-based morphometry with the scaled subprofile model to (1) identify regional covariance patterns of gray matter volume differences associated with white matter lesion load, (2) compare this relationship across blood pressure groups, and (3) relate it to cognitive performance. In this group of participants aged 60-86 years, we identified a pattern of reduced gray matter volume associated with white matter lesion load in bilateral temporal-parietal regions with relative preservation of volume in the basal forebrain, thalami and cingulate cortex. This pattern was expressed most in the uncontrolled hypertension group and least in the normotensives, but was also more evident in older and more educated individuals. Expression of this pattern was associated with worse performance in executive function and memory. In summary, white matter lesions from small-vessel disease are associated with a regional pattern of gray matter atrophy that is mitigated by blood pressure control, exacerbated by aging, and associated with cognitive performance.

Ultrasonographic evaluation of equine tendons: a quantitative in vitro study of the effects of amplifier gain level, transducer-tilt, and transducer-displacement.

PubMed

van Schie, J T; Bakker, E M; van Weeren, P R

1999-01-01

The objective of the in vitro experiments described in this paper was to quantify the effects of some instrumental variables on the quantitative evaluation, by means of first-order gray-level statistics, of ultrasonographic images of equine tendons. The experiments were done on three isolated equine superficial digital flexor tendons that were mounted in a frame and submerged in a waterbath. Sections with either normal tendon tissue, an acute lesion, or a chronic scar, were selected. In these sections, the following experiments were done: 1) a gradual increase of total amplifier gain output subdivided in 12 equal steps; 2) a transducer tilt plus or minus 3 degrees from perpendicular, with steps of 1 degree; and 3) a transducer displacement along, and perpendicular to, the tendon long axis, with 16 steps of 0.25 mm each. Transverse ultrasonographic images were collected, and in the regions of interest (ROI) first-order gray-level statistics were calculated to quantify the effects of each experiment. Some important observations were: 1) the total amplifier gain output has a substantial influence on the ultrasonographic image; for example, in the case of an acute lesion, a low gain setting results in an almost completely black image; whereas, with higher gain settings, a marked "filling in" effect on the lesion can be observed; 2) the relative effects of the tilting of the transducer are substantial in normal tendon tissue (18%) and chronic scar (12%); whereas, in the event of an acute lesion, the effects on the mean gray level are dramatic (40%); and 3) the relative effects of displacement of the transducer are small in normal tendon tissue, but on the other hand, the mean gray-level changes 7% in chronic scar, and even 20% in an acute lesion. In general, slight variations in scanner settings and transducer handling can have considerable effects on the gray levels of the ultrasonographic image. Furthermore, there is a strong indication that this quantitative method, as far as based exclusively on the first-order gray-level statistics, may be not discriminative enough to accurately assess the integrity of the tendon. Therefore, the value of a quantitative evaluation of the first-order gray-level statistics for the assessment of the integrity of the equine tendon is questionable.

Measuring surface topography with scanning electron microscopy. I. EZEImage: a program to obtain 3D surface data.

PubMed

Ponz, Ezequiel; Ladaga, Juan Luis; Bonetto, Rita Dominga

2006-04-01

Scanning electron microscopy (SEM) is widely used in the science of materials and different parameters were developed to characterize the surface roughness. In a previous work, we studied the surface topography with fractal dimension at low scale and two parameters at high scale by using the variogram, that is, variance vs. step log-log graph, of a SEM image. Those studies were carried out with the FERImage program, previously developed by us. To verify the previously accepted hypothesis by working with only an image, it is indispensable to have reliable three-dimensional (3D) surface data. In this work, a new program (EZEImage) to characterize 3D surface topography in SEM has been developed. It uses fast cross correlation and dynamic programming to obtain reliable dense height maps in a few seconds which can be displayed as an image where each gray level represents a height value. This image can be used for the FERImage program or any other software to obtain surface topography characteristics. EZEImage also generates anaglyph images as well as characterizes 3D surface topography by means of a parameter set to describe amplitude properties and three functional indices for characterizing bearing and fluid properties.

A prototype retinal prosthesis for visual stimulation.

PubMed

Abu-Faraj, Ziad O; Rjeily, Dany M Abou; Nasreddine, Rayan W; Andari, Majid A; Taok, Habib H

2007-01-01

Vision loss has severe impacts on its victims, carrying with it physiological, psychological, social, and economic consequences thereby degrading the quality of life and depriving the individual from performing many of the daily living activities. This article describes the design and development of a prototype retinal prosthesis for visual stimulation. The system consists of a webcam, a notebook computer, and a prototype excitatory circuit. The system is driven by a MATLAB-based custom-built software. Live webcam images are converted to an 8 x 8 mosaic of 256 gray scale shades. Subsequently, electrical impulses are generated by the excitatory circuit in real-time to topographically stimulate the corresponding epiretinal cells. Following their conversion to gray scale, recorded data from the central pixel of the mosaic yielded: 36.24 nC for black, 48.48 nC for red, 55.68 nC for green, 67.68 nC for blue, and 91.92 nC for white. These results correlate well with data reported in the literature. The hallmark of this work is in the potential of partial restoration of sight that would add quality to the life of individuals with vision loss.

Origins of R2∗ and white matter

PubMed Central

Rudko, David A.; Klassen, L. Martyn; de Chickera, Sonali N.; Gati, Joseph S.; Dekaban, Gregory A.; Menon, Ravi S.

2014-01-01

Estimates of the apparent transverse relaxation rate () can be used to quantify important properties of biological tissue. Surprisingly, the mechanism of dependence on tissue orientation is not well understood. The primary goal of this paper was to characterize orientation dependence of in gray and white matter and relate it to independent measurements of two other susceptibility based parameters: the local Larmor frequency shift (fL) and quantitative volume magnetic susceptibility (Δχ). Through this comparative analysis we calculated scaling relations quantifying (reversible contribution to the transverse relaxation rate from local field inhomogeneities) in a voxel given measurements of the local Larmor frequency shift. is a measure of both perturber geometry and density and is related to tissue microstructure. Additionally, two methods (the Generalized Lorentzian model and iterative dipole inversion) for calculating Δχ were compared in gray and white matter. The value of Δχ derived from fitting the Generalized Lorentzian model was then connected to the observed orientation dependence using image-registered optical density measurements from histochemical staining. Our results demonstrate that the and fL of white and cortical gray matter are well described by a sinusoidal dependence on the orientation of the tissue and a linear dependence on the volume fraction of myelin in the tissue. In deep brain gray matter structures, where there is no obvious symmetry axis, and fL have no orientation dependence but retain a linear dependence on tissue iron concentration and hence Δχ. PMID:24374633

Researches on Position Detection for Vacuum Switch Electrode

NASA Astrophysics Data System (ADS)

Dong, Huajun; Guo, Yingjie; Li, Jie; Kong, Yihan

2018-03-01

Form and transformation character of vacuum arc is important influencing factor on the vacuum switch performance, and the dynamic separations of electrode is the chief effecting factor on the transformation of vacuum arcs forms. Consequently, how to detect the position of electrode to calculate the separations in the arcs image is of great significance. However, gray level distribution of vacuum arcs image isn’t even, the gray level of burning arcs is high, but the gray level of electrode is low, meanwhile, the forms of vacuum arcs changes sharply, the problems above restrict electrode position detection precisely. In this paper, algorithm of detecting electrode position base on vacuum arcs image was proposed. The digital image processing technology was used in vacuum switch arcs image analysis, the upper edge and lower edge were detected respectively, then linear fitting was done using the result of edge detection, the fitting result was the position of electrode, thus, accurate position detection of electrode was realized. From the experimental results, we can see that: algorithm described in this paper detected upper and lower edge of arcs successfully and the position of electrode was obtained through calculation.

Research and implementation of finger-vein recognition algorithm

NASA Astrophysics Data System (ADS)

Pang, Zengyao; Yang, Jie; Chen, Yilei; Liu, Yin

2017-06-01

In finger vein image preprocessing, finger angle correction and ROI extraction are important parts of the system. In this paper, we propose an angle correction algorithm based on the centroid of the vein image, and extract the ROI region according to the bidirectional gray projection method. Inspired by the fact that features in those vein areas have similar appearance as valleys, a novel method was proposed to extract center and width of palm vein based on multi-directional gradients, which is easy-computing, quick and stable. On this basis, an encoding method was designed to determine the gray value distribution of texture image. This algorithm could effectively overcome the edge of the texture extraction error. Finally, the system was equipped with higher robustness and recognition accuracy by utilizing fuzzy threshold determination and global gray value matching algorithm. Experimental results on pairs of matched palm images show that, the proposed method has a EER with 3.21% extracts features at the speed of 27ms per image. It can be concluded that the proposed algorithm has obvious advantages in grain extraction efficiency, matching accuracy and algorithm efficiency.

White-matter functional networks changes in patients with schizophrenia.

PubMed

Jiang, Yuchao; Luo, Cheng; Li, Xuan; Li, Yingjia; Yang, Hang; Li, Jianfu; Chang, Xin; Li, Hechun; Yang, Huanghao; Wang, Jijun; Duan, Mingjun; Yao, Dezhong

2018-04-13

Resting-state functional MRI (rsfMRI) is a useful technique for investigating the functional organization of human gray-matter in neuroscience and neuropsychiatry. Nevertheless, most studies have demonstrated the functional connectivity and/or task-related functional activity in the gray-matter. White-matter functional networks have been investigated in healthy subjects. Schizophrenia has been hypothesized to be a brain disorder involving insufficient or ineffective communication associated with white-matter abnormalities. However, previous studies have mainly examined the structural architecture of white-matter using MRI or diffusion tensor imaging and failed to uncover any dysfunctional connectivity within the white-matter on rsfMRI. The current study used rsfMRI to evaluate white-matter functional connectivity in a large cohort of ninety-seven schizophrenia patients and 126 healthy controls. Ten large-scale white-matter networks were identified by a cluster analysis of voxel-based white-matter functional connectivity and classified into superficial, middle and deep layers of networks. Evaluation of the spontaneous oscillation of white-matter networks and the functional connectivity between them showed that patients with schizophrenia had decreased amplitudes of low-frequency oscillation and increased functional connectivity in the superficial perception-motor networks. Additionally, we examined the interactions between white-matter and gray-matter networks. The superficial perception-motor white-matter network had decreased functional connectivity with the cortical perception-motor gray-matter networks. In contrast, the middle and deep white-matter networks had increased functional connectivity with the superficial perception-motor white-matter network and the cortical perception-motor gray-matter network. Thus, we presumed that the disrupted association between the gray-matter and white-matter networks in the perception-motor system may be compensated for through the middle-deep white-matter networks, which may be the foundation of the extensively disrupted connections in schizophrenia. Copyright © 2018 Elsevier Inc. All rights reserved.

Spirit Scans Winter Haven False Color

NASA Image and Video Library

2006-04-24

This false-color image shows paper-thin layers of light-toned, jagged-edged rocks; a light gray rock with smooth, rounded edges atop and drifts; and several dark gray to black, angular rocks with vesicles typical of hardened lava scattered across the sand

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1993-01-01

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images.

PubMed

Fan, Chong; Chen, Xushuai; Zhong, Lei; Zhou, Min; Shi, Yun; Duan, Yulin

2017-03-18

A sub-block algorithm is usually applied in the super-resolution (SR) reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

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

PubMed

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

2015-09-01

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

Tumor detection in mice by measurement of fluorescence decay time matrices

NASA Astrophysics Data System (ADS)

Cubeddu, R.; Pifferi, A.; Taroni, P.; Valentini, G.; Canti, G.

1995-12-01

An intensified CCD video camera has been used to measure the spatial distribution of the fluorescence decay time in tumor-bearing mice sensitized with hematoporphyrin derivative. Mice were injected with five doses of sensitizer, ranging from 0.1 to 10 mg / kg body weight. For any drug dose the decay time of the exogenous fluorescence in the tumor is always significantly longer than in normal tissues. The image created by associating a gray-shade scale to the decay time matrix of each mouse permits a reliable and precise detection of the neoplasia.

Neutrons Image Additive Manufactured Turbine Blade in 3-D

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

None

2016-04-29

The video displays the Inconel 718 Turbine Blade made by Additive Manufacturing. First a gray scale neutron computed tomogram (CT) is displayed with transparency in order to show the internal structure. Then the neutron CT is overlapped with the engineering drawing that was used to print the part and a comparison of external and internal structures is possible. This provides a map of the accuracy of the printed turbine (printing tolerance). Internal surface roughness can also be observed. Credits: Experimental Measurements: Hassina Z. Bilheaux, Video and Printing Tolerance Analysis: Jean C. Bilheaux

Localizing gray matter deficits in late-onset depression using computational cortical pattern matching methods.

PubMed

Ballmaier, Martina; Kumar, Anand; Thompson, Paul M; Narr, Katherine L; Lavretsky, Helen; Estanol, Laverne; Deluca, Heather; Toga, Arthur W

2004-11-01

The authors used magnetic resonance imaging and an image analysis technique known as cortical pattern matching to map cortical gray matter deficits in elderly depressed patients with an illness onset after age 60 (late-onset depression). Seventeen patients with late-onset depression (11 women and six men; mean age=75.24, SD=8.52) and 17 group-matched comparison subjects (11 women and six men; mean age=73.88, SD=7.61) were included. Detailed spatial analyses of gray matter were conducted across the entire cortex by measuring local proportions of gray matter at thousands of homologous cortical surface locations in each subject, and these patterns were matched across subjects by using elastic transformations to align sulcal topography. To visualize regional changes, statistical differences were mapped at each cortical surface location in three dimensions. The late-onset depression group exhibited significant gray matter deficits in the right lateral temporal cortex and the right parietal cortex, where decreases were most pronounced in sensorimotor regions. The statistical maps also showed gray matter deficits in the same regions of the left hemisphere that approached significance after permutation testing. No significant group differences were detected in frontal cortices or any other anatomical region. Regionally specific decreases of gray matter occur in late-onset depression, supporting the hypothesis that this subset of elderly patients with major depression presents with certain unique neuroanatomical abnormalities that may differ from patients with an earlier onset of illness.

Joint source based morphometry identifies linked gray and white matter group differences.

PubMed

Xu, Lai; Pearlson, Godfrey; Calhoun, Vince D

2009-02-01

We present a multivariate approach called joint source based morphometry (jSBM), to identify linked gray and white matter regions which differ between groups. In jSBM, joint independent component analysis (jICA) is used to decompose preprocessed gray and white matter images into joint sources and statistical analysis is used to determine the significant joint sources showing group differences and their relationship to other variables of interest (e.g. age or sex). The identified joint sources are groupings of linked gray and white matter regions with common covariation among subjects. In this study, we first provide a simulation to validate the jSBM approach. To illustrate our method on real data, jSBM is then applied to structural magnetic resonance imaging (sMRI) data obtained from 120 chronic schizophrenia patients and 120 healthy controls to identify group differences. JSBM identified four joint sources as significantly associated with schizophrenia. Linked gray-white matter regions identified in each of the joint sources included: 1) temporal--corpus callosum, 2) occipital/frontal--inferior fronto-occipital fasciculus, 3) frontal/parietal/occipital/temporal--superior longitudinal fasciculus and 4) parietal/frontal--thalamus. Age effects on all four joint sources were significant, but sex effects were significant only for the third joint source. Our findings demonstrate that jSBM can exploit the natural linkage between gray and white matter by incorporating them into a unified framework. This approach is applicable to a wide variety of problems to study linked gray and white matter group differences.

Surface-based reconstruction and diffusion MRI in the assessment of gray and white matter damage in multiple sclerosis

NASA Astrophysics Data System (ADS)

Caffini, Matteo; Bergsland, Niels; LaganÃ, Marcella; Tavazzi, Eleonora; Tortorella, Paola; Rovaris, Marco; Baselli, Giuseppe

2014-03-01

Despite advances in the application of nonconventional MRI techniques in furthering the understanding of multiple sclerosis pathogenic mechanisms, there are still many unanswered questions, such as the relationship between gray and white matter damage. We applied a combination of advanced surface-based reconstruction and diffusion tensor imaging techniques to address this issue. We found significant relationships between white matter tract integrity indices and corresponding cortical structures. Our results suggest a direct link between damage in white and gray matter and contribute to the notion of gray matter loss relating to clinical disability.

Computerized image analysis: estimation of breast density on mammograms

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Petrick, Nicholas; Sahiner, Berkman; Helvie, Mark A.; Roubidoux, Marilyn A.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

2000-06-01

An automated image analysis tool is being developed for estimation of mammographic breast density, which may be useful for risk estimation or for monitoring breast density change in a prevention or intervention program. A mammogram is digitized using a laser scanner and the resolution is reduced to a pixel size of 0.8 mm X 0.8 mm. Breast density analysis is performed in three stages. First, the breast region is segmented from the surrounding background by an automated breast boundary-tracking algorithm. Second, an adaptive dynamic range compression technique is applied to the breast image to reduce the range of the gray level distribution in the low frequency background and to enhance the differences in the characteristic features of the gray level histogram for breasts of different densities. Third, rule-based classification is used to classify the breast images into several classes according to the characteristic features of their gray level histogram. For each image, a gray level threshold is automatically determined to segment the dense tissue from the breast region. The area of segmented dense tissue as a percentage of the breast area is then estimated. In this preliminary study, we analyzed the interobserver variation of breast density estimation by two experienced radiologists using BI-RADS lexicon. The radiologists' visually estimated percent breast densities were compared with the computer's calculation. The results demonstrate the feasibility of estimating mammographic breast density using computer vision techniques and its potential to improve the accuracy and reproducibility in comparison with the subjective visual assessment by radiologists.

Image segmentation using local shape and gray-level appearance models

NASA Astrophysics Data System (ADS)

Seghers, Dieter; Loeckx, Dirk; Maes, Frederik; Suetens, Paul

2006-03-01

A new generic model-based segmentation scheme is presented, which can be trained from examples akin to the Active Shape Model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Because in the ASM approach the intensity and shape models are typically applied alternately during optimizing as first an optimal target location is selected for each landmark separately based on local gray-level appearance information only to which the shape model is fitted subsequently, the ASM may be misled in case of wrongly selected landmark locations. Instead, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized non-iteratively using dynamic programming which allows to find the optimal landmark positions using combined shape and intensity information, without the need for initialization.

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

NASA Astrophysics Data System (ADS)

Mirzaei Talarposhti, Khadijeh; Khaki Jamei, Mehrzad

2016-06-01

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

Space Radar Image of Moscow, Russia

NASA Image and Video Library

1999-05-01

This is a vertically polarized L-band image of the southern half of Moscow, an area which has been inhabited for 2,000 years. The image covers a diameter of approximately 50 kilometers (31 miles) and was taken on September 30, 1994 by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar aboard the space shuttle Endeavour. The city of Moscow was founded about 750 years ago and today is home to about 8 million residents. The southern half of the circular highway (a road that looks like a ring) can easily be identified as well as the roads and railways radiating out from the center of the city. The city was named after the Moskwa River and replaced Russia's former capital, St. Petersburg, after the Russian Revolution in 1917. The river winding through Moscow shows up in various gray shades. The circular structure of many city roads can easily be identified, although subway connections covering several hundred kilometers are not visible in this image. The white areas within the ring road and outside of it are buildings of the city itself and it suburban towns. Two of many airports are located in the west and southeast of Moscow, near the corners of the image. The Kremlin is located north just outside of the imaged city center. It was actually built in the 16th century, when Ivan III was czar, and is famous for its various churches. In the surrounding area, light gray indicates forests, while the dark patches are agricultural areas. The various shades from middle gray to dark gray indicate different stages of harvesting, ploughing and grassland. http://photojournal.jpl.nasa.gov/catalog/PIA01752

Significance of perceptually relevant image decolorization for scene classification

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Topology preserve gray image skeletonization algorithm

NASA Astrophysics Data System (ADS)

Qian, Kai; Zhu, Weibin; Bhattacharya, Prabir

1993-10-01

A new algorithm which can skeletonize both black-white and gray pictures is presented. This algorithm is based on distance transformation and can preserve the topology of the original picture. It can be extended to 3-D skeletonization and can be implemented by parallel processing.

Objective analysis of image quality of video image capture systems

NASA Astrophysics Data System (ADS)

Rowberg, Alan H.

1990-07-01

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

Infrared and visible image fusion with the target marked based on multi-resolution visual attention mechanisms

NASA Astrophysics Data System (ADS)

Huang, Yadong; Gao, Kun; Gong, Chen; Han, Lu; Guo, Yue

2016-03-01

During traditional multi-resolution infrared and visible image fusion processing, the low contrast ratio target may be weakened and become inconspicuous because of the opposite DN values in the source images. So a novel target pseudo-color enhanced image fusion algorithm based on the modified attention model and fast discrete curvelet transformation is proposed. The interesting target regions are extracted from source images by introducing the motion features gained from the modified attention model, and source images are performed the gray fusion via the rules based on physical characteristics of sensors in curvelet domain. The final fusion image is obtained by mapping extracted targets into the gray result with the proper pseudo-color instead. The experiments show that the algorithm can highlight dim targets effectively and improve SNR of fusion image.

[Voxel-Based Morphometry in Medicated-naive Boys with Attention-deficit/hyperactivity Disorder(ADHD)].

PubMed

Liu, Qi; Chen, Lizhou; Li, Fei; Chen, Ying; Guo, Lanting; Gong, Qiyong; Huang, Xiaoqi

2016-06-01

Attention-deficit/hyperactivity disorder(ADHD)is one of the most common neuro-developmental disorders occurring in childhood,characterized by symptoms of age-inappropriate inattention,hyperactivity/impulsivity,and the prevalence is higher in boys.Although gray matter volume deficits have been frequently reported for ADHD children via structural magnetic resonance imaging,few of them had specifically focused on male patients.The present study aimed to explore the alterations of gray matter volumes in medicated-naive boys with ADHD via a relatively new voxel-based morphometry technique.According to the criteria of DSM-IV-TR,43medicated-naive ADHD boys and 44age-matched healthy boys were recruited.The magnetic resonance image(MRI)scan was performed via a 3T MRI system with three-dimensional(3D)spoiled gradient recalled echo(SPGR)sequence.Voxel-based morphometry with diffeomorphic anatomical registration through exponentiated lie algebra in SPM8 was used to preprocess the3DT1-weighted images.To identify gray matter volume differences between the ADHD and the controls,voxelbased analysis of whole brain gray matter volumes between two groups were done via two sample t-test in SPM8 with age as covariate,threshold at P<0.001.Finally,compared to the controls,significantly reduced gray matter volumes were identified in the right orbitofrontal cortex(peak coordinates[-2,52,-25],t=4.01),and bilateral hippocampus(Left:peak coordinates[14,0,-18],t=3.61;Right:peak coordinates[-14,15,-28],t=3.64)of ADHD boys.Our results demonstrated obvious reduction of whole brain gray matter volumes in right orbitofrontal cortex and bilateral hippocampus in boys with ADHD.This suggests that the abnormalities of prefrontal-hippocampus circuit may be the underlying cause of the cognitive dysfunction and abnormal behavioral inhibition in medicatednaive boys with ADHD.

A Cross-Sectional Voxel-Based Morphometric Study of Age- and Sex-Related Changes in Gray Matter Volume in the Normal Aging Brain.

PubMed

Peng, Fei; Wang, Lixin; Geng, Zuojun; Zhu, Qingfeng; Song, Zhenhu

2016-01-01

The aim of the study was to carry out a cross-sectional study of 124 cognitively normal Chinese adults using the voxel-based morphometry approach to delineate age-related changes in the gray matter volume of regions of interest (ROI) in the brain and further analyze their correlation with age. One hundred twenty-four cognitively normal adults were divided into the young age group, the middle age group, and the old age group. Conventional magnetic resonance imaging was performed with the Achieva 3.0 T system. Structural images were processed using VBM8 and SPM8. Regions of interest were obtained by WFU PickAtlas and all realigned images were spatially normalized. Females showed significantly greater total gray matter volume than males (t = 4.81, P = 0.0000, false discovery rate corrected). Compared with young subjects, old-aged subjects showed extensive reduction in gray matter volumes in all ROIs examined except the occipital lobe. In young- and middle-aged subjects, female and male subjects showed significant difference in the right middle temporal gyrus, right superior temporal gyrus, left angular gyrus, right middle occipital lobe, left middle cingulate gyrus, and the pars triangularis of the right inferior frontal gyrus, suggesting an interaction between age and sex (P < 0.001, uncorrected). Logistic regression analysis revealed linear negative correlation between the total gray matter volume and age (R = 0.529, P < 0.001). Significant age-related differences are present in gray matter volume across multiple brain regions during aging. The VPM approach may provide an emerging paradigm in the normal aging brain that may help differentiate underlying normal neurobiological aging changes of specific brain regions from neurodegenerative impairments.

ROBOSIGHT: Robotic Vision System For Inspection And Manipulation

NASA Astrophysics Data System (ADS)

Trivedi, Mohan M.; Chen, ChuXin; Marapane, Suresh

1989-02-01

Vision is an important sensory modality that can be used for deriving information critical to the proper, efficient, flexible, and safe operation of an intelligent robot. Vision systems are uti-lized for developing higher level interpretation of the nature of a robotic workspace using images acquired by cameras mounted on a robot. Such information can be useful for tasks such as object recognition, object location, object inspection, obstacle avoidance and navigation. In this paper we describe efforts directed towards developing a vision system useful for performing various robotic inspection and manipulation tasks. The system utilizes gray scale images and can be viewed as a model-based system. It includes general purpose image analysis modules as well as special purpose, task dependent object status recognition modules. Experiments are described to verify the robust performance of the integrated system using a robotic testbed.

Development and investigation of single-scan TV radiography for the acquisition of dynamic physiologic data

NASA Technical Reports Server (NTRS)

Baily, N. A.

1975-01-01

A light amplifier for large flat screen fluoroscopy was investigated which will decrease both its size and weight. The work on organ contouring was extended to yield volumes. This is a simple extension since the fluoroscopic image contains density (gray scale) information which can be translated as tissue thickness, integrated, yielding accurate volume data in an on-line situation. A number of devices were developed for analog image processing of video signals, operating on-line in real time, and with simple selection mechanisms. The results show that this approach is feasible and produces are improvement in image quality which should make diagnostic error significantly lower. These are all low cost devices, small and light in weight, thereby making them usable in a space environment, on the Ames centrifuge, and in a typical clinical situation.

Migratory behavior of eastern North Pacific gray whales tracked using a hydrophone array

PubMed Central

Helble, Tyler A.; D’Spain, Gerald L.; Weller, David W.; Wiggins, Sean M.; Hildebrand, John A.

2017-01-01

Eastern North Pacific gray whales make one of the longest annual migrations of any mammal, traveling from their summer feeding areas in the Bering and Chukchi Seas to their wintering areas in the lagoons of Baja California, Mexico. Although a significant body of knowledge on gray whale biology and behavior exists, little is known about their vocal behavior while migrating. In this study, we used a sparse hydrophone array deployed offshore of central California to investigate how gray whales behave and use sound while migrating. We detected, localized, and tracked whales for one full migration season, a first for gray whales. We verified and localized 10,644 gray whale M3 calls and grouped them into 280 tracks. Results confirm that gray whales are acoustically active while migrating and their swimming and acoustic behavior changes on daily and seasonal time scales. The seasonal timing of the calls verifies the gray whale migration timing determined using other methods such as counts conducted by visual observers. The total number of calls and the percentage of calls that were part of a track changed significantly over both seasonal and daily time scales. An average calling rate of 5.7 calls/whale/day was observed, which is significantly greater than previously reported migration calling rates. We measured a mean speed of 1.6 m/s and quantified heading, direction, and water depth where tracks were located. Mean speed and water depth remained constant between night and day, but these quantities had greater variation at night. Gray whales produce M3 calls with a root mean square source level of 156.9 dB re 1 μPa at 1 m. Quantities describing call characteristics were variable and dependent on site-specific propagation characteristics. PMID:29084266

Migratory behavior of eastern North Pacific gray whales tracked using a hydrophone array.

PubMed

Guazzo, Regina A; Helble, Tyler A; D'Spain, Gerald L; Weller, David W; Wiggins, Sean M; Hildebrand, John A

2017-01-01

Eastern North Pacific gray whales make one of the longest annual migrations of any mammal, traveling from their summer feeding areas in the Bering and Chukchi Seas to their wintering areas in the lagoons of Baja California, Mexico. Although a significant body of knowledge on gray whale biology and behavior exists, little is known about their vocal behavior while migrating. In this study, we used a sparse hydrophone array deployed offshore of central California to investigate how gray whales behave and use sound while migrating. We detected, localized, and tracked whales for one full migration season, a first for gray whales. We verified and localized 10,644 gray whale M3 calls and grouped them into 280 tracks. Results confirm that gray whales are acoustically active while migrating and their swimming and acoustic behavior changes on daily and seasonal time scales. The seasonal timing of the calls verifies the gray whale migration timing determined using other methods such as counts conducted by visual observers. The total number of calls and the percentage of calls that were part of a track changed significantly over both seasonal and daily time scales. An average calling rate of 5.7 calls/whale/day was observed, which is significantly greater than previously reported migration calling rates. We measured a mean speed of 1.6 m/s and quantified heading, direction, and water depth where tracks were located. Mean speed and water depth remained constant between night and day, but these quantities had greater variation at night. Gray whales produce M3 calls with a root mean square source level of 156.9 dB re 1 μPa at 1 m. Quantities describing call characteristics were variable and dependent on site-specific propagation characteristics.

Glutaric aciduria type 1: neuroimaging features with clinical correlation.

PubMed

Mohammad, Shaimaa Abdelsattar; Abdelkhalek, Heba Salah; Ahmed, Khaled A; Zaki, Osama K

2015-10-01

Glutaric aciduria type 1 is a rare neurometabolic disease with high morbidity. To describe the MR imaging abnormalities in glutaric aciduria type 1 and to identify any association between the clinical and imaging features. MRI scans of 29 children (mean age: 16.9 months) with confirmed diagnosis of glutaric aciduria type 1 were retrospectively reviewed. Gray matter and white matter scores were calculated based on a previously published pattern-recognition approach of assessing leukoencephalopathies. Hippocampal formation and opercular topography were assessed in relation to the known embryological basis. MRI scores were correlated with morbidity score. The most consistent MRI abnormality was widened operculum with dilatation of the subarachnoid spaces surrounding underdeveloped frontotemporal lobes. Incomplete hippocampal inversion was also seen. The globus pallidus was the most frequently involved gray matter structure (86%). In addition to the central tegmental tract, white matter abnormalities preferentially involved the central and periventricular regions. The morbidity score correlated with the gray matter abnormality score (P = 0.004). Patients with dystonia had higher gray matter and morbidity scores. Morbidity is significantly correlated with abnormality of gray matter, rather than white matter, whether secondary to acute encephalopathic crisis or insidious onset disease.

Medial frontal white and gray matter contributions to general intelligence.

PubMed

Ohtani, Toshiyuki; Nestor, Paul G; Bouix, Sylvain; Saito, Yukiko; Hosokawa, Taiga; Kubicki, Marek

2014-01-01

The medial orbitofrontal cortex (mOFC) and rostral anterior cingulate cortex (rACC) are part of a wider neural network that plays an important role in general intelligence and executive function. We used structural brain imaging to quantify magnetic resonance gray matter volume and diffusion tensor white matter integrity of the mOFC-rACC network in 26 healthy participants who also completed neuropsychological tests of intellectual abilities and executive function. Stochastic tractography, the most effective Diffusion Tensor Imaging method for examining white matter connections between adjacent gray matter regions, was employed to assess the integrity of mOFC-rACC pathways. Fractional anisotropy (FA), which reflects the integrity of white matter connections, was calculated. Results indicated that higher intelligence correlated with greater gray matter volumes for both mOFC and rACC, as well as with increased FA for left posterior mOFC-rACC connectivity. Hierarchical regression analyses revealed that DTI-derived FA of left posterior mOFC-rACC uniquely accounted for 29%-34% of the variance in IQ, in comparison to 11%-16% uniquely explained by gray matter volume of the left rACC. Together, left rACC gray matter volume and white matter connectivity between left posterior mOFC and rACC accounted for up to 50% of the variance in general intelligence. This study is to our knowledge the first to examine white matter connectivity between OFC and ACC, two gray matter regions of interests that are very close in physical proximity, and underscores the important independent contributions of variations in rACC gray matter volume and mOFC-rACC white matter connectivity to individual differences in general intelligence.

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow

PubMed Central

Zhang, Weilong; Guo, Bingxuan; Liao, Xuan; Li, Wenzhuo

2018-01-01

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images. PMID:29659526

Compression of Encrypted Images Using Set Partitioning In Hierarchical Trees Algorithm

NASA Astrophysics Data System (ADS)

Sarika, G.; Unnithan, Harikuttan; Peter, Smitha

2011-10-01

When it is desired to transmit redundant data over an insecure channel, it is customary to encrypt the data. For encrypted real world sources such as images, the use of Markova properties in the slepian-wolf decoder does not work well for gray scale images. Here in this paper we propose a method of compression of an encrypted image. In the encoder section, the image is first encrypted and then it undergoes compression in resolution. The cipher function scrambles only the pixel values, but does not shuffle the pixel locations. After down sampling, each sub-image is encoded independently and the resulting syndrome bits are transmitted. The received image undergoes a joint decryption and decompression in the decoder section. By using the local statistics based on the image, it is recovered back. Here the decoder gets only lower resolution version of the image. In addition, this method provides only partial access to the current source at the decoder side, which improves the decoder's learning of the source statistics. The source dependency is exploited to improve the compression efficiency. This scheme provides better coding efficiency and less computational complexity.

Fibromyalgia interacts with age to change the brain☆☆☆

PubMed Central

Ceko, Marta; Bushnell, M. Catherine; Fitzcharles, Mary-Ann; Schweinhardt, Petra

2013-01-01

Although brain plasticity in the form of gray matter increases and decreases has been observed in chronic pain, factors determining the patterns of directionality are largely unknown. Here we tested the hypothesis that fibromyalgia interacts with age to produce distinct patterns of gray matter differences, specifically increases in younger and decreases in older patients, when compared to age-matched healthy controls. The relative contribution of pain duration was also investigated. Regional gray matter was measured in younger (n = 14, mean age 43, range 29–49) and older (n = 14; mean age 55, range 51–60) female fibromyalgia patients and matched controls using voxel-based morphometry and cortical thickness analysis of T1-weighted magnetic resonance images. To examine their functional significance, gray matter differences were compared with experimental pain sensitivity. Diffusion-tensor imaging was used to assess whether white matter changed in parallel with gray matter, and resting-state fMRI was acquired to examine whether pain-related gray matter changes are associated with altered functional connectivity. Older patients showed exclusively decreased gray matter, accompanied by compromised white matter integrity. In contrast, younger patients showed exclusively gray matter increases, namely in the basal ganglia and insula, which were independent of pain duration. Associated white matter changes in younger patients were compatible with gray matter hypertrophy. In both age groups, structural brain alterations were associated with experimental pain sensitivity, which was increased in older patients but normal in younger patients. Whereas more pronounced gray matter decreases in the posterior cingulate cortex were related to increased experimental pain sensitivity in older patients, insular gray matter increases in younger patients correlated with lower pain sensitivity, possibly indicating the recruitment of endogenous pain modulatory mechanisms. This is supported by the finding that the insula in younger patients showed functional decoupling from an important pain-processing region, the dorsal anterior cingulate cortex. These results suggest that brain structure and function shift from being adaptive in younger to being maladaptive in older patients, which might have important treatment implications. PMID:24273710

Detection of pre-symptomatic rose powdery-mildew and gray-mold diseases based on thermal vision

NASA Astrophysics Data System (ADS)

Jafari, M.; Minaei, S.; Safaie, N.

2017-09-01

Roses are the most important plants in ornamental horticulture. Roses are susceptible to a number of phytopathogenic diseases. Among the most serious diseases of rose, powdery mildew (Podosphaera pannosa var. rosae) and gray mold (Botrytis cinerea) are widespread which require considerable attention. In this study, the potential of implementing thermal imaging to detect the pre-symptomatic appearance of these fungal diseases was investigated. Effects of powdery mildew and gray mold diseases on rose plants (Rosa hybrida L.) were examined by two experiments conducted in a growth chamber. To classify the healthy and infected plants, feature selection was carried out and the best extracted thermal features with the largest linguistic hedge values were chosen. Two neuro-fuzzy classifiers were trained to distinguish between the healthy and infected plants. Best estimation rates of 92.55% and 92.3% were achieved in training and testing the classifier with 8 clusters in order to identify the leaves infected with powdery mildew. In addition, the best estimation rates of 97.5% and 92.59% were achieved in training and testing the classifier with 4 clusters to identify the gray mold disease on flowers. Performance of the designed neuro-fuzzy classifiers were evaluated with the thermal images captured using an automatic imaging setup. Best correct estimation rates of 69% and 80% were achieved (on the second day post-inoculation) for pre-symptomatic appearance detection of powdery mildew and gray mold diseases, respectively.

Image Transmission through OFDM System under the Influence of AWGN Channel

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Characterization of lipid-rich plaques using spectroscopic optical coherence tomography

NASA Astrophysics Data System (ADS)

Nam, Hyeong Soo; Song, Joon Woo; Jang, Sun-Joo; Lee, Jae Joong; Oh, Wang-Yuhl; Kim, Jin Won; Yoo, Hongki

2016-07-01

Intravascular optical coherence tomography (IV-OCT) is a high-resolution imaging method used to visualize the internal structures of walls of coronary arteries in vivo. However, accurate characterization of atherosclerotic plaques with gray-scale IV-OCT images is often limited by various intrinsic artifacts. In this study, we present an algorithm for characterizing lipid-rich plaques with a spectroscopic OCT technique based on a Gaussian center of mass (GCOM) metric. The GCOM metric, which reflects the absorbance properties of lipids, was validated using a lipid phantom. In addition, the proposed characterization method was successfully demonstrated in vivo using an atherosclerotic rabbit model and was found to have a sensitivity and specificity of 94.3% and 76.7% for lipid classification, respectively.

Simulation of speckle patterns with pre-defined correlation distributions.

PubMed

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

2016-03-01

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

Smeared spectrum jamming suppression based on generalized S transform and threshold segmentation

NASA Astrophysics Data System (ADS)

Li, Xin; Wang, Chunyang; Tan, Ming; Fu, Xiaolong

2018-04-01

Smeared Spectrum (SMSP) jamming is an effective jamming in countering linear frequency modulation (LFM) radar. According to the time-frequency distribution difference between jamming and echo, a jamming suppression method based on Generalized S transform (GST) and threshold segmentation is proposed. The sub-pulse period is firstly estimated based on auto correlation function firstly. Secondly, the time-frequency image and the related gray scale image are achieved based on GST. Finally, the Tsallis cross entropy is utilized to compute the optimized segmentation threshold, and then the jamming suppression filter is constructed based on the threshold. The simulation results show that the proposed method is of good performance in the suppression of false targets produced by SMSP.

Simulation of speckle patterns with pre-defined correlation distributions

PubMed Central

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

2016-01-01

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

How color enhances visual memory for natural scenes.

PubMed

Spence, Ian; Wong, Patrick; Rusan, Maria; Rastegar, Naghmeh

2006-01-01

We offer a framework for understanding how color operates to improve visual memory for images of the natural environment, and we present an extensive data set that quantifies the contribution of color in the encoding and recognition phases. Using a continuous recognition task with colored and monochrome gray-scale images of natural scenes at short exposure durations, we found that color enhances recognition memory by conferring an advantage during encoding and by strengthening the encoding-specificity effect. Furthermore, because the pattern of performance was similar at all exposure durations, and because form and color are processed in different areas of cortex, the results imply that color must be bound as an integral part of the representation at the earliest stages of processing.

Cerebral vessels segmentation for light-sheet microscopy image using convolutional neural networks

NASA Astrophysics Data System (ADS)

Hu, Chaoen; Hui, Hui; Wang, Shuo; Dong, Di; Liu, Xia; Yang, Xin; Tian, Jie

2017-03-01

Cerebral vessel segmentation is an important step in image analysis for brain function and brain disease studies. To extract all the cerebrovascular patterns, including arteries and capillaries, some filter-based methods are used to segment vessels. However, the design of accurate and robust vessel segmentation algorithms is still challenging, due to the variety and complexity of images, especially in cerebral blood vessel segmentation. In this work, we addressed a problem of automatic and robust segmentation of cerebral micro-vessels structures in cerebrovascular images acquired by light-sheet microscope for mouse. To segment micro-vessels in large-scale image data, we proposed a convolutional neural networks (CNNs) architecture trained by 1.58 million pixels with manual label. Three convolutional layers and one fully connected layer were used in the CNNs model. We extracted a patch of size 32x32 pixels in each acquired brain vessel image as training data set to feed into CNNs for classification. This network was trained to output the probability that the center pixel of input patch belongs to vessel structures. To build the CNNs architecture, a series of mouse brain vascular images acquired from a commercial light sheet fluorescence microscopy (LSFM) system were used for training the model. The experimental results demonstrated that our approach is a promising method for effectively segmenting micro-vessels structures in cerebrovascular images with vessel-dense, nonuniform gray-level and long-scale contrast regions.

Stacked STN LCDs for true-color projection systems

NASA Astrophysics Data System (ADS)

Gulick, Paul E.; Conner, Arlie R.

1991-08-01

The demand for a true color LCD projection panel for use with standard overhead projectors has been around ever since the first monochrome OHP projection panel was introduced in 1986. The monochrome panels evolved along with the LCD technology from the first blue- and-yellow mode units to black-and-white with levels of gray, and to yellow-and-magenta panels with limited intermediate color shades known as pseudo-color. Finally, a novel solution has been implemented using a stack of custom designed STN panels, making possible true color LCD projection panels that are reasonably priced, available in high volume and quite acceptable in overall image quality. This stacked technology relies on the inherent birefringence colors of each layer to switch between white (passing all wavelengths) and a subtractive color primary (passing all wavelengths but red, green, or blue) so the full spectrum can be projected. Standard gray-scale techniques expand the displayable color palette to almost 5,000 colors and beyond. The same technology can also be applied to various self-contained projection architectures.

A 1500-year record of climatic and environmental change in Elk Lake, Minnesota I: Varve thickness and gray-scale density

USGS Publications Warehouse

Dean, W.; Anderson, R.; Platt, Bradbury J.; Anderson, D.

2002-01-01

The deepest part (29.5 m) of Elk Lake, Clearwater County, northwestern Minnesota, contains a complete Holocene section that is continuously varved. The varve components are predominantly autochthonous (CaCO3, organic matter, biogenic silica, and several iron and manganese minerals), but the varves do contain a minor detrital-clastic (aluminosilicate) component that is predominantly wind-borne (eolian) and provides an important record of atmospheric conditions. Singular spectrum analysis (SSA) and wavelet analysis of varve thickness recognized significant periodicities in the multicentennial and multidecadal bands that varied in power (i.e., variable significance) and position (i.e., variable period) within the periodic bands. Persistent periodicities of about 10, 22, 40, and 90 years, and, in particular, multicentennial periodicities in varve thickness and other proxy variables are similar to those in spectra of radiocarbon production, a proxy for past solar activity. This suggests that there may be a solar control, perhaps through geomagnetic effects on atmospheric circulation. Multicentennial and multidecadal periodicities also occur in wavelet spectra of relative gray-scale density. However, gray-scale density does not appear to correlate with any of the measured proxy variables, and at this point we do not know what controlled gray scale.

Illumination normalization of face image based on illuminant direction estimation and improved Retinex.

PubMed

Yi, Jizheng; Mao, Xia; Chen, Lijiang; Xue, Yuli; Rovetta, Alberto; Caleanu, Catalin-Daniel

2015-01-01

Illumination normalization of face image for face recognition and facial expression recognition is one of the most frequent and difficult problems in image processing. In order to obtain a face image with normal illumination, our method firstly divides the input face image into sixteen local regions and calculates the edge level percentage in each of them. Secondly, three local regions, which meet the requirements of lower complexity and larger average gray value, are selected to calculate the final illuminant direction according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model. After knowing the final illuminant direction of the input face image, the Retinex algorithm is improved from two aspects: (1) we optimize the surround function; (2) we intercept the values in both ends of histogram of face image, determine the range of gray levels, and stretch the range of gray levels into the dynamic range of display device. Finally, we achieve illumination normalization and get the final face image. Unlike previous illumination normalization approaches, the method proposed in this paper does not require any training step or any knowledge of 3D face and reflective surface model. The experimental results using extended Yale face database B and CMU-PIE show that our method achieves better normalization effect comparing with the existing techniques.

Ultrasound physics and instrumentation for pathologists.

PubMed

Lieu, David

2010-10-01

Interest in pathologist-performed ultrasound-guided fine-needle aspiration is increasing. Educational courses discuss clinical ultrasound and biopsy techniques but not ultrasound physics and instrumentation. To review modern ultrasound physics and instrumentation to help pathologists understand the basis of modern ultrasound. A review of recent literature and textbooks was performed. Ultrasound physics and instrumentation are the foundations of clinical ultrasound. The key physical principle is the piezoelectric effect. When stimulated by an electric current, certain crystals vibrate and produce ultrasound. A hand-held transducer converts electricity into ultrasound, transmits it into tissue, and listens for reflected ultrasound to return. The returning echoes are converted into electrical signals and used to create a 2-dimensional gray-scale image. Scanning at a high frequency improves axial resolution but has low tissue penetration. Electronic focusing moves the long-axis focus to depth of the object of interest and improves lateral resolution. The short-axis focus in 1-dimensional transducers is fixed, which results in poor elevational resolution away from the focal zone. Using multiple foci improves lateral resolution but degrades temporal resolution. The sonographer can adjust the dynamic range to change contrast and bring out subtle masses. Contrast resolution is limited by processing speed, monitor resolution, and gray-scale perception of the human eye. Ultrasound is an evolving field. New technologies include miniaturization, spatial compound imaging, tissue harmonics, and multidimensional transducers. Clinical cytopathologists who understand ultrasound physics, instrumentation, and clinical ultrasound are ready for the challenges of cytopathologist-performed ultrasound-guided fine-needle aspiration and core-needle biopsy in the 21st century.

The implementation of thermal image visualization by HDL based on pseudo-color

NASA Astrophysics Data System (ADS)

Zhu, Yong; Zhang, JiangLing

2004-11-01

The pseudo-color method which maps the sampled data to intuitive perception colors is a kind of powerful visualization way. And the all-around system of pseudo-color visualization, which includes the primary principle, model and HDL (Hardware Description Language) implementation for the thermal images, is expatiated on in the paper. The thermal images whose signal is modulated as video reflect the temperature distribution of measured object, so they have the speciality of mass and real-time. The solution to the intractable problem is as follows: First, the reasonable system, i.e. the combining of global pseudo-color visualization and local special area accurate measure, muse be adopted. Then, the HDL pseudo-color algorithms in SoC (System on Chip) carry out the system to ensure the real-time. Finally, the key HDL algorithms for direct gray levels connection coding, proportional gray levels map coding and enhanced gray levels map coding are presented, and its simulation results are showed. The pseudo-color visualization of thermal images implemented by HDL in the paper has effective application in the aspect of electric power equipment test and medical health diagnosis.

Visual enhancement of unmixed multispectral imagery using adaptive smoothing

USGS Publications Warehouse

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

2004-01-01

Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

Standardized volume-rendering of contrast-enhanced renal magnetic resonance angiography.

PubMed

Smedby, O; Oberg, R; Asberg, B; Stenström, H; Eriksson, P

2005-08-01

To propose a technique for standardizing volume-rendering technique (VRT) protocols and to compare this with maximum intensity projection (MIP) in regard to image quality and diagnostic confidence in stenosis diagnosis with magnetic resonance angiography (MRA). Twenty patients were examined with MRA under suspicion of renal artery stenosis. Using the histogram function in the volume-rendering software, the 95th and 99th percentiles of the 3D data set were identified and used to define the VRT transfer function. Two radiologists assessed the stenosis pathology and image quality from rotational sequences of MIP and VRT images. Good overall agreement (mean kappa=0.72) was found between MIP and VRT diagnoses. The agreement between MIP and VRT was considerably better than that between observers (mean kappa=0.43). One of the observers judged VRT images as having higher image quality than MIP images. Presenting renal MRA images with VRT gave results in good agreement with MIP. With VRT protocols defined from the histogram of the image, the lack of an absolute gray scale in MRI need not be a major problem.

Phase Composition Maps integrate mineral compositions with rock textures from the micro-meter to the thin section scale

NASA Astrophysics Data System (ADS)

Willis, Kyle V.; Srogi, LeeAnn; Lutz, Tim; Monson, Frederick C.; Pollock, Meagen

2017-12-01

Textures and compositions are critical information for interpreting rock formation. Existing methods to integrate both types of information favor high-resolution images of mineral compositions over small areas or low-resolution images of larger areas for phase identification. The method in this paper produces images of individual phases in which textural and compositional details are resolved over three orders of magnitude, from tens of micrometers to tens of millimeters. To construct these images, called Phase Composition Maps (PCMs), we make use of the resolution in backscattered electron (BSE) images and calibrate the gray scale values with mineral analyses by energy-dispersive X-ray spectrometry (EDS). The resulting images show the area of a standard thin section (roughly 40 mm × 20 mm) with spatial resolution as good as 3.5 μm/pixel, or more than 81 000 pixels/mm2, comparable to the resolution of X-ray element maps produced by wavelength-dispersive spectrometry (WDS). Procedures to create PCMs for mafic igneous rocks with multivariate linear regression models for minerals with solid solution (olivine, plagioclase feldspar, and pyroxenes) are presented and are applicable to other rock types. PCMs are processed using threshold functions based on the regression models to image specific composition ranges of minerals. PCMs are constructed using widely-available instrumentation: a scanning-electron microscope (SEM) with BSE and EDS X-ray detectors and standard image processing software such as ImageJ and Adobe Photoshop. Three brief applications illustrate the use of PCMs as petrologic tools: to reveal mineral composition patterns at multiple scales; to generate crystal size distributions for intracrystalline compositional zones and compare growth over time; and to image spatial distributions of minerals at different stages of magma crystallization by integrating textures and compositions with thermodynamic modeling.

A completely automated CAD system for mass detection in a large mammographic database.

PubMed

Bellotti, R; De Carlo, F; Tangaro, S; Gargano, G; Maggipinto, G; Castellano, M; Massafra, R; Cascio, D; Fauci, F; Magro, R; Raso, G; Lauria, A; Forni, G; Bagnasco, S; Cerello, P; Zanon, E; Cheran, S C; Lopez Torres, E; Bottigli, U; Masala, G L; Oliva, P; Retico, A; Fantacci, M E; Cataldo, R; De Mitri, I; De Nunzio, G

2006-08-01

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing second-order spatial statistics information on the pixel gray level intensity. As the images under study were recorded in different centers and with different machine settings, eight GTSDM features were selected so as to be invariant under monotonic transformation. In this way, the images do not need to be normalized, as the adopted features depend on the texture only, rather than on the gray tone levels, too. (c) ROI classification by means of a neural network, with supervision provided by the radiologist's diagnosis. The CAD system was evaluated on a large database of 3369 mammographic images [2307 negative, 1062 pathological (or positive), containing at least one confirmed mass, as diagnosed by an expert radiologist]. To assess the performance of the system, receiver operating characteristic (ROC) and free-response ROC analysis were employed. The area under the ROC curve was found to be Az = 0.783 +/- 0.008 for the ROI-based classification. When evaluating the accuracy of the CAD against the radiologist-drawn boundaries, 4.23 false positives per image are found at 80% of mass sensitivity.

Histogram contrast analysis and the visual segregation of IID textures.

PubMed

Chubb, C; Econopouly, J; Landy, M S

1994-09-01

A new psychophysical methodology is introduced, histogram contrast analysis, that allows one to measure stimulus transformations, f, used by the visual system to draw distinctions between different image regions. The method involves the discrimination of images constructed by selecting texture micropatterns randomly and independently (across locations) on the basis of a given micropattern histogram. Different components of f are measured by use of different component functions to modulate the micropattern histogram until the resulting textures are discriminable. When no discrimination threshold can be obtained for a given modulating component function, a second titration technique may be used to measure the contribution of that component to f. The method includes several strong tests of its own assumptions. An example is given of the method applied to visual textures composed of small, uniform squares with randomly chosen gray levels. In particular, for a fixed mean gray level mu and a fixed gray-level variance sigma 2, histogram contrast analysis is used to establish that the class S of all textures composed of small squares with jointly independent, identically distributed gray levels with mean mu and variance sigma 2 is perceptually elementary in the following sense: there exists a single, real-valued function f S of gray level, such that two textures I and J in S are discriminable only if the average value of f S applied to the gray levels in I is significantly different from the average value of f S applied to the gray levels in J. Finally, histogram contrast analysis is used to obtain a seventh-order polynomial approximation of f S.

Median Robust Extended Local Binary Pattern for Texture Classification.

PubMed

Liu, Li; Lao, Songyang; Fieguth, Paul W; Guo, Yulan; Wang, Xiaogang; Pietikäinen, Matti

2016-03-01

Local binary patterns (LBP) are considered among the most computationally efficient high-performance texture features. However, the LBP method is very sensitive to image noise and is unable to capture macrostructure information. To best address these disadvantages, in this paper, we introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP). Different from the traditional LBP and many LBP variants, MRELBP compares regional image medians rather than raw image intensities. A multiscale LBP type descriptor is computed by efficiently comparing image medians over a novel sampling scheme, which can capture both microstructure and macrostructure texture information. A comprehensive evaluation on benchmark data sets reveals MRELBP's high performance-robust to gray scale variations, rotation changes and noise-but at a low computational cost. MRELBP produces the best classification scores of 99.82%, 99.38%, and 99.77% on three popular Outex test suites. More importantly, MRELBP is shown to be highly robust to image noise, including Gaussian noise, Gaussian blur, salt-and-pepper noise, and random pixel corruption.

Comparison of imaging characteristics of multiple-beam equalization and storage phosphor direct digitizer radiographic systems

NASA Astrophysics Data System (ADS)

Sankaran, A.; Chuang, Keh-Shih; Yonekawa, Hisashi; Huang, H. K.

1992-06-01

The imaging characteristics of two chest radiographic equipment, Advanced Multiple Beam Equalization Radiography (AMBER) and Konica Direct Digitizer [using a storage phosphor (SP) plate] systems have been compared. The variables affecting image quality and the computer display/reading systems used are detailed. Utilizing specially designed wedge, geometric, and anthropomorphic phantoms, studies were conducted on: exposure and energy response of detectors; nodule detectability; different exposure techniques; various look- up tables (LUTs), gray scale displays and laser printers. Methods for scatter estimation and reduction were investigated. It is concluded that AMBER with screen-film and equalization techniques provides better nodule detectability than SP plates. However, SP plates have other advantages such as flexibility in the selection of exposure techniques, image processing features, and excellent sensitivity when combined with optimum reader operating modes. The equalization feature of AMBER provides better nodule detectability under the denser regions of the chest. Results of diagnostic accuracy are demonstrated with nodule detectability plots and analysis of images obtained with phantoms.

Format preferences of district attorneys for post-mortem medical imaging reports: understandability, cost effectiveness, and suitability for the courtroom: a questionnaire based study.

PubMed

Ampanozi, Garyfalia; Zimmermann, David; Hatch, Gary M; Ruder, Thomas D; Ross, Steffen; Flach, Patricia M; Thali, Michael J; Ebert, Lars C

2012-05-01

The objective of this study was to explore the perception of the legal authorities regarding different report types and visualization techniques for post-mortem radiological findings. A standardized digital questionnaire was developed and the district attorneys in the catchment area of the affiliated Forensic Institute were requested to evaluate four different types of forensic imaging reports based on four cases examples. Each case was described in four different report types (short written report only, gray-scale CT image with figure caption, color-coded CT image with figure caption, 3D-reconstruction with figure caption). The survey participants were asked to evaluate those types of reports regarding understandability, cost effectiveness and overall appropriateness for the courtroom. 3D reconstructions and color-coded CT images accompanied by written report were preferred regarding understandability and cost/effectiveness. 3D reconstructions of the forensic findings reviewed as most adequate for court. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Regional gray matter density associated with emotional intelligence: evidence from voxel-based morphometry.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Sassa, Yuko; Hashizume, Hiroshi; Sekiguchi, Atsushi; Fukushima, Ai; Kawashima, Ryuta

2011-09-01

Emotional Intelligence (EI) is the ability to monitor one's own and others' emotions and the ability to use the gathered information to guide one's thinking and action. EI is thought to be important for social life making it a popular subject of research. However, despite the existence of previous functional imaging studies on EI, the relationship between regional gray matter morphology and EI has never been investigated. We used voxel-based morphometry (VBM) and a questionnaire (Emotional Intelligence Scale) to measure EI to identify the gray matter correlates of each factor of individual EI (Intrapersonal factor, Interpersonal factor, Situation Management factor). We found significant negative relationships between the Intrapersonal factor and regional gray matter density (rGMD) (1-a) in an anatomical cluster that included the right anterior insula, (1-b) in the right cerebellum, (1-c) in an anatomical cluster that extends from the cuneus to the precuneus, (1-d) and in an anatomical cluster that extends from the medial prefrontal cortex to the left lateral fronto-polar cortex. We also found significant positive correlations between the Interpersonal factor and rGMD in the right superior temporal sulcus, and significant negative correlations between the Situation Management factor and rGMD in the ventromedial prefrontal cortex. These findings suggest that each factor of EI in healthy young people is related to the specific brain regions known to be involved in the networks of social cognition and self-related recognition, and in the somatic marker circuitry. Copyright © 2010 Wiley-Liss, Inc.

Monitoring machining conditions by infrared images

NASA Astrophysics Data System (ADS)

Borelli, Joao E.; Gonzaga Trabasso, Luis; Gonzaga, Adilson; Coelho, Reginaldo T.

2001-03-01

During machining process the knowledge of the temperature is the most important factor in tool analysis. It allows to control main factors that influence tool use, life time and waste. The temperature in the contact area between the piece and the tool is resulting from the material removal in cutting operation and it is too difficult to be obtained because the tool and the work piece are in motion. One way to measure the temperature in this situation is detecting the infrared radiation. This work presents a new methodology for diagnosis and monitoring of machining processes with the use of infrared images. The infrared image provides a map in gray tones of the elements in the process: tool, work piece and chips. Each gray tone in the image corresponds to a certain temperature for each one of those materials and the relationship between the gray tones and the temperature is gotten by the previous of infrared camera calibration. The system developed in this work uses an infrared camera, a frame grabber board and a software composed of three modules. The first module makes the image acquisition and processing. The second module makes the feature image extraction and performs the feature vector. Finally, the third module uses fuzzy logic to evaluate the feature vector and supplies the tool state diagnostic as output.

Skeleton-based region competition for automated gray matter and white matter segmentation of human brain MR images

NASA Astrophysics Data System (ADS)

Chu, Yong; Chen, Ya-Fang; Su, Min-Ying; Nalcioglu, Orhan

2005-04-01

Image segmentation is an essential process for quantitative analysis. Segmentation of brain tissues in magnetic resonance (MR) images is very important for understanding the structural-functional relationship for various pathological conditions, such as dementia vs. normal brain aging. Different brain regions are responsible for certain functions and may have specific implication for diagnosis. Segmentation may facilitate the analysis of different brain regions to aid in early diagnosis. Region competition has been recently proposed as an effective method for image segmentation by minimizing a generalized Bayes/MDL criterion. However, it is sensitive to initial conditions - the "seeds", therefore an optimal choice of "seeds" is necessary for accurate segmentation. In this paper, we present a new skeleton-based region competition algorithm for automated gray and white matter segmentation. Skeletons can be considered as good "seed regions" since they provide the morphological a priori information, thus guarantee a correct initial condition. Intensity gradient information is also added to the global energy function to achieve a precise boundary localization. This algorithm was applied to perform gray and white matter segmentation using simulated MRI images from a realistic digital brain phantom. Nine different brain regions were manually outlined for evaluation of the performance in these separate regions. The results were compared to the gold-standard measure to calculate the true positive and true negative percentages. In general, this method worked well with a 96% accuracy, although the performance varied in different regions. We conclude that the skeleton-based region competition is an effective method for gray and white matter segmentation.

Fusiform gyrus volume reduction and facial recognition in chronic schizophrenia.

PubMed

Onitsuka, Toshiaki; Shenton, Martha E; Kasai, Kiyoto; Nestor, Paul G; Toner, Sarah K; Kikinis, Ron; Jolesz, Ferenc A; McCarley, Robert W

2003-04-01

The fusiform gyrus (FG), or occipitotemporal gyrus, is thought to subserve the processing and encoding of faces. Of note, several studies have reported that patients with schizophrenia show deficits in facial processing. It is thus hypothesized that the FG might be one brain region underlying abnormal facial recognition in schizophrenia. The objectives of this study were to determine whether there are abnormalities in gray matter volumes for the anterior and the posterior FG in patients with chronic schizophrenia and to investigate relationships between FG subregions and immediate and delayed memory for faces. Patients were recruited from the Boston VA Healthcare System, Brockton Division, and control subjects were recruited through newspaper advertisement. Study participants included 21 male patients diagnosed as having chronic schizophrenia and 28 male controls. Participants underwent high-spatial-resolution magnetic resonance imaging, and facial recognition memory was evaluated. Main outcome measures included anterior and posterior FG gray matter volumes based on high-spatial-resolution magnetic resonance imaging, a detailed and reliable manual delineation using 3-dimensional information, and correlation coefficients between FG subregions and raw scores on immediate and delayed facial memory derived from the Wechsler Memory Scale III. Patients with chronic schizophrenia had overall smaller FG gray matter volumes (10%) than normal controls. Additionally, patients with schizophrenia performed more poorly than normal controls in both immediate and delayed facial memory tests. Moreover, the degree of poor performance on delayed memory for faces was significantly correlated with the degree of bilateral anterior FG reduction in patients with schizophrenia. These results suggest that neuroanatomic FG abnormalities underlie at least some of the deficits associated with facial recognition in schizophrenia.

Implementation of a watershed algorithm on FPGAs

NASA Astrophysics Data System (ADS)

Zahirazami, Shahram; Akil, Mohamed

1998-10-01

In this article we present an implementation of a watershed algorithm on a multi-FPGA architecture. This implementation is based on an hierarchical FIFO. A separate FIFO for each gray level. The gray scale value of a pixel is taken for the altitude of the point. In this way we look at the image as a relief. We proceed by a flooding step. It's like as we immerse the relief in a lake. The water begins to come up and when the water of two different catchment basins reach each other, we will construct a separator or a `Watershed'. This approach is data dependent, hence the process time is different for different images. The H-FIFO is used to guarantee the nature of immersion, it means that we need two types of priority. All the points of an altitude `n' are processed before any point of altitude `n + 1'. And inside an altitude water propagates with a constant velocity in all directions from the source. This operator needs two images as input. An original image or it's gradient and the marker image. A classic way to construct the marker image is to build an image of minimal regions. Each minimal region has it's unique label. This label is the color of the water and will be used to see whether two different water touch each other. The algorithm at first fill the hierarchy FIFO with neighbors of all the regions who are not colored. Next it fetches the first pixel from the first non-empty FIFO and treats this pixel. This pixel will take the color of its neighbor, and all the neighbors who are not already in the H-FIFO are put in their correspondent FIFO. The process is over when the H-FIFO is empty. The result is a segmented and labeled image.

A Partnership Training Program in Breast Cancer Research Using Molecular Imaging Techniques

DTIC Science & Technology

2008-07-01

PubMed) 2. Berlier J.E., Rothe A., Buller G., Bradford J., Gray D.R., Filanoski B.J., Telford W.G., Yue S., Liu J., Cheung C.Y., et al. Quantitative...3 3 cm3 voxel within the gray matter of the occipitoparietal lobe was established using anatomic landmarks. Pulse Sequences All experiments were...software (SAS Institute, Cary, NC, USA). RESULTS Figure 1 shows a PRESS spectrum recorded from the occipitoparietal gray matter region of a 25-year-old sub

The Potential of Using Brain Images for Authentication

PubMed Central

Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition. PMID:25126604

The potential of using brain images for authentication.

PubMed

Chen, Fanglin; Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition.

Forum on Alternate Assessment and "Gray Area" Assessment: A Report on the Pre-Conference Session at the National Conference on Large Scale Assessment (Snowbird, Utah, June 11-12, 1999).

ERIC Educational Resources Information Center

National Center on Educational Outcomes, Minneapolis, MN.

This report discusses the outcomes of a June 11-12, 1999, forum that addressed alternative assessments and gray areas in large-scale assessments for students with disabilities. The forum included 161 representatives from 42 state departments of education, 3 large school districts, 1 territory, and the Department of Defense Dependent Schools. Five…

Integration of Sparse Multi-modality Representation and Anatomical Constraint for Isointense Infant Brain MR Image Segmentation

PubMed Central

Wang, Li; Shi, Feng; Gao, Yaozong; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to poor spatial resolution, severe partial volume effect, and the ongoing maturation and myelination process. During the first year of life, the brain image contrast between white and gray matters undergoes dramatic changes. In particular, the image contrast inverses around 6–8 months of age, where the white and gray matter tissues are isointense in T1 and T2 weighted images and hence exhibit the extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a general framework that adopts sparse representation to fuse the multi-modality image information and further incorporate the anatomical constraints for brain tissue segmentation. Specifically, we first derive an initial segmentation from a library of aligned images with ground-truth segmentations by using sparse representation in a patch-based fashion for the multi-modality T1, T2 and FA images. The segmentation result is further iteratively refined by integration of the anatomical constraint. The proposed method was evaluated on 22 infant brain MR images acquired at around 6 months of age by using a leave-one-out cross-validation, as well as other 10 unseen testing subjects. Our method achieved a high accuracy for the Dice ratios that measure the volume overlap between automated and manual segmentations, i.e., 0.889±0.008 for white matter and 0.870±0.006 for gray matter. PMID:24291615

Matching shapes with self-intersections: application to leaf classification.

PubMed

Mokhtarian, Farzin; Abbasi, Sadegh

2004-05-01

We address the problem of two-dimensional (2-D) shape representation and matching in presence of self-intersection for large image databases. This may occur when part of an object is hidden behind another part and results in a darker section in the gray level image of the object. The boundary contour of the object must include the boundary of this part which is entirely inside the outline of the object. The Curvature Scale Space (CSS) image of a shape is a multiscale organization of its inflection points as it is smoothed. The CSS-based shape representation method has been selected for MPEG-7 standardization. We study the effects of contour self-intersection on the Curvature Scale Space image. When there is no self-intersection, the CSS image contains several arch shape contours, each related to a concavity or a convexity of the shape. Self intersections create contours with minima as well as maxima in the CSS image. An efficient shape representation method has been introduced in this paper which describes a shape using the maxima as well as the minima of its CSS contours. This is a natural generalization of the conventional method which only includes the maxima of the CSS image contours. The conventional matching algorithm has also been modified to accommodate the new information about the minima. The method has been successfully used in a real world application to find, for an unknown leaf, similar classes from a database of classified leaf images representing different varieties of chrysanthemum. For many classes of leaves, self-intersection is inevitable during the scanning of the image. Therefore the original contributions of this paper is the generalization of the Curvature Scale Space representation to the class of 2-D contours with self-intersection, and its application to the classification of Chrysanthemum leaves.

Endoscopic ultrasound for the characterization and staging of rectal cancer. Current state of the method. Technological advances and perspectives.

PubMed

Gersak, Mariana M; Badea, Radu; Graur, Florin; Hajja, Nadim Al; Furcea, Luminita; Dudea, Sorin M

2015-06-01

Endoscopic ultrasound is the most accurate type of examination for the assessment of rectal tumors. Over the years, the method has advanced from gray-scale examination to intravenous contrast media administration and to different types of elastography. The multimodal approach of tumors (transrectal, transvaginal) is adapted to each case. 3D ultrasound is useful for spatial representation and precise measurement of tumor formations, using CT/MR image reconstruction; color elastography is useful for tumor characterization and staging; endoscopic ultrasound using intravenous contrast agents can help study the amount of contrast agent targeted at the level of the tumor formations and contrast wash-in/wash-out time, based on the curves displayed on the device. The transvaginal approach often allows better visualization of the tumor than the transrectal approach. Performing the procedure with the rectal ampulla distended with contrast agent may be seen as an optimization of the examination methodology. All these aspects are additional methods for gray-scale endoscopic ultrasound, capable of increasing diagnostic accuracy. This paper aims at reviewing the progress of transrectal and transvaginal ultrasound, generically called endoscopic ultrasound, for rectal tumor diagnosis and staging, with emphasis on the current state of the method and its development trends.

Reduced gray matter volume is correlated with frontal cognitive and behavioral impairments in Parkinson's disease.

PubMed

Terada, Tatsuhiro; Miyata, Jun; Obi, Tomokazu; Kubota, Manabu; Yoshizumi, Miho; Murai, Toshiya

2018-07-15

To identify the brain-volume reductions associated with frontal cognitive and behavioral impairments in Parkinson's disease (PD). Forty PD patients without dementia or amnesia (Hoehn and Yahr stage 3) and 10 age-matched controls underwent brain magnetic resonance imaging. Cognitive and behavioral impairments were assessed by using the Frontal Assessment Battery (FAB) and Frontal Systems Behavioral Scale (FrSBe), respectively. We applied voxel-based morphometry to investigate the correlations of regional gray matter volume with FAB, FrSBe, and physical disability. FAB was significantly lower in PD than in controls. FrSBe was significantly higher after PD onset than before, notably in the apathy subscale. FAB and FrSBe were significantly intercorrelated. In PD patients, left inferior frontal volume was positively correlated with FAB, whereas right precentral volume was negatively correlated with FrSBe total score. The brain volumes in both of these regions were not correlated with the Unified PD Rating Scale III. Behavioral impairments in PD tended to coexist with progression of frontal cognitive impairment. Regional atrophy within the frontal lobe was associated with both frontal cognitive and behavioral impairments. However, the specific region responsible for behavioral impairment differed from that for frontal cognitive impairment. These associations were independent of physical disability. Copyright © 2018 Elsevier B.V. All rights reserved.

ASTER First Views of San Francisco River, Brazil - Visible/near Infrared VNIR Image monochrome

NASA Image and Video Library

2000-03-11

This image of the San Francisco River channel, and its surrounding flood zone, in Brazil was acquired by band 3N of ASTER's Visible/Near Infrared sensor. The surrounding area along the river channel in light gray to white could be covered by dense tropical rain forests. The water surface of the San Francisco River shows rather gray color as compared to small lakes and tributaries, which could indicate that the river water is contaminated by suspended material. The size of image: 20 km x 20 km approx., ground resolution 15 m x 15 m approximately. http://photojournal.jpl.nasa.gov/catalog/PIA02451

Efficacy and Clinical Utility of a High-Attenuation Object Artifact Reduction Algorithm in Flat-Detector Image Reconstruction Compared With Standard Image Reconstruction.

PubMed

Naehle, Claas P; Hechelhammer, Lukas; Richter, Heiko; Ryffel, Fabian; Wildermuth, Simon; Weber, Johannes

To evaluate the effectiveness and clinical utility of a metal artifact reduction (MAR) image reconstruction algorithm for the reduction of high-attenuation object (HAO)-related image artifacts. Images were quantitatively evaluated for image noise (noiseSD and noiserange) and qualitatively for artifact severity, gray-white-matter delineation, and diagnostic confidence with conventional reconstruction and after applying a MAR algorithm. Metal artifact reduction reduces noiseSD and noiserange (median [interquartile range]) at the level of HAO in 1-cm distance compared with conventional reconstruction (noiseSD: 60.0 [71.4] vs 12.8 [16.1] and noiserange: 262.0 [236.8] vs 72.0 [28.3]; P < 0.0001). Artifact severity (reader 1 [mean ± SD]: 1.1 ± 0.6 vs 2.4 ± 0.5, reader 2: 0.8 ± 0.6 vs 2.0 ± 0.4) at level of HAO and diagnostic confidence (reader 1: 1.6 ± 0.7 vs 2.6 ± 0.5, reader 2: 1.0 ± 0.6 vs 2.3 ± 0.7) significantly improved with MAR (P < 0.0001). Metal artifact reduction did not affect gray-white-matter delineation. Metal artifact reduction effectively reduces image artifacts caused by HAO and significantly improves diagnostic confidence without worsening gray-white-matter delineation.

Longitudinal Study of Gray Matter Changes in Parkinson Disease.

PubMed

Jia, X; Liang, P; Li, Y; Shi, L; Wang, D; Li, K

2015-12-01

The pathology of Parkinson disease leads to morphological brain volume changes. So far, the progressive gray matter volume change across time specific to patients with Parkinson disease compared controls remains unclear. Our aim was to investigate the pattern of gray matter changes in patients with Parkinson disease and to explore the progressive gray matter volume change specific to patients with Parkinson disease with disease progression by using voxel-based morphometry analysis. Longitudinal cognitive assessment and structural MR imaging of 89 patients with Parkinson disease (62 men) and 55 healthy controls (33 men) were from the Parkinson's Progression Markers Initiative data base, including the initial baseline and 12-month follow-up data. Two-way analysis of covariance was performed with covariates of age, sex, years of education, imaging data from multiple centers, and total intracranial volume by using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra tool from SPM8 software. Gray matter volume changes for patients with Parkinson disease were detected with decreased gray matter volume in the frontotemporoparietal areas and the bilateral caudate, with increased gray matter volume in the bilateral limbic/paralimbic areas, medial globus pallidus/putamen, and the right occipital cortex compared with healthy controls. Progressive gray matter volume decrease in the bilateral caudate was found for both patients with Parkinson disease and healthy controls, and this caudate volume was positively associated with cognitive ability for both groups. The progressive gray matter volume increase specific to the patients with Parkinson disease was identified close to the left ventral lateral nucleus of thalamus, and a positive relationship was found between the thalamic volume and the tremor scores in a subgroup with tremor-dominant patients with Parkinson disease. The observed progressive changes in gray matter volume in Parkinson disease may provide new insights into the neurodegenerative process. The current findings suggest that the caudate volume loss may contribute to cognitive decline in patients with Parkinson disease and the progressive thalamus enlargement may have relevance to tremor severity in Parkinson disease. © 2015 by American Journal of Neuroradiology.

[Rational imaging in locally advanced prostate cancer].

PubMed

Beissert, M; Lorenz, R; Gerharz, E W

2008-11-01

Prostate cancer is one of the principal medical problems facing the male population in developed countries with an increasing need for sophisticated imaging techniques and risk-adapted treatment options. This article presents an overview of the current imaging procedures in the diagnosis of locally advanced prostate cancer. Apart from conventional gray-scale transrectal ultrasound (TRUS) as the most frequently used primary imaging modality we describe computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). CT and MRI not only allow assessment of prostate anatomy but also a specific evaluation of the pelvic region. Color-coded and contrast-enhanced ultrasound, real-time elastography, dynamic contrast enhancement in MR imaging, diffusion imaging, and MR spectroscopy may lead to a clinically relevant improvement in the diagnosis of prostate cancer. While bone scintigraphy with (99m)Tc-bisphosphonates is still the method of choice in the evaluation of bone metastasis, whole-body MRI and PET using (18)F-NaF, (18)F-FDG, (11)C-choline, (11)C-acetate, and (18)F-choline as tracers achieve higher sensitivities.

[Computer aided diagnosis model for lung tumor based on ensemble convolutional neural network].

PubMed

Wang, Yuanyuan; Zhou, Tao; Lu, Huiling; Wu, Cuiying; Yang, Pengfei

2017-08-01

The convolutional neural network (CNN) could be used on computer-aided diagnosis of lung tumor with positron emission tomography (PET)/computed tomography (CT), which can provide accurate quantitative analysis to compensate for visual inertia and defects in gray-scale sensitivity, and help doctors diagnose accurately. Firstly, parameter migration method is used to build three CNNs (CT-CNN, PET-CNN, and PET/CT-CNN) for lung tumor recognition in CT, PET, and PET/CT image, respectively. Then, we aimed at CT-CNN to obtain the appropriate model parameters for CNN training through analysis the influence of model parameters such as epochs, batchsize and image scale on recognition rate and training time. Finally, three single CNNs are used to construct ensemble CNN, and then lung tumor PET/CT recognition was completed through relative majority vote method and the performance between ensemble CNN and single CNN was compared. The experiment results show that the ensemble CNN is better than single CNN on computer-aided diagnosis of lung tumor.

Cortical magnetic resonance imaging findings in familial pediatric bipolar disorder.

PubMed

Chang, Kiki; Barnea-Goraly, Naama; Karchemskiy, Asya; Simeonova, Diana Iorgova; Barnes, Patrick; Ketter, Terence; Reiss, Allan L

2005-08-01

Morphometric magnetic resonance imaging (MRI) studies of pediatric bipolar disorder (BD) have not reported on gray matter volumes but have reported increased lateral ventricular size and presence of white matter hyperintensities (WMH). We studied gray matter volume, ventricular-to-brain ratios (VBR), and number of WMH in patients with familial, pediatric BD compared with control subjects. Twenty subjects with BD (aged 14.6 +/- 2.8 years; 4 female) according to the Washington University in St. Louis Kiddie Schedule for Affective Disorders and Schizophrenia, each with a parent with BD, and 20 age-, gender-, and intelligence quotient-matched healthy control subjects (aged 14.1 +/- 2.8 years; 4 female) were scanned at 3 T. Most subjects were taking psychotropic medications. A high-resolution T1-weighted spoiled gradient echo three-dimensional MRI sequence was analyzed by BrainImage for volumetric measurements, and T2-weighted images were read by a neuroradiologist to determine presence of WMH. After covarying for age and total brain volume, there were no significant differences between subjects with BD and control subjects in volume of cerebral (p = .09) or prefrontal gray matter (p = .34). Subjects with BD did not have elevated numbers of WMH or greater VBR when compared with control subjects. Children and adolescents with familial BD do not seem to have decreased cerebral grey matter or increased numbers of WMH, dissimilar to findings in adults with BD. Gray matter decreases and development of WMH might be later sequelae of BD or unique to adult-onset BD.

Effect of Heating Time on Hardness Properties of Laser Clad Gray Cast Iron Surface

NASA Astrophysics Data System (ADS)

Norhafzan, B.; Aqida, S. N.; Mifthal, F.; Zulhishamuddin, A. R.; Ismail, I.

2018-03-01

This paper presents effect of heating time on cladded gray cast iron. In this study, the effect of heating time on cladded gray cast iron and melted gray cast iron were analysed. The gray cast iron sample were added with mixed Mo-Cr powder using laser cladding technique. The mixed Mo and Cr powder was pre-placed on gray cast iron surface. Modified layer were sectioned using diamond blade cutter and polish using SiC abrasive paper before heated. Sample was heated in furnace for 15, 30 and 45 minutes at 650 °C and cool down in room temperature. Metallographic study was conduct using inverted microscope while surface hardness properties were tested using Wilson hardness test with Vickers scale. Results for metallographic study showed graphite flakes within matrix of pearlite. The surface hardness for modified layer decreased when increased heating time process. These findings are significant to structure stability of laser cladded gray cast iron with different heating times.

Tissue-Selective Salvage of the White Matter by Successful Endovascular Stroke Therapy.

PubMed

Kleine, Justus F; Kaesmacher, Mirjam; Wiestler, Benedikt; Kaesmacher, Johannes

2017-10-01

White matter (WM) is less vulnerable to ischemia than gray matter. In ischemic stroke caused by acute large-vessel occlusion, successful recanalization might therefore sometimes selectively salvage the WM, leading to infarct patterns confined to gray matter. This study examines occurrence, determinants, and clinical significance of such effects. Three hundred twenty-two patients with acute middle cerebral artery occlusion subjected to mechanical thrombectomy were included. Infarct patterns were categorized into WM - (sparing the WM) and WM + (involving WM). National Institutes of Health Stroke Scale-based measures of neurological outcome, including National Institutes of Health Stroke Scale improvement or National Institutes of Health Stroke Scale worsening, good functional midterm outcome (day 90-modified Rankin Scale score of ≤2), the occurrence of malignant swelling, and in-hospital mortality were predefined outcome measures. WM - infarcts occurred in 118 of 322 patients and were associated with successful recanalization and better collateral grades ( P <0.05). Shorter symptom-onset to recanalization times were also associated with WM - infarcts in univariate analysis, but not when adjusted for collateral grades. WM - infarcts were independently associated with good neurological outcome (adjusted odds ratio, 3.003; 95% confidence interval, 1.186-7.607; P =0.020) and good functional midterm outcome (adjusted odds ratio, 8.618; 95% confidence interval, 2.409-30.828; P =0.001) after correcting for potential confounders, including final infarct volume. Only 2.6% of WM - patients, but 20.5% of WM + patients exhibited neurological worsening, and none versus 12.8% developed malignant swelling ( P <0.001), contributing to lower mortality in this group (2.5% versus 10.3%; P =0.014). WM infarction commonly commences later than gray matter infarction after acute middle cerebral artery occlusion. Successful recanalization can therefore salvage completely the WM at risk in many patients even several hours after symptom onset. Preservation of the WM is associated with better neurological recovery, prevention of malignant swelling, and reduced mortality. This has important implications for neuroprotective strategies, and perfusion imaging-based patient selection, and provides a rationale for treating selected patients in extended time windows. © 2017 American Heart Association, Inc.

TVR-DART: A More Robust Algorithm for Discrete Tomography From Limited Projection Data With Automated Gray Value Estimation.

PubMed

Xiaodong Zhuge; Palenstijn, Willem Jan; Batenburg, Kees Joost

2016-01-01

In this paper, we present a novel iterative reconstruction algorithm for discrete tomography (DT) named total variation regularized discrete algebraic reconstruction technique (TVR-DART) with automated gray value estimation. This algorithm is more robust and automated than the original DART algorithm, and is aimed at imaging of objects consisting of only a few different material compositions, each corresponding to a different gray value in the reconstruction. By exploiting two types of prior knowledge of the scanned object simultaneously, TVR-DART solves the discrete reconstruction problem within an optimization framework inspired by compressive sensing to steer the current reconstruction toward a solution with the specified number of discrete gray values. The gray values and the thresholds are estimated as the reconstruction improves through iterations. Extensive experiments from simulated data, experimental μCT, and electron tomography data sets show that TVR-DART is capable of providing more accurate reconstruction than existing algorithms under noisy conditions from a small number of projection images and/or from a small angular range. Furthermore, the new algorithm requires less effort on parameter tuning compared with the original DART algorithm. With TVR-DART, we aim to provide the tomography society with an easy-to-use and robust algorithm for DT.

Small gray matter volume in orbitofrontal cortex in Prader-Willi syndrome: a voxel-based MRI study.

PubMed

Ogura, Kaeko; Fujii, Toshikatsu; Abe, Nobuhito; Hosokai, Yoshiyuki; Shinohara, Mayumi; Takahashi, Shoki; Mori, Etsuro

2011-07-01

Prader-Willi syndrome (PWS) is a genetically determined neurodevelopmental disorder presenting with behavioral symptoms including hyperphagia, disinhibition, and compulsive behavior. The behavioral problems in individuals with PWS are strikingly similar to those in patients with frontal pathologies, particularly those affecting the orbitofrontal cortex (OFC). However, neuroanatomical abnormalities in the frontal lobe have not been established in PWS. The aim of this study was to look, using volumetric analysis, for morphological changes in the frontal lobe, especially the OFC, of the brains of individuals with PWS. Twelve adults with PWS and 13 age- and gender-matched control subjects participated in structural magnetic resonance imaging (MRI) scans. The whole-brain images were segmented and normalized to a standard stereotactic space. Regional gray matter volumes were compared between the PWS group and the control group using voxel-based morphometry. The PWS subjects showed small gray-matter volume in several regions, including the OFC, caudate nucleus, inferior temporal gyrus, precentral gyrus, supplementary motor area, postcentral gyrus, and cerebellum. The small gray-matter volume in the OFC remained significant in a separate analysis that included total gray matter volume as a covariate. These preliminary findings suggest that the neurobehavioral symptoms in individuals with PWS are related to structural brain abnormalities in these areas. Copyright © 2010 Wiley-Liss, Inc.

Gray QB-sing-faced version 2 (SF2) open environment test report

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

Plummer, J.; Immel, D.; Bobbitt, J.

This report details the design upgrades incorporated into the new version of the GrayQbTM SF2 device and the characterization testing of this upgraded device. Results from controlled characterization testing in the Savannah River National Laboratory (SRNL) R&D Engineering Imaging and Radiation Lab (IRL) and the Savannah River Site (SRS) Health Physics Instrument Calibration Laboratory (HPICL) is presented, as well as results from the open environment field testing performed in the E-Area Low Level Waste Storage Area. Resultant images presented in this report were generated using the SRNL developed Radiation Analyzer (RAzerTM) software program which overlays the radiation contour images ontomore » the visual image of the location being surveyed.« less

Correction method for stripe nonuniformity.

PubMed

Qian, Weixian; Chen, Qian; Gu, Guohua; Guan, Zhiqiang

2010-04-01

Stripe nonuniformity is very typical in line infrared focal plane arrays (IR-FPA) and uncooled staring IR-FPA. In this paper, the mechanism of the stripe nonuniformity is analyzed, and the gray-scale co-occurrence matrix theory and optimization theory are studied. Through these efforts, the stripe nonuniformity correction problem is translated into the optimization problem. The goal of the optimization is to find the minimal energy of the image's line gradient. After solving the constrained nonlinear optimization equation, the parameters of the stripe nonuniformity correction are obtained and the stripe nonuniformity correction is achieved. The experiments indicate that this algorithm is effective and efficient.

Ultrasonography of ovarian masses using a pattern recognition approach

PubMed Central

Jung, Sung Il

2015-01-01

As a primary imaging modality, ultrasonography (US) can provide diagnostic information for evaluating ovarian masses. Using a pattern recognition approach through gray-scale transvaginal US, ovarian masses can be diagnosed with high specificity and sensitivity. Doppler US may allow ovarian masses to be diagnosed as benign or malignant with even greater confidence. In order to differentiate benign and malignant ovarian masses, it is necessary to categorize ovarian masses into unilocular cyst, unilocular solid cyst, multilocular cyst, multilocular solid cyst, and solid tumor, and then to detect typical US features that demonstrate malignancy based on pattern recognition approach. PMID:25797108

Geographic applications of ERTS-1 data to landscape change

NASA Technical Reports Server (NTRS)

Rehder, J. B.

1973-01-01

The analysis of landscape change requires large area coverage on a periodic basis in order to analyze aggregate changes over an extended period of time. To date, only the ERTS program can provide this capability. Three avenues of experimentation and analysis are being used in the investigation: (1) a multi-scale sampling procedure utilizing aircraft imagery for ground truth and control; (2) a densitometric and computer analytical experiment for the analysis of gray tone signatures, comparisons and ultimately for landscape change detection and monitoring; and (3) an ERTS image enhancement procedure for the detection and analysis of photomorphic regions.

Method and algorithm for efficient calibration of compressive hyperspectral imaging system based on a liquid crystal retarder

NASA Astrophysics Data System (ADS)

Shecter, Liat; Oiknine, Yaniv; August, Isaac; Stern, Adrian

2017-09-01

Recently we presented a Compressive Sensing Miniature Ultra-spectral Imaging System (CS-MUSI)1 . This system consists of a single Liquid Crystal (LC) phase retarder as a spectral modulator and a gray scale sensor array to capture a multiplexed signal of the imaged scene. By designing the LC spectral modulator in compliance with the Compressive Sensing (CS) guidelines and applying appropriate algorithms we demonstrated reconstruction of spectral (hyper/ ultra) datacubes from an order of magnitude fewer samples than taken by conventional sensors. The LC modulator is designed to have an effective width of a few tens of micrometers, therefore it is prone to imperfections and spatial nonuniformity. In this work, we present the study of this nonuniformity and present a mathematical algorithm that allows the inference of the spectral transmission over the entire cell area from only a few calibration measurements.

On vegetation mapping in Alaska using LANDSAT imagery with primary concerns for method and purpose in satellite image-based vegetation and land-use mapping and the visual interpretation of imagery in photographic format

NASA Technical Reports Server (NTRS)

Anderson, J. H. (Principal Investigator)

1976-01-01

The author has identified the following significant results. A simulated color infrared LANDSAT image covering the western Seward Peninsula was used for identifying and mapping vegetation by direct visual examination. The 1:1,083,400 scale print used was prepared by a color additive process using positive transparencies from MSS bands 4, 5, and 7. Seven color classes were recognized. A vegetation map of 3200 sq km area just west of Fairbanks, Alaska was made. Five colors were recognized on the image and identified to vegetation types roughly equivalent to formations in the UNESCO classification: orange - broadleaf deciduous forest; gray - needleleaf evergreen forest; light violet - subarctic alpine tundra vegetation; violet - broadleaf deciduous shrub thicket; and dull violet - bog vegetation.

Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy.

PubMed

Kramer, Harald; Pickhardt, Perry J; Kliewer, Mark A; Hernando, Diego; Chen, Guang-Hong; Zagzebski, James A; Reeder, Scott B

2017-01-01

The purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT), gray-scale ultrasound (US), and US shear-wave elastography (US-SWE) in the quantification of hepatic steatosis with MR spectroscopy (MRS) as the reference standard. Fifty adults who did not have symptoms (23 men, 27 women; mean age, 57 ± 5 years; body mass index, 27 ± 5) underwent liver imaging with un-enhanced SECT, DECT, gray-scale US, US-SWE, proton-density fat-fraction MRI, and MRS for this prospective trial. MRS voxels for the reference standard were colocalized with all other modalities under investigation. For SECT (120 kVp), attenuation values were recorded. For rapid-switching DECT (80/140 kVp), monochromatic images (70-140 keV) and fat density-derived material decomposition images were reconstructed. For proton-density fat fraction MRI, a quantitative chemical shift-encoded method was used. For US, echogenicity was evaluated on a qualitative 0-3 scale. Quantitative US shear-wave velocities were also recorded. Data were analyzed by linear regression for each technique compared with MRS. There was excellent correlation between MRS and both proton-density fat-fraction MRI (r 2 = 0.992; slope, 0.974; intercept, -0.943) and SECT (r 2 = 0.856; slope, -0.559; intercept, 35.418). DECT fat attenuation had moderate correlation with MRS measurements (r 2 = 0.423; slope, 0.034; intercept, 8.459). There was good correlation between qualitative US echogenicity and MRS measurements with a weighted kappa value of 0.82. US-SWE velocity did not have reliable correlation with MRS measurements (r 2 = 0.004; slope, 0.069; intercept, 6.168). Quantitative MRI proton-density fat fraction and SECT fat attenuation have excellent linear correlation with MRS measurements and can serve as accurate noninvasive biomarkers for quantifying steatosis. Material decomposition with DECT does not improve the accuracy of fat quantification over conventional SECT attenuation. US-SWE has poor accuracy for liver fat quantification.

[Accuracy of computer aided measurement for detecting dental proximal caries lesions in images of cone-beam computed tomography].

PubMed

Zhang, Z L; Li, J P; Li, G; Ma, X C

2017-02-09

Objective: To establish and validate a computer program used to aid the detection of dental proximal caries in the images cone beam computed tomography (CBCT) images. Methods: According to the characteristics of caries lesions in X-ray images, a computer aided detection program for proximal caries was established with Matlab and Visual C++. The whole process for caries lesion detection included image import and preprocessing, measuring average gray value of air area, choosing region of interest and calculating gray value, defining the caries areas. The program was used to examine 90 proximal surfaces from 45 extracted human teeth collected from Peking University School and Hospital of Stomatology. The teeth were then scanned with a CBCT scanner (Promax 3D). The proximal surfaces of the teeth were respectively detected by caries detection program and scored by human observer for the extent of lesions with 6-level-scale. With histologic examination serving as the reference standard, the caries detection program and the human observer performances were assessed with receiver operating characteristic (ROC) curves. Student t -test was used to analyze the areas under the ROC curves (AUC) for the differences between caries detection program and human observer. Spearman correlation coefficient was used to analyze the detection accuracy of caries depth. Results: For the diagnosis of proximal caries in CBCT images, the AUC values of human observers and caries detection program were 0.632 and 0.703, respectively. There was a statistically significant difference between the AUC values ( P= 0.023). The correlation between program performance and gold standard (correlation coefficient r (s)=0.525) was higher than that of observer performance and gold standard ( r (s)=0.457) and there was a statistically significant difference between the correlation coefficients ( P= 0.000). Conclusions: The program that automatically detects dental proximal caries lesions could improve the diagnostic value of CBCT images.

Reduced volume of gray matter in patients with trigeminal neuralgia.

PubMed

Li, Meng; Yan, Jianhao; Li, Shumei; Wang, Tianyue; Zhan, Wenfeng; Wen, Hua; Ma, Xiaofen; Zhang, Yong; Tian, Junzhang; Jiang, Guihua

2017-04-01

Accumulating evidence from brain structural imaging studies has supported that chronic pain could induce changes in brain gray matter volume. However, few studies have focused on the gray matter alterations of Trigeminal neuralgia (TN). In this study, twenty-eight TN patients (thirteen females; mean age, 45.86 years ±11.17) and 28 healthy controls (HC; thirteen females; mean age, 44.89 years ±7.67) were included. Using voxel-based morphometry (VBM), we detected abnormalities in gray matter volume in the TN patients. Based on a voxel-wise analysis, the TN group showed significantly decreased gray matter volume in the bilateral superior/middle temporal gyrus (STG/MTG), bilateral parahippocampus, left anterior cingulate cortex (ACC), caudate nucleus, right fusiform gyrus, and right cerebellum compared with the HC. In addition, we found that the gray matter volume in the bilateral STG/MTG was negatively correlated with the duration of TN. These results provide compelling evidence for gray matter abnormalities in TN and suggest that the duration of TN may be a critical factor associated with brain alterations.

Forecasts for NOAA Marine Sanctuaries

Science.gov Websites

/Forecast The Gray's Reef Sea Turtle Satellite Tagging Project utilizes satellite transmitter tags to Synopsis/Forecast(0-20nm) Synopsis/Forecast(20-60nm) The Gray's Reef Sea Turtle Satellite Tagging Project utilizes satellite transmitter tags to monitor adult and juvenile loggerhead sea click image for more

Cortical Gray Matter in Attention-Deficit/Hyperactivity Disorder: A Structural Magnetic Resonance Imaging Study

ERIC Educational Resources Information Center

Batty, Martin J.; Liddle, Elizabeth B.; Pitiot, Alain; Toro, Roberto; Groom, Madeleine J.; Scerif, Gaia; Liotti, Mario; Liddle, Peter F.; Paus, Tomas; Hollis, Chris

2010-01-01

Objective: Previous studies have shown smaller brain volume and less gray matter in children with attention-deficit/hyperactivity disorder (ADHD). Relatively few morphological studies have examined structures thought to subserve inhibitory control, one of the diagnostic features of ADHD. We examined one such region, the pars opercularis,…

Method for simulating dose reduction in digital mammography using the Anscombe transformation.

PubMed

Borges, Lucas R; Oliveira, Helder C R de; Nunes, Polyana F; Bakic, Predrag R; Maidment, Andrew D A; Vieira, Marcelo A C

2016-06-01

This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose. The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the detective quantum efficiency. The scaling process takes into account the linearity of the system and the offset of the detector elements. The inserted noise is obtained by acquiring images of a flat-field phantom at the standard radiation dose and at the simulated dose. Using the Anscombe transformation, a relationship is created between the calculated noise mask and the scaled image, resulting in a clinical mammogram with the same noise and gray level characteristics as an image acquired at the lower-radiation dose. The performance of the proposed algorithm was validated using real images acquired with an anthropomorphic breast phantom at four different doses, with five exposures for each dose and 256 nonoverlapping ROIs extracted from each image and with uniform images. The authors simulated lower-dose images and compared these with the real images. The authors evaluated the similarity between the normalized noise power spectrum (NNPS) and power spectrum (PS) of simulated images and real images acquired with the same dose. The maximum relative error was less than 2.5% for every ROI. The added noise was also evaluated by measuring the local variance in the real and simulated images. The relative average error for the local variance was smaller than 1%. A new method is proposed for simulating dose reduction in clinical mammograms. In this method, the dependency between image noise and image signal is addressed using a novel application of the Anscombe transformation. NNPS, PS, and local noise metrics confirm that this method is capable of precisely simulating various dose reductions.

A multiresolution processing method for contrast enhancement in portal imaging.

PubMed

Gonzalez-Lopez, Antonio

2018-06-18

Portal images have a unique feature among the imaging modalities used in radiotherapy: they provide direct visualization of the irradiated volumes. However, contrast and spatial resolution are strongly limited due to the high energy of the radiation sources. Because of this, imaging modalities using x-ray energy beams have gained importance in the verification of patient positioning, replacing portal imaging. The purpose of this work was to develop a method for the enhancement of local contrast in portal images. The method operates in the subbands of a wavelet decomposition of the image, re-scaling them in such a way that coefficients in the high and medium resolution subbands are amplified, an approach totally different of those operating on the image histogram, widely used nowadays. Portal images of an anthropomorphic phantom were acquired in an electronic portal imaging device (EPID). Then, different re-scaling strategies were investigated, studying the effects of the scaling parameters on the enhanced images. Also, the effect of using different types of transforms was studied. Finally, the implemented methods were combined with histogram equalization methods like the contrast limited adaptive histogram equalization (CLAHE), and these combinations were compared. Uniform amplification of the detail subbands shows the best results in contrast enhancement. On the other hand, linear re-escalation of the high resolution subbands increases the visibility of fine detail of the images, at the expense of an increase in noise levels. Also, since processing is applied only to detail subbands, not to the approximation, the mean gray level of the image is minimally modified and no further display adjustments are required. It is shown that re-escalation of the detail subbands of portal images can be used as an efficient method for the enhancement of both, the local contrast and the resolution of these images. © 2018 Institute of Physics and Engineering in Medicine.

Color correction with blind image restoration based on multiple images using a low-rank model

NASA Astrophysics Data System (ADS)

Li, Dong; Xie, Xudong; Lam, Kin-Man

2014-03-01

We present a method that can handle the color correction of multiple photographs with blind image restoration simultaneously and automatically. We prove that the local colors of a set of images of the same scene exhibit the low-rank property locally both before and after a color-correction operation. This property allows us to correct all kinds of errors in an image under a low-rank matrix model without particular priors or assumptions. The possible errors may be caused by changes of viewpoint, large illumination variations, gross pixel corruptions, partial occlusions, etc. Furthermore, a new iterative soft-segmentation method is proposed for local color transfer using color influence maps. Due to the fact that the correct color information and the spatial information of images can be recovered using the low-rank model, more precise color correction and many other image-restoration tasks-including image denoising, image deblurring, and gray-scale image colorizing-can be performed simultaneously. Experiments have verified that our method can achieve consistent and promising results on uncontrolled real photographs acquired from the Internet and that it outperforms current state-of-the-art methods.

New Capabilities With Dry Silver Recording Materials

NASA Astrophysics Data System (ADS)

Morgan, David A.

1987-04-01

Dry Silver technology was discovered at 3M and introduced into various imaging applications in the mid-sixties. In the early 1980's, quality films and papers with extended spectral responses, greater dynamic ranges, and improved sensitivity and edge acuity were introduced into sophisticated imaging systems. These products also have improved shelf life at elevated storage temperatures, and improved print stability. At the present time, 3M is developing a full-color dry silver product. This product has the same rapid-access, easy-to-use characteristics as the black and white dry silver recording materials. It has high resolution, long gray scale, and adequate sensitivity for CRT's and other electronically addressable exposure devices. The product can be processed in the same processors used for the black and white dry silver products.

Sedimentary Petrography and Facies Analysis at the Shaler Outcrop, Gale Crater, Mars

NASA Astrophysics Data System (ADS)

Edgar, L. A.; Gupta, S.; Rubin, D. M.; Lewis, K. W.; Kocurek, G.; Anderson, R. B.; Bell, J. F.; Dromart, G.; Edgett, K. S.; Grotzinger, J. P.; Hardgrove, C. J.; Kah, L. C.; Leveille, R. J.; Malin, M.; Mangold, N.; Milliken, R.; Minitti, M. E.; Rice, M. S.; Rowland, S. K.; Schieber, J.; Stack, K.; Sumner, D. Y.; Team, M.

2013-12-01

The Mars Science Laboratory Curiosity rover has recently completed an investigation of a large fluvial deposit known informally as the Shaler outcrop (~1 m thick). Curiosity acquired data at the Shaler outcrop during sols 120-121 and 309-324. The Shaler outcrop is comprised of cross-bedded coarse-grained sandstones and recessive finer-grained intervals. Shaler is distinguished from the surrounding units by the presence of resistant beds exhibiting decimeter scale trough cross-bedding. Observations using the Mast Cameras, Mars Hand Lens Imager (MAHLI) and ChemCam Remote Micro Imager (RMI) enable the recognition of several distinct facies. MAHLI images were acquired on five distinct rock targets, and RMI images were acquired at 33 different locations. On the basis of grain size, erosional resistance, color, and sedimentary structures, we identify four facies: 1) resistant cross-stratified facies, 2) smooth, fine-grained cross-stratified facies, 3) dark gray, pitted facies, and 4) recessive, vertically fractured facies. Panoramic Mastcam observations reveal facies distributions and associations, and show cross-bedded facies that are similar to those observed at the Rocknest and Bathurst_Inlet locations. MAHLI and RMI images are used to determine the grain size, sorting, rounding and sedimentary fabric of the different facies. High-resolution images also reveal small-scale diagenetic features and sedimentary structures that are used to reconstruct the depositional and diagenetic history.

PIV measurements in near-wake turbulent regions

NASA Astrophysics Data System (ADS)

Chen, Wei-Cheng; Chang, Keh-Chin

2018-05-01

Particle image velocimetry (PIV) is a non-intrusive optical diagnostic and must be made of the seedings (foreign particles) instead of the fluid itself. However, reliable PIV measurement of turbulence requires sufficient numbers of seeding falling in each interrogation window of image. A gray-level criterion is developed in this work to check the attainment of statistically stationary status of turbulent flow properties. It is suggested that the gray level of no less than 0.66 is used as the threshold for reliable PIV measurements in the present near-wake turbulent regions.

Automated geographic registration and radiometric correction for UAV-based mosaics

NASA Astrophysics Data System (ADS)

Thomasson, J. Alex; Shi, Yeyin; Sima, Chao; Yang, Chenghai; Cope, Dale A.

2017-05-01

Texas A and M University has been operating a large-scale, UAV-based, agricultural remote-sensing research project since 2015. To use UAV-based images in agricultural production, many high-resolution images must be mosaicked together to create an image of an agricultural field. Two key difficulties to science-based utilization of such mosaics are geographic registration and radiometric calibration. In our current research project, image files are taken to the computer laboratory after the flight, and semi-manual pre-processing is implemented on the raw image data, including ortho-mosaicking and radiometric calibration. Ground control points (GCPs) are critical for high-quality geographic registration of images during mosaicking. Applications requiring accurate reflectance data also require radiometric-calibration references so that reflectance values of image objects can be calculated. We have developed a method for automated geographic registration and radiometric correction with targets that are installed semi-permanently at distributed locations around fields. The targets are a combination of black (≍5% reflectance), dark gray (≍20% reflectance), and light gray (≍40% reflectance) sections that provide for a transformation of pixel-value to reflectance in the dynamic range of crop fields. The exact spectral reflectance of each target is known, having been measured with a spectrophotometer. At the time of installation, each target is measured for position with a real-time kinematic GPS receiver to give its precise latitude and longitude. Automated location of the reference targets in the images is required for precise, automated, geographic registration; and automated calculation of the digital-number to reflectance transformation is required for automated radiometric calibration. To validate the system for radiometric calibration, a calibrated UAV-based image mosaic of a field was compared to a calibrated single image from a manned aircraft. Reflectance values in selected zones of each image were strongly linearly related, and the average error of UAV-mosaic reflectances was 3.4% in the red band, 1.9% in the green band, and 1.5% in the blue band. Based on these results, the proposed physical system and automated software for calibrating UAV mosaics show excellent promise.

An index of beam hardening artifact for two-dimensional cone-beam CT tomographic images: establishment and preliminary evaluation

NASA Astrophysics Data System (ADS)

Yuan, Fusong; Lv, Peijun; Yang, Huifang; Wang, Yong; Sun, Yuchun

2015-07-01

Objectives: Based on the pixel gray value measurements, establish a beam-hardening artifacts index of the cone-beam CT tomographic image, and preliminarily evaluate its applicability. Methods: The 5mm-diameter metal ball and resin ball were fixed on the light-cured resin base plate respectively, while four vitro molars were fixed above and below the ball, on the left and right respectively, which have 10mm distance with the metal ball. Then, cone beam CT was used to scan the fixed base plate twice. The same layer tomographic images were selected from the two data and imported into the Photoshop software. The circle boundary was built through the determination of the center and radius of the circle, according to the artifact-free images section. Grayscale measurement tools were used to measure the internal boundary gray value G0, gray value G1 and G2 of 1mm and 20mm artifacts outside the circular boundary, the length L1 of the arc with artifacts in the circular boundary, the circumference L2. Hardening artifacts index was set A = (G1 / G0) * 0.5 + (G2 / G1) * 0.4 + (L2 / L1) * 0.1. Then, the A values of metal and resin materials were calculated respectively. Results: The A value of cobalt-chromium alloy material is 1, and resin material is 0. Conclusion: The A value reflects comprehensively the three factors of hardening artifacts influencing normal oral tissue image sharpness of cone beam CT. The three factors include relative gray value, the decay rate and range of artifacts.

Assessing the disturbance potential of small unoccupied aircraft systems (UAS) on gray seals (Halichoerus grypus) at breeding colonies in Nova Scotia, Canada

PubMed Central

Arona, Lauren; Dale, Julian; Heaslip, Susan G.; Hammill, Michael O.

2018-01-01

The use of small unoccupied aircraft systems (UAS) for ecological studies and wildlife population assessments is increasing. These methods can provide significant benefits in terms of costs and reductions in human risk, but little is known if UAS-based approaches cause disturbance of animals during operations. To address this knowledge gap, we conducted a series of UAS flights at gray seal breeding colonies on Hay and Saddle Islands in Nova Scotia, Canada. Using a small fixed-wing UAS, we assessed both immediate and short-term effects of surveys using sequential image analysis and between-flight seal counts in ten, 50 m2 random quadrats at each colony. Counts of adult gray seals and young-of-the-year animals between first and second flights revealed no changes in abundance in quadrats (matched pair t-test p > 0.69) and slopes approaching 1 for linear regression comparisons (r2 > 0.80). Sequential image analysis revealed no changes in orientation or posture of imaged animals. We also assessed the acoustic properties of the small UAS in relation to low ambient noise conditions using sound equivalent level (Leq) measurements with a calibrated U-MIK 1 and a 1/3 octave band soundscape approach. The results of Leq measurements indicate that small fixed-wing UAS are quiet, with most energy above 160 Hz, and that levels across 1/3 octave bands do not greatly exceed ambient acoustic measurements in a quiet field during operations at standard survey altitudes. As such, this platform is unlikely to acoustically disturb gray seals at breeding colonies during population surveys. The results of the present study indicate that the effects of small fixed-wing UAS on gray seals at breeding colonies are negligible, and that fixed-wing UAS-based approaches should be considered amongst best practices for assessing gray seal colonies. PMID:29576950

Assessment of body fat based on potential function clustering segmentation of computed tomography images

NASA Astrophysics Data System (ADS)

Zhang, Lixin; Lin, Min; Wan, Baikun; Zhou, Yu; Wang, Yizhong

2005-01-01

In this paper, a new method of body fat and its distribution testing is proposed based on CT image processing. As it is more sensitive to slight differences in attenuation than standard radiography, CT depicts the soft tissues with better clarity. And body fat has a distinct grayness range compared with its neighboring tissues in a CT image. An effective multi-thresholds image segmentation method based on potential function clustering is used to deal with multiple peaks in the grayness histogram of a CT image. The CT images of abdomens of 14 volunteers with different fatness are processed with the proposed method. Not only can the result of total fat area be got, but also the differentiation of subcutaneous fat from intra-abdominal fat has been identified. The results show the adaptability and stability of the proposed method, which will be a useful tool for diagnosing obesity.

Stroke-model-based character extraction from gray-level document images.

PubMed

Ye, X; Cheriet, M; Suen, C Y

2001-01-01

Global gray-level thresholding techniques such as Otsu's method, and local gray-level thresholding techniques such as edge-based segmentation or the adaptive thresholding method are powerful in extracting character objects from simple or slowly varying backgrounds. However, they are found to be insufficient when the backgrounds include sharply varying contours or fonts in different sizes. A stroke-model is proposed to depict the local features of character objects as double-edges in a predefined size. This model enables us to detect thin connected components selectively, while ignoring relatively large backgrounds that appear complex. Meanwhile, since the stroke width restriction is fully factored in, the proposed technique can be used to extract characters in predefined font sizes. To process large volumes of documents efficiently, a hybrid method is proposed for character extraction from various backgrounds. Using the measurement of class separability to differentiate images with simple backgrounds from those with complex backgrounds, the hybrid method can process documents with different backgrounds by applying the appropriate methods. Experiments on extracting handwriting from a check image, as well as machine-printed characters from scene images demonstrate the effectiveness of the proposed model.

Automated segmentation of three-dimensional MR brain images

NASA Astrophysics Data System (ADS)

Park, Jonggeun; Baek, Byungjun; Ahn, Choong-Il; Ku, Kyo Bum; Jeong, Dong Kyun; Lee, Chulhee

2006-03-01

Brain segmentation is a challenging problem due to the complexity of the brain. In this paper, we propose an automated brain segmentation method for 3D magnetic resonance (MR) brain images which are represented as a sequence of 2D brain images. The proposed method consists of three steps: pre-processing, removal of non-brain regions (e.g., the skull, meninges, other organs, etc), and spinal cord restoration. In pre-processing, we perform adaptive thresholding which takes into account variable intensities of MR brain images corresponding to various image acquisition conditions. In segmentation process, we iteratively apply 2D morphological operations and masking for the sequences of 2D sagittal, coronal, and axial planes in order to remove non-brain tissues. Next, final 3D brain regions are obtained by applying OR operation for segmentation results of three planes. Finally we reconstruct the spinal cord truncated during the previous processes. Experiments are performed with fifteen 3D MR brain image sets with 8-bit gray-scale. Experiment results show the proposed algorithm is fast, and provides robust and satisfactory results.

Gray matter atrophy associated with mild cognitive impairment in Parkinson's disease.

PubMed

Chen, Fu-Xiang; Kang, De-Zhi; Chen, Fu-Yong; Liu, Ying; Wu, Gang; Li, Xun; Yu, Liang-Hong; Lin, Yuan-Xiang; Lin, Zhang-Ya

2016-03-23

The underlying pathology of brain leading to cognitive impairment in Parkinson's disease (PD) remains poorly understood. The aim of our study was to test the hypothesis that mild cognitive impairment (MCI) in PD may be related to atrophy of special gray matter regions. High-resolution T1-weighted magnetic resonance images of the brains and comprehensive cognitive function tests were acquired in 37 PD patients and 21 healthy controls (HC) from September 2013 to October 2014. Patients were divided into two groups: PD with MCI (PD-MCI, n=18) and PD with normal cognition (PDNC, n=19). Gray matter density differences were analyzed using voxel-based morphometry (VBM). VBM and cognitive results, UPDRS scores and Hoehn-Yahr stages were compared between PD-MCI, PDCN and HC group, and correlation analyses were performed between those brain areas and cognition scores, UPDRS scores and disease duration, which showed significant group differences. The demographic data and motor severity among three groups were similar. However, comprehensive cognitive function results were more severe in PD-MCI than the other two groups. Compared to the HC group, the PDNC group showed reductions in gray matter density in frontal, temporal, parietal, bilateral insula lobes and many other regions of brain. Besides above changes, the PD-MCI group also revealed gray matter concentration decrease in left hippocampus and thalamus, and these changes still remained when compared with the PDNC group. The HC group did not show any more areas of atrophy in gray matter than others. Gray matter loss in PD represented significant correlations with global cognitive scores, motor severity or disease duration in some of these atrophic regions. The initial stages of cognitive function decline in patients with PD is closely associated with gray matter atrophy in left hippocampus and thalamus. These two regions may serve as potential imaging biomarkers for PD-MCI. Copyright © 2016. Published by Elsevier Ireland Ltd.

Structured Light Based 3d Scanning for Specular Surface by the Combination of Gray Code and Phase Shifting

NASA Astrophysics Data System (ADS)

Zhang, Yujia; Yilmaz, Alper

2016-06-01

Surface reconstruction using coded structured light is considered one of the most reliable techniques for high-quality 3D scanning. With a calibrated projector-camera stereo system, a light pattern is projected onto the scene and imaged by the camera. Correspondences between projected and recovered patterns are computed in the decoding process, which is used to generate 3D point cloud of the surface. However, the indirect illumination effects on the surface, such as subsurface scattering and interreflections, will raise the difficulties in reconstruction. In this paper, we apply maximum min-SW gray code to reduce the indirect illumination effects of the specular surface. We also analysis the errors when comparing the maximum min-SW gray code and the conventional gray code, which justifies that the maximum min-SW gray code has significant superiority to reduce the indirect illumination effects. To achieve sub-pixel accuracy, we project high frequency sinusoidal patterns onto the scene simultaneously. But for specular surface, the high frequency patterns are susceptible to decoding errors. Incorrect decoding of high frequency patterns will result in a loss of depth resolution. Our method to resolve this problem is combining the low frequency maximum min-SW gray code and the high frequency phase shifting code, which achieves dense 3D reconstruction for specular surface. Our contributions include: (i) A complete setup of the structured light based 3D scanning system; (ii) A novel combination technique of the maximum min-SW gray code and phase shifting code. First, phase shifting decoding with sub-pixel accuracy. Then, the maximum min-SW gray code is used to resolve the ambiguity resolution. According to the experimental results and data analysis, our structured light based 3D scanning system enables high quality dense reconstruction of scenes with a small number of images. Qualitative and quantitative comparisons are performed to extract the advantages of our new combined coding method.

Regional shape-based feature space for segmenting biomedical images using neural networks

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Gopal; Hoford, John D.; Hoffman, Eric A.

1993-07-01

In biomedical images, structure of interest, particularly the soft tissue structures, such as the heart, airways, bronchial and arterial trees often have grey-scale and textural characteristics similar to other structures in the image, making it difficult to segment them using only gray- scale and texture information. However, these objects can be visually recognized by their unique shapes and sizes. In this paper we discuss, what we believe to be, a novel, simple scheme for extracting features based on regional shapes. To test the effectiveness of these features for image segmentation (classification), we use an artificial neural network and a statistical cluster analysis technique. The proposed shape-based feature extraction algorithm computes regional shape vectors (RSVs) for all pixels that meet a certain threshold criteria. The distance from each such pixel to a boundary is computed in 8 directions (or in 26 directions for a 3-D image). Together, these 8 (or 26) values represent the pixel's (or voxel's) RSV. All RSVs from an image are used to train a multi-layered perceptron neural network which uses these features to 'learn' a suitable classification strategy. To clearly distinguish the desired object from other objects within an image, several examples from inside and outside the desired object are used for training. Several examples are presented to illustrate the strengths and weaknesses of our algorithm. Both synthetic and actual biomedical images are considered. Future extensions to this algorithm are also discussed.

Tests of various colorants for application of a Fourier transform infrared imaging system to deciphering obliterated writings

NASA Astrophysics Data System (ADS)

Sugawara, Shigeru

2015-10-01

Obliterated writing is writing that has been obscured by different-colored materials. There are obliterated writings that cannot be detected by conventional methods. A method for deciphering such obliterated writings was developed in this study. Mid-infrared spectroscopic imaging in the wavelength range of 2.5-14 μm was used for deciphering because the infrared spectrum differs among different brands of colorants. Obliterated writings were made by pressing information protection stamps onto characters written by 4 kinds of colorants. The samples were tested for deciphering by the Fourier-transform infrared imaging system. Two peak areas of two specific wavenumber regions of each reflectance spectrum were calculated and the ratio of the two values is displayed as a unique gray scale in the spectroscopic image. As a result, the absorption peak at various wavenumbers could be used to decipher obliterated writings that could not be detected by the conventional methods. Ten different parameters for deciphering obliterated writing were found in this study.

Change Detection Analysis of Water Pollution in Coimbatore Region using Different Color Models

NASA Astrophysics Data System (ADS)

Jiji, G. Wiselin; Devi, R. Naveena

2017-12-01

The data acquired through remote sensing satellites furnish facts about the land and water at varying resolutions and has been widely used for several change detection studies. Apart from the existence of many change detection methodologies and techniques, emergence of new ones continues to subsist. Existing change detection techniques exploit images that are either in gray scale or RGB color model. In this paper we introduced color models for performing change detection for water pollution. Here the polluted lakes are classified and post-classification change detection techniques are applied to RGB images and results obtained are analysed for changes to exist or not. Furthermore RGB images obtained after classification when converted to any of the two color models YCbCr and YIQ is found to produce the same results as that of the RGB model images. Thus it can be concluded that other color models like YCbCr, YIQ can be used as substitution to RGB color model for analysing change detection with regard to water pollution.

Radiomics: a new application from established techniques

PubMed Central

Parekh, Vishwa; Jacobs, Michael A.

2016-01-01

The increasing use of biomarkers in cancer have led to the concept of personalized medicine for patients. Personalized medicine provides better diagnosis and treatment options available to clinicians. Radiological imaging techniques provide an opportunity to deliver unique data on different types of tissue. However, obtaining useful information from all radiological data is challenging in the era of “big data”. Recent advances in computational power and the use of genomics have generated a new area of research termed Radiomics. Radiomics is defined as the high throughput extraction of quantitative imaging features or texture (radiomics) from imaging to decode tissue pathology and creating a high dimensional data set for feature extraction. Radiomic features provide information about the gray-scale patterns, inter-pixel relationships. In addition, shape and spectral properties can be extracted within the same regions of interest on radiological images. Moreover, these features can be further used to develop computational models using advanced machine learning algorithms that may serve as a tool for personalized diagnosis and treatment guidance. PMID:28042608

Incoherent coincidence imaging of space objects

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Medipix-based Spectral Micro-CT.

PubMed

Yu, Hengyong; Xu, Qiong; He, Peng; Bennett, James; Amir, Raja; Dobbs, Bruce; Mou, Xuanqin; Wei, Biao; Butler, Anthony; Butler, Phillip; Wang, Ge

2012-12-01

Since Hounsfield's Nobel Prize winning breakthrough decades ago, X-ray CT has been widely applied in the clinical and preclinical applications - producing a huge number of tomographic gray-scale images. However, these images are often insufficient to distinguish crucial differences needed for diagnosis. They have poor soft tissue contrast due to inherent photon-count issues, involving high radiation dose. By physics, the X-ray spectrum is polychromatic, and it is now feasible to obtain multi-energy, spectral, or true-color, CT images. Such spectral images promise powerful new diagnostic information. The emerging Medipix technology promises energy-sensitive, high-resolution, accurate and rapid X-ray detection. In this paper, we will review the recent progress of Medipix-based spectral micro-CT with the emphasis on the results obtained by our team. It includes the state- of-the-art Medipix detector, the system and method of a commercial MARS (Medipix All Resolution System) spectral micro-CT, and the design and color diffusion of a hybrid spectral micro-CT.

Word recognition using a lexicon constrained by first/last character decisions

NASA Astrophysics Data System (ADS)

Zhao, Sheila X.; Srihari, Sargur N.

1995-03-01

In lexicon based recognition of machine-printed word images, the size of the lexicon can be quite extensive. The recognition performance is closely related to the size of the lexicon. Recognition performance drops quickly when lexicon size increases. Here, we present an algorithm to improve the word recognition performance by reducing the size of the given lexicon. The algorithm utilizes the information provided by the first and last characters of a word to reduce the size of the given lexicon. Given a word image and a lexicon that contains the word in the image, the first and last characters are segmented and then recognized by a character classifier. The possible candidates based on the results given by the classifier are selected, which give us the sub-lexicon. Then a word shape analysis algorithm is applied to produce the final ranking of the given lexicon. The algorithm was tested on a set of machine- printed gray-scale word images which includes a wide range of print types and qualities.

MToS: A Tree of Shapes for Multivariate Images.

PubMed

Carlinet, Edwin; Géraud, Thierry

2015-12-01

The topographic map of a gray-level image, also called tree of shapes, provides a high-level hierarchical representation of the image contents. This representation, invariant to contrast changes and to contrast inversion, has been proved very useful to achieve many image processing and pattern recognition tasks. Its definition relies on the total ordering of pixel values, so this representation does not exist for color images, or more generally, multivariate images. Common workarounds, such as marginal processing, or imposing a total order on data, are not satisfactory and yield many problems. This paper presents a method to build a tree-based representation of multivariate images, which features marginally the same properties of the gray-level tree of shapes. Briefly put, we do not impose an arbitrary ordering on values, but we only rely on the inclusion relationship between shapes in the image definition domain. The interest of having a contrast invariant and self-dual representation of multivariate image is illustrated through several applications (filtering, segmentation, and object recognition) on different types of data: color natural images, document images, satellite hyperspectral imaging, multimodal medical imaging, and videos.

Interest point detection for hyperspectral imagery

NASA Astrophysics Data System (ADS)

Dorado-Muñoz, Leidy P.; Vélez-Reyes, Miguel; Roysam, Badrinath; Mukherjee, Amit

2009-05-01

This paper presents an algorithm for automated extraction of interest points (IPs)in multispectral and hyperspectral images. Interest points are features of the image that capture information from its neighbours and they are distinctive and stable under transformations such as translation and rotation. Interest-point operators for monochromatic images were proposed more than a decade ago and have since been studied extensively. IPs have been applied to diverse problems in computer vision, including image matching, recognition, registration, 3D reconstruction, change detection, and content-based image retrieval. Interest points are helpful in data reduction, and reduce the computational burden of various algorithms (like registration, object detection, 3D reconstruction etc) by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. An interest operator seeks out points in an image that are structurally distinct, invariant to imaging conditions, stable under geometric transformation, and interpretable which are good candidates for interest points. Our approach extends ideas from Lowe's keypoint operator that uses local extrema of Difference of Gaussian (DoG) operator at multiple scales to detect interest point in gray level images. The proposed approach extends Lowe's method by direct conversion of scalar operations such as scale-space generation, and extreme point detection into operations that take the vector nature of the image into consideration. Experimental results with RGB and hyperspectral images which demonstrate the potential of the method for this application and the potential improvements of a fully vectorial approach over band-by-band approaches described in the literature.

A simple and robust method for artifacts correction on X-ray microtomography images

NASA Astrophysics Data System (ADS)

Timofey, Sizonenko; Marina, Karsanina; Dina, Gilyazetdinova; Irina, Bayuk; Kirill, Gerke

2017-04-01

X-ray microtomography images of rock material often have some kinds of distortion due to different reasons such as X-ray attenuation, beam hardening, irregularity of distribution of liquid/solid phases. Several kinds of distortion can arise from further image processing and stitching of images from different measurements. Beam-hardening is a well-known and studied distortion which is relative easy to be described, fitted and corrected using a number of equations. However, this is not the case for other grey scale intensity distortions. Shading by irregularity of distribution of liquid phases, incorrect scanner operating/parameters choosing, as well as numerous artefacts from mathematical reconstructions from projections, including stitching from separate scans cannot be described using single mathematical model. To correct grey scale intensities on large 3D images we developed a package Traditional method for removing the beam hardening [1] has been modified in order to find the center of distortion. The main contribution of this work is in development of a method for arbitrary image correction. This method is based on fitting the distortion by Bezier curve using image histogram. The distortion along the image is represented by a number of Bezier curves and one base line that characterizes the natural distribution of gray value along the image. All of these curves are set manually by the operator. We have tested our approaches on different X-ray microtomography images of porous media. Arbitrary correction removes all principal distortion. After correction the images has been binarized with subsequent pore-network extracted. Equal distribution of pore-network elements along the image was the criteria to verify the proposed technique to correct grey scale intensities. [1] Iassonov, P. and Tuller, M., 2010. Application of segmentation for correction of intensity bias in X-ray computed tomography images. Vadose Zone Journal, 9(1), pp.187-191.

A research on radiation calibration of high dynamic range based on the dual channel CMOS

NASA Astrophysics Data System (ADS)

Ma, Kai; Shi, Zhan; Pan, Xiaodong; Wang, Yongsheng; Wang, Jianghua

2017-10-01

The dual channel complementary metal-oxide semiconductor (CMOS) can get high dynamic range (HDR) image through extending the gray level of the image by using image fusion with high gain channel image and low gain channel image in a same frame. In the process of image fusion with dual channel, it adopts the coefficients of radiation response of a pixel from dual channel in a same frame, and then calculates the gray level of the pixel in the HDR image. For the coefficients of radiation response play a crucial role in image fusion, it has to find an effective method to acquire these parameters. In this article, it makes a research on radiation calibration of high dynamic range based on the dual channel CMOS, and designs an experiment to calibrate the coefficients of radiation response for the sensor it used. In the end, it applies these response parameters in the dual channel CMOS which calibrates, and verifies the correctness and feasibility of the method mentioned in this paper.

Thin and Slow Smoke Detection by Using Frequency Image

NASA Astrophysics Data System (ADS)

Zheng, Guang; Oe, Shunitiro

In this paper, a new method to detect thin and slow smoke for early fire alarm by using frequency image has been proposed. The correlation coefficient of the frequency image between the current stage and the initial stage are calculated, so are the gray image correlation coefficient of the color image. When the thin smoke close to transparent enters into the camera view, the correlation coefficient of the frequency image becomes small, while the gray image correlation coefficient of the color image hardly change and keep large. When something which is not transparent, like human beings, etc., enters into the camera view, the correlation coefficient of the frequency image becomes small, as well as that of color image. Based on the difference of correlation coefficient between frequency image and color image in different situations, the thin smoke can be detected. Also, considering the movement of the thin smoke, miss detection caused by the illustration change or noise can be avoided. Several experiments in different situations are carried out, and the experimental results show the effect of the proposed method.

Neuroanatomy of the killer whale (Orcinus orca): a magnetic resonance imaging investigation of structure with insights on function and evolution.

PubMed

Wright, Alexandra; Scadeng, Miriam; Stec, Dominik; Dubowitz, Rebecca; Ridgway, Sam; Leger, Judy St

2017-01-01

The evolutionary process of adaptation to an obligatory aquatic existence dramatically modified cetacean brain structure and function. The brain of the killer whale (Orcinus orca) may be the largest of all taxa supporting a panoply of cognitive, sensory, and sensorimotor abilities. Despite this, examination of the O. orca brain has been limited in scope resulting in significant deficits in knowledge concerning its structure and function. The present study aims to describe the neural organization and potential function of the O. orca brain while linking these traits to potential evolutionary drivers. Magnetic resonance imaging was used for volumetric analysis and three-dimensional reconstruction of an in situ postmortem O. orca brain. Measurements were determined for cortical gray and cerebral white matter, subcortical nuclei, cerebellar gray and white matter, corpus callosum, hippocampi, superior and inferior colliculi, and neuroendocrine structures. With cerebral volume comprising 81.51 % of the total brain volume, this O. orca brain is one of the most corticalized mammalian brains studied to date. O. orca and other delphinoid cetaceans exhibit isometric scaling of cerebral white matter with increasing brain size, a trait that violates an otherwise evolutionarily conserved cerebral scaling law. Using comparative neurobiology, it is argued that the divergent cerebral morphology of delphinoid cetaceans compared to other mammalian taxa may have evolved in response to the sensorimotor demands of the aquatic environment. Furthermore, selective pressures associated with the evolution of echolocation and unihemispheric sleep are implicated in substructure morphology and function. This neuroanatomical dataset, heretofore absent from the literature, provides important quantitative data to test hypotheses regarding brain structure, function, and evolution within Cetacea and across Mammalia.

Latest generation of flat detector CT as a peri-interventional diagnostic tool: a comparative study with multidetector CT.

PubMed

Leyhe, Johanna Rosemarie; Tsogkas, Ioannis; Hesse, Amélie Carolina; Behme, Daniel; Schregel, Katharina; Papageorgiou, Ismini; Liman, Jan; Knauth, Michael; Psychogios, Marios-Nikos

2017-12-01

Flat detector CT (FDCT) has been used as a peri-interventional diagnostic tool in numerous studies with mixed results regarding image quality and detection of intracranial lesions. We compared the diagnostic aspects of the latest generation FDCT with standard multidetector CT (MDCT). 102 patients were included in our retrospective study. All patients had undergone interventional procedures. FDCT was acquired peri-interventionally and compared with postinterventional MDCT regarding depiction of ventricular/subarachnoidal spaces, detection of intracranial hemorrhage, and delineation of ischemic lesions using an ordinal scale. Ischemic lesions were quantified with the Alberta Stroke Program Early CT Scale (ASPECTS) on both examinations. Two neuroradiologists with varying grades of experience and a medical student scored the anonymized images separately, blinded to the clinical history. The two methods were of equal diagnostic value regarding evaluation of the ventricular system and the subarachnoidal spaces. Subarachnoidal, intraventricular, and parenchymal hemorrhages were detected with a sensitivity of 95%, 97%, and 100% and specificity of 97%, 100%, and 99%, respectively, using FDCT. Gray-white differentiation was feasible in the majority of FDCT scans, and ischemic lesions were detected with a sensitivity of 71% on FDCT, compared with MDCT scans. The mean difference in ASPECTS values on FDCT and MDCT was 0.5 points (95% CI 0.12 to 0.88). The latest generation of FDCT is a reliable and accurate tool for the detection of intracranial hemorrhage. Gray-white differentiation is feasible in the supratentorial region. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

PubMed

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

a New Color Correction Method for Underwater Imaging

NASA Astrophysics Data System (ADS)

Bianco, G.; Muzzupappa, M.; Bruno, F.; Garcia, R.; Neumann, L.

2015-04-01

Recovering correct or at least realistic colors of underwater scenes is a very challenging issue for imaging techniques, since illumination conditions in a refractive and turbid medium as the sea are seriously altered. The need to correct colors of underwater images or videos is an important task required in all image-based applications like 3D imaging, navigation, documentation, etc. Many imaging enhancement methods have been proposed in literature for these purposes. The advantage of these methods is that they do not require the knowledge of the medium physical parameters while some image adjustments can be performed manually (as histogram stretching) or automatically by algorithms based on some criteria as suggested from computational color constancy methods. One of the most popular criterion is based on gray-world hypothesis, which assumes that the average of the captured image should be gray. An interesting application of this assumption is performed in the Ruderman opponent color space lαβ, used in a previous work for hue correction of images captured under colored light sources, which allows to separate the luminance component of the scene from its chromatic components. In this work, we present the first proposal for color correction of underwater images by using lαβ color space. In particular, the chromatic components are changed moving their distributions around the white point (white balancing) and histogram cutoff and stretching of the luminance component is performed to improve image contrast. The experimental results demonstrate the effectiveness of this method under gray-world assumption and supposing uniform illumination of the scene. Moreover, due to its low computational cost it is suitable for real-time implementation.

LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

PubMed Central

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8 months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. PMID:25541188

Gray Matter Atrophy Is Primarily Related to Demyelination of Lesions in Multiple Sclerosis: A Diffusion Tensor Imaging MRI Study.

PubMed

Tóth, Eszter; Szabó, Nikoletta; Csete, Gergõ; Király, András; Faragó, Péter; Spisák, Tamás; Bencsik, Krisztina; Vécsei, László; Kincses, Zsigmond T

2017-01-01

Objective: Cortical pathology, periventricular demyelination, and lesion formation in multiple sclerosis (MS) are related (Hypothesis 1). Factors in the cerebrospinal fluid close to these compartments could possibly drive the parallel processes. Alternatively, the cortical atrophy could be caused by remote axonal transection (Hypothesis 2). Since MRI can differentiate between demyelination and axon loss, we used this imaging modality to investigate the correlation between the pattern of diffusion parameter changes in the periventricular- and deep white matter and the gray matter atrophy. Methods: High-resolution T1-weighted, FLAIR, and diffusion MRI images were acquired in 52 RRMS patients and 50 healthy, age-matched controls. We used EDSS to estimate the clinical disability. We used Tract Based Spatial Statistics to compare diffusion parameters (fractional anisotropy, mean, axial, and radial diffusivity) between groups. We evaluated global brain, white, and gray matter atrophy with SIENAX. Averaged, standard diffusion parameters were calculated in four compartment: periventricular lesioned and normal appearing white matter, non-periventricular lesioned and normal appearing white matter. PLS regression was used to identify which diffusion parameter and in which compartment best predicts the brain atrophy and clinical disability. Results: In our diffusion tensor imaging study compared to controls we found extensive alterations of fractional anisotropy, mean and radial diffusivity and smaller changes of axial diffusivity (maximal p > 0.0002) in patients that suggested demyelination in the lesioned and in the normal appearing white matter. We found significant reduction in total brain, total white, and gray matter (patients: 718.764 ± 14.968, 323.237 ± 7.246, 395.527 ± 8.050 cm 3 , controls: 791.772 ± 22.692, 355.350 ± 10.929, 436.422 ± 12.011 cm 3 ; mean ± SE), ( p < 0.015; p < 0.0001; p < 0.009; respectively) of patients compared to controls. The PLS analysis revealed a combination of demyelination-like diffusion parameters (higher mean and radial diffusivity in patients) in the lesions and in the non-lesioned periventricular white matter, which best predicted the gray matter atrophy ( p < 0.001). Similarly, EDSS was best predicted by the radial diffusivity of the lesions and the non-lesioned periventricular white matter, but axial diffusivity of the periventricular lesions also contributed significantly ( p < 0.0001). Interpretation: Our investigation showed that gray matter atrophy and white matter demyelination are related in MS but white matter axonal loss does not significantly contribute to the gray matter pathology.

Ink-jet printout of radiographs on transparent film and glossy paper versus monitor display: an ROC analysis.

PubMed

Kühl, Sebastian; Krummenauer, Frank; Dagassan-Berndt, Dorothea; Lambrecht, Thomas J; d'Hoedt, Bernd; Schulze, Ralf Kurt Willy

2011-06-01

The aim of this study was to compare the depiction ability of small grayscale contrasts in ink-jet printouts of digital radiographs on different print media with CRT monitor. A CCD-based digital cephalometric image of a stepless aluminum wedge containing 50 bur holes of different depth was cut into 100 isometric images. Each image was printed on glossy paper and on transparent film by means of a high-resolution desktop inkjet printer at specific settings. The printed images were viewed under standardized conditions, and the perceptibility of the bur holes was evaluated and compared to the perceptibility on a 17-in CRT monitor. Thirty observers stated their blinded decision on a five-point confidence scale. Areas (Az) under receiver operating characteristics curves were calculated and compared using the pair wise sign tests. Overall agreement was estimated using Cohen's kappa device and observer bias using McNemar's test. Glossy paper prints and monitor display revealed significantly higher (P < 0.001) average Az values (0.83) compared to prints on transparent film (0.79), which was caused by higher sensitivity. Specificity was similar for all modalities. The sensitivity was dependent on the mean gray scale values for the transparent film.

Anterior cruciate ligament tears treated with percutaneous injection of autologous bone marrow nucleated cells: a case series

PubMed Central

Centeno, Christopher J; Pitts, John; Al-Sayegh, Hasan; Freeman, Michael D

2015-01-01

Introduction This was a prospective case series designed to investigate treatment for anterior cruciate ligament (ACL) tears using an injection of autologous bone marrow concentrate. Methods Consecutive adult patients presenting to a private outpatient interventional musculoskeletal and pain practice with knee pain, ACL laxity on exam, and magnetic resonance imaging (MRI) evidence of a grade 1, 2, or 3 ACL tears with less than 1 cm retraction were eligible for this study. Eligible patients were treated with an intraligamentous injection of autologous bone marrow concentrate, using fluoroscopic guidance. Pre- and postprocedural sagittal MRI images of the ACLs were analyzed using ImageJ software to objectively quantify changes between pre- and posttreatment scans. Five different types of measurement of ACL pixel intensity were examined as a proxy for ligament integrity. In addition pain visual analog scale (VAS) and Lower Extremity Functional Scale (LEFS) values were recorded at baseline and at 1 month, 3 months, 6 months, and annually postinjection. Objective outcomes measured were pre- to post-MRI measurement changes, as analyzed by the ImageJ software. Subjective outcomes measured were changes in the VAS and LEFS, and a self-rated percentage improvement. Results Seven of ten patients showed improvement in at least four of five objective measures of ACL integrity in their postprocedure MRIs. In the entire study group, the mean gray value, median, raw integrated density, and modal gray value all decreased toward low-signal ACLs (P=0.01, P=0.02, P=0.002, and P=0.08), indications of improved ligament integrity. Seven of ten patients responded to the self-rated metrics follow up. The mean VAS change was a decrease of 1.7 (P=0.25), the mean LEFS change was an increase of 23.3 (P=0.03), and mean reported improvement was 86.7%. Conclusion Based on this small case series, autologous bone marrow concentrate shows promise in the treatment of grade 1, 2, and possibly grade 3 ACL tears without retraction. Further investigation using a controlled study design is warranted. PMID:26261424

Joint source based morphometry identifies linked gray and white matter group differences

PubMed Central

Xu, Lai; Pearlson, Godfrey; Calhoun, Vince D.

2009-01-01

We present a multivariate approach called joint source based morphometry (jSBM), to identify linked gray and white matter regions which differ between groups. In jSBM, joint independent component analysis (jICA) is used to decompose preprocessed gray and white matter images into joint sources and statistical analysis is used to determine the significant joint sources showing group differences and their relationship to other variables of interest (e.g. age or sex). The identified joint sources are groupings of linked gray and white matter regions with common covariation among subjects. In this study, we first provide a simulation to validate the jSBM approach. To illustrate our method on real data, jSBM is then applied to structural magnetic resonance imaging (sMRI) data obtained from 120 chronic schizophrenia patients and 120 healthy controls to identify group differences. JSBM identified four joint sources as significantly associated with schizophrenia. Linked gray–white matter regions identified in each of the joint sources included: 1) temporal — corpus callosum, 2) occipital/frontal — inferior fronto-occipital fasciculus, 3) frontal/parietal/occipital/temporal —superior longitudinal fasciculus and 4) parietal/frontal — thalamus. Age effects on all four joint sources were significant, but sex effects were significant only for the third joint source. Our findings demonstrate that jSBM can exploit the natural linkage between gray and white matter by incorporating them into a unified framework. This approach is applicable to a wide variety of problems to study linked gray and white matter group differences. PMID:18992825

Gray matter alterations and correlation of nutritional intake with the gray matter volume in prediabetes

PubMed Central

Hou, Yi-Cheng; Lai, Chien-Han; Wu, Yu-Te; Yang, Shwu-Huey

2016-01-01

Abstract The neurophysiology of prediabetes plays an important role in preventive medicine. The dysregulation of glucose metabolism is likely linked to changes in neuron-related gray matter. Therefore, we designed this study to investigate gray matter alterations in medication-naive prediabetic patients. We expected to find alterations in the gray matter of prediabetic patients. A total of 64 prediabetic patients and 54 controls were enrolled. All subjects received T1 scans using a 3-T magnetic resonance imaging machine. Subjects also completed nutritional intake records at the 24-hour and 3-day time points to determine their carbohydrate, protein, fat, and total calorie intake. We utilized optimized voxel-based morphometry to estimate the gray matter differences between the patients and controls. In addition, the preprandial serum glucose level and the carbohydrate, protein, fat, and total calorie intake levels were tested to determine whether these parameters were correlated with the gray matter volume. Prediabetic patients had lower gray matter volumes than controls in the right anterior cingulate gyrus, right posterior cingulate gyrus, left insula, left super temporal gyrus, and left middle temporal gyrus (corrected P < 0.05; voxel threshold: 33). Gray matter volume in the right anterior cingulate was also negatively correlated with the preprandial serum glucose level gyrus in a voxel-dependent manner (r = –0.501; 2-tailed P = 0.001). The cingulo-temporal and insula gray matter alterations may be associated with the glucose dysregulation in prediabetic patients. PMID:27336893

A neural network detection model of spilled oil based on the texture analysis of SAR image

NASA Astrophysics Data System (ADS)

An, Jubai; Zhu, Lisong

2006-01-01

A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.

LSB-Based Steganography Using Reflected Gray Code

NASA Astrophysics Data System (ADS)

Chen, Chang-Chu; Chang, Chin-Chen

Steganography aims to hide secret data into an innocuous cover-medium for transmission and to make the attacker cannot recognize the presence of secret data easily. Even the stego-medium is captured by the eavesdropper, the slight distortion is hard to be detected. The LSB-based data hiding is one of the steganographic methods, used to embed the secret data into the least significant bits of the pixel values in a cover image. In this paper, we propose an LSB-based scheme using reflected-Gray code, which can be applied to determine the embedded bit from secret information. Following the transforming rule, the LSBs of stego-image are not always equal to the secret bits and the experiment shows that the differences are up to almost 50%. According to the mathematical deduction and experimental results, the proposed scheme has the same image quality and payload as the simple LSB substitution scheme. In fact, our proposed data hiding scheme in the case of G1 (one bit Gray code) system is equivalent to the simple LSB substitution scheme.

Effect of scaling and root planing on alveolar bone as measured by subtraction radiography.

PubMed

Hwang, You-Jeong; Fien, Matthew Jonas; Lee, Sam-Sun; Kim, Tae-Il; Seol, Yang-Jo; Lee, Yong-Moo; Ku, Young; Rhyu, In-Chul; Chung, Chong-Pyoung; Han, Soo-Boo

2008-09-01

Scaling and root planing of diseased periodontal pockets is fundamental to the treatment of periodontal disease. Although various clinical parameters have been used to assess the efficacy of this therapy, radiographic analysis of changes in bone density following scaling and root planing has not been extensively researched. In this study, digital subtraction radiography was used to analyze changes that occurred in the periodontal hard tissues following scaling and root planing. Thirteen subjects with a total of 39 sites that presented with >3 mm of vertical bone loss were included in this study. Clinical examinations were performed and radiographs were taken prior to treatment and were repeated 6 months following scaling and root planing. Radiographic analysis was performed with computer-assisted radiographic evaluation software. Three regions of interest (ROI) were defined as the most coronal, middle, and apical portions of each defect. A fourth ROI was used for each site as a control region and was placed at a distant, untreated area. Statistical analysis was carried out to evaluate changes in the mean gray level at the coronal, middle, and apical region of each treated defect. Digital subtraction radiography revealed an increase in radiographic density in 101 of the 117 test regions (83.3%). A 256 gray level was used, and a value >128 was assumed to represent a density gain in the ROI. The average gray level increase was 18.65. Although the coronal, middle, and apical regions displayed increases in bone density throughout this study, the bone density of the apical ROI (gray level = 151.27 +/- 20.62) increased significantly more than the bone density of the coronal ROI (gray level = 139.19 +/- 21.78). A significant increase in bone density was seen in probing depths >5 mm compared to those <5 mm in depth. No significant difference was found with regard to bone-density changes surrounding single- versus multiple-rooted teeth. Scaling and root planing of diseased periodontal pockets can significantly increase radiographic alveolar bone density as demonstrated through the use of digital subtraction radiography.

Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

PubMed

Renjith, Arokia; Manjula, P; Mohan Kumar, P

2015-01-01

Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

Image authentication by means of fragile CGH watermarking

NASA Astrophysics Data System (ADS)

Schirripa Spagnolo, Giuseppe; Simonetti, Carla; Cozzella, Lorenzo

2005-09-01

In this paper we propose a fragile marking system based on Computer Generated Hologram coding techniques, which is able to detect malicious tampering while tolerating some incidental distortions. A fragile watermark is a mark that is readily altered or destroyed when the host image is modified through a linear or nonlinear transformation. A fragile watermark monitors the integrity of the content of the image but not its numerical representation. Therefore the watermark is designed so that the integrity is proven if the content of the image has not been tampered. Since digital images can be altered or manipulated with ease, the ability to detect changes to digital images is very important for many applications such as news reporting, medical archiving, or legal usages. The proposed technique could be applied to Color Images as well as to Gray Scale ones. Using Computer Generated Hologram watermarking, the embedded mark could be easily recovered by means of a Fourier Transform. Due to this fact host image can be tampered and watermarked with the same holographic pattern. To avoid this possibility we have introduced an encryption method using a asymmetric Cryptography. The proposed schema is based on the knowledge of original mark from the Authentication

Fast evolution of image manifolds and application to filtering and segmentation in 3D medical images.

PubMed

Deschamps, Thomas; Malladi, Ravi; Ravve, Igor

2004-01-01

In many instances, numerical integration of space-scale PDEs is the most time consuming operation of image processing. This is because the scale step is limited by conditional stability of explicit schemes. In this work, we introduce the unconditionally stable semi-implicit linearized difference scheme that is fashioned after additive operator split (AOS) [1], [2] for Beltrami and the subjective surface computation. The Beltrami flow [3], [4], [5] is one of the most effective denoising algorithms in image processing. For gray-level images, we show that the flow equation can be arranged in an advection-diffusion form, revealing the edge-enhancing properties of this flow. This also suggests the application of AOS method for faster convergence. The subjective surface [6] deals with constructing a perceptually meaningful interpretation from partial image data by mimicking the human visual system. However, initialization of the surface is critical for the final result and its main drawbacks are very slow convergence and the huge number of iterations required. In this paper, we first show that the governing equation for the subjective surface flow can be rearranged in an AOS implementation, providing a near real-time solution to the shape completion problem in 2D and 3D. Then, we devise a new initialization paradigm where we first "condition" the viewpoint surface using the Fast-Marching algorithm. We compare the original method with our new algorithm on several examples of real 3D medical images, thus revealing the improvement achieved.

Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma

NASA Astrophysics Data System (ADS)

Kawamura, Harumi; Yonemura, Shunichi; Ohya, Jun; Kojima, Akira

2013-02-01

A new approach is proposed for estimating illuminant colors from color images under an unknown scene illuminant. The approach is based on a combination of a gray-world-assumption-based illuminant color estimation method and a method using color gamuts. The former method, which is one we had previously proposed, improved on the original method that hypothesizes that the average of all the object colors in a scene is achromatic. Since the original method estimates scene illuminant colors by calculating the average of all the image pixel values, its estimations are incorrect when certain image colors are dominant. Our previous method improves on it by choosing several colors on the basis of an opponent-color property, which is that the average color of opponent colors is achromatic, instead of using all colors. However, it cannot estimate illuminant colors when there are only a few image colors or when the image colors are unevenly distributed in local areas in the color space. The approach we propose in this paper combines our previous method and one using high chroma and low chroma gamuts, which makes it possible to find colors that satisfy the gray world assumption. High chroma gamuts are used for adding appropriate colors to the original image and low chroma gamuts are used for narrowing down illuminant color possibilities. Experimental results obtained using actual images show that even if the image colors are localized in a certain area in the color space, the illuminant colors are accurately estimated, with smaller estimation error average than that generated in the conventional method.

Complexity of low-frequency blood oxygen level-dependent fluctuations covaries with local connectivity.

PubMed

Anderson, Jeffrey S; Zielinski, Brandon A; Nielsen, Jared A; Ferguson, Michael A

2014-04-01

Very low-frequency blood oxygen level-dependent (BOLD) fluctuations have emerged as a valuable tool for describing brain anatomy, neuropathology, and development. Such fluctuations exhibit power law frequency dynamics, with largest amplitude at lowest frequencies. The biophysical mechanisms generating such fluctuations are poorly understood. Using publicly available data from 1,019 subjects of age 7-30, we show that BOLD fluctuations exhibit temporal complexity that is linearly related to local connectivity (regional homogeneity), consistently and significantly covarying across subjects and across gray matter regions. This relationship persisted independently of covariance with gray matter density or standard deviation of BOLD signal. During late neurodevelopment, BOLD fluctuations were unchanged with age in association cortex while becoming more random throughout the rest of the brain. These data suggest that local interconnectivity may play a key role in establishing the complexity of low-frequency BOLD fluctuations underlying functional magnetic resonance imaging connectivity. Stable low-frequency power dynamics may emerge through segmentation and integration of connectivity during development of distributed large-scale brain networks. Copyright © 2013 Wiley Periodicals, Inc.

Image enhancement and color constancy for a vehicle-mounted change detection system

NASA Astrophysics Data System (ADS)

Tektonidis, Marco; Monnin, David

2016-10-01

Vehicle-mounted change detection systems allow to improve situational awareness on outdoor itineraries of inter- est. Since the visibility of acquired images is often affected by illumination effects (e.g., shadows) it is important to enhance local contrast. For the analysis and comparison of color images depicting the same scene at different time points it is required to compensate color and lightness inconsistencies caused by the different illumination conditions. We have developed an approach for image enhancement and color constancy based on the center/surround Retinex model and the Gray World hypothesis. The combination of the two methods using a color processing function improves color rendition, compared to both methods. The use of stacked integral images (SII) allows to efficiently perform local image processing. Our combined Retinex/Gray World approach has been successfully applied to image sequences acquired on outdoor itineraries at different time points and a comparison with previous Retinex-based approaches has been carried out.

Optical texture analysis for automatic cytology and histology: a Markovian approach

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

Pressman, N.J.

1976-10-12

Markovian analysis is a method to measure optical texture based on gray-level transition probabilities in digitized images. The experiments described in this dissertation investigate the classification performance of parameters generated by this method. Three types of data sets are used: images of (1) human blood leukocytes (nuclei of monocytes, neutrophils, and lymphocytes; Wright stain; (0.125 ..mu..m)/sup 2//picture point), (2) cervical exfoliative cells (nuclei of normal intermediate squamous cells and dysplastic and carcinoma in situ cells; azure-A/Feulgen stain; (0.125 ..mu..m)/sup 2//picture point), and (3) lymph-node tissue sections (6-..mu..m thick sections from normal, acute lymphadenitis, and Hodgkin lymph nodes; hematoxylin and eosinmore » stain; (0.625 ..mu..m)/sup 2/ picture point). Each image consists of 128 x 128 picture points originally scanned with a 256 gray-level resolution. Each image class is defined by 75 images.« less

High-grade video compression of echocardiographic studies: a multicenter validation study of selected motion pictures expert groups (MPEG)-4 algorithms.

PubMed

Barbier, Paolo; Alimento, Marina; Berna, Giovanni; Celeste, Fabrizio; Gentile, Francesco; Mantero, Antonio; Montericcio, Vincenzo; Muratori, Manuela

2007-05-01

Large files produced by standard compression algorithms slow down spread of digital and tele-echocardiography. We validated echocardiographic video high-grade compression with the new Motion Pictures Expert Groups (MPEG)-4 algorithms with a multicenter study. Seven expert cardiologists blindly scored (5-point scale) 165 uncompressed and compressed 2-dimensional and color Doppler video clips, based on combined diagnostic content and image quality (uncompressed files as references). One digital video and 3 MPEG-4 algorithms (WM9, MV2, and DivX) were used, the latter at 3 compression levels (0%, 35%, and 60%). Compressed file sizes decreased from 12 to 83 MB to 0.03 to 2.3 MB (1:1051-1:26 reduction ratios). Mean SD of differences was 0.81 for intraobserver variability (uncompressed and digital video files). Compared with uncompressed files, only the DivX mean score at 35% (P = .04) and 60% (P = .001) compression was significantly reduced. At subcategory analysis, these differences were still significant for gray-scale and fundamental imaging but not for color or second harmonic tissue imaging. Original image quality, session sequence, compression grade, and bitrate were all independent determinants of mean score. Our study supports use of MPEG-4 algorithms to greatly reduce echocardiographic file sizes, thus facilitating archiving and transmission. Quality evaluation studies should account for the many independent variables that affect image quality grading.

The application of an optical Fourier spectrum analyzer on detecting defects in mass-produced satellite photographs

NASA Technical Reports Server (NTRS)

Athale, R.; Lee, S. H.

1976-01-01

Various defects in mass-produced pictures transmitted to earth from a satellite are investigated. It is found that the following defects are readily detectable via Fourier spectrum analysis: (1) bit slip, (2) breakup causing loss of image, and (3) disabled track at the top of the imagery. The scratches made on the film during mass production, which are difficult to detect by visual observation, also show themselves readily in Fourier spectrum analysis. A relation is established between the number of scratches, their width and depth and the intensity of their Fourier spectra. Other defects that are found to be equally suitable for Fourier spectrum analysis or visual (image analysis) detection are synchronous loss without blurring of image, and density variation in gray scale. However, the Fourier spectrum analysis is found to be unsuitable for detection of such defects as pin holes, annotation error, synchronous loss with blurring of images, and missing image in the beginning of the work order. The design of an automated, real time system, which will reject defective films, is treated.

Total rate imaging with x-rays (TRIX)--a simple method of forming a non-projection x-ray image in the SEM using an energy dispersive detector and its application to biological specimens.

PubMed

Ingram, P; Shelburne, J D

1980-01-01

X-ray images can be formed in a conventional scanning electron microscope equipped with a Si(Li) energy dispersive spectrometer. All the x-ray events generated in the electron beam scanning process are synchronously displayed in the same manner as for dot maps. The quasi-digital image formed using Total Rate Imaging with X-rays (TRIX) exhibits good gray scale contrast and is dependent on topography, orientation and atomic number. Although this latter dependence is complex, it has been found useful in locating several types of inclusions in lung tissue (silicosis), human alveolar macrophages and cigarette smoke condensate. This is because of the greater depth of penetration of x-rays than backscattered electrons (BSE) usually used for such localizations in a matrix, and the negligible sensitivity of the Si(Li) detector to x-rays from an organic biological matrix. The optimum procedure is to use a combination of TRIX and BSE to investigate such specimens.

X-window-based 2K display workstation

NASA Astrophysics Data System (ADS)

Weinberg, Wolfram S.; Hayrapetian, Alek S.; Cho, Paul S.; Valentino, Daniel J.; Taira, Ricky K.; Huang, H. K.

1991-07-01

A high-definition, high-performance display station for reading and review of digital radiological images is introduced. The station is based on a Sun SPARC Station 4 and employs X window system for display and manipulation of images. A mouse-operated graphic user interface is implemented utilizing Motif-style tools. The system supports up to four MegaScan gray-scale 2560 X 2048 monitors. A special configuration of frame and video buffer yields a data transfer of 50 M pixels/s. A magnetic disk array supplies a storage capacity of 2 GB with a data transfer rate of 4-6 MB/s. The system has access to the central archive through an ultrahigh-speed fiber-optic network and patient studies are automatically transferred to the local disk. The available image processing functions include change of lookup table, zoom and pan, and cine. Future enhancements will provide for manual contour tracing, length, area, and density measurements, text and graphic overlay, as well as composition of selected images. Additional preprocessing procedures under development will optimize the initial lookup table and adjust the images to a standard orientation.

Identification of a common neurobiological substrate for mental illness.

PubMed

Goodkind, Madeleine; Eickhoff, Simon B; Oathes, Desmond J; Jiang, Ying; Chang, Andrew; Jones-Hagata, Laura B; Ortega, Brissa N; Zaiko, Yevgeniya V; Roach, Erika L; Korgaonkar, Mayuresh S; Grieve, Stuart M; Galatzer-Levy, Isaac; Fox, Peter T; Etkin, Amit

2015-04-01

Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, suggesting that a common neurobiological substrate may exist across mental illness. To conduct a meta-analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large-scale healthy participant data sets to help interpret structural findings in the meta-analysis. PubMed was searched to identify voxel-based morphometry studies through July 2012 comparing psychiatric patients to healthy control individuals for the meta-analysis. The 3 parallel healthy participant data sets included resting-state functional magnetic resonance imaging, a database of activation foci across thousands of neuroimaging experiments, and a data set with structural imaging and cognitive task performance data. Studies were included in the meta-analysis if they reported voxel-based morphometry differences between patients with an Axis I diagnosis and control individuals in stereotactic coordinates across the whole brain, did not present predominantly in childhood, and had at least 10 studies contributing to that diagnosis (or across closely related diagnoses). The meta-analysis was conducted on peak voxel coordinates using an activation likelihood estimation approach. We tested for areas of common gray matter volume increase or decrease across Axis I diagnoses, as well as areas differing between diagnoses. Follow-up analyses on other healthy participant data sets tested connectivity related to regions arising from the meta-analysis and the relationship of gray matter volume to cognition. Based on the voxel-based morphometry meta-analysis of 193 studies comprising 15 892 individuals across 6 diverse diagnostic groups (schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety), we found that gray matter loss converged across diagnoses in 3 regions: the dorsal anterior cingulate, right insula, and left insula. By contrast, there were few diagnosis-specific effects, distinguishing only schizophrenia and depression from other diagnoses. In the parallel follow-up analyses of the 3 independent healthy participant data sets, we found that the common gray matter loss regions formed a tightly interconnected network during tasks and at resting and that lower gray matter in this network was associated with poor executive functioning. We identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate-based network, which may relate to executive function deficits observed across diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates across psychopathology, despite likely diverse etiologies, which is currently not an explicit component of psychiatric nosology.

ASTER Views California Crown Fire

NASA Image and Video Library

2010-08-03

NASA Terra spacecraft captured this image of the wildfire near Palmdale, Calif. on August 1, 2010 called the Crown fire. The burned areas appear in shades of gray in this simulated natural color image.

White Matter Tract Injury is Associated with Deep Gray Matter Iron Deposition in Multiple Sclerosis.

PubMed

Bergsland, Niels; Tavazzi, Eleonora; Laganà, Maria Marcella; Baglio, Francesca; Cecconi, Pietro; Viotti, Stefano; Zivadinov, Robert; Baselli, Giuseppe; Rovaris, Marco

2017-01-01

With respect to healthy controls (HCs), increased iron concentrations in the deep gray matter (GM) and decreased white matter (WM) integrity are common findings in multiple sclerosis (MS) patients. The association between these features of the disease remains poorly understood. We investigated the relationship between deep iron deposition in the deep GM and WM injury in associated fiber tracts in MS patients. Sixty-six MS patients (mean age 50.0 years, median Expanded Disability Status Scale 5.25, mean disease duration 19.1 years) and 29 HCs, group matched for age and sex were imaged on a 1.5T scanner. Susceptibility-weighted imaging and diffusion tensor imaging (DTI) were used for assessing high-pass filtered phase values in the deep GM and normal appearing WM (NAWM) integrity in associated fiber tracts, respectively. Correlation analyses investigated the associations between filtered phase values (suggestive of iron content) and WM damage. Areas indicative of increased iron levels were found in the left and right caudates as well as in the left thalamus. MS patients presented with decreased DTI-derived measures of tissue integrity in the associated WM tracts. Greater mean, axial and radial diffusivities were associated with increased iron levels in all three GM areas (r values .393 to .514 with corresponding P values .003 to <.0001). Global NAWM diffusivity measures were not related to mean filtered phase values within the deep GM. Increased iron concentration in the deep GM is associated with decreased tissue integrity of the connected WM in MS patients. Copyright © 2016 by the American Society of Neuroimaging.

A century of guayule: Comprehensive genetic characterization of the US national guayule (Parthenium argentatum A. Gray) germplasm collection

USDA-ARS?s Scientific Manuscript database

The fragility of a single-source, geographically concentrated supply of natural rubber, a critical material of the modern economy, has brought guayule (Parthenium argentatum A. Gray) to the forefront as an alternative source of natural rubber. The improvement of guayule for commercial-scale producti...

Regional gray matter correlates of vocational interests

PubMed Central

2012-01-01

Background Previous studies have identified brain areas related to cognitive abilities and personality, respectively. In this exploratory study, we extend the application of modern neuroimaging techniques to another area of individual differences, vocational interests, and relate the results to an earlier study of cognitive abilities salient for vocations. Findings First, we examined the psychometric relationships between vocational interests and abilities in a large sample. The primary relationships between those domains were between Investigative (scientific) interests and general intelligence and between Realistic (“blue-collar”) interests and spatial ability. Then, using MRI and voxel-based morphometry, we investigated the relationships between regional gray matter volume and vocational interests. Specific clusters of gray matter were found to be correlated with Investigative and Realistic interests. Overlap analyses indicated some common brain areas between the correlates of Investigative interests and general intelligence and between the correlates of Realistic interests and spatial ability. Conclusions Two of six vocational-interest scales show substantial relationships with regional gray matter volume. The overlap between the brain correlates of these scales and cognitive-ability factors suggest there are relationships between individual differences in brain structure and vocations. PMID:22591829

Regional gray matter correlates of vocational interests.

PubMed

Schroeder, David H; Haier, Richard J; Tang, Cheuk Ying

2012-05-16

Previous studies have identified brain areas related to cognitive abilities and personality, respectively. In this exploratory study, we extend the application of modern neuroimaging techniques to another area of individual differences, vocational interests, and relate the results to an earlier study of cognitive abilities salient for vocations. First, we examined the psychometric relationships between vocational interests and abilities in a large sample. The primary relationships between those domains were between Investigative (scientific) interests and general intelligence and between Realistic ("blue-collar") interests and spatial ability. Then, using MRI and voxel-based morphometry, we investigated the relationships between regional gray matter volume and vocational interests. Specific clusters of gray matter were found to be correlated with Investigative and Realistic interests. Overlap analyses indicated some common brain areas between the correlates of Investigative interests and general intelligence and between the correlates of Realistic interests and spatial ability. Two of six vocational-interest scales show substantial relationships with regional gray matter volume. The overlap between the brain correlates of these scales and cognitive-ability factors suggest there are relationships between individual differences in brain structure and vocations.

Real-Time In Vivo Imaging of Butterfly Wing Development: Revealing the Cellular Dynamics of the Pupal Wing Tissue

PubMed Central

Iwata, Masaki; Ohno, Yoshikazu; Otaki, Joji M.

2014-01-01

Butterfly wings are covered with regularly arranged single-colored scales that are formed at the pupal stage. Understanding pupal wing development is therefore crucial to understand wing color pattern formation. Here, we successfully employed real-time in vivo imaging techniques to observe pupal hindwing development over time in the blue pansy butterfly, Junonia orithya. A transparent sheet of epithelial cells that were not yet regularly arranged was observed immediately after pupation. Bright-field imaging and autofluorescent imaging revealed free-moving hemocytes and tracheal branches of a crinoid-like structure underneath the epithelium. The wing tissue gradually became gray-white, epithelial cells were arranged regularly, and hemocytes disappeared, except in the bordering lacuna, after which scales grew. The dynamics of the epithelial cells and scale growth were also confirmed by fluorescent imaging. Fluorescent in vivo staining further revealed that these cells harbored many mitochondria at the surface of the epithelium. Organizing centers for the border symmetry system were apparent immediately after pupation, exhibiting a relatively dark optical character following treatment with fluorescent dyes, as well as in autofluorescent images. The wing tissue exhibited slow and low-frequency contraction pulses with a cycle of approximately 10 to 20 minutes, mainly occurring at 2 to 3 days postpupation. The pulses gradually became slower and weaker and eventually stopped. The wing tissue area became larger after contraction, which also coincided with an increase in the autofluorescence intensity that might have been caused by scale growth. Examination of the pattern of color development revealed that the black pigment was first deposited in patches in the central areas of an eyespot black ring and a parafocal element. These results of live in vivo imaging that covered wide wing area for a long time can serve as a foundation for studying the cellular dynamics of living wing tissues in butterflies. PMID:24586829

Real-time in vivo imaging of butterfly wing development: revealing the cellular dynamics of the pupal wing tissue.

PubMed

Iwata, Masaki; Ohno, Yoshikazu; Otaki, Joji M

2014-01-01

Butterfly wings are covered with regularly arranged single-colored scales that are formed at the pupal stage. Understanding pupal wing development is therefore crucial to understand wing color pattern formation. Here, we successfully employed real-time in vivo imaging techniques to observe pupal hindwing development over time in the blue pansy butterfly, Junonia orithya. A transparent sheet of epithelial cells that were not yet regularly arranged was observed immediately after pupation. Bright-field imaging and autofluorescent imaging revealed free-moving hemocytes and tracheal branches of a crinoid-like structure underneath the epithelium. The wing tissue gradually became gray-white, epithelial cells were arranged regularly, and hemocytes disappeared, except in the bordering lacuna, after which scales grew. The dynamics of the epithelial cells and scale growth were also confirmed by fluorescent imaging. Fluorescent in vivo staining further revealed that these cells harbored many mitochondria at the surface of the epithelium. Organizing centers for the border symmetry system were apparent immediately after pupation, exhibiting a relatively dark optical character following treatment with fluorescent dyes, as well as in autofluorescent images. The wing tissue exhibited slow and low-frequency contraction pulses with a cycle of approximately 10 to 20 minutes, mainly occurring at 2 to 3 days postpupation. The pulses gradually became slower and weaker and eventually stopped. The wing tissue area became larger after contraction, which also coincided with an increase in the autofluorescence intensity that might have been caused by scale growth. Examination of the pattern of color development revealed that the black pigment was first deposited in patches in the central areas of an eyespot black ring and a parafocal element. These results of live in vivo imaging that covered wide wing area for a long time can serve as a foundation for studying the cellular dynamics of living wing tissues in butterflies.

Early Gray-Matter and White-Matter Concentration in Infancy Predict Later Language Skills: A Whole Brain Voxel-Based Morphometry Study

ERIC Educational Resources Information Center

Can, Dilara Deniz; Richards, Todd; Kuhl, Patricia K.

2013-01-01

Magnetic Resonance Imaging (MRI) brain scans were obtained from 19 infants at 7 months. Expressive and receptive language performance was assessed at 12 months. Voxel-based morphometry (VBM) identified brain regions where gray-matter and white-matter concentrations at 7 months correlated significantly with children's language scores at 12 months.…

Supplemental Fingerprint Card Data (SFCD) for NIST Special Database 9

National Institute of Standards and Technology Data Gateway

Supplemental Fingerprint Card Data (SFCD) for NIST Special Database 9 (Web, free access)   NIST Special Database 10 (Supplemental Fingerprint Card Data for Special Database 9 - 8-Bit Gray Scale Images) provides a larger sample of fingerprint patterns that have a low natural frequency of occurrence and transitional fingerprint classes in NIST Special Database 9. The software is the same code used with NIST Special Database 4 and 9. A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

Mexican sign language recognition using normalized moments and artificial neural networks

NASA Astrophysics Data System (ADS)

Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita

2014-09-01

This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

Color-coded duplex sonography for diagnosis of testicular torsion.

PubMed

Zoeller, G; Ringert, R H

1991-11-01

By color-coded duplex sonography moving structures are visualized as red or blue colors within a normal gray-scale B-mode ultrasound image. Thus, blood flow even within small vessels can be visualized clearly. Color-coded duplex sonographic examination was performed in 11 patients who presented with scrotal pain. This method proved to be reliable to differentiate between testicular torsion and testicular inflammation. By clearly demonstrating a lack of intratesticular blood flow in testicular torsion, while avoiding flow in scrotal skin vessels being misinterpreted as intratesticular blood flow, this method significantly decreases the number of patients in whom surgical evaluation is necessary to exclude testicular torsion.

Oregon Wildfire Captured in NASA Satellite Image

NASA Image and Video Library

2017-08-24

In early August 2017, the Cinder Butte fire burned 9 miles (15 kilometers) outside of the town of Riley, Oregon, and consumed more than 82 square miles (53,000 acres) of forest and brushland. The fire threatened tribal archaeological sites with strong significance to the Burns Paiute and Klamath tribes. Firefighters were able to contain the fire before it could damage the historic sites. On the image, the burned area is gray-brown, and cloud shadows are dark gray-to-black. The image was acquired Aug. 23, 2017, covers an area of 20 by 25 miles (31.5 by 39.9 kilometers), and is located at 43.5 degrees north, 119.9 degrees west. https://photojournal.jpl.nasa.gov/catalog/PIA21879

Correspondence Between Aberrant Intrinsic Network Connectivity and Gray-Matter Volume in the Ventral Brain of Preterm Born Adults.

PubMed

Bäuml, Josef G; Daamen, Marcel; Meng, Chun; Neitzel, Julia; Scheef, Lukas; Jaekel, Julia; Busch, Barbara; Baumann, Nicole; Bartmann, Peter; Wolke, Dieter; Boecker, Henning; Wohlschläger, Afra M; Sorg, Christian

2015-11-01

Widespread brain changes are present in preterm born infants, adolescents, and even adults. While neurobiological models of prematurity facilitate powerful explanations for the adverse effects of preterm birth on the developing brain at microscale, convincing linking principles at large-scale level to explain the widespread nature of brain changes are still missing. We investigated effects of preterm birth on the brain's large-scale intrinsic networks and their relation to brain structure in preterm born adults. In 95 preterm and 83 full-term born adults, structural and functional magnetic resonance imaging at-rest was used to analyze both voxel-based morphometry and spatial patterns of functional connectivity in ongoing blood oxygenation level-dependent activity. Differences in intrinsic functional connectivity (iFC) were found in cortical and subcortical networks. Structural differences were located in subcortical, temporal, and cingulate areas. Critically, for preterm born adults, iFC-network differences were overlapping and correlating with aberrant regional gray-matter (GM) volume specifically in subcortical and temporal areas. Overlapping changes were predicted by prematurity and in particular by neonatal medical complications. These results provide evidence that preterm birth has long-lasting effects on functional connectivity of intrinsic networks, and these changes are specifically related to structural alterations in ventral brain GM. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Tropical Timber Identification using Backpropagation Neural Network

NASA Astrophysics Data System (ADS)

Siregar, B.; Andayani, U.; Fatihah, N.; Hakim, L.; Fahmi, F.

2017-01-01

Each and every type of wood has different characteristics. Identifying the type of wood properly is important, especially for industries that need to know the type of timber specifically. However, it requires expertise in identifying the type of wood and only limited experts available. In addition, the manual identification even by experts is rather inefficient because it requires a lot of time and possibility of human errors. To overcome these problems, a digital image based method to identify the type of timber automatically is needed. In this study, backpropagation neural network is used as artificial intelligence component. Several stages were developed: a microscope image acquisition, pre-processing, feature extraction using gray level co-occurrence matrix and normalization of data extraction using decimal scaling features. The results showed that the proposed method was able to identify the timber with an accuracy of 94%.

Novel Digital Driving Method Using Dual Scan for Active Matrix Organic Light-Emitting Diode Displays

NASA Astrophysics Data System (ADS)

Jung, Myoung Hoon; Choi, Inho; Chung, Hoon-Ju; Kim, Ohyun

2008-11-01

A new digital driving method has been developed for low-temperature polycrystalline silicon, transistor-driven, active-matrix organic light-emitting diode (AM-OLED) displays by time-ratio gray-scale expression. This driving method effectively increases the emission ratio and the number of subfields by inserting another subfield set into nondisplay periods in the conventional digital driving method. By employing the proposed modified gravity center coding, this method can be used to effectively compensate for dynamic false contour noise. The operation and performance were verified by current measurement and image simulation. The simulation results using eight test images show that the proposed approach improves the average peak signal-to-noise ratio by 2.61 dB, and the emission ratio by 20.5%, compared with the conventional digital driving method.

SU-F-R-35: Repeatability of Texture Features in T1- and T2-Weighted MR Images

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

Mahon, R; Weiss, E; Karki, K

Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from themore » delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated for use in specific applications such as tissue classification and changes during radiation therapy utilizing a standard imaging protocol. Authors have the following disclosures: a research agreement with Philips Medical systems (Hugo, Weiss), a license agreement with Varian Medical Systems (Hugo, Weiss), research grants from the National Institute of Health (Hugo, Weiss), UpToDate royalties (Weiss), and none(Mahon, Ford, Karki). Authors have no potential conflicts of interest to disclose.« less

Gray level co-occurrence and random forest algorithm-based gender determination with maxillary tooth plaster images.

PubMed

Akkoç, Betül; Arslan, Ahmet; Kök, Hatice

2016-06-01

Gender is one of the intrinsic properties of identity, with performance enhancement reducing the cluster when a search is performed. Teeth have durable and resistant structure, and as such are important sources of identification in disasters (accident, fire, etc.). In this study, gender determination is accomplished by maxillary tooth plaster models of 40 people (20 males and 20 females). The images of tooth plaster models are taken with a lighting mechanism set-up. A gray level co-occurrence matrix of the image with segmentation is formed and classified via a Random Forest (RF) algorithm by extracting pertinent features of the matrix. Automatic gender determination has a 90% success rate, with an applicable system to determine gender from maxillary tooth plaster images. Copyright © 2016 Elsevier Ltd. All rights reserved.

Image segmentation by EM-based adaptive pulse coupled neural networks in brain magnetic resonance imaging.

PubMed

Fu, J C; Chen, C C; Chai, J W; Wong, S T C; Li, I C

2010-06-01

We propose an automatic hybrid image segmentation model that integrates the statistical expectation maximization (EM) model and the spatial pulse coupled neural network (PCNN) for brain magnetic resonance imaging (MRI) segmentation. In addition, an adaptive mechanism is developed to fine tune the PCNN parameters. The EM model serves two functions: evaluation of the PCNN image segmentation and adaptive adjustment of the PCNN parameters for optimal segmentation. To evaluate the performance of the adaptive EM-PCNN, we use it to segment MR brain image into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). The performance of the adaptive EM-PCNN is compared with that of the non-adaptive EM-PCNN, EM, and Bias Corrected Fuzzy C-Means (BCFCM) algorithms. The result is four sets of boundaries for the GM and the brain parenchyma (GM+WM), the two regions of most interest in medical research and clinical applications. Each set of boundaries is compared with the golden standard to evaluate the segmentation performance. The adaptive EM-PCNN significantly outperforms the non-adaptive EM-PCNN, EM, and BCFCM algorithms in gray mater segmentation. In brain parenchyma segmentation, the adaptive EM-PCNN significantly outperforms the BCFCM only. However, the adaptive EM-PCNN is better than the non-adaptive EM-PCNN and EM on average. We conclude that of the three approaches, the adaptive EM-PCNN yields the best results for gray matter and brain parenchyma segmentation. Copyright 2009 Elsevier Ltd. All rights reserved.

If it bleeds, it leads: separating threat from mere negativity

PubMed Central

Boshyan, Jasmine; Adams, Reginald B.; Mote, Jasmine; Betz, Nicole; Ward, Noreen; Hadjikhani, Nouchine; Bar, Moshe; Barrett, Lisa F.

2015-01-01

Most theories of emotion hold that negative stimuli are threatening and aversive. Yet in everyday experiences some negative sights (e.g. car wrecks) attract curiosity, whereas others repel (e.g. a weapon pointed in our face). To examine the diversity in negative stimuli, we employed four classes of visual images (Direct Threat, Indirect Threat, Merely Negative and Neutral) in a set of behavioral and functional magnetic resonance imaging studies. Participants reliably discriminated between the images, evaluating Direct Threat stimuli most quickly, and Merely Negative images most slowly. Threat images evoked greater and earlier blood oxygen level-dependent (BOLD) activations in the amygdala and periaqueductal gray, structures implicated in representing and responding to the motivational salience of stimuli. Conversely, the Merely Negative images evoked larger BOLD signal in the parahippocampal, retrosplenial, and medial prefrontal cortices, regions which have been implicated in contextual association processing. Ventrolateral as well as medial and lateral orbitofrontal cortices were activated by both threatening and Merely Negative images. In conclusion, negative visual stimuli can repel or attract scrutiny depending on their current threat potential, which is assessed by dynamic shifts in large-scale brain network activity. PMID:24493851

Ultrasound of the fingers for human identification using biometrics.

PubMed

Narayanasamy, Ganesh; Fowlkes, J Brian; Kripfgans, Oliver D; Jacobson, Jon A; De Maeseneer, Michel; Schmitt, Rainer M; Carson, Paul L

2008-03-01

It was hypothesized that the use of internal finger structure as imaged using commercially available ultrasound (US) scanners could act as a supplement to standard methods of biometric identification, as well as a means of assessing physiological and cardiovascular status. Anatomical structures in the finger including bone contour, tendon and features along the interphalangeal joint were investigated as potential biometric identifiers. Thirty-six pairs of three-dimensional (3D) gray-scale images of second to fourth finger (index, middle and ring) data taken from 20 individuals were spatially registered using MIAMI-Fuse software developed at our institution and also visually matched by four readers. The image-based registration met the criteria for matching successfully in 14 out of 15 image pairs on the same individual and did not meet criteria for matching in any of the 12 image pairs from different subjects, providing a sensitivity and specificity of 0.93 and 1.00, respectively. Visual matching of all image pairs by four readers yielded 96% successful match. Power Doppler imaging was performed to calculate the change in color pixel density due to physical exercise as a surrogate of stress level and to provide basic physiological information. (E-mail: gnarayan@umich.edu).

Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy.

PubMed

Medyukhina, Anna; Meyer, Tobias; Schmitt, Michael; Romeike, Bernd F M; Dietzek, Benjamin; Popp, Jürgen

2012-11-01

Nonlinear optical (NLO) imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or two photon excited fluorescence (TPEF) show great potential for biomedical imaging. In order to facilitate the diagnostic process based on NLO imaging, there is need for an automated calculation of quantitative values such as cell density, nucleus-to-cytoplasm ratio, average nuclear size. Extraction of these parameters is helpful for the histological assessment in general and specifically e.g. for the determination of tumor grades. This requires an accurate image segmentation and detection of locations and boundaries of cells and nuclei. Here we present an image processing approach for the detection of nuclei and cells in co-registered TPEF and CARS images. The algorithm developed utilizes the gray-scale information for the detection of the nuclei locations and the gradient information for the delineation of the nuclear and cellular boundaries. The approach reported is capable for an automated segmentation of cells and nuclei in multimodal TPEF-CARS images of human brain tumor samples. The results are important for the development of NLO microscopy into a clinically relevant diagnostic tool. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enhanced fluorescence microscope and its application

NASA Astrophysics Data System (ADS)

Wang, Susheng; Li, Qin; Yu, Xin

1997-12-01

A high gain fluorescence microscope is developed to meet the needs in medical and biological research. By the help of an image intensifier with luminance gain of 4 by 104 the sensitivity of the system can achieve 10-6 1x level and be 104 times higher than ordinary fluorescence microscope. Ultra-weak fluorescence image can be detected by it. The concentration of fluorescent label and emitting light intensity of the system are decreased as much as possible, therefore, the natural environment of the detected call can be kept. The CCD image acquisition set-up controlled by computer obtains the quantitative data of each point according to the gray scale. The relation between luminous intensity and output of CCD is obtained by using a wide range weak photometry. So the system not only shows the image of ultra-weak fluorescence distribution but also gives the intensity of fluorescence of each point. Using this system, we obtained the images of distribution of hypocrellin A (HA) in Hela cell, the images of Hela cell being protected by antioxidant reagent Vit. E, SF and BHT. The images show that the digitized ultra-sensitive fluorescence microscope is a useful tool for medical and biological research.

Time-efficient high-resolution whole-brain three-dimensional macromolecular proton fraction mapping

PubMed Central

Yarnykh, Vasily L.

2015-01-01

Purpose Macromolecular proton fraction (MPF) mapping is a quantitative MRI method that reconstructs parametric maps of a relative amount of macromolecular protons causing the magnetization transfer (MT) effect and provides a biomarker of myelination in neural tissues. This study aimed to develop a high-resolution whole-brain MPF mapping technique utilizing a minimal possible number of source images for scan time reduction. Methods The described technique is based on replacement of an actually acquired reference image without MT saturation by a synthetic one reconstructed from R1 and proton density maps, thus requiring only three source images. This approach enabled whole-brain three-dimensional MPF mapping with isotropic 1.25×1.25×1.25 mm3 voxel size and scan time of 20 minutes. The synthetic reference method was validated against standard MPF mapping with acquired reference images based on data from 8 healthy subjects. Results Mean MPF values in segmented white and gray matter appeared in close agreement with no significant bias and small within-subject coefficients of variation (<2%). High-resolution MPF maps demonstrated sharp white-gray matter contrast and clear visualization of anatomical details including gray matter structures with high iron content. Conclusions Synthetic reference method improves resolution of MPF mapping and combines accurate MPF measurements with unique neuroanatomical contrast features. PMID:26102097

Classification of CT examinations for COPD visual severity analysis

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Pu, Jiantao; Gur, David; Sciurba, Frank C.; Leader, J. Ken

2012-03-01

In this study we present a computational method of CT examination classification into visual assessed emphysema severity. The visual severity categories ranged from 0 to 5 and were rated by an experienced radiologist. The six categories were none, trace, mild, moderate, severe and very severe. Lung segmentation was performed for every input image and all image features are extracted from the segmented lung only. We adopted a two-level feature representation method for the classification. Five gray level distribution statistics, six gray level co-occurrence matrix (GLCM), and eleven gray level run-length (GLRL) features were computed for each CT image depicted segment lung. Then we used wavelets decomposition to obtain the low- and high-frequency components of the input image, and again extract from the lung region six GLCM features and eleven GLRL features. Therefore our feature vector length is 56. The CT examinations were classified using the support vector machine (SVM) and k-nearest neighbors (KNN) and the traditional threshold (density mask) approach. The SVM classifier had the highest classification performance of all the methods with an overall sensitivity of 54.4% and a 69.6% sensitivity to discriminate "no" and "trace visually assessed emphysema. We believe this work may lead to an automated, objective method to categorically classify emphysema severity on CT exam.

Characterization of Nanoporous as a Medium for Size-Selective Filtration, Preconcentration, and Detection of Biomolecules

DTIC Science & Technology

2016-07-04

dimensional patterning and morphological control of porous nanomaterials by gray -scale direct imprinting, Scientific Reports, (03 2013): 1502. doi: 10.1038...detection with the exception that a different DNA apatamer sequence was required:  5’-GAT CGG GTG TGG GTG GCG TAA AGG GAG CAT CGG ACA-3’. Figure 6b shows...nanomaterials by gray -scale direct imprinting," Sci Rep 3, 1502 (2013). 8J. D. Ryckman, M. Liscidini, J. E. Sipe, S. M. Weiss, "Porous silicon structures

Computerized Classification of Pneumoconiosis on Digital Chest Radiography Artificial Neural Network with Three Stages.

PubMed

Okumura, Eiichiro; Kawashita, Ikuo; Ishida, Takayuki

2017-08-01

It is difficult for radiologists to classify pneumoconiosis from category 0 to category 3 on chest radiographs. Therefore, we have developed a computer-aided diagnosis (CAD) system based on a three-stage artificial neural network (ANN) method for classification based on four texture features. The image database consists of 36 chest radiographs classified as category 0 to category 3. Regions of interest (ROIs) with a matrix size of 32 × 32 were selected from chest radiographs. We obtained a gray-level histogram, histogram of gray-level difference, gray-level run-length matrix (GLRLM) feature image, and gray-level co-occurrence matrix (GLCOM) feature image in each ROI. For ROI-based classification, the first ANN was trained with each texture feature. Next, the second ANN was trained with output patterns obtained from the first ANN. Finally, we obtained a case-based classification for distinguishing among four categories with the third ANN method. We determined the performance of the third ANN by receiver operating characteristic (ROC) analysis. The areas under the ROC curve (AUC) of the highest category (severe pneumoconiosis) case and the lowest category (early pneumoconiosis) case were 0.89 ± 0.09 and 0.84 ± 0.12, respectively. The three-stage ANN with four texture features showed the highest performance for classification among the four categories. Our CAD system would be useful for assisting radiologists in classification of pneumoconiosis from category 0 to category 3.

Differential regional gray matter volumes in patients with on-line game addiction and professional gamers

PubMed Central

Han, Doug Hyun; Lyoo, In Kyoon; Renshaw, Perry F.

2015-01-01

Patients with on-line game addiction (POGA) and professional video game players play video games for extended periods of time, but experience very different consequences for their on-line game play. Brain regions consisting of anterior cingulate, thalamus and occpito-temporal areas may increase the likelihood of becoming a pro-gamer or POGA. Twenty POGA, seventeen pro-gamers, and eighteen healthy comparison subjects (HC) were recruited. All magnetic resonance imaging (MRI) was performed on a 1.5 Tesla Espree MRI scanner (SIEMENS, Erlangen, Germany). Voxel-wise comparisons of gray matter volume were performed between the groups using the two-sample t-test with statistical parametric mapping (SPM5). Compared to HC, the POGA group showed increased impulsiveness and perseverative errors, and volume in left thalamus gray matter, but decreased gray matter volume in both inferior temporal gyri, right middle occipital gyrus, and left inferior occipital gyrus, compared with HC. Pro-gamers showed increased gray matter volume in left cingulate gyrus, but decreased gray matter volume in left middle occipital gyrus and right inferior temporal gyrus compared with HC. Additionally, the pro-gamer group showed increased gray matter volume in left cingulate gyrus and decreased left thalamus gray matter volume compared with the POGA group. The current study suggests that increased gray matter volumes of the left cingulate gyrus in pro-gamers and of the left thalamus in POGA may contribute to the different clinical characteristics of pro-gamers and POGA. PMID:22277302

Gray whale distribution relative to benthic invertebrate biomass and abundance: Northeastern Chukchi Sea 2009-2012

NASA Astrophysics Data System (ADS)

Brower, Amelia A.; Ferguson, Megan C.; Schonberg, Susan V.; Jewett, Stephen C.; Clarke, Janet T.

2017-10-01

The shallow continental shelf waters of the Bering and Chukchi seas are the northernmost foraging grounds of North Pacific gray whales (Eschrichtius robustus). Benthic amphipods are considered the primary prey of gray whales in these waters, although no comprehensive quantitative analysis has been performed to support this assumption. Gray whale relative abundance, distribution, and behavior in the northeastern Chukchi Sea (69°-72°N, 155-169°W) were documented during aerial surveys in June-October 2009-2012. Concurrently, vessel-based benthic infaunal sampling was conducted in the area in July-August 2009-10, September 2011, and August 2012. Gray whales were seen in the study area each month that surveys were conducted, with the majority of whales feeding. Statistical analyses confirm that the highest densities of feeding gray whales were associated with high benthic amphipod abundance, primarily within 70 km of shore from Point Barrow to Icy Cape, in water <50 m deep. Conversely, gray whales were not seen in 40-km×40-km cells containing benthic sampling stations with 85 m-2 or fewer amphipods. Continuing broad-scale aerial surveys in the Chukchi Sea and prey sampling near feeding gray whales will be an important means to monitor and document ongoing and predicted ecosystem changes.

High-performance floating-point image computing workstation for medical applications

NASA Astrophysics Data System (ADS)

Mills, Karl S.; Wong, Gilman K.; Kim, Yongmin

1990-07-01

The medical imaging field relies increasingly on imaging and graphics techniques in diverse applications with needs similar to (or more stringent than) those of the military, industrial and scientific communities. However, most image processing and graphics systems available for use in medical imaging today are either expensive, specialized, or in most cases both. High performance imaging and graphics workstations which can provide real-time results for a number of applications, while maintaining affordability and flexibility, can facilitate the application of digital image computing techniques in many different areas. This paper describes the hardware and software architecture of a medium-cost floating-point image processing and display subsystem for the NeXT computer, and its applications as a medical imaging workstation. Medical imaging applications of the workstation include use in a Picture Archiving and Communications System (PACS), in multimodal image processing and 3-D graphics workstation for a broad range of imaging modalities, and as an electronic alternator utilizing its multiple monitor display capability and large and fast frame buffer. The subsystem provides a 2048 x 2048 x 32-bit frame buffer (16 Mbytes of image storage) and supports both 8-bit gray scale and 32-bit true color images. When used to display 8-bit gray scale images, up to four different 256-color palettes may be used for each of four 2K x 2K x 8-bit image frames. Three of these image frames can be used simultaneously to provide pixel selectable region of interest display. A 1280 x 1024 pixel screen with 1: 1 aspect ratio can be windowed into the frame buffer for display of any portion of the processed image or images. In addition, the system provides hardware support for integer zoom and an 82-color cursor. This subsystem is implemented on an add-in board occupying a single slot in the NeXT computer. Up to three boards may be added to the NeXT for multiple display capability (e.g., three 1280 x 1024 monitors, each with a 16-Mbyte frame buffer). Each add-in board provides an expansion connector to which an optional image computing coprocessor board may be added. Each coprocessor board supports up to four processors for a peak performance of 160 MFLOPS. The coprocessors can execute programs from external high-speed microcode memory as well as built-in internal microcode routines. The internal microcode routines provide support for 2-D and 3-D graphics operations, matrix and vector arithmetic, and image processing in integer, IEEE single-precision floating point, or IEEE double-precision floating point. In addition to providing a library of C functions which links the NeXT computer to the add-in board and supports its various operational modes, algorithms and medical imaging application programs are being developed and implemented for image display and enhancement. As an extension to the built-in algorithms of the coprocessors, 2-D Fast Fourier Transform (FF1), 2-D Inverse FFF, convolution, warping and other algorithms (e.g., Discrete Cosine Transform) which exploit the parallel architecture of the coprocessor board are being implemented.

Structural neurobiological correlates of Mayer-Salovery-Caruso Emotional Intelligence Test performance in early course schizophrenia.

PubMed

Wojtalik, Jessica A; Eack, Shaun M; Keshavan, Matcheri S

2013-01-10

The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) is a key measure of social cognition in schizophrenia that has good psychometric properties and is recommended by the MATRICS committee. As a way to further investigate the validity of the MSCEIT, this study sought to examine the neurobiological correlates of MSCEIT performance in patients with early course schizophrenia. A total of 51 patients diagnosed with early course, stabilized schizophrenia or schizoaffective disorder completed structural magnetic resonance imaging (MRI) scans and the MSCEIT. Investigation of the associations between MSCEIT performance and gray matter morphology was examined by conducting voxel-based morphometry (VBM) analyses across hypothesized social-cognitive regions of interest using automated anatomical labeling in Statistical Parametric Mapping Software, version 5 (SPM5). All VBM analyses utilized general linear models examining gray matter density partitioned images, adjusting for demographic and illness-related confounds. VBM results were then followed up with confirmatory volumetric analyses. Patients with poorer overall and Facilitating, Understanding, and Managing Emotions subscale performances on the MSCEIT showed significantly reduced gray matter density in the left parahippocampal gyrus. Additionally, attenuated performance on the Facilitating and Managing Emotions subscales was significantly associated with reduced right posterior cingulate gray matter density. All associations observed between MSCEIT performance and gray matter density were supported with confirmatory gray matter volumetric analyses, with the exception of the association between the right posterior cingulate and the facilitation of emotions. These findings provide additional evidence for the MSCEIT as a valid social-cognitive measure by elucidating its correlates with neurobiological structures commonly implicated in emotion processing. These findings provide additional biological evidence supporting the use of the MSCEIT in cognitive enhancing clinical trials in schizophrenia. Copyright © 2012 Elsevier Inc. All rights reserved.

Signal enhancement in optical projection tomography via virtual high dynamic range imaging of single exposure

NASA Astrophysics Data System (ADS)

Yang, Yujie; Dong, Di; Shi, Liangliang; Wang, Jun; Yang, Xin; Tian, Jie

2015-03-01

Optical projection tomography (OPT) is a mesoscopic scale optical imaging technique for specimens between 1mm and 10mm. OPT has been proven to be immensely useful in a wide variety of biological applications, such as developmental biology and pathology, but its shortcomings in imaging specimens containing widely differing contrast elements are obvious. The longer exposure for high intensity tissues may lead to over saturation of other areas, whereas a relatively short exposure may cause similarity with surrounding background. In this paper, we propose an approach to make a trade-off between capturing weak signals and revealing more details for OPT imaging. This approach consists of three steps. Firstly, the specimens are merely scanned in 360 degrees above a normal exposure but non-overexposure to acquire the projection data. This reduces the photo bleaching and pre-registration computation compared with multiple different exposures in conventional high dynamic range (HDR) imaging method. Secondly, three virtual channels are produced for each projection image based on the histogram distribution to simulate the low, normal and high exposure images used in the traditional HDR technology in photography. Finally, each virtual channel is normalized to the full gray scale range and three channels are recombined into one image using weighting coefficients optimized by a standard eigen-decomposition method. After applying our approach on the projection data, filtered back projection (FBP) algorithm is carried out for 3-dimentional reconstruction. The neonatal wild-type mouse paw has been scanned to verify this approach. Results demonstrated the effectiveness of the proposed approach.

Application of RNAMlet to surface defect identification of steels

NASA Astrophysics Data System (ADS)

Xu, Ke; Xu, Yang; Zhou, Peng; Wang, Lei

2018-06-01

As three main production lines of steels, continuous casting slabs, hot rolled steel plates and cold rolled steel strips have different surface appearances and are produced at different speeds of their production lines. Therefore, the algorithms for the surface defect identifications of the three steel products have different requirements for real-time and anti-interference. The existing algorithms cannot be adaptively applied to surface defect identification of the three steel products. A new method of adaptive multi-scale geometric analysis named RNAMlet was proposed. The idea of RNAMlet came from the non-symmetry anti-packing pattern representation model (NAM). The image is decomposed into a set of rectangular blocks asymmetrically according to gray value changes of image pixels. Then two-dimensional Haar wavelet transform is applied to all blocks. If the image background is complex, the number of blocks is large, and more details of the image are utilized. If the image background is simple, the number of blocks is small, and less computation time is needed. RNAMlet was tested with image samples of the three steel products, and compared with three classical methods of multi-scale geometric analysis, including Contourlet, Shearlet and Tetrolet. For the image samples with complicated backgrounds, such as continuous casting slabs and hot rolled steel plates, the defect identification rate obtained by RNAMlet was 1% higher than other three methods. For the image samples with simple backgrounds, such as cold rolled steel strips, the computation time of RNAMlet was one-tenth of the other three MGA methods, while the defect identification rates obtained by RNAMlet were higher than the other three methods.

In Vivo Evidence of Reduced Integrity of the Gray-White Matter Boundary in Autism Spectrum Disorder.

PubMed

Andrews, Derek Sayre; Avino, Thomas A; Gudbrandsen, Maria; Daly, Eileen; Marquand, Andre; Murphy, Clodagh M; Lai, Meng-Chuan; Lombardo, Michael V; Ruigrok, Amber N V; Williams, Steven C; Bullmore, Edward T; The Mrc Aims Consortium; Suckling, John; Baron-Cohen, Simon; Craig, Michael C; Murphy, Declan G M; Ecker, Christine

2017-02-01

Atypical cortical organization and reduced integrity of the gray-white matter boundary have been reported by postmortem studies in individuals with autism spectrum disorder (ASD). However, there are no in vivo studies that examine these particular features of cortical organization in ASD. Hence, we used structural magnetic resonance imaging to examine differences in tissue contrast between gray and white matter in 98 adults with ASD and 98 typically developing controls, to test the hypothesis that individuals with ASD have significantly reduced tissue contrast. More specifically, we examined contrast as a percentage between gray and white matter tissue signal intensities (GWPC) sampled at the gray-white matter boundary, and across different cortical layers. We found that individuals with ASD had significantly reduced GWPC in several clusters throughout the cortex (cluster, P < 0.05). As expected, these reductions were greatest when tissue intensities were sampled close to gray-white matter interface, which indicates a less distinct gray-white matter boundary in ASD. Our in vivo findings of reduced GWPC in ASD are therefore consistent with prior postmortem findings of a less well-defined gray-white matter boundary in ASD. Taken together, these results indicate that GWPC might be utilized as an in vivo proxy measure of atypical cortical microstructural organization in future studies. © The Author 2017. Published by Oxford University Press.

Image-Data Compression Using Edge-Optimizing Algorithm for WFA Inference.

ERIC Educational Resources Information Center

Culik, Karel II; Kari, Jarkko

1994-01-01

Presents an inference algorithm that produces a weighted finite automata (WFA), in particular, the grayness functions of graytone images. Image-data compression results based on the new inference algorithm produces a WFA with a relatively small number of edges. Image-data compression results alone and in combination with wavelets are discussed.…

Auditory Short-Term Memory Capacity Correlates with Gray Matter Density in the Left Posterior STS in Cognitively Normal and Dyslexic Adults

ERIC Educational Resources Information Center

Richardson, Fiona M.; Ramsden, Sue; Ellis, Caroline; Burnett, Stephanie; Megnin, Odette; Catmur, Caroline; Schofield, Tom M.; Leff, Alex P.; Price, Cathy J.

2011-01-01

A central feature of auditory STM is its item-limited processing capacity. We investigated whether auditory STM capacity correlated with regional gray and white matter in the structural MRI images from 74 healthy adults, 40 of whom had a prior diagnosis of developmental dyslexia whereas 34 had no history of any cognitive impairment. Using…

Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures.

PubMed

Lim, Issel Anne L; Faria, Andreia V; Li, Xu; Hsu, Johnny T C; Airan, Raag D; Mori, Susumu; van Zijl, Peter C M

2013-11-15

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a "deep gray matter parcellation map" (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established "white matter parcellation map" (WMPM) from the same subject's T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the "Everything Parcellation Map in Eve Space," also known as the "EvePM." It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting "almost perfect" agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray matter structures measured by Hallgren and Sourander (1958) allowed interpolation of the average iron concentration of several deep gray matter regions delineated in the EvePM. Copyright © 2013 Elsevier Inc. All rights reserved.

Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures

PubMed Central

Lim, Issel Anne L.; Faria, Andreia V.; Li, Xu; Hsu, Johnny T.C.; Airan, Raag D.; Mori, Susumu; van Zijl, Peter C. M.

2013-01-01

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a “deep gray matter parcellation map” (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established “white matter parcellation map” (WMPM) from the same subject’s T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the “Everything Parcellation Map in Eve Space,” also known as the “EvePM.” It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting “almost perfect” agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray matter structures measured by Hallgren and Sourander (1958) allowed interpolation of the average iron concentration of several deep gray matter regions delineated in the EvePM. PMID:23769915

Clinical and imaging correlates of amyloid deposition in dementia with Lewy bodies.

PubMed

Donaghy, Paul C; Firbank, Michael J; Thomas, Alan J; Lloyd, Jim; Petrides, George; Barnett, Nicola; Olsen, Kirsty; O'Brien, John T

2018-04-19

Amyloid deposition is common in dementia with Lewy bodies, but its pathophysiological significance is unclear. The objective of this study was to investigate the relationship between amyloid deposition and clinical profile, gray matter volume, and brain perfusion in dementia with Lewy bodies. Dementia with Lewy bodies (n = 37), Alzheimer's disease (n = 20), and controls (n = 20) underwent a thorough clinical assessment, 3T MRI, and early- and late-phase 18 F-Florbetapir PET-CT to assess cortical perfusion and amyloid deposition, respectively. Amyloid scans were visually categorized as positive or negative. Image analysis was carried out using statistical parametric mapping (SPM) 8. There were no significant differences between amyloid-positive and amyloid-negative dementia with Lewy bodies cases in age (P = .78), overall cognitive impairment (P = .83), level of functional impairment (P = .80), or any other clinical or cognitive scale. There were also no significant differences in hippocampal or gray matter volumes. However, amyloid-positive dementia with Lewy bodies cases had lower medial temporal lobe perfusion (P = .03) than amyloid-negative cases, although a combination of medial temporal lobe perfusion, hippocampal volume, and cognitive measures was unable to accurately predict amyloid status in dementia with Lewy bodies. Amyloid deposition was not associated with differences in clinical or neuropsychological profiles in dementia with Lewy bodies, but was associated with imaging evidence of medial temporal lobe dysfunction. The presence of amyloid in dementia with Lewy bodies cannot be identified on the basis of clinical and other imaging features and will require direct assessment via PET imaging or CSF. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Gray matter alterations in chronic pain: A network-oriented meta-analytic approach

PubMed Central

Cauda, Franco; Palermo, Sara; Costa, Tommaso; Torta, Riccardo; Duca, Sergio; Vercelli, Ugo; Geminiani, Giuliano; Torta, Diana M.E.

2014-01-01

Several studies have attempted to characterize morphological brain changes due to chronic pain. Although it has repeatedly been suggested that longstanding pain induces gray matter modifications, there is still some controversy surrounding the direction of the change (increase or decrease in gray matter) and the role of psychological and psychiatric comorbidities. In this study, we propose a novel, network-oriented, meta-analytic approach to characterize morphological changes in chronic pain. We used network decomposition to investigate whether different kinds of chronic pain are associated with a common or specific set of altered networks. Representational similarity techniques, network decomposition and model-based clustering were employed: i) to verify the presence of a core set of brain areas commonly modified by chronic pain; ii) to investigate the involvement of these areas in a large-scale network perspective; iii) to study the relationship between altered networks and; iv) to find out whether chronic pain targets clusters of areas. Our results showed that chronic pain causes both core and pathology-specific gray matter alterations in large-scale networks. Common alterations were observed in the prefrontal regions, in the anterior insula, cingulate cortex, basal ganglia, thalamus, periaqueductal gray, post- and pre-central gyri and inferior parietal lobule. We observed that the salience and attentional networks were targeted in a very similar way by different chronic pain pathologies. Conversely, alterations in the sensorimotor and attention circuits were differentially targeted by chronic pain pathologies. Moreover, model-based clustering revealed that chronic pain, in line with some neurodegenerative diseases, selectively targets some large-scale brain networks. Altogether these findings indicate that chronic pain can be better conceived and studied in a network perspective. PMID:24936419

Aging in deep gray matter and white matter revealed by diffusional kurtosis imaging.

PubMed

Gong, Nan-Jie; Wong, Chun-Sing; Chan, Chun-Chung; Leung, Lam-Ming; Chu, Yiu-Ching

2014-10-01

Diffusion tensor imaging has already been extensively used to probe microstructural alterations in white matter tracts, and scarcely, in deep gray matter. However, results in literature regarding age-related degenerative mechanisms in white matter tracts and parametric changes in the putamen are inconsistent. Diffusional kurtosis imaging is a mathematical extension of diffusion tensor imaging, which could more comprehensively mirror microstructure, particularly in isotropic tissues such as gray matter. In this study, we used the diffusional kurtosis imaging method and a white-matter model that provided metrics of explicit neurobiological interpretations in healthy participants (58 in total, aged from 25 to 84 years). Tract-based whole-brain analyses and regions-of-interest (anterior and posterior limbs of the internal capsule, cerebral peduncle, fornix, genu and splenium of corpus callosum, globus pallidus, substantia nigra, red nucleus, putamen, caudate nucleus, and thalamus) analyses were performed to examine parametric differences across regions and correlations with age. In white matter tracts, evidence was found supportive for anterior-posterior gradient and not completely supportive for retrogenesis theory. Age-related degenerations appeared to be broadly driven by axonal loss. Demyelination may also be a major driving mechanism, although confined to the anterior brain. In terms of deep gray matter, higher mean kurtosis and fractional anisotropy in the globus pallidus, substantia nigra, and red nucleus reflected higher microstructural complexity and directionality compared with the putamen, caudate nucleus, and thalamus. In particular, the unique age-related positive correlations for fractional anisotropy, mean kurtosis, and radial kurtosis in the putamen opposite to those in other regions call for further investigation of exact underlying mechanisms. In summary, the results suggested that diffusional kurtosis can provide measurements in a new dimension that were complementary to diffusivity metrics. Kurtosis together with diffusivity can more comprehensively characterize microstructural compositions and age-related changes than diffusivity alone. Combined with proper model, it may also assist in providing neurobiological interpretations of the identified alterations. Copyright © 2014 Elsevier Inc. All rights reserved.

Earth Observations taken by the Expedition 10 crew

NASA Image and Video Library

2005-01-14

ISS010-E-13088 (15 January 2005) --- Tsunami damage, northwestern Sumatra (Indonesia) is featured in this image photographed by an Expedition 10 crewmember on the International Space Station. On December 26, 2004 a large (magnitude 9.0) earthquake occurred off the western coast of Sumatra in the Indian Ocean. Scientists believe the earthquake was caused by the release of stresses accumulated as the India tectonic plate is overridden by the Burma tectonic plate. Movement of the seafloor due to the earthquake generated a tsunami, or seismic sea wave, that affected coastal regions around the Indian Ocean. The northwestern Sumatra coastline in particular suffered extensive damage and loss of life. This photo, along with image ISS010-E-13079, illustrates damage along the southwestern coast of Aceh Province in the vicinity of the city of Lho’ Kruet, Indonesia. The image captures the sunglint illuminating the Indian Ocean and standing water inland (light gray). Distortion and scale differences are caused by increased obliquity of the view from the Station.

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

PubMed

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

SU-F-R-36: Validating Quantitative Radiomic Texture Features for Oncologic PET: A Digital Phantom Study

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

Yang, F; Yang, Y; Young, L

Purpose: Radiomic texture features derived from the oncologic PET have recently been brought under intense investigation within the context of patient stratification and treatment outcome prediction in a variety of cancer types; however, their validity has not yet been examined. This work is aimed to validate radiomic PET texture metrics through the use of realistic simulations in the ground truth setting. Methods: Simulation of FDG-PET was conducted by applying the Zubal phantom as an attenuation map to the SimSET software package that employs Monte Carlo techniques to model the physical process of emission imaging. A total of 15 irregularly-shaped lesionsmore » featuring heterogeneous activity distribution were simulated. For each simulated lesion, 28 texture features in relation to the intensity histograms (GLIH), grey-level co-occurrence matrices (GLCOM), neighborhood difference matrices (GLNDM), and zone size matrices (GLZSM) were evaluated and compared with their respective values extracted from the ground truth activity map. Results: In reference to the values from the ground truth images, texture parameters appearing on the simulated data varied with a range of 0.73–3026.2% for GLIH-based, 0.02–100.1% for GLCOM-based, 1.11–173.8% for GLNDM-based, and 0.35–66.3% for GLZSM-based. For majority of the examined texture metrics (16/28), their values on the simulated data differed significantly from those from the ground truth images (P-value ranges from <0.0001 to 0.04). Features not exhibiting significant difference comprised of GLIH-based standard deviation, GLCO-based energy and entropy, GLND-based coarseness and contrast, and GLZS-based low gray-level zone emphasis, high gray-level zone emphasis, short zone low gray-level emphasis, long zone low gray-level emphasis, long zone high gray-level emphasis, and zone size nonuniformity. Conclusion: The extent to which PET imaging disturbs texture appearance is feature-dependent and could be substantial. It is thus advised that use of PET texture parameters for predictive and prognostic measurements in oncologic setting awaits further systematic and critical evaluation.« less

Comparison of lossless compression techniques for prepress color images

NASA Astrophysics Data System (ADS)

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

1998-12-01

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

Rough-Fuzzy Clustering and Unsupervised Feature Selection for Wavelet Based MR Image Segmentation

PubMed Central

Maji, Pradipta; Roy, Shaswati

2015-01-01

Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices. PMID:25848961

Iran-Iraq Border Quake Region Imaged by NASA Satellite

NASA Image and Video Library

2017-11-15

On Sunday, Nov. 12, 2017, a magnitude 7.3 earthquake struck along the Iran-Iraq border near Halabjah, Iraq. The earthquake was felt as far away as Kuwait, Qatar, Turkey, Lebanon and Israel. Extensive damage and numerous casualties were reported in the area near the epicenter (yellow star on image). The earthquake occurred along the boundary between the Arabian and Eurasian tectonic plates. This is an earthquake-prone area, and has experienced many deadly earthquakes in the past. In this perspective-view image, bright red areas are crops in fields, pale red on mountain ridges are shrubs and trees, dark gray areas are traces of earlier brush fires, and gray and tan colors are different rock types. The image was acquired Sept. 8, 2017, and the star marks the earthquake epicenter at 34.9 degrees north, 45.9 degrees east. https://photojournal.jpl.nasa.gov/catalog/PIA22112

Detailed Magnetic Resonance Imaging (MRI) Analysis in Infantile Spasms.

PubMed

Harini, Chellamani; Sharda, Sonal; Bergin, Ann Marie; Poduri, Annapurna; Yuskaitis, Christopher J; Peters, Jurriaan M; Rakesh, Kshitiz; Kapur, Kush; Pearl, Phillip L; Prabhu, Sanjay P

2018-05-01

To evaluate initial magnetic resonance imaging (MRI) abnormalities in infantile spasms, correlate them to clinical characteristics, and describe repeat imaging findings. A retrospective review of infantile spasm patients was conducted, classifying abnormal MRI into developmental, acquired, and nonspecific subgroups. MRIs were abnormal in 52 of 71 infantile spasm patients (23 developmental, 23 acquired, and 6 nonspecific) with no correlation to the clinical infantile spasm characteristics. Both developmental and acquired subgroups exhibited cortical gray and/or white matter abnormalities. Additional abnormalities of deep gray structures, brain stem, callosum, and volume loss occurred in the structural acquired subgroup. Repeat MRI showed better definition of the extent of existing malformations. In structural infantile spasms, developmental/acquired subgroups showed differences in pattern of MRI abnormalities but did not correlate with clinical characteristics.

Spring in Inca City IV

NASA Image and Video Library

2014-11-13

At certain times in spring, fans take on a gray or blue appearance. This is the time in Inca City when this phenomenon happens, as seen in this image acquired by NASA Mars Reconnaissance Orbiter. On the ridge at the top of the image fans have lengthened and now look more gray than the blotches on the araneiforms. At the bottom of the image they are distinctly blue in color. Two theories have been suggested: perhaps fine particles sink into the seasonal layer of ice so they no longer appear dark. Or, maybe the gas that is released from under the ice condenses and falls to the surface as a bright fresh layer of frost. It is quite likely that both of these theories are correct. http://photojournal.jpl.nasa.gov/catalog/PIA18895

A method of camera calibration with adaptive thresholding

NASA Astrophysics Data System (ADS)

Gao, Lei; Yan, Shu-hua; Wang, Guo-chao; Zhou, Chun-lei

2009-07-01

In order to calculate the parameters of the camera correctly, we must figure out the accurate coordinates of the certain points in the image plane. Corners are the important features in the 2D images. Generally speaking, they are the points that have high curvature and lie in the junction of different brightness regions of images. So corners detection has already widely used in many fields. In this paper we use the pinhole camera model and SUSAN corner detection algorithm to calibrate the camera. When using the SUSAN corner detection algorithm, we propose an approach to retrieve the gray difference threshold, adaptively. That makes it possible to pick up the right chessboard inner comers in all kinds of gray contrast. The experiment result based on this method was proved to be feasible.

Method for simulating dose reduction in digital mammography using the Anscombe transformation

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

Borges, Lucas R., E-mail: lucas.rodrigues.borges@usp.br; Oliveira, Helder C. R. de; Nunes, Polyana F.

2016-06-15

Purpose: This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose. Methods: The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the detective quantum efficiency. The scaling process takes into account the linearity of the system and the offset of the detector elements. The inserted noise is obtainedmore » by acquiring images of a flat-field phantom at the standard radiation dose and at the simulated dose. Using the Anscombe transformation, a relationship is created between the calculated noise mask and the scaled image, resulting in a clinical mammogram with the same noise and gray level characteristics as an image acquired at the lower-radiation dose. Results: The performance of the proposed algorithm was validated using real images acquired with an anthropomorphic breast phantom at four different doses, with five exposures for each dose and 256 nonoverlapping ROIs extracted from each image and with uniform images. The authors simulated lower-dose images and compared these with the real images. The authors evaluated the similarity between the normalized noise power spectrum (NNPS) and power spectrum (PS) of simulated images and real images acquired with the same dose. The maximum relative error was less than 2.5% for every ROI. The added noise was also evaluated by measuring the local variance in the real and simulated images. The relative average error for the local variance was smaller than 1%. Conclusions: A new method is proposed for simulating dose reduction in clinical mammograms. In this method, the dependency between image noise and image signal is addressed using a novel application of the Anscombe transformation. NNPS, PS, and local noise metrics confirm that this method is capable of precisely simulating various dose reductions.« less

Method for simulating dose reduction in digital mammography using the Anscombe transformation

PubMed Central

Borges, Lucas R.; de Oliveira, Helder C. R.; Nunes, Polyana F.; Bakic, Predrag R.; Maidment, Andrew D. A.; Vieira, Marcelo A. C.

2016-01-01

Purpose: This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose. Methods: The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the detective quantum efficiency. The scaling process takes into account the linearity of the system and the offset of the detector elements. The inserted noise is obtained by acquiring images of a flat-field phantom at the standard radiation dose and at the simulated dose. Using the Anscombe transformation, a relationship is created between the calculated noise mask and the scaled image, resulting in a clinical mammogram with the same noise and gray level characteristics as an image acquired at the lower-radiation dose. Results: The performance of the proposed algorithm was validated using real images acquired with an anthropomorphic breast phantom at four different doses, with five exposures for each dose and 256 nonoverlapping ROIs extracted from each image and with uniform images. The authors simulated lower-dose images and compared these with the real images. The authors evaluated the similarity between the normalized noise power spectrum (NNPS) and power spectrum (PS) of simulated images and real images acquired with the same dose. The maximum relative error was less than 2.5% for every ROI. The added noise was also evaluated by measuring the local variance in the real and simulated images. The relative average error for the local variance was smaller than 1%. Conclusions: A new method is proposed for simulating dose reduction in clinical mammograms. In this method, the dependency between image noise and image signal is addressed using a novel application of the Anscombe transformation. NNPS, PS, and local noise metrics confirm that this method is capable of precisely simulating various dose reductions. PMID:27277017

Early visual cortical structural changes in diabetic patients without diabetic retinopathy.

PubMed

Ferreira, Fábio S; Pereira, João M S; Reis, Aldina; Sanches, Mafalda; Duarte, João V; Gomes, Leonor; Moreno, Carolina; Castelo-Branco, Miguel

2017-11-01

It is known that diabetic patients have changes in cortical morphometry as compared to controls, but it remains to be clarified whether the visual cortex is a disease target, even when diabetes complications such as retinopathy are absent. Therefore, we compared type 2 diabetes patients without diabetic retinopathy with control subjects using magnetic resonance imaging to assess visual cortical changes when retinal damage is not yet present. We performed T1-weighted imaging in 24 type 2 diabetes patients without diabetic retinopathy and 27 age- and gender-matched controls to compare gray matter changes in the occipital cortex between groups using voxel based morphometry. Patients without diabetic retinopathy showed reduced gray matter volume in the occipital lobe when compared with controls. Reduced gray matter volume in the occipital cortex was found in diabetic patients without retinal damage. We conclude that cortical early visual processing regions may be affected in diabetic patients even before retinal damage occurs.

Brain volume change and cognitive trajectories in aging.

PubMed

Fletcher, Evan; Gavett, Brandon; Harvey, Danielle; Farias, Sarah Tomaszewski; Olichney, John; Beckett, Laurel; DeCarli, Charles; Mungas, Dan

2018-05-01

Examine how longitudinal cognitive trajectories relate to brain baseline measures and change in lobar volumes in a racially/ethnically and cognitively diverse sample of older adults. Participants were 460 older adults enrolled in a longitudinal aging study. Cognitive outcomes were measures of episodic memory, semantic memory, executive function, and spatial ability derived from the Spanish and English Neuropsychological Assessment Scales (SENAS). Latent variable multilevel modeling of the four cognitive outcomes as parallel longitudinal processes identified intercepts for each outcome and a second order global change factor explaining covariance among the highly correlated slopes. We examined how baseline brain volumes (lobar gray matter, hippocampus, and white matter hyperintensity) and change in brain volumes (lobar gray matter) were associated with cognitive intercepts and global cognitive change. Lobar volumes were dissociated into global and specific components using latent variable methods. Cognitive change was most strongly associated with brain gray matter volume change, with strong independent effects of global gray matter change and specific temporal lobe gray matter change. Baseline white matter hyperintensity and hippocampal volumes had significant incremental effects on cognitive decline beyond gray matter change. Baseline lobar gray matter was related to cognitive decline, but did not contribute beyond gray matter change. Cognitive decline was strongly influenced by gray matter volume change and, especially, temporal lobe change. The strong influence of temporal lobe gray matter change on cognitive decline may reflect involvement of temporal lobe structures that are critical for late life cognitive health but also are vulnerable to diseases of aging. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Attention and Regional Gray Matter Development in Very Preterm Children at Age 12 Years.

PubMed

Lean, Rachel E; Melzer, Tracy R; Bora, Samudragupta; Watts, Richard; Woodward, Lianne J

2017-08-01

This study examines the selective, sustained, and executive attention abilities of very preterm (VPT) born children in relation to concurrent structural magnetic resonance imaging (MRI) measures of regional gray matter development at age 12 years. A regional cohort of 110 VPT (≤32 weeks gestation) and 113 full term (FT) born children were assessed at corrected age 12 years on the Test of Everyday Attention-Children. They also had a structural MRI scan that was subsequently analyzed using voxel-based morphometry to quantify regional between-group differences in cerebral gray matter development, which were then related to attention measures using multivariate methods. VPT children obtained similar selective (p=.85), but poorer sustained (p=.02) and executive attention (p=.01) scores than FT children. VPT children were also characterized by reduced gray matter in the bilateral parietal, temporal, prefrontal and posterior cingulate cortices, bilateral thalami, and left hippocampus; and increased gray matter in the occipital and anterior cingulate cortices (family-wise error-corrected p<.05). Poorer sustained auditory attention was associated with increased gray matter in the anterior cingulate cortex (p=.04). Poor executive shifting attention was associated with reduced gray matter in the right superior temporal cortex (p=.04) and bilateral thalami (p=.05). Poorer executive divided attention was associated with reduced gray matter in the occipital (p=.001), posterior cingulate (p=.02), and left temporal (p=.01) cortices; and increased gray matter in the anterior cingulate cortex (p=.001). Disturbances in regional gray matter development appear to contribute, at least in part, to the poorer attentional performance of VPT children at school age. (JINS, 2017, 23, 539-550).

Reduced Gray Matter Volume Is Associated With Poorer Instrumental Activities of Daily Living Performance in Heart Failure.

PubMed

Alosco, Michael L; Brickman, Adam M; Spitznagel, Mary Beth; Narkhede, Atul; Griffith, Erica Y; Cohen, Ronald; Sweet, Lawrence H; Josephson, Richard; Hughes, Joel; Gunstad, John

2016-01-01

Heart failure patients require assistance with instrumental activities of daily living in part because of the high rates of cognitive impairment in this population. Structural brain insult (eg, reduced gray matter volume) is theorized to underlie cognitive dysfunction in heart failure, although no study has examined the association among gray matter, cognition, and instrumental activities of daily living in heart failure. The aim of this study was to investigate the associations among gray matter volume, cognitive function, and functional ability in heart failure. A total of 81 heart failure patients completed a cognitive test battery and the Lawton-Brody self-report questionnaire to assess instrumental activities of daily living. Participants underwent magnetic resonance imaging to quantify total gray matter and subcortical gray matter volume. Impairments in instrumental activities of daily living were common in this sample of HF patients. Regression analyses controlling for demographic and medical confounders showed that smaller total gray matter volume predicted decreased scores on the instrumental activities of daily living composite, with specific associations noted for medication management and independence in driving. Interaction analyses showed that reduced total gray matter volume interacted with worse attention/executive function and memory to negatively impact instrumental activities of daily living. Smaller gray matter volume is associated with greater impairment in instrumental activities of daily living in persons with heart failure, possibly via cognitive dysfunction. Prospective studies are needed to clarify the utility of clinical correlates of gray matter volume (eg, cognitive dysfunction) in identifying heart failure patients at risk for functional decline and determine whether interventions that target improved brain and cognitive function can preserve functional independence in this high-risk population.

3D nonrigid registration via optimal mass transport on the GPU.

PubMed

Ur Rehman, Tauseef; Haber, Eldad; Pryor, Gallagher; Melonakos, John; Tannenbaum, Allen

2009-12-01

In this paper, we present a new computationally efficient numerical scheme for the minimizing flow approach for optimal mass transport (OMT) with applications to non-rigid 3D image registration. The approach utilizes all of the gray-scale data in both images, and the optimal mapping from image A to image B is the inverse of the optimal mapping from B to A. Further, no landmarks need to be specified, and the minimizer of the distance functional involved is unique. Our implementation also employs multigrid, and parallel methodologies on a consumer graphics processing unit (GPU) for fast computation. Although computing the optimal map has been shown to be computationally expensive in the past, we show that our approach is orders of magnitude faster then previous work and is capable of finding transport maps with optimality measures (mean curl) previously unattainable by other works (which directly influences the accuracy of registration). We give results where the algorithm was used to compute non-rigid registrations of 3D synthetic data as well as intra-patient pre-operative and post-operative 3D brain MRI datasets.

Efficient Data Mining for Local Binary Pattern in Texture Image Analysis

PubMed Central

Kwak, Jin Tae; Xu, Sheng; Wood, Bradford J.

2015-01-01

Local binary pattern (LBP) is a simple gray scale descriptor to characterize the local distribution of the grey levels in an image. Multi-resolution LBP and/or combinations of the LBPs have shown to be effective in texture image analysis. However, it is unclear what resolutions or combinations to choose for texture analysis. Examining all the possible cases is impractical and intractable due to the exponential growth in a feature space. This limits the accuracy and time- and space-efficiency of LBP. Here, we propose a data mining approach for LBP, which efficiently explores a high-dimensional feature space and finds a relatively smaller number of discriminative features. The features can be any combinations of LBPs. These may not be achievable with conventional approaches. Hence, our approach not only fully utilizes the capability of LBP but also maintains the low computational complexity. We incorporated three different descriptors (LBP, local contrast measure, and local directional derivative measure) with three spatial resolutions and evaluated our approach using two comprehensive texture databases. The results demonstrated the effectiveness and robustness of our approach to different experimental designs and texture images. PMID:25767332