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.

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%.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms.

PubMed

Altazi, Baderaldeen A; Zhang, Geoffrey G; Fernandez, Daniel C; Montejo, Michael E; Hunt, Dylan; Werner, Joan; Biagioli, Matthew C; Moros, Eduardo G

2017-11-01

Site-specific investigations of the role of radiomics in cancer diagnosis and therapy are emerging. We evaluated the reproducibility of radiomic features extracted from 18 Flourine-fluorodeoxyglucose ( 18 F-FDG) PET images for three parameters: manual versus computer-aided segmentation methods, gray-level discretization, and PET image reconstruction algorithms. Our cohort consisted of pretreatment PET/CT scans from 88 cervical cancer patients. Two board-certified radiation oncologists manually segmented the metabolic tumor volume (MTV 1 and MTV 2 ) for each patient. For comparison, we used a graphical-based method to generate semiautomated segmented volumes (GBSV). To address any perturbations in radiomic feature values, we down-sampled the tumor volumes into three gray-levels: 32, 64, and 128 from the original gray-level of 256. Finally, we analyzed the effect on radiomic features on PET images of eight patients due to four PET 3D-reconstruction algorithms: maximum likelihood-ordered subset expectation maximization (OSEM) iterative reconstruction (IR) method, fourier rebinning-ML-OSEM (FOREIR), FORE-filtered back projection (FOREFBP), and 3D-Reprojection (3DRP) analytical method. We extracted 79 features from all segmentation method, gray-levels of down-sampled volumes, and PET reconstruction algorithms. The features were extracted using gray-level co-occurrence matrices (GLCM), gray-level size zone matrices (GLSZM), gray-level run-length matrices (GLRLM), neighborhood gray-tone difference matrices (NGTDM), shape-based features (SF), and intensity histogram features (IHF). We computed the Dice coefficient between each MTV and GBSV to measure segmentation accuracy. Coefficient values close to one indicate high agreement, and values close to zero indicate low agreement. We evaluated the effect on radiomic features by calculating the mean percentage differences (d¯) between feature values measured from each pair of parameter elements (i.e. segmentation methods: MTV 1 -MTV 2 , MTV 1 -GBSV, MTV 2 -GBSV; gray-levels: 64-32, 64-128, and 64-256; reconstruction algorithms: OSEM-FORE-OSEM, OSEM-FOREFBP, and OSEM-3DRP). We used |d¯| as a measure of radiomic feature reproducibility level, where any feature scored |d¯| ±SD ≤ |25|% ± 35% was considered reproducible. We used Bland-Altman analysis to evaluate the mean, standard deviation (SD), and upper/lower reproducibility limits (U/LRL) for radiomic features in response to variation in each testing parameter. Furthermore, we proposed U/LRL as a method to classify the level of reproducibility: High- ±1% ≤ U/LRL ≤ ±30%; Intermediate- ±30% < U/LRL ≤ ±45%; Low- ±45 < U/LRL ≤ ±50%. We considered any feature below the low level as nonreproducible (NR). Finally, we calculated the interclass correlation coefficient (ICC) to evaluate the reliability of radiomic feature measurements for each parameter. The segmented volumes of 65 patients (81.3%) scored Dice coefficient >0.75 for all three volumes. The result outcomes revealed a tendency of higher radiomic feature reproducibility among segmentation pair MTV 1 -GBSV than MTV 2 -GBSV, gray-level pairs of 64-32 and 64-128 than 64-256, and reconstruction algorithm pairs of OSEM-FOREIR and OSEM-FOREFBP than OSEM-3DRP. Although the choice of cervical tumor segmentation method, gray-level value, and reconstruction algorithm may affect radiomic features, some features were characterized by high reproducibility through all testing parameters. The number of radiomic features that showed insensitivity to variations in segmentation methods, gray-level discretization, and reconstruction algorithms was 10 (13%), 4 (5%), and 1 (1%), respectively. These results suggest that a careful analysis of the effects of these parameters is essential prior to any radiomics clinical application. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

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.

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.

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.

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.

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

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.

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

Patient dose, gray level and exposure index with a computed radiography system

NASA Astrophysics Data System (ADS)

Silva, T. R.; Yoshimura, E. M.

2014-02-01

Computed radiography (CR) is gradually replacing conventional screen-film system in Brazil. To assess image quality, manufactures provide the calculation of an exposure index through the acquisition software of the CR system. The objective of this study is to verify if the CR image can be used as an evaluator of patient absorbed dose too, through a relationship between the entrance skin dose and the exposure index or the gray level values obtained in the image. The CR system used for this study (Agfa model 30-X with NX acquisition software) calculates an exposure index called Log of the Median (lgM), related to the absorbed dose to the IP. The lgM value depends on the average gray level (called Scan Average Level (SAL)) of the segmented pixel value histogram of the whole image. A Rando male phantom was used to simulate a human body (chest and head), and was irradiated with an X-ray equipment, using usual radiologic techniques for chest exams. Thermoluminescent dosimeters (LiF, TLD100) were used to evaluate entrance skin dose and exit dose. The results showed a logarithm relation between entrance dose and SAL in the image center, regardless of the beam filtration. The exposure index varies linearly with the entrance dose, but the angular coefficient is beam quality dependent. We conclude that, with an adequate calibration, the CR system can be used to evaluate the patient absorbed dose.

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.

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

Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters.

PubMed

Galavis, Paulina E; Hollensen, Christian; Jallow, Ngoneh; Paliwal, Bhudatt; Jeraj, Robert

2010-10-01

Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45-60 minutes post-injection of 10 mCi of [(18)F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor segmentation.

Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters

PubMed Central

GALAVIS, PAULINA E.; HOLLENSEN, CHRISTIAN; JALLOW, NGONEH; PALIWAL, BHUDATT; JERAJ, ROBERT

2014-01-01

Background Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Material and methods Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45–60 minutes post-injection of 10 mCi of [18F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Results Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Conclusion Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor segmentation. PMID:20831489

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.

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.

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.

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

PubMed

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

2015-11-01

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

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.

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.

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.

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.

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.

Efficiency of quantitative echogenicity for investigating supraspinatus tendinopathy by the gray-level histogram of two ultrasound devices.

PubMed

Hsu, Jiun-Cheng; Chen, Po-Han; Huang, Kuo-Chin; Tsai, Yao-Hung; Hsu, Wei-Hsiu

2017-10-01

The gray-level histogram of ultrasound is a promising tool for scanning the hypoechogenic appearance of supraspinatus tendinopathy, and the aim of this study was to test the hypothesis that the gray-level value of the supraspinatus tendon in the painful shoulder has a lower value on B-mode images even though in different ultrasound devices. Sixty-seven patients who had unilateral shoulder pain with rotator cuff tendinopathy underwent bilateral shoulder ultrasonography, and we compared the mean gray-level values of painful shoulders and contralateral shoulders without any pain in each patient using two ultrasound devices. The echogenicity ratio (symptomatic/asymptomatic side) of two ultrasound devices was compared. A significant difference existed between the symptomatic shoulder and contralateral asymptomatic shoulder (p < 0.001) on the mean gray-level value measurements of each device. The symptomatic-to-asymptomatic tendon echogenicity ratio of device A was 0.919 ± 0.090 in the transverse plane and 0.937 ± 0.081 in the longitudinal plane, and the echogenicity ratio of device B was 0.899 ± 0.113 in the transverse plane and 0.940 ± 0.113 in the longitudinal plane. The decline of the mean gray-level value and the echogenicity ratio of the supraspinatus tendon in the painful shoulder may be utilized as a useful sonographic reference of unilateral rotator cuff lesions. Diagnostic level III.

8-Bit Gray Scale Images of Fingerprint Image Groups

National Institute of Standards and Technology Data Gateway

NIST 8-Bit Gray Scale Images of Fingerprint Image Groups (Web, free access)   The NIST database of fingerprint images contains 2000 8-bit gray scale fingerprint image pairs. 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.

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.

Gray matter network disruptions and amyloid beta in cognitively normal adults.

PubMed

Tijms, Betty M; Kate, Mara Ten; Wink, Alle Meije; Visser, Pieter Jelle; Ecay, Mirian; Clerigue, Montserrat; Estanga, Ainara; Garcia Sebastian, Maite; Izagirre, Andrea; Villanua, Jorge; Martinez Lage, Pablo; van der Flier, Wiesje M; Scheltens, Philip; Sanz Arigita, Ernesto; Barkhof, Frederik

2016-01-01

Gray matter networks are disrupted in Alzheimer's disease (AD). It is unclear when these disruptions start during the development of AD. Amyloid beta 1-42 (Aβ42) is among the earliest changes in AD. We studied, in cognitively healthy adults, the relationship between Aβ42 levels in cerebrospinal fluid (CSF) and single-subject cortical gray matter network measures. Single-subject gray matter networks were extracted from structural magnetic resonance imaging scans in a sample of cognitively healthy adults (N = 185; age range 39-79, mini-mental state examination >25, N = 12 showed abnormal Aβ42 < 550 pg/mL). Degree, clustering coefficient, and path length were computed at whole brain level and for 90 anatomical areas. Associations between continuous Aβ42 CSF levels and single-subject cortical gray matter network measures were tested. Smoothing splines were used to determine whether a linear or nonlinear relationship gave a better fit to the data. Lower Aβ42 CSF levels were linearly associated at whole brain level with lower connectivity density, and nonlinearly with lower clustering values and higher path length values, which is indicative of a less-efficient network organization. These relationships were specific to medial temporal areas, precuneus, and the middle frontal gyrus (all p < 0.05). These results suggest that mostly within the normal spectrum of amyloid, lower Aβ42 levels can be related to gray matter networks disruptions. Copyright © 2016 Elsevier Inc. All rights reserved.

Digital analysis of changes by Plasmodium vivax malaria in erythrocytes.

PubMed

Edison, Maombi; Jeeva, J B; Singh, Megha

2011-01-01

Blood samples of malaria patients (n = 30), selected based on the severity of parasitemia, were divided into low (LP), medium (MP) and high (HP) parasitemia, which represent increasing levels of the disease severity. Healthy subjects (n = 10) without any history of disease were selected as a control group. By processing of erythrocytes images their contours were obtained and from these the shape parameters area, perimeter and form factor were obtained. The gray level intensity was determined by scanning of erythrocyte along its largest diameter. A comparison of these with that of normal cells showed a significant change in shape parameters. The gray level intensity decreases with the increase of severity of the disease. The changes in shape parameters directly and gray level intensity variation inversely are correlated with the increase in parasite density due to the disease.

A systematic review and meta-analysis of structural magnetic resonance imaging studies investigating cognitive and social activity levels in older adults.

PubMed

Anatürk, M; Demnitz, N; Ebmeier, K P; Sexton, C E

2018-06-22

Population aging has prompted considerable interest in identifying modifiable factors that may help protect the brain and its functions. Collectively, epidemiological studies show that leisure activities with high mental and social demands are linked with better cognition in old age. The extent to which socio-intellectual activities relate to the brain's structure is, however, not yet fully understood. This systematic review and meta-analysis summarizes magnetic resonance imaging studies that have investigated whether cognitive and social activities correlate with measures of gray and white matter volume, white matter microstructure and white matter lesions. Across eighteen included studies (total n = 8429), activity levels were associated with whole-brain white matter volume, white matter lesions and regional gray matter volume, although effect sizes were small. No associations were found for global gray matter volume and the evidence concerning white matter microstructure was inconclusive. While the causality of the reviewed associations needs to be established, our findings implicate socio-intellectual activity levels as promising targets for interventions aimed at promoting healthy brain aging. Copyright © 2018. Published by Elsevier Ltd.

Skeletonization with hollow detection on gray image by gray weighted distance transform

NASA Astrophysics Data System (ADS)

Bhattacharya, Prabir; Qian, Kai; Cao, Siqi; Qian, Yi

1998-10-01

A skeletonization algorithm that could be used to process non-uniformly distributed gray-scale images with hollows was presented. This algorithm is based on the Gray Weighted Distance Transformation. The process includes a preliminary phase of investigation in the hollows in the gray-scale image, whether these hollows are considered as topological constraints for the skeleton structure depending on their statistically significant depth. We then extract the resulting skeleton that has certain meaningful information for understanding the object in the image. This improved algorithm can overcome the possible misinterpretation of some complicated images in the extracted skeleton, especially in images with asymmetric hollows and asymmetric features. This algorithm can be executed on a parallel machine as all the operations are executed in local. Some examples are discussed to illustrate the algorithm.

Reduction of image-based ADI-to-AEI overlay inconsistency with improved algorithm

NASA Astrophysics Data System (ADS)

Chen, Yen-Liang; Lin, Shu-Hong; Chen, Kai-Hsiung; Ke, Chih-Ming; Gau, Tsai-Sheng

2013-04-01

In image-based overlay (IBO) measurement, the measurement quality of various measurement spectra can be judged by quality indicators and also the ADI-to-AEI similarity to determine the optimum light spectrum. However we found some IBO measured results showing erroneous indication of wafer expansion from the difference between the ADI and the AEI maps, even after their measurement spectra were optimized. To reduce this inconsistency, an improved image calculation algorithm is proposed in this paper. Different gray levels composed of inner- and outer-box contours are extracted to calculate their ADI overlay errors. The symmetry of intensity distribution at the thresholds dictated by a range of gray levels is used to determine the particular gray level that can minimize the ADI-to-AEI overlay inconsistency. After this improvement, the ADI is more similar to AEI with less expansion difference. The same wafer was also checked by the diffraction-based overlay (DBO) tool to verify that there is no physical wafer expansion. When there is actual wafer expansion induced by large internal stress, both the IBO and the DBO measurements indicate similar expansion results. The scanning white-light interference microscope was used to check the variation of wafer warpage during the ADI and AEI stages. It predicts a similar trend with the overlay difference map, confirming the internal stress.

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

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.

Robust algebraic image enhancement for intelligent control systems

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morrelli, Michael

1993-01-01

Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

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

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.

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

A color-coded vision scheme for robotics

NASA Technical Reports Server (NTRS)

Johnson, Kelley Tina

1991-01-01

Most vision systems for robotic applications rely entirely on the extraction of information from gray-level images. Humans, however, regularly depend on color to discriminate between objects. Therefore, the inclusion of color in a robot vision system seems a natural extension of the existing gray-level capabilities. A method for robot object recognition using a color-coding classification scheme is discussed. The scheme is based on an algebraic system in which a two-dimensional color image is represented as a polynomial of two variables. The system is then used to find the color contour of objects. In a controlled environment, such as that of the in-orbit space station, a particular class of objects can thus be quickly recognized by its color.

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

Frequency identification of vibration signals using video camera image data.

PubMed

Jeng, Yih-Nen; Wu, Chia-Hung

2012-10-16

This study showed that an image data acquisition system connecting a high-speed camera or webcam to a notebook or personal computer (PC) can precisely capture most dominant modes of vibration signal, but may involve the non-physical modes induced by the insufficient frame rates. Using a simple model, frequencies of these modes are properly predicted and excluded. Two experimental designs, which involve using an LED light source and a vibration exciter, are proposed to demonstrate the performance. First, the original gray-level resolution of a video camera from, for instance, 0 to 256 levels, was enhanced by summing gray-level data of all pixels in a small region around the point of interest. The image signal was further enhanced by attaching a white paper sheet marked with a black line on the surface of the vibration system in operation to increase the gray-level resolution. Experimental results showed that the Prosilica CV640C CMOS high-speed camera has the critical frequency of inducing the false mode at 60 Hz, whereas that of the webcam is 7.8 Hz. Several factors were proven to have the effect of partially suppressing the non-physical modes, but they cannot eliminate them completely. Two examples, the prominent vibration modes of which are less than the associated critical frequencies, are examined to demonstrate the performances of the proposed systems. In general, the experimental data show that the non-contact type image data acquisition systems are potential tools for collecting the low-frequency vibration signal of a system.

Frequency Identification of Vibration Signals Using Video Camera Image Data

PubMed Central

Jeng, Yih-Nen; Wu, Chia-Hung

2012-01-01

This study showed that an image data acquisition system connecting a high-speed camera or webcam to a notebook or personal computer (PC) can precisely capture most dominant modes of vibration signal, but may involve the non-physical modes induced by the insufficient frame rates. Using a simple model, frequencies of these modes are properly predicted and excluded. Two experimental designs, which involve using an LED light source and a vibration exciter, are proposed to demonstrate the performance. First, the original gray-level resolution of a video camera from, for instance, 0 to 256 levels, was enhanced by summing gray-level data of all pixels in a small region around the point of interest. The image signal was further enhanced by attaching a white paper sheet marked with a black line on the surface of the vibration system in operation to increase the gray-level resolution. Experimental results showed that the Prosilica CV640C CMOS high-speed camera has the critical frequency of inducing the false mode at 60 Hz, whereas that of the webcam is 7.8 Hz. Several factors were proven to have the effect of partially suppressing the non-physical modes, but they cannot eliminate them completely. Two examples, the prominent vibration modes of which are less than the associated critical frequencies, are examined to demonstrate the performances of the proposed systems. In general, the experimental data show that the non-contact type image data acquisition systems are potential tools for collecting the low-frequency vibration signal of a system. PMID:23202026

Can Laws Be a Potential PET Image Texture Analysis Approach for Evaluation of Tumor Heterogeneity and Histopathological Characteristics in NSCLC?

PubMed

Karacavus, Seyhan; Yılmaz, Bülent; Tasdemir, Arzu; Kayaaltı, Ömer; Kaya, Eser; İçer, Semra; Ayyıldız, Oguzhan

2018-04-01

We investigated the association between the textural features obtained from 18 F-FDG images, metabolic parameters (SUVmax , SUVmean, MTV, TLG), and tumor histopathological characteristics (stage and Ki-67 proliferation index) in non-small cell lung cancer (NSCLC). The FDG-PET images of 67 patients with NSCLC were evaluated. MATLAB technical computing language was employed in the extraction of 137 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run length matrix (GLRLM), and Laws' texture filters. Textural features and metabolic parameters were statistically analyzed in terms of good discrimination power between tumor stages, and selected features/parameters were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). We showed that one textural feature (gray-level nonuniformity, GLN) obtained using GLRLM approach and nine textural features using Laws' approach were successful in discriminating all tumor stages, unlike metabolic parameters. There were significant correlations between Ki-67 index and some of the textural features computed using Laws' method (r = 0.6, p = 0.013). In terms of automatic classification of tumor stage, the accuracy was approximately 84% with k-NN classifier (k = 3) and SVM, using selected five features. Texture analysis of FDG-PET images has a potential to be an objective tool to assess tumor histopathological characteristics. The textural features obtained using Laws' approach could be useful in the discrimination of tumor stage.

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.

Global gray-level thresholding based on object size.

PubMed

Ranefall, Petter; Wählby, Carolina

2016-04-01

In this article, we propose a fast and robust global gray-level thresholding method based on object size, where the selection of threshold level is based on recall and maximum precision with regard to objects within a given size interval. The method relies on the component tree representation, which can be computed in quasi-linear time. Feature-based segmentation is especially suitable for biomedical microscopy applications where objects often vary in number, but have limited variation in size. We show that for real images of cell nuclei and synthetic data sets mimicking fluorescent spots the proposed method is more robust than all standard global thresholding methods available for microscopy applications in ImageJ and CellProfiler. The proposed method, provided as ImageJ and CellProfiler plugins, is simple to use and the only required input is an interval of the expected object sizes. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

A neural net based architecture for the segmentation of mixed gray-level and binary pictures

NASA Technical Reports Server (NTRS)

Tabatabai, Ali; Troudet, Terry P.

1991-01-01

A neural-net-based architecture is proposed to perform segmentation in real time for mixed gray-level and binary pictures. In this approach, the composite picture is divided into 16 x 16 pixel blocks, which are identified as character blocks or image blocks on the basis of a dichotomy measure computed by an adaptive 16 x 16 neural net. For compression purposes, each image block is further divided into 4 x 4 subblocks; a one-bit nonparametric quantizer is used to encode 16 x 16 character and 4 x 4 image blocks; and the binary map and quantizer levels are obtained through a neural net segmentor over each block. The efficiency of the neural segmentation in terms of computational speed, data compression, and quality of the compressed picture is demonstrated. The effect of weight quantization is also discussed. VLSI implementations of such adaptive neural nets in CMOS technology are described and simulated in real time for a maximum block size of 256 pixels.

In vivo skin imaging for hydration and micro relief-measurement.

PubMed

Kardosova, Z; Hegyi, V

2013-01-01

We present the results of our work with device used for measurement of skin capacitance before and after application of moisturizing creams and results of experiment performed on cellulose filter papers soaked with different solvents. The measurements were performed by a device built on capacitance sensor, which provides an investigator with a capacitance image of the skin. The capacitance values are coded in a range of 256 gray levels then the skin hydration can be characterized using parameters derived from gray level histogram by specific software. The images obtained by device allow a highly precise observation of skin topography. Measuring of skin capacitance brings new, objective, reliable information about topographical, physical and chemical parameters of the skin. The study shows that there is a good correlation between the average grayscale values and skin hydration. In future works we need to complete more comparison studies, interpret the average grayscale values to skin hydration levels and use it for follow-up of dynamics of skin micro-relief and hydration changes (Fig. 6, Ref. 15).

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.

Calibrators measurement system for headlamp tester of motor vehicle base on machine vision

NASA Astrophysics Data System (ADS)

Pan, Yue; Zhang, Fan; Xu, Xi-ping; Zheng, Zhe

2014-09-01

With the development of photoelectric detection technology, machine vision has a wider use in the field of industry. The paper mainly introduces auto lamps tester calibrator measuring system, of which CCD image sampling system is the core. Also, it shows the measuring principle of optical axial angle and light intensity, and proves the linear relationship between calibrator's facula illumination and image plane illumination. The paper provides an important specification of CCD imaging system. Image processing by MATLAB can get flare's geometric midpoint and average gray level. By fitting the statistics via the method of the least square, we can get regression equation of illumination and gray level. It analyzes the error of experimental result of measurement system, and gives the standard uncertainty of synthesis and the resource of optical axial angle. Optical axial angle's average measuring accuracy is controlled within 40''. The whole testing process uses digital means instead of artificial factors, which has higher accuracy, more repeatability and better mentality than any other measuring systems.

Fuzzy Matching Based on Gray-scale Difference for Quantum Images

NASA Astrophysics Data System (ADS)

Luo, GaoFeng; Zhou, Ri-Gui; Liu, XingAo; Hu, WenWen; Luo, Jia

2018-05-01

Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.

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

A study on using texture analysis methods for identifying lobar fissure regions in isotropic CT images.

PubMed

Wei, Q; Hu, Y

2009-01-01

The major hurdle for segmenting lung lobes in computed tomographic (CT) images is to identify fissure regions, which encase lobar fissures. Accurate identification of these regions is difficult due to the variable shape and appearance of the fissures, along with the low contrast and high noise associated with CT images. This paper studies the effectiveness of two texture analysis methods - the gray level co-occurrence matrix (GLCM) and the gray level run length matrix (GLRLM) - in identifying fissure regions from isotropic CT image stacks. To classify GLCM and GLRLM texture features, we applied a feed-forward back-propagation neural network and achieved the best classification accuracy utilizing 16 quantized levels for computing the GLCM and GLRLM texture features and 64 neurons in the input/hidden layers of the neural network. Tested on isotropic CT image stacks of 24 patients with the pathologic lungs, we obtained accuracies of 86% and 87% for identifying fissure regions using the GLCM and GLRLM methods, respectively. These accuracies compare favorably with surgeons/radiologists' accuracy of 80% for identifying fissure regions in clinical settings. This shows promising potential for segmenting lung lobes using the GLCM and GLRLM methods.

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.

Computerized detection of unruptured aneurysms in MRA images: reduction of false positives using anatomical location features

NASA Astrophysics Data System (ADS)

Uchiyama, Yoshikazu; Gao, Xin; Hara, Takeshi; Fujita, Hiroshi; Ando, Hiromichi; Yamakawa, Hiroyasu; Asano, Takahiko; Kato, Hiroki; Iwama, Toru; Kanematsu, Masayuki; Hoshi, Hiroaki

2008-03-01

The detection of unruptured aneurysms is a major subject in magnetic resonance angiography (MRA). However, their accurate detection is often difficult because of the overlapping between the aneurysm and the adjacent vessels on maximum intensity projection images. The purpose of this study is to develop a computerized method for the detection of unruptured aneurysms in order to assist radiologists in image interpretation. The vessel regions were first segmented using gray-level thresholding and a region growing technique. The gradient concentration (GC) filter was then employed for the enhancement of the aneurysms. The initial candidates were identified in the GC image using a gray-level threshold. For the elimination of false positives (FPs), we determined shape features and an anatomical location feature. Finally, rule-based schemes and quadratic discriminant analysis were employed along with these features for distinguishing between the aneurysms and the FPs. The sensitivity for the detection of unruptured aneurysms was 90.0% with 1.52 FPs per patient. Our computerized scheme can be useful in assisting the radiologists in the detection of unruptured aneurysms in MRA images.

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.

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.

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.

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.

Relationship between Hounsfield unit in CT scan and gray scale in CBCT

NASA Astrophysics Data System (ADS)

Kamaruddin, Noorshaida; Rajion, Zainul Ahmad; Yusof, Asilah; Aziz, Mohd Ezane

2016-12-01

Cone-beam computed tomography (CBCT) is an imaging system which has advantages over computed tomography (CT). Recently, CBCT has become widely used for oral and maxillofacial imaging. In CT scan, Hounsfield Unit (HU) is proportional to the degree of x-ray attenuation by the tissue. In CBCT, the degree of x-ray attenuation is shown by gray scale (voxel value). The aim of the present (in vitro) study was to investigate the relationship between gray scale in CBCT and HU in CT scan. In this descriptive study, the anthropomorphic head phantom was scanned with CBCT and CT scanner. Gray scales and HUs were detected on images at the crown of the teeth, trabecular and cortical bone of mandible. The images were analyzed to obtain the gray scale value and HU value. The obtained value then used to investigate the relationship between CBCT gray scales and HUs. For the statistical analysis, t-test, Pearson's correlation and regression analysis were used. The differences between the gray scale of CBCT and HU of CT were statistically not significant, whereas the Pearson's correlation coefficients demonstrated a statistically significant correlation between gray scale of CBCT and HU of CT values. Considering the fact that gray scale in CBCT is important in pre assessment evaluation of bone density before implant treatments, it is recommended because of the lower dose and cost compared to CT scan.

Technical Note: Gray tracking in medical color displays-A report of Task Group 196.

PubMed

Badano, Aldo; Wang, Joel; Boynton, Paul; Le Callet, Patrick; Cheng, Wei-Chung; Deroo, Danny; Flynn, Michael J; Matsui, Takashi; Penczek, John; Revie, Craig; Samei, Ehsan; Steven, Peter M; Swiderski, Stan; Van Hoey, Gert; Yamaguchi, Matsuhiro; Hasegawa, Mikio; Nagy, Balázs Vince

2016-07-01

The authors discuss measurement methods and instrumentation useful for the characterization of the gray tracking performance of medical color monitors for diagnostic applications. The authors define gray tracking as the variability in the chromaticity of the gray levels in a color monitor. The authors present data regarding the capability of color measurement instruments with respect to their abilities to measure a target white point corresponding to the CIE Standard Illuminant D65 at different luminance values within the grayscale palette of a medical display. The authors then discuss evidence of significant differences in performance among color measurement instruments currently available for medical physicists to perform calibrations and image quality checks for the consistent representation of color in medical displays. In addition, the authors introduce two metrics for quantifying grayscale chromaticity consistency of gray tracking. The authors' findings show that there is an order of magnitude difference in the accuracy of field and reference instruments. The gray tracking metrics quantify how close the grayscale chromaticity is to the chromaticity of the full white point (equal amounts of red, green, and blue at maximum level) or to consecutive levels (equal values for red, green, and blue), with a lower value representing an improved grayscale tracking performance. An illustrative example of how to calculate and report the gray tracking performance according to the Task Group definitions is provided. The authors' proposed methodology for characterizing the grayscale degradation in chromaticity for color monitors that can be used to establish standards and procedures aiding in the quality control testing of color displays and color measurement instrumentation.

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

Expression profiling suggests a regulatory role of gallbladder in lipid homeostasis

PubMed Central

Yuan, Zuo-Biao; Han, Tian-Quan; Jiang, Zhao-Yan; Fei, Jian; Zhang, Yi; Qin, Jian; Tian, Zhi-Jie; Shang, Jun; Jiang, Zhi-Hong; Cai, Xing-Xing; Jiang, Yu; Zhang, Sheng-Dao; Jin, Gang

2005-01-01

AIM: To examine expression profile of gallbladder using microarray and to investigate the role of gallbladder in lipid homeostasis. METHODS: 33P-labelled cDNA derived from total RNA of gallbladder tissue was hybridized to a cDNA array representing 17000 cDNA clusters. Genes with intensities ≥2 and variation <0.33 between two samples were considered as positive signals with subtraction of background chosen from an area where no cDNA was spotted. The average gray level of two gallbladders was adopted to analyze its bioinformatics. Identified target genes were confirmed by touch-down polymerase chain reaction and sequencing. RESULTS: A total of 11 047 genes expressed in normal gallbladder, which was more than that predicted by another author, and the first 10 genes highly expressed (high gray level in hybridization image), e.g., ARPC5 (2225.88±90.46), LOC55972 (2220.32±446.51) and SLC20A2 (1865.21±98.02), were related to the function of smooth muscle contraction and material transport. Meanwhile, 149 lipid-related genes were expressed in the gallbladder, 89 of which were first identified (with gray level in hybridization image), e.g., FASN (11.42±2.62), APOD (92.61±8.90) and CYP21A2 (246.11±42.36), and they were involved in each step of lipid metabolism pathway. In addition, 19 of those 149 genes were gallstone candidate susceptibility genes (with gray level in hybridization image), e.g., HMGCR (10.98±0.31), NPC1 (34.88±12.12) and NR1H4 (16.8±0.65), which were previously thought to be expressed in the liver and/or intestine tissue only. CONCLUSION: Gallbladder expresses 11 047 genes and takes part in lipid homeostasis. PMID:15810076

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

PubMed

Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Classification of fresh and frozen-thawed pork muscles using visible and near infrared hyperspectral imaging and textural analysis.

PubMed

Pu, Hongbin; Sun, Da-Wen; Ma, Ji; Cheng, Jun-Hu

2015-01-01

The potential of visible and near infrared hyperspectral imaging was investigated as a rapid and nondestructive technique for classifying fresh and frozen-thawed meats by integrating critical spectral and image features extracted from hyperspectral images in the region of 400-1000 nm. Six feature wavelengths (400, 446, 477, 516, 592 and 686 nm) were identified using uninformative variable elimination and successive projections algorithm. Image textural features of the principal component images from hyperspectral images were obtained using histogram statistics (HS), gray level co-occurrence matrix (GLCM) and gray level-gradient co-occurrence matrix (GLGCM). By these spectral and textural features, probabilistic neural network (PNN) models for classification of fresh and frozen-thawed pork meats were established. Compared with the models using the optimum wavelengths only, optimum wavelengths with HS image features, and optimum wavelengths with GLCM image features, the model integrating optimum wavelengths with GLGCM gave the highest classification rate of 93.14% and 90.91% for calibration and validation sets, respectively. Results indicated that the classification accuracy can be improved by combining spectral features with textural features and the fusion of critical spectral and textural features had better potential than single spectral extraction in classifying fresh and frozen-thawed pork meat. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

PubMed

Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

2015-06-01

The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

Gray-level co-occurrence matrix analysis of several cell types in mouse brain using resolution-enhanced photothermal microscopy

NASA Astrophysics Data System (ADS)

Kobayashi, Takayoshi; Sundaram, Durga; Nakata, Kazuaki; Tsurui, Hiromichi

2017-03-01

Qualifications of intracellular structure were performed for the first time using the gray-level co-occurrence matrix (GLCM) method for images of cells obtained by resolution-enhanced photothermal imaging. The GLCM method has been used to extract five parameters of texture features for five different types of cells in mouse brain; pyramidal neurons and glial cells in the basal nucleus (BGl), dentate gyrus granule cells, cerebellar Purkinje cells, and cerebellar granule cells. The parameters are correlation, contrast, angular second moment (ASM), inverse difference moment (IDM), and entropy for the images of cells of interest in a mouse brain. The parameters vary depending on the pixel distance taken in the analysis method. Based on the obtained results, we identified that the most suitable GLCM parameter is IDM for pyramidal neurons and BGI, granule cells in the dentate gyrus, Purkinje cells and granule cells in the cerebellum. It was also found that the ASM is the most appropriate for neurons in the basal nucleus.

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.

Gender classification from face images by using local binary pattern and gray-level co-occurrence matrix

NASA Astrophysics Data System (ADS)

Uzbaş, Betül; Arslan, Ahmet

2018-04-01

Gender is an important step for human computer interactive processes and identification. Human face image is one of the important sources to determine gender. In the present study, gender classification is performed automatically from facial images. In order to classify gender, we propose a combination of features that have been extracted face, eye and lip regions by using a hybrid method of Local Binary Pattern and Gray-Level Co-Occurrence Matrix. The features have been extracted from automatically obtained face, eye and lip regions. All of the extracted features have been combined and given as input parameters to classification methods (Support Vector Machine, Artificial Neural Networks, Naive Bayes and k-Nearest Neighbor methods) for gender classification. The Nottingham Scan face database that consists of the frontal face images of 100 people (50 male and 50 female) is used for this purpose. As the result of the experimental studies, the highest success rate has been achieved as 98% by using Support Vector Machine. The experimental results illustrate the efficacy of our proposed method.

Structure-Preserving Smoothing of Biomedical Images

NASA Astrophysics Data System (ADS)

Gil, Debora; Hernàndez-Sabaté, Aura; Burnat, Mireia; Jansen, Steven; Martínez-Villalta, Jordi

Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood.

Image Processing for Binarization Enhancement via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A. (Inventor)

2009-01-01

A technique for enhancing a gray-scale image to improve conversions of the image to binary employs fuzzy reasoning. In the technique, pixels in the image are analyzed by comparing the pixel's gray scale value, which is indicative of its relative brightness, to the values of pixels immediately surrounding the selected pixel. The degree to which each pixel in the image differs in value from the values of surrounding pixels is employed as the variable in a fuzzy reasoning-based analysis that determines an appropriate amount by which the selected pixel's value should be adjusted to reduce vagueness and ambiguity in the image and improve retention of information during binarization of the enhanced gray-scale image.

Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

NASA Astrophysics Data System (ADS)

Yan, Dan; Bai, Lianfa; Zhang, Yi; Han, Jing

2018-02-01

For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

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.

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

Complex-valued multistate associative memory with nonlinear multilevel functions for gray-level image reconstruction.

PubMed

Tanaka, Gouhei; Aihara, Kazuyuki

2009-09-01

A widely used complex-valued activation function for complex-valued multistate Hopfield networks is revealed to be essentially based on a multilevel step function. By replacing the multilevel step function with other multilevel characteristics, we present two alternative complex-valued activation functions. One is based on a multilevel sigmoid function, while the other on a characteristic of a multistate bifurcating neuron. Numerical experiments show that both modifications to the complex-valued activation function bring about improvements in network performance for a multistate associative memory. The advantage of the proposed networks over the complex-valued Hopfield networks with the multilevel step function is more outstanding when a complex-valued neuron represents a larger number of multivalued states. Further, the performance of the proposed networks in reconstructing noisy 256 gray-level images is demonstrated in comparison with other recent associative memories to clarify their advantages and disadvantages.

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.

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

Fractal and Gray Level Cooccurrence Matrix Computational Analysis of Primary Osteosarcoma Magnetic Resonance Images Predicts the Chemotherapy Response.

PubMed

Djuričić, Goran J; Radulovic, Marko; Sopta, Jelena P; Nikitović, Marina; Milošević, Nebojša T

2017-01-01

The prediction of induction chemotherapy response at the time of diagnosis may improve outcomes in osteosarcoma by allowing for personalized tailoring of therapy. The aim of this study was thus to investigate the predictive potential of the so far unexploited computational analysis of osteosarcoma magnetic resonance (MR) images. Fractal and gray level cooccurrence matrix (GLCM) algorithms were employed in retrospective analysis of MR images of primary osteosarcoma localized in distal femur prior to the OsteoSa induction chemotherapy. The predicted and actual chemotherapy response outcomes were then compared by means of receiver operating characteristic (ROC) analysis and accuracy calculation. Dbin, Λ, and SCN were the standard fractal and GLCM features which significantly associated with the chemotherapy outcome, but only in one of the analyzed planes. Our newly developed normalized fractal dimension, called the space-filling ratio (SFR) exerted an independent and much better predictive value with the prediction significance accomplished in two of the three imaging planes, with accuracy of 82% and area under the ROC curve of 0.20 (95% confidence interval 0-0.41). In conclusion, SFR as the newly designed fractal coefficient provided superior predictive performance in comparison to standard image analysis features, presumably by compensating for the tumor size variation in MR images.

Performance evaluation of an automatic segmentation method of cerebral arteries in MRA images by use of a large image database

NASA Astrophysics Data System (ADS)

Uchiyama, Yoshikazu; Asano, Tatsunori; Hara, Takeshi; Fujita, Hiroshi; Kinosada, Yasutomi; Asano, Takahiko; Kato, Hiroki; Kanematsu, Masayuki; Hoshi, Hiroaki; Iwama, Toru

2009-02-01

The detection of cerebrovascular diseases such as unruptured aneurysm, stenosis, and occlusion is a major application of magnetic resonance angiography (MRA). However, their accurate detection is often difficult for radiologists. Therefore, several computer-aided diagnosis (CAD) schemes have been developed in order to assist radiologists with image interpretation. The purpose of this study was to develop a computerized method for segmenting cerebral arteries, which is an essential component of CAD schemes. For the segmentation of vessel regions, we first used a gray level transformation to calibrate voxel values. To adjust for variations in the positioning of patients, registration was subsequently employed to maximize the overlapping of the vessel regions in the target image and reference image. The vessel regions were then segmented from the background using gray-level thresholding and region growing techniques. Finally, rule-based schemes with features such as size, shape, and anatomical location were employed to distinguish between vessel regions and false positives. Our method was applied to 854 clinical cases obtained from two different hospitals. The segmentation of cerebral arteries in 97.1%(829/854) of the MRA studies was attained as an acceptable result. Therefore, our computerized method would be useful in CAD schemes for the detection of cerebrovascular diseases in MRA images.

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%.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

Effect of color coding and subtraction on the accuracy of contrast echocardiography

NASA Technical Reports Server (NTRS)

Pasquet, A.; Greenberg, N.; Brunken, R.; Thomas, J. D.; Marwick, T. H.

1999-01-01

BACKGROUND: Contrast echocardiography may be used to assess myocardial perfusion. However, gray scale assessment of myocardial contrast echocardiography (MCE) is difficult because of variations in regional backscatter intensity, difficulties in distinguishing varying shades of gray, and artifacts or attenuation. We sought to determine whether the assessment of rest myocardial perfusion by MCE could be improved with subtraction and color coding. METHODS AND RESULTS: MCE was performed in 31 patients with previous myocardial infarction with a 2nd generation agent (NC100100, Nycomed AS), using harmonic triggered or continuous imaging and gain settings were kept constant throughout the study. Digitized images were post processed by subtraction of baseline from contrast data and colorized to reflect the intensity of myocardial contrast. Gray scale MCE alone, MCE images combined with baseline and subtracted colorized images were scored independently using a 16 segment model. The presence and severity of myocardial contrast abnormalities were compared with perfusion defined by rest MIBI-SPECT. Segments that were not visualized by continuous (17%) or triggered imaging (14%) after color processing were excluded from further analysis. The specificity of gray scale MCE alone (56%) or MCE combined with baseline 2D (47%) was significantly enhanced by subtraction and color coding (76%, p<0.001) of triggered images. The accuracy of the gray scale approaches (respectively 52% and 47%) was increased to 70% (p<0.001). Similarly, for continuous images, the specificity of gray scale MCE with and without baseline comparison was 23% and 42% respectively, compared with 60% after post processing (p<0.001). The accuracy of colorized images (59%) was also significantly greater than gray scale MCE (43% and 29%, p<0.001). The sensitivity of MCE for both acquisitions was not altered by subtraction. CONCLUSION: Post-processing with subtraction and color coding significantly improves the accuracy and specificity of MCE for detection of perfusion defects.

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

Image editing with Adobe Photoshop 6.0.

PubMed

Caruso, Ronald D; Postel, Gregory C

2002-01-01

The authors introduce Photoshop 6.0 for radiologists and demonstrate basic techniques of editing gray-scale cross-sectional images intended for publication and for incorporation into computerized presentations. For basic editing of gray-scale cross-sectional images, the Tools palette and the History/Actions palette pair should be displayed. The History palette may be used to undo a step or series of steps. The Actions palette is a menu of user-defined macros that save time by automating an action or series of actions. Converting an image to 8-bit gray scale is the first editing function. Cropping is the next action. Both decrease file size. Use of the smallest file size necessary for the purpose at hand is recommended. Final file size for gray-scale cross-sectional neuroradiologic images (8-bit, single-layer TIFF [tagged image file format] at 300 pixels per inch) intended for publication varies from about 700 Kbytes to 3 Mbytes. Final file size for incorporation into computerized presentations is about 10-100 Kbytes (8-bit, single-layer, gray-scale, high-quality JPEG [Joint Photographic Experts Group]), depending on source and intended use. Editing and annotating images before they are inserted into presentation software is highly recommended, both for convenience and flexibility. Radiologists should find that image editing can be carried out very rapidly once the basic steps are learned and automated. Copyright RSNA, 2002

Comparison of rotation algorithms for digital images

NASA Astrophysics Data System (ADS)

Starovoitov, Valery V.; Samal, Dmitry

1999-09-01

The paper presents a comparative study of several algorithms developed for digital image rotation. No losing generality we studied gray scale images. We have tested methods preserving gray values of the original images, performing some interpolation and two procedures implemented into the Corel Photo-paint and Adobe Photoshop soft packages. By the similar way methods for rotation of color images may be evaluated also.

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.

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.

Entropy-Based Adaptive Nuclear Texture Features are Independent Prognostic Markers in a Total Population of Uterine Sarcomas

PubMed Central

Nielsen, Birgitte; Hveem, Tarjei Sveinsgjerd; Kildal, Wanja; Abeler, Vera M; Kristensen, Gunnar B; Albregtsen, Fritz; Danielsen, Håvard E; Rohde, Gustavo K

2015-01-01

Nuclear texture analysis measures the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image and is a promising quantitative tool for prognosis of cancer. The aim of this study was to evaluate the prognostic value of entropy-based adaptive nuclear texture features in a total population of 354 uterine sarcomas. Isolated nuclei (monolayers) were prepared from 50 µm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices, and two superior adaptive texture features were calculated from each matrix. The 5-year crude survival was significantly higher (P < 0.001) for patients with high texture feature values (72%) than for patients with low feature values (36%). When combining DNA ploidy classification (diploid/nondiploid) and texture (high/low feature value), the patients could be stratified into three risk groups with 5-year crude survival of 77, 57, and 34% (Hazard Ratios (HR) of 1, 2.3, and 4.1, P < 0.001). Entropy-based adaptive nuclear texture was an independent prognostic marker for crude survival in multivariate analysis including relevant clinicopathological features (HR = 2.1, P = 0.001), and should therefore be considered as a potential prognostic marker in uterine sarcomas. © The Authors. Published 2014 International Society for Advancement of Cytometry PMID:25483227

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

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.

Quantum watermarking scheme through Arnold scrambling and LSB steganography

NASA Astrophysics Data System (ADS)

Zhou, Ri-Gui; Hu, Wenwen; Fan, Ping

2017-09-01

Based on the NEQR of quantum images, a new quantum gray-scale image watermarking scheme is proposed through Arnold scrambling and least significant bit (LSB) steganography. The sizes of the carrier image and the watermark image are assumed to be 2n× 2n and n× n, respectively. Firstly, a classical n× n sized watermark image with 8-bit gray scale is expanded to a 2n× 2n sized image with 2-bit gray scale. Secondly, through the module of PA-MOD N, the expanded watermark image is scrambled to a meaningless image by the Arnold transform. Then, the expanded scrambled image is embedded into the carrier image by the steganography method of LSB. Finally, the time complexity analysis is given. The simulation experiment results show that our quantum circuit has lower time complexity, and the proposed watermarking scheme is superior to others.

A method for smoothing segmented lung boundary in chest CT images

NASA Astrophysics Data System (ADS)

Yim, Yeny; Hong, Helen

2007-03-01

To segment low density lung regions in chest CT images, most of methods use the difference in gray-level value of pixels. However, radiodense pulmonary vessels and pleural nodules that contact with the surrounding anatomy are often excluded from the segmentation result. To smooth lung boundary segmented by gray-level processing in chest CT images, we propose a new method using scan line search. Our method consists of three main steps. First, lung boundary is extracted by our automatic segmentation method. Second, segmented lung contour is smoothed in each axial CT slice. We propose a scan line search to track the points on lung contour and find rapidly changing curvature efficiently. Finally, to provide consistent appearance between lung contours in adjacent axial slices, 2D closing in coronal plane is applied within pre-defined subvolume. Our method has been applied for performance evaluation with the aspects of visual inspection, accuracy and processing time. The results of our method show that the smoothness of lung contour was considerably increased by compensating for pulmonary vessels and pleural nodules.

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.

Improvement of gray-scale representation of horizontally scanning holographic display using error diffusion.

PubMed

Matsumoto, Yuji; Takaki, Yasuhiro

2014-06-15

Horizontally scanning holography can enlarge both screen size and viewing zone angle. A microelectromechanical-system spatial light modulator, which can generate only binary images, is used to generate hologram patterns. Thus, techniques to improve gray-scale representation in reconstructed images should be developed. In this study, the error diffusion technique was used for the binarization of holograms. When the Floyd-Steinberg error diffusion coefficients were used, gray-scale representation was improved. However, the linearity in the gray-scale representation was not satisfactory. We proposed the use of a correction table and showed that the linearity was greatly improved.

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.

Conventional vs  invert-grayscale X-ray for diagnosis of pneumothorax in the emergency setting.

PubMed

Musalar, Ekrem; Ekinci, Salih; Ünek, Orkun; Arş, Eda; Eren, Hakan Şevki; Gürses, Bengi; Aktaş, Can

2017-09-01

Pneumothorax is a pathologic condition in which air is accumulated between the visceral and parietal pleura. After clinical suspicion, in order to diagnose the severity of the condition, imaging is necessary. By using the help of Picture Archiving and Communication Systems (PACS) direct conventional X-rays are converted to gray-scale and this has become a preferred method among many physicians. Our study design was a case-control study with cross-over design study. Posterior-anterior chest X-rays of patients were evaluated for pneumothorax by 10 expert physicians with at least 3years of experience and who have used inverted gray-scale posterior anterior chest X-ray for diagnosing pneumothorax. The study included posterior anterior chest X-ray images of 268 patients of which 106 were diagnosed with spontaneous pneumothorax and 162 patients used as a control group. The sensitivity of Digital-conventional X-rays was found to be higher than that of inverted gray-scale images (95% CI (2,08-5,04), p<0,01). There was no statistically significant difference between the gold standard and digital-conventional images (95% CI (0,45-2,17), p=0,20), while the evaluations of the gray-scale images were found to be less sensitive for diagnosis (95% CI (3,16-5,67) p<0,01). Inverted gray-scale imaging is not a superior imaging modality over digital-conventional X-ray for the diagnosis of pneumothorax. Prospective studies should be performed where diagnostic potency of inverted gray-scale radiograms is tested against gold standard chest CT. Further research should compare inverted grayscale to lung ultrasound to assess them as alternatives prior to CT. Copyright © 2017 Elsevier Inc. All rights reserved.

Color line scan camera technology and machine vision: requirements to consider

NASA Astrophysics Data System (ADS)

Paernaenen, Pekka H. T.

1997-08-01

Color machine vision has shown a dynamic uptrend in use within the past few years as the introduction of new cameras and scanner technologies itself underscores. In the future, the movement from monochrome imaging to color will hasten, as machine vision system users demand more knowledge about their product stream. As color has come to the machine vision, certain requirements for the equipment used to digitize color images are needed. Color machine vision needs not only a good color separation but also a high dynamic range and a good linear response from the camera used. Good dynamic range and linear response is necessary for color machine vision. The importance of these features becomes even more important when the image is converted to another color space. There is always lost some information when converting integer data to another form. Traditionally the color image processing has been much slower technique than the gray level image processing due to the three times greater data amount per image. The same has applied for the three times more memory needed. The advancements in computers, memory and processing units has made it possible to handle even large color images today cost efficiently. In some cases he image analysis in color images can in fact even be easier and faster than with a similar gray level image because of more information per pixel. Color machine vision sets new requirements for lighting, too. High intensity and white color light is required in order to acquire good images for further image processing or analysis. New development in lighting technology is bringing eventually solutions for color imaging.

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

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.

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.

Topology-Preserving Rigid Transformation of 2D Digital Images.

PubMed

Ngo, Phuc; Passat, Nicolas; Kenmochi, Yukiko; Talbot, Hugues

2014-02-01

We provide conditions under which 2D digital images preserve their topological properties under rigid transformations. We consider the two most common digital topology models, namely dual adjacency and well-composedness. This paper leads to the proposal of optimal preprocessing strategies that ensure the topological invariance of images under arbitrary rigid transformations. These results and methods are proved to be valid for various kinds of images (binary, gray-level, label), thus providing generic and efficient tools, which can be used in particular in the context of image registration and warping.

[MRI for brain structure and function in patients with first-episode panic disorder].

PubMed

Zhang, Yan; Duan, Lian; Liao, Mei; Yang, Fan; Liu, Jun; Shan, Baoci; Li, Lingjiang

2011-12-01

To determine the brain function and structure in patinets with first-episode panic disorder (PD). All subjects (24 PD patients and 24 healthy subjects) received MRI scan and emotional counting Stroop task during the functional magnetic resonance imaging. Blood oxygenation level dependent functional magnetic resonance imaging and voxel-based morphometric technology were used to detect the gray matter volume. Compared with the healthy controls, left thalamus, left medial frontal gyrus, left anterior cingulate gyrus, left inferior frontal gyrus, left insula (panic-related words vs. neutral words) lacked activation in PD patients, but the over-activation were found in right brain stem, right occipital lobe/lingual gyrus in PD patients. Compared with the healthy controls, the gray matter volume in the PD patients significantly decreased in the left superior temporal gyrus, right medial frontal gyrus, left medial occipital gyrus, dorsomedial nucleus of left thalamus and right anterior cingulate gyrus. There was no significantly increased gray matter volume in any brain area in PD patients. PD patients have selective attentional bias in processing threatening information due to the depression and weakening of the frontal cingulated gyrus.

In vivo magnetic resonance spectroscopy measurement of gray-matter and white-matter gamma-aminobutyric acid concentration in sensorimotor cortex using a motion-controlled MEGA point-resolved spectroscopy sequence.

PubMed

Bhattacharyya, Pallab K; Phillips, Micheal D; Stone, Lael A; Lowe, Mark J

2011-04-01

Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter in the brain. Understanding the GABA concentration, in vivo, is important to understand normal brain function. Using MEGA point-resolved spectroscopy sequence with interleaved water scans to detect subject motion, GABA level of sensorimotor cortex was measured using a voxel identified from a functional magnetic resonance imaging scan. The GABA level in a 20×20×20-mm(3) voxel consisting of 37%±7% gray matter, 52%±12% white matter and 11%±8% cerebrospinal fluid in the sensorimotor region was measured to be 1.43±0.48 mM. In addition, using linear regression analysis, GABA concentrations within gray and white matter were calculated to be 2.87±0.61 and 0.33±0.11 mM, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

Graphics-Printing Program For The HP Paintjet Printer

NASA Technical Reports Server (NTRS)

Atkins, Victor R.

1993-01-01

IMPRINT utility computer program developed to print graphics specified in raster files by use of Hewlett-Packard Paintjet(TM) color printer. Reads bit-mapped images from files on UNIX-based graphics workstation and prints out three different types of images: wire-frame images, solid-color images, and gray-scale images. Wire-frame images are in continuous tone or, in case of low resolution, in random gray scale. In case of color images, IMPRINT also prints by use of default palette of solid colors. Written in C language.

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.

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.

Estimation of Articular Cartilage Surface Roughness Using Gray-Level Co-Occurrence Matrix of Laser Speckle Image.

PubMed

Youssef, Doaa; El-Ghandoor, Hatem; Kandel, Hamed; El-Azab, Jala; Hassab-Elnaby, Salah

2017-06-28

The application of He-Ne laser technologies for description of articular cartilage degeneration, one of the most common diseases worldwide, is an innovative usage of these technologies used primarily in material engineering. Plain radiography and magnetic resonance imaging are insufficient to allow the early assessment of the disease. As surface roughness of articular cartilage is an important indicator of articular cartilage degeneration progress, a safe and noncontact technique based on laser speckle image to estimate the surface roughness is provided. This speckle image from the articular cartilage surface, when illuminated by laser beam, gives very important information about the physical properties of the surface. An experimental setup using a low power He-Ne laser and a high-resolution digital camera was implemented to obtain speckle images of ten bovine articular cartilage specimens prepared for different average roughness values. Texture analysis method based on gray-level co-occurrence matrix (GLCM) analyzed on the captured speckle images is used to characterize the surface roughness of the specimens depending on the computation of Haralick's texture features. In conclusion, this promising method can accurately estimate the surface roughness of articular cartilage even for early signs of degeneration. The method is effective for estimation of average surface roughness values ranging from 0.09 µm to 2.51 µm with an accuracy of 0.03 µm.

Estimation of Articular Cartilage Surface Roughness Using Gray-Level Co-Occurrence Matrix of Laser Speckle Image

PubMed Central

El-Ghandoor, Hatem; Kandel, Hamed; El-Azab, Jala; Hassab-Elnaby, Salah

2017-01-01

The application of He-Ne laser technologies for description of articular cartilage degeneration, one of the most common diseases worldwide, is an innovative usage of these technologies used primarily in material engineering. Plain radiography and magnetic resonance imaging are insufficient to allow the early assessment of the disease. As surface roughness of articular cartilage is an important indicator of articular cartilage degeneration progress, a safe and noncontact technique based on laser speckle image to estimate the surface roughness is provided. This speckle image from the articular cartilage surface, when illuminated by laser beam, gives very important information about the physical properties of the surface. An experimental setup using a low power He-Ne laser and a high-resolution digital camera was implemented to obtain speckle images of ten bovine articular cartilage specimens prepared for different average roughness values. Texture analysis method based on gray-level co-occurrence matrix (GLCM) analyzed on the captured speckle images is used to characterize the surface roughness of the specimens depending on the computation of Haralick’s texture features. In conclusion, this promising method can accurately estimate the surface roughness of articular cartilage even for early signs of degeneration. The method is effective for estimation of average surface roughness values ranging from 0.09 µm to 2.51 µm with an accuracy of 0.03 µm. PMID:28773080

Substance use and regional gray matter volume in individuals at high risk of psychosis.

PubMed

Stone, James M; Bhattacharyya, Sagnik; Barker, Gareth J; McGuire, Philip K

2012-02-01

Individuals with an at risk mental state (ARMS) are at greatly increased risk of developing a psychotic illness. Risk of transition to psychosis is associated with regionally reduced cortical gray matter volume. There has been considerable interest in the interaction between psychosis risk and substance use. In this study we investigate the relationship between alcohol, cannabis and nicotine use with gray matter volume in ARMS subjects and healthy volunteers. Twenty seven ARMS subjects and 27 healthy volunteers took part in the study. All subjects underwent volumetric MRI imaging. The relationship between regional gray matter volume and cannabis use, smoking, and alcohol use in controls and ARMS subjects was analysed using voxel-based morphometry. In any region where a significant relationship with drug was present, data were analysed to determine if there was any group difference in this relationship. Alcohol intake was inversely correlated with gray matter volume in cerebellum, cannabis intake was use was inversely correlated with gray matter volume in prefrontal cortex and tobacco intake was inversely correlated with gray matter volume in left temporal cortex. There were no significant interactions by group in any region. There is no evidence to support the hypothesis of increased susceptibility to harmful effects of drugs and alcohol on regional gray matter in ARMS subjects. However, alcohol, tobacco and cannabis at low to moderate intake may be associated with lower gray matter in both ARMS subjects and healthy volunteers-possibly representing low-level cortical damage or change in neural plasticity. Copyright © 2011 Elsevier B.V. All rights reserved.

BP fusion model for the detection of oil spills on the sea by remote sensing

NASA Astrophysics Data System (ADS)

Chen, Weiwei; An, Jubai; Zhang, Hande; Lin, Bin

2003-06-01

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills" image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators" result of edge gray level and the image"s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image"s edge detection.

Association of white matter hyperintensities and gray matter volume with cognition in older individuals without cognitive impairment.

PubMed

Arvanitakis, Zoe; Fleischman, Debra A; Arfanakis, Konstantinos; Leurgans, Sue E; Barnes, Lisa L; Bennett, David A

2016-05-01

Both presence of white matter hyperintensities (WMH) and smaller total gray matter volume on brain magnetic resonance imaging (MRI) are common findings in old age, and contribute to impaired cognition. We tested whether total WMH volume and gray matter volume had independent associations with cognition in community-dwelling individuals without dementia or mild cognitive impairment (MCI). We used data from participants of the Rush Memory and Aging Project. Brain MRI was available in 209 subjects without dementia or MCI (mean age 80; education = 15 years; 74 % women). WMH and gray matter were automatically segmented, and the total WMH and gray matter volumes were measured. Both MRI-derived measures were normalized by the intracranial volume. Cognitive data included composite measures of five different cognitive domains, based on 19 individual tests. Linear regression analyses, adjusted for age, sex, and education, were used to examine the relationship of logarithmically-transformed total WMH volume and of total gray matter volume to cognition. Larger total WMH volumes were associated with lower levels of perceptual speed (p < 0.001), but not with episodic memory, semantic memory, working memory, or visuospatial abilities (all p > 0.10). Smaller total gray matter volumes were associated with lower levels of perceptual speed (p = 0.013) and episodic memory (p = 0.001), but not with the other three cognitive domains (all p > 0.14). Larger total WMH volume was correlated with smaller total gray matter volume (p < 0.001). In a model with both MRI-derived measures included, the relation of WMH to perceptual speed remained significant (p < 0.001), while gray matter volumes were no longer related (p = 0.14). This study of older community-dwelling individuals without overt cognitive impairment suggests that the association of larger total WMH volume with lower perceptual speed is independent of total gray matter volume. These results help elucidate the pathological processes leading to lower cognitive function in aging.

Comparison between different cost devices for digital capture of X-ray films: an image characteristics detection approach.

PubMed

Salazar, Antonio José; Camacho, Juan Camilo; Aguirre, Diego Andrés

2012-02-01

A common teleradiology practice is digitizing films. The costs of specialized digitizers are very high, that is why there is a trend to use conventional scanners and digital cameras. Statistical clinical studies are required to determine the accuracy of these devices, which are very difficult to carry out. The purpose of this study was to compare three capture devices in terms of their capacity to detect several image characteristics. Spatial resolution, contrast, gray levels, and geometric deformation were compared for a specialized digitizer ICR (US$ 15,000), a conventional scanner UMAX (US$ 1,800), and a digital camera LUMIX (US$ 450, but require an additional support system and a light box for about US$ 400). Test patterns printed in films were used. The results detected gray levels lower than real values for all three devices; acceptable contrast and low geometric deformation with three devices. All three devices are appropriate solutions, but a digital camera requires more operator training and more settings.

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.

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.

Bit-level quantum color image encryption scheme with quantum cross-exchange operation and hyper-chaotic system

NASA Astrophysics Data System (ADS)

Zhou, Nanrun; Chen, Weiwei; Yan, Xinyu; Wang, Yunqian

2018-06-01

In order to obtain higher encryption efficiency, a bit-level quantum color image encryption scheme by exploiting quantum cross-exchange operation and a 5D hyper-chaotic system is designed. Additionally, to enhance the scrambling effect, the quantum channel swapping operation is employed to swap the gray values of corresponding pixels. The proposed color image encryption algorithm has larger key space and higher security since the 5D hyper-chaotic system has more complex dynamic behavior, better randomness and unpredictability than those based on low-dimensional hyper-chaotic systems. Simulations and theoretical analyses demonstrate that the presented bit-level quantum color image encryption scheme outperforms its classical counterparts in efficiency and security.

[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.

Image processing on the image with pixel noise bits removed

NASA Astrophysics Data System (ADS)

Chuang, Keh-Shih; Wu, Christine

1992-06-01

Our previous studies used statistical methods to assess the noise level in digital images of various radiological modalities. We separated the pixel data into signal bits and noise bits and demonstrated visually that the removal of the noise bits does not affect the image quality. In this paper we apply image enhancement techniques on noise-bits-removed images and demonstrate that the removal of noise bits has no effect on the image property. The image processing techniques used are gray-level look up table transformation, Sobel edge detector, and 3-D surface display. Preliminary results show no noticeable difference between original image and noise bits removed image using look up table operation and Sobel edge enhancement. There is a slight enhancement of the slicing artifact in the 3-D surface display of the noise bits removed image.

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

Influence of parameter settings in voxel-based morphometry 8. Using DARTEL and region-of-interest on reproducibility in gray matter volumetry.

PubMed

Goto, M; Abe, O; Aoki, S; Hayashi, N; Miyati, T; Takao, H; Matsuda, H; Yamashita, F; Iwatsubo, T; Mori, H; Kunimatsu, A; Ino, K; Yano, K; Ohtomo, K

2015-01-01

To investigate whether reproducibility of gray matter volumetry is influenced by parameter settings for VBM 8 using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL) with region-of-interest (ROI) analyses. We prepared three-dimensional T1-weighted magnetic resonance images (3D-T1WIs) of 21 healthy subjects. All subjects were imaged with each of five MRI systems. Voxel-based morphometry 8 (VBM 8) and WFU PickAtlas software were used for gray matter volumetry. The bilateral ROI labels used were those provided as default settings with the software: Frontal Lobe, Hippocampus, Occipital Lobe, Orbital Gyrus, Parietal Lobe, Putamen, and Temporal Lobe. All 3D-T1WIs were segmented to gray matter with six parameters of VBM 8, with each parameter having between three and eight selectable levels. Reproducibility was evaluated as the standard deviation (mm³) of measured values for the five MRI systems. Reproducibility was influenced by 'Bias regularization (BiasR)', 'Bias FWHM', and 'De-noising filter' settings, but not by 'MRF weighting', 'Sampling distance', or 'Warping regularization' settings. Reproducibility in BiasR was influenced by ROI. Superior reproducibility was observed in Frontal Lobe with the BiasR1 setting, and in Hippocampus, Parietal Lobe, and Putamen with the BiasR3*, BiasR1, and BiasR5 settings, respectively. Reproducibility of gray matter volumetry was influenced by parameter settings in VBM 8 using DARTEL and ROI. In multi-center studies, the use of appropriate settings in VBM 8 with DARTEL results in reduced scanner effect.

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.

Updates to the QBIC system

NASA Astrophysics Data System (ADS)

Niblack, Carlton W.; Zhu, Xiaoming; Hafner, James L.; Breuel, Tom; Ponceleon, Dulce B.; Petkovic, Dragutin; Flickner, Myron D.; Upfal, Eli; Nin, Sigfredo I.; Sull, Sanghoon; Dom, Byron E.; Yeo, Boon-Lock; Srinivasan, Savitha; Zivkovic, Dan; Penner, Mike

1997-12-01

QBICTM (Query By Image Content) is a set of technologies and associated software that allows a user to search, browse, and retrieve image, graphic, and video data from large on-line collections. This paper discusses current research directions of the QBIC project such as indexing for high-dimensional multimedia data, retrieval of gray level images, and storyboard generation suitable for video. It describes aspects of QBIC software including scripting tools, application interfaces, and available GUIs, and gives examples of applications and demonstration systems using it.

A threshold selection method based on edge preserving

NASA Astrophysics Data System (ADS)

Lou, Liantang; Dan, Wei; Chen, Jiaqi

2015-12-01

A method of automatic threshold selection for image segmentation is presented. An optimal threshold is selected in order to preserve edge of image perfectly in image segmentation. The shortcoming of Otsu's method based on gray-level histograms is analyzed. The edge energy function of bivariate continuous function is expressed as the line integral while the edge energy function of image is simulated by discretizing the integral. An optimal threshold method by maximizing the edge energy function is given. Several experimental results are also presented to compare with the Otsu's method.

The use of in vivo fluorescence image sequences to indicate the occurrence and propagation of transient focal depolarizations in cerebral ischemia.

PubMed

Strong, A J; Harland, S P; Meldrum, B S; Whittington, D J

1996-05-01

A method for the detection and tracking of propagated fluorescence transients as indicators of depolarizations in focal cerebral ischemia is described, together with initial results indicating the potential of the method. The cortex of the right cerebral hemisphere was exposed for nonrecovery experiments in five cats anesthetized with chloralose and subjected to permanent middle cerebral artery (MCA) occlusion. Fluorescence with 370-nm excitation (attributed to the degree of reduction of the NAD/H couple) was imaged with an intensified charge-coupled device camera and digitized. Sequences of images representing changes in gray level from a baseline image were examined, together with the time courses of mean gray levels in specified regions of interest. Spontaneous increases in fluorescence occurred, starting most commonly at the edge of areas of core ischemia; they propagated usually throughout the periinfarct zone and resolved to varying degrees and at varying rates, depending on proximity of the locus to the MCA input. When a fluorescence transient reached the anterior cerebral artery territory, its initial polarity reversed from an increase to a decrease in fluorescence. An initial increase in fluorescence in response to the arrival of a transient may characterize cortex that will become infarcted, if pathophysiological changes in the periinfarct zone are allowed to evolve naturally.

Texture feature extraction based on wavelet transform and gray-level co-occurrence matrices applied to osteosarcoma diagnosis.

PubMed

Hu, Shan; Xu, Chao; Guan, Weiqiao; Tang, Yong; Liu, Yana

2014-01-01

Osteosarcoma is the most common malignant bone tumor among children and adolescents. In this study, image texture analysis was made to extract texture features from bone CR images to evaluate the recognition rate of osteosarcoma. To obtain the optimal set of features, Sym4 and Db4 wavelet transforms and gray-level co-occurrence matrices were applied to the image, with statistical methods being used to maximize the feature selection. To evaluate the performance of these methods, a support vector machine algorithm was used. The experimental results demonstrated that the Sym4 wavelet had a higher classification accuracy (93.44%) than the Db4 wavelet with respect to osteosarcoma occurrence in the epiphysis, whereas the Db4 wavelet had a higher classification accuracy (96.25%) for osteosarcoma occurrence in the diaphysis. Results including accuracy, sensitivity, specificity and ROC curves obtained using the wavelets were all higher than those obtained using the features derived from the GLCM method. It is concluded that, a set of texture features can be extracted from the wavelets and used in computer-aided osteosarcoma diagnosis systems. In addition, this study also confirms that multi-resolution analysis is a useful tool for texture feature extraction during bone CR image processing.

Real-time monitoring of ultrasound imaging of clinical high intensity focused ultrasound (HIFU) exposures

NASA Astrophysics Data System (ADS)

Ter Haar, Gail; Kennedy, James; Leslie, Tom; Wu, Feng

2005-09-01

Currently, many clinical devices use the change in gray scale seen on a real-time ultrasound image for the assessment of the success of HIFU treatment. It has been shown previously that, for a single HIFU lesion, the presence of gray-scale change was indicative of successful ablation in 100% of cases for 1.6-MHz beams, and in 90% of cases for 0.8-MHz exposures. The absence of gray-scale change was a reliable indicator of lack of ablative damage only for 0.8-MHz exposures (80%) in 80% of exposures using 1.6-MHz beams there was a lesion even in the absence of gray-scale change. This study has been extended to more realistic clinical treatment protocols. The image appearance has been studied for the different volume ablation techniques that are used in the treatment of liver and kidney cancer. The results will be presented.

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).

Changes in lactate dehydrogenase are associated with central gray matter lesions in newborns with hypoxic-ischemic encephalopathy.

PubMed

Yum, Sook Kyung; Moon, Cheong-Jun; Youn, Young-Ah; Sung, In Kyung

2017-05-01

Biomarkers may predict neurological prognosis in infants with hypoxic-ischemic encephalopathy (HIE). We evaluated the relationship between serum lactate dehydrogenase (LDH) and brain magnetic resonance imaging (MRI), which predicts neurodevelopmental outcomes, in order to assess whether LDH levels are similarly predictive. Medical records were reviewed for infants with HIE and LDH levels were assessed on the first (LDH 1 ) and third (LDH 3 ) days following birth. Receiver operating characteristic curves were obtained in relation to central gray matter hypoxic-ischemic lesions. Of 92 patients, 52 (56.5%) had hypoxic-ischemic lesions on brain MRI, and 21 of these infants (40.4%) had central gray matter lesions. LDH 1 and LDH 3 did not differ; however, the percentage change (ΔLDH%) was significantly higher in infants with central gray matter lesions (36.9% versus 6.6%, p = 0.006). With cutoffs of 187 (IU/L, ΔLDH) and 19.4 (%, ΔLDH%), the sensitivity, specificity, positive predictive value and negative predictive value were 71.4, 69.0, 40.5 and 89.1%, respectively. The relative risk was 5.57 (p = 0.001). Changes in serum LDH may be a useful biomarker for predicting future neurodevelopmental prognosis in infants with HIE.

Concept of a photon-counting camera based on a diffraction-addressed Gray-code mask

NASA Astrophysics Data System (ADS)

Morel, Sébastien

2004-09-01

A new concept of photon counting camera for fast and low-light-level imaging applications is introduced. The possible spectrum covered by this camera ranges from visible light to gamma rays, depending on the device used to transform an incoming photon into a burst of visible photons (photo-event spot) localized in an (x,y) image plane. It is actually an evolution of the existing "PAPA" (Precision Analog Photon Address) Camera that was designed for visible photons. This improvement comes from a simplified optics. The new camera transforms, by diffraction, each photo-event spot from an image intensifier or a scintillator into a cross-shaped pattern, which is projected onto a specific Gray code mask. The photo-event position is then extracted from the signal given by an array of avalanche photodiodes (or photomultiplier tubes, alternatively) downstream of the mask. After a detailed explanation of this camera concept that we have called "DIAMICON" (DIffraction Addressed Mask ICONographer), we briefly discuss about technical solutions to build such a camera.

Polished sample preparing and backscattered electron imaging and of fly ash-cement paste

NASA Astrophysics Data System (ADS)

Feng, Shuxia; Li, Yanqi

2018-03-01

In recent decades, the technology of backscattered electron imaging and image analysis was applied in more and more study of mixed cement paste because of its special advantages. Test accuracy of this technology is affected by polished sample preparation and image acquisition. In our work, effects of two factors in polished sample preparing and backscattered electron imaging were investigated. The results showed that increasing smoothing pressure could improve the flatness of polished surface and then help to eliminate interference of morphology on grey level distribution of backscattered electron images; increasing accelerating voltage was beneficial to increase gray difference among different phases in backscattered electron images.

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

PubMed

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Serum vitamin D and hippocampal gray matter volume in schizophrenia.

PubMed

Shivakumar, Venkataram; Kalmady, Sunil V; Amaresha, Anekal C; Jose, Dania; Narayanaswamy, Janardhanan C; Agarwal, Sri Mahavir; Joseph, Boban; Venkatasubramanian, Ganesan; Ravi, Vasanthapuram; Keshavan, Matcheri S; Gangadhar, Bangalore N

2015-08-30

Disparate lines of evidence including epidemiological and case-control studies have increasingly implicated vitamin D in the pathogenesis of schizophrenia. Vitamin D deficiency can lead to dysfunction of the hippocampus--a brain region hypothesized to be critically involved in schizophrenia. In this study, we examined for potential association between serum vitamin D level and hippocampal gray matter volume in antipsychotic-naïve or antipsychotic-free schizophrenia patients (n = 35). Serum vitamin D level was estimated using 25-OH vitamin D immunoassay. Optimized voxel-based morphometry was used to analyze 3-Tesla magnetic resonance imaging (MRI) (1-mm slice thickness). Ninety-seven percent of the schizophrenia patients (n = 34) had sub-optimal levels of serum vitamin D (83%, deficiency; 14%, insufficiency). A significant positive correlation was seen between vitamin D and regional gray matter volume in the right hippocampus after controlling for age, years of education and total intracranial volume (Montreal Neurological Institute (MNI) coordinates: x = 35, y = -18, z = -8; t = 4.34 pFWE(Corrected) = 0.018). These observations support a potential role of vitamin D deficiency in mediating hippocampal volume deficits, possibly through neurotrophic, neuroimmunomodulatory and glutamatergic effects. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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.

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

A Novel Machine Vision System for the Inspection of Micro-Spray Nozzle

PubMed Central

Huang, Kuo-Yi; Ye, Yu-Ting

2015-01-01

In this study, we present an application of neural network and image processing techniques for detecting the defects of an internal micro-spray nozzle. The defect regions were segmented by Canny edge detection, a randomized algorithm for detecting circles and a circle inspection (CI) algorithm. The gray level co-occurrence matrix (GLCM) was further used to evaluate the texture features of the segmented region. These texture features (contrast, entropy, energy), color features (mean and variance of gray level) and geometric features (distance variance, mean diameter and diameter ratio) were used in the classification procedures. A back-propagation neural network classifier was employed to detect the defects of micro-spray nozzles. The methodology presented herein effectively works for detecting micro-spray nozzle defects to an accuracy of 90.71%. PMID:26131678

A Novel Machine Vision System for the Inspection of Micro-Spray Nozzle.

PubMed

Huang, Kuo-Yi; Ye, Yu-Ting

2015-06-29

In this study, we present an application of neural network and image processing techniques for detecting the defects of an internal micro-spray nozzle. The defect regions were segmented by Canny edge detection, a randomized algorithm for detecting circles and a circle inspection (CI) algorithm. The gray level co-occurrence matrix (GLCM) was further used to evaluate the texture features of the segmented region. These texture features (contrast, entropy, energy), color features (mean and variance of gray level) and geometric features (distance variance, mean diameter and diameter ratio) were used in the classification procedures. A back-propagation neural network classifier was employed to detect the defects of micro-spray nozzles. The methodology presented herein effectively works for detecting micro-spray nozzle defects to an accuracy of 90.71%.

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.

Complementary-encoding holographic associative memory using a photorefractive crystal

NASA Astrophysics Data System (ADS)

Yuan, ShiFu; Wu, Minxian; Yan, Yingbai; Jin, Guofan

1996-06-01

We present a holographic implementation of accurate associative memory with only one holographic memory system. In the implementation, the stored and test images are coded by using complementary-encoding method. The recalled complete image is also a coded image that can be decoded with a decoding mask to get an original image or its complement image. The experiment shows that the complementary encoding can efficiently increase the addressing accuracy in a simple way. Instead of the above complementary-encoding method, a scheme that uses complementary area-encoding method is also proposed for the holographic implementation of gray-level image associative memory with accurate addressing.

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

GrayQb TM Single-Faced Version 2 (SF2) Hanford Plutonium Reclamation Facility (PRF) deployment report

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

Plummer, J. R.; Immel, D. M.; Serrato, M. G.

2015-11-18

The Savannah River National Laboratory (SRNL) in partnership with CH2M Plateau Remediation Company (CHPRC) deployed the GrayQb TM SF2 radiation imaging device at the Hanford Plutonium Reclamation Facility (PRF) to assist in the radiological characterization of the canyon. The deployment goal was to locate radiological contamination hot spots in the PRF canyon, where pencil tanks were removed and decontamination/debris removal operations are on-going, to support the CHPRC facility decontamination and decommissioning (D&D) effort. The PRF canyon D&D effort supports completion of the CHPRC Plutonium Finishing Plant Decommissioning Project. The GrayQb TM SF2 (Single Faced Version 2) is a non-destructive examinationmore » device developed by SRNL to generate radiation contour maps showing source locations and relative radiological levels present in the area under examination. The Hanford PRF GrayQbTM Deployment was sponsored by CH2M Plateau Remediation Company (CHPRC) through the DOE Richland Operations Office, Inter-Entity Work Order (IEWO), DOE-RL IEWO- M0SR900210.« less

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.

Earth Observations taken by the Expedition 15 Crew

NASA Image and Video Library

2007-04-30

ISS015-E-05977 (1 May 2007) --- Den Helder, Netherlands is featured in this image photographed by an Expedition 15 crewmember on the International Space Station. The city and harbor of Den Helder in the northern Netherlands has been the home port of the Dutch Royal Navy for over 175 years. Its favorable location provides access to the North Sea, and has made it an important commercial shipping port in addition to its strategic role. Bright red agricultural fields to the south of Den Helder indicate another noteworthy aspect of the region--commercial farming of tulips and hyacinth. This image is an oblique view--the camera is oriented at an angle relative to "straight down"--of the Den Helder region taken from the space station, which was located to the southeast, near Dulmen, Germany (approximately 225 kilometers away in terms of ground distance) when the image was acquired. In addition to the manmade structures of the Den Helder urban area (reddish gray to gray street grids) and dockyards to the east of the city, several striking geomorphic features are visible. The extensive gray mudflats, with their prominent branching pattern (top right), indicate that this image was acquired at low tide, and suggest the general low elevation of the region. Parallel wave patterns along the mudflats and in the Marsdiep strait are formed as water interacts with the sea bottom between Den Helder and Texel Island during tidal flow. Some ship wakes are also visible. According to scientists, the bright white-gray triangular region at the southern tip of Texel Island (bottom center) is a dune field, consisting mainly of eolian (windborne) sands deposited during the last Ice Age. Subsequent sea level rise and shoreline processes have mobilized and re-deposited these sands into their current configuration -- including a new dune field island to the southwest of Texel (bottom center).

Computer-aided diagnostic method for classification of Alzheimer's disease with atrophic image features on MR images

NASA Astrophysics Data System (ADS)

Arimura, Hidetaka; Yoshiura, Takashi; Kumazawa, Seiji; Tanaka, Kazuhiro; Koga, Hiroshi; Mihara, Futoshi; Honda, Hiroshi; Sakai, Shuji; Toyofuku, Fukai; Higashida, Yoshiharu

2008-03-01

Our goal for this study was to attempt to develop a computer-aided diagnostic (CAD) method for classification of Alzheimer's disease (AD) with atrophic image features derived from specific anatomical regions in three-dimensional (3-D) T1-weighted magnetic resonance (MR) images. Specific regions related to the cerebral atrophy of AD were white matter and gray matter regions, and CSF regions in this study. Cerebral cortical gray matter regions were determined by extracting a brain and white matter regions based on a level set based method, whose speed function depended on gradient vectors in an original image and pixel values in grown regions. The CSF regions in cerebral sulci and lateral ventricles were extracted by wrapping the brain tightly with a zero level set determined from a level set function. Volumes of the specific regions and the cortical thickness were determined as atrophic image features. Average cortical thickness was calculated in 32 subregions, which were obtained by dividing each brain region. Finally, AD patients were classified by using a support vector machine, which was trained by the image features of AD and non-AD cases. We applied our CAD method to MR images of whole brains obtained from 29 clinically diagnosed AD cases and 25 non-AD cases. As a result, the area under a receiver operating characteristic (ROC) curve obtained by our computerized method was 0.901 based on a leave-one-out test in identification of AD cases among 54 cases including 8 AD patients at early stages. The accuracy for discrimination between 29 AD patients and 25 non-AD subjects was 0.840, which was determined at the point where the sensitivity was the same as the specificity on the ROC curve. This result showed that our CAD method based on atrophic image features may be promising for detecting AD patients by using 3-D MR images.

A robust fuzzy local Information c-means clustering algorithm with noise detection

NASA Astrophysics Data System (ADS)

Shang, Jiayu; Li, Shiren; Huang, Junwei

2018-04-01

Fuzzy c-means clustering (FCM), especially with spatial constraints (FCM_S), is an effective algorithm suitable for image segmentation. Its reliability contributes not only to the presentation of fuzziness for belongingness of every pixel but also to exploitation of spatial contextual information. But these algorithms still remain some problems when processing the image with noise, they are sensitive to the parameters which have to be tuned according to prior knowledge of the noise. In this paper, we propose a new FCM algorithm, combining the gray constraints and spatial constraints, called spatial and gray-level denoised fuzzy c-means (SGDFCM) algorithm. This new algorithm conquers the parameter disadvantages mentioned above by considering the possibility of noise of each pixel, which aims to improve the robustness and obtain more detail information. Furthermore, the possibility of noise can be calculated in advance, which means the algorithm is effective and efficient.

A computer-aided diagnosis system to detect pathologies in temporal subtraction images of chest radiographs

NASA Astrophysics Data System (ADS)

Looper, Jared; Harrison, Melanie; Armato, Samuel G.

2016-03-01

Radiologists often compare sequential radiographs to identify areas of pathologic change; however, this process is prone to error, as human anatomy can obscure the regions of change, causing the radiologists to overlook pathology. Temporal subtraction (TS) images can provide enhanced visualization of regions of change in sequential radiographs and allow radiologists to better detect areas of change in radiographs. Not all areas of change shown in TS images, however, are actual pathology. The purpose of this study was to create a computer-aided diagnostic (CAD) system that identifies which regions of change are caused by pathology and which are caused by misregistration of the radiographs used to create the TS image. The dataset used in this study contained 120 images with 74 pathologic regions on 54 images outlined by an experienced radiologist. High and low ("light" and "dark") gray-level candidate regions were extracted from the images using gray-level thresholding. Then, sampling techniques were used to address the class imbalance problem between "true" and "false" candidate regions. Next, the datasets of light candidate regions, dark candidate regions, and the combined set of light and dark candidate regions were used as training and testing data for classifiers by using five-fold cross validation. Of the classifiers tested (support vector machines, discriminant analyses, logistic regression, and k-nearest neighbors), the support vector machine on the combined candidates using synthetic minority oversampling technique (SMOTE) performed best with an area under the receiver operating characteristic curve value of 0.85, a sensitivity of 85%, and a specificity of 84%.

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…

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.

Integrating image processing and classification technology into automated polarizing film defect inspection

NASA Astrophysics Data System (ADS)

Kuo, Chung-Feng Jeffrey; Lai, Chun-Yu; Kao, Chih-Hsiang; Chiu, Chin-Hsun

2018-05-01

In order to improve the current manual inspection and classification process for polarizing film on production lines, this study proposes a high precision automated inspection and classification system for polarizing film, which is used for recognition and classification of four common defects: dent, foreign material, bright spot, and scratch. First, the median filter is used to remove the impulse noise in the defect image of polarizing film. The random noise in the background is smoothed by the improved anisotropic diffusion, while the edge detail of the defect region is sharpened. Next, the defect image is transformed by Fourier transform to the frequency domain, combined with a Butterworth high pass filter to sharpen the edge detail of the defect region, and brought back by inverse Fourier transform to the spatial domain to complete the image enhancement process. For image segmentation, the edge of the defect region is found by Canny edge detector, and then the complete defect region is obtained by two-stage morphology processing. For defect classification, the feature values, including maximum gray level, eccentricity, the contrast, and homogeneity of gray level co-occurrence matrix (GLCM) extracted from the images, are used as the input of the radial basis function neural network (RBFNN) and back-propagation neural network (BPNN) classifier, 96 defect images are then used as training samples, and 84 defect images are used as testing samples to validate the classification effect. The result shows that the classification accuracy by using RBFNN is 98.9%. Thus, our proposed system can be used by manufacturing companies for a higher yield rate and lower cost. The processing time of one single image is 2.57 seconds, thus meeting the practical application requirement of an industrial production line.

Female adolescents with severe substance and conduct problems have substantially less brain gray matter volume.

PubMed

Dalwani, Manish S; McMahon, Mary Agnes; Mikulich-Gilbertson, Susan K; Young, Susan E; Regner, Michael F; Raymond, Kristen M; McWilliams, Shannon K; Banich, Marie T; Tanabe, Jody L; Crowley, Thomas J; Sakai, Joseph T

2015-01-01

Structural neuroimaging studies have demonstrated lower regional gray matter volume in adolescents with severe substance and conduct problems. These research studies, including ours, have generally focused on male-only or mixed-sex samples of adolescents with conduct and/or substance problems. Here we compare gray matter volume between female adolescents with severe substance and conduct problems and female healthy controls of similar ages. Female adolescents with severe substance and conduct problems will show significantly less gray matter volume in frontal regions critical to inhibition (i.e. dorsolateral prefrontal cortex and ventrolateral prefrontal cortex), conflict processing (i.e., anterior cingulate), valuation of expected outcomes (i.e., medial orbitofrontal cortex) and the dopamine reward system (i.e. striatum). We conducted whole-brain voxel-based morphometric comparison of structural MR images of 22 patients (14-18 years) with severe substance and conduct problems and 21 controls of similar age using statistical parametric mapping (SPM) and voxel-based morphometric (VBM8) toolbox. We tested group differences in regional gray matter volume with analyses of covariance, adjusting for age and IQ at p<0.05, corrected for multiple comparisons at whole-brain cluster-level threshold. Female adolescents with severe substance and conduct problems compared to controls showed significantly less gray matter volume in right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, medial orbitofrontal cortex, anterior cingulate, bilateral somatosensory cortex, left supramarginal gyrus, and bilateral angular gyrus. Considering the entire brain, patients had 9.5% less overall gray matter volume compared to controls. Female adolescents with severe substance and conduct problems in comparison to similarly aged female healthy controls showed substantially lower gray matter volume in brain regions involved in inhibition, conflict processing, valuation of outcomes, decision-making, reward, risk-taking, and rule-breaking antisocial behavior.

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.

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

Spoofing detection on facial images recognition using LBP and GLCM combination

NASA Astrophysics Data System (ADS)

Sthevanie, F.; Ramadhani, K. N.

2018-03-01

The challenge for the facial based security system is how to detect facial image falsification such as facial image spoofing. Spoofing occurs when someone try to pretend as a registered user to obtain illegal access and gain advantage from the protected system. This research implements facial image spoofing detection method by analyzing image texture. The proposed method for texture analysis combines the Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) method. The experimental results show that spoofing detection using LBP and GLCM combination achieves high detection rate compared to that of using only LBP feature or GLCM feature.

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

Efficient OCT Image Enhancement Based on Collaborative Shock Filtering

PubMed Central

2018-01-01

Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments. PMID:29599954

Efficient OCT Image Enhancement Based on Collaborative Shock Filtering.

PubMed

Liu, Guohua; Wang, Ziyu; Mu, Guoying; Li, Peijin

2018-01-01

Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments.

On the detection of pornographic digital images

NASA Astrophysics Data System (ADS)

Schettini, Raimondo; Brambilla, Carla; Cusano, Claudio; Ciocca, Gianluigi

2003-06-01

The paper addresses the problem of distinguishing between pornographic and non-pornographic photographs, for the design of semantic filters for the web. Both, decision forests of trees built according to CART (Classification And Regression Trees) methodology and Support Vectors Machines (SVM), have been used to perform the classification. The photographs are described by a set of low-level features, features that can be automatically computed simply on gray-level and color representation of the image. The database used in our experiments contained 1500 photographs, 750 of which labeled as pornographic on the basis of the independent judgement of several viewers.

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.

Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure☆

PubMed Central

Frick, Andreas; Gingnell, Malin; Marquand, Andre F.; Howner, Katarina; Fischer, Håkan; Kristiansson, Marianne; Williams, Steven C.R.; Fredrikson, Mats; Furmark, Tomas

2014-01-01

Functional neuroimaging of social anxiety disorder (SAD) support altered neural activation to threat-provoking stimuli focally in the fear network, while structural differences are distributed over the temporal and frontal cortices as well as limbic structures. Previous neuroimaging studies have investigated the brain at the voxel level using mass-univariate methods which do not enable detection of more complex patterns of activity and structural alterations that may separate SAD from healthy individuals. Support vector machine (SVM) is a supervised machine learning method that capitalizes on brain activation and structural patterns to classify individuals. The aim of this study was to investigate if it is possible to discriminate SAD patients (n = 14) from healthy controls (n = 12) using SVM based on (1) functional magnetic resonance imaging during fearful face processing and (2) regional gray matter volume. Whole brain and region of interest (fear network) SVM analyses were performed for both modalities. For functional scans, significant classifications were obtained both at whole brain level and when restricting the analysis to the fear network while gray matter SVM analyses correctly classified participants only when using the whole brain search volume. These results support that SAD is characterized by aberrant neural activation to affective stimuli in the fear network, while disorder-related alterations in regional gray matter volume are more diffusely distributed over the whole brain. SVM may thus be useful for identifying imaging biomarkers of SAD. PMID:24239689

Gray Matter Hypertrophy and Thickening with Obstructive Sleep Apnea in Middle-aged and Older Adults.

PubMed

Baril, Andrée-Ann; Gagnon, Katia; Brayet, Pauline; Montplaisir, Jacques; De Beaumont, Louis; Carrier, Julie; Lafond, Chantal; L'Heureux, Francis; Gagnon, Jean-François; Gosselin, Nadia

2017-06-01

Obstructive sleep apnea causes intermittent hypoxemia, hemodynamic fluctuations, and sleep fragmentation, all of which could damage cerebral gray matter that can be indirectly assessed by neuroimaging. To investigate whether markers of obstructive sleep apnea severity are associated with gray matter changes among middle-aged and older individuals. Seventy-one subjects (ages, 55-76 yr; apnea-hypopnea index, 0.2-96.6 events/h) were evaluated by magnetic resonance imaging. Two techniques were used: (1) voxel-based morphometry, which measures gray matter volume and concentration; and (2) FreeSurfer (an open source software suite) automated segmentation, which estimates the volume of predefined cortical/subcortical regions and cortical thickness. Regression analyses were performed between gray matter characteristics and markers of obstructive sleep apnea severity (hypoxemia, respiratory disturbances, and sleep fragmentation). Subjects had few symptoms, that is, sleepiness, depression, anxiety, and cognitive deficits. Although no association was found with voxel-based morphometry, FreeSurfer revealed increased gray matter with obstructive sleep apnea. Higher levels of hypoxemia correlated with increased volume and thickness of the left lateral prefrontal cortex as well as increased thickness of the right frontal pole, the right lateral parietal lobules, and the left posterior cingulate cortex. Respiratory disturbances positively correlated with right amygdala volume, and more severe sleep fragmentation was associated with increased thickness of the right inferior frontal gyrus. Gray matter hypertrophy and thickening were associated with hypoxemia, respiratory disturbances, and sleep fragmentation. These structural changes in a group of middle-aged and older individuals may represent adaptive/reactive brain mechanisms attributed to a presymptomatic stage of obstructive sleep apnea.

Imaging Lenticular Autofluorescence in Older Subjects.

PubMed

Charng, Jason; Tan, Rose; Luu, Chi D; Sadigh, Sam; Stambolian, Dwight; Guymer, Robyn H; Jacobson, Samuel G; Cideciyan, Artur V

2017-10-01

To evaluate whether a practical method of imaging lenticular autofluorescence (AF) can provide an individualized measure correlated with age-related lens yellowing in older subjects undergoing tests involving shorter wavelength lights. Lenticular AF was imaged with 488-nm excitation using a confocal scanning laser ophthalmoscope (cSLO) routinely used for retinal AF imaging. There were 75 older subjects (ages 47-87) at two sites; a small cohort of younger subjects served as controls. At one site, the cSLO was equipped with an internal reference to allow quantitative AF measurements; at the other site, reduced-illuminance AF imaging (RAFI) was used. In a subset of subjects, lens density index was independently estimated from dark-adapted spectral sensitivities performed psychophysically. Lenticular AF intensity was significantly higher in the older eyes than the younger cohort when measured with the internal reference (59.2 ± 15.4 vs. 134.4 ± 31.7 gray levels; P < 0.05) as well as when recorded with RAFI without the internal reference (10.9 ± 1.5 vs. 26.1 ± 5.7 gray levels; P < 0.05). Lenticular AF was positively correlated with age; however, there could also be large differences between individuals of similar age. Lenticular AF intensity correlated well with lens density indices estimated from psychophysical measures. Lenticular AF measured with a retinal cSLO can provide a practical and individualized measure of lens yellowing, and may be a good candidate to distinguish between preretinal and retinal deficits involving short-wavelength lights in older eyes.

Development of a video-based slurry sensor for on-line ash analysis. Fifth quarterly technical progress report, October 1, 1995--December 31, 1995

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

Adel, G.T.; Luttrell, G.H.

Automatic control of fine coal cleaning circuits has traditionally been limited by the lack of sensors for on-line ash analysis. Although several nuclear-based analyzers are available, none have seen widespread acceptance. This is largely due to the fact that nuclear sensors are expensive and tend to be influenced by changes in seam type and pyrite content. Recently, researchers at VPI&SU have developed an optical sensor for phosphate analysis. The sensor uses image processing technology to analyze video images of phosphate ore. It is currently being used by PCS Phosphate for off-line analysis of dry flotation concentrate. The primary advantages ofmore » optical sensors over nuclear sensors are that hey are significantly cheaper, are not subject to measurement variations due to changes in high atomic number materials, are inherently safer and require no special radiation permitting. The purpose of this work is to apply the knowledge gained in the development of an optical phosphate analyzer to the development of an on-line ash analyzer for fine coal slurries. During the past quarter, the current prototype of the on-line optical ash analyzer was subjected to extensive testing at the Middlefork coal preparation plant. Initial work focused on obtaining correlations between ash content and mean gray level, while developmental work on the more comprehensive neural network calibration approach continued. Test work to date shows a promising trend in the correlation between ash content and mean gray level. Unfortunately, data scatter remains significant. Recent tests seem to eliminate variations in percent solids, particle size distribution, measurement angle and light setting as causes for the data scatter; however, equipment warm-up time and number of images taken per measurement appear to have a significant impact on the gray-level values obtained. 8 figs., 8 tabs.« less

Metacarpal head biomechanics: a comparative backscattered electron image analysis of trabecular bone mineral density in Pan troglodytes, Pongo pygmaeus, and Homo sapiens.

PubMed

Zeininger, Angel; Richmond, Brian G; Hartman, Gideon

2011-06-01

Great apes and humans use their hands in fundamentally different ways, but little is known about joint biomechanics and internal bone variation. This study examines the distribution of mineral density in the third metacarpal heads in three hominoid species that differ in their habitual joint postures and loading histories. We test the hypothesis that micro-architectural properties relating to bone mineral density reflect habitual joint use. The third metacarpal heads of Pan troglodytes, Pongo pygmaeus, and Homo sapiens were sectioned in a sagittal plane and imaged using backscattered electron microscopy (BSE-SEM). For each individual, 72 areas of subarticular cortical (subchondral) and trabecular bone were sampled from within 12 consecutive regions of the BSE-SEM images. In each area, gray levels (representing relative mineralization density) were quantified. Results show that chimpanzee, orangutan, and human metacarpal III heads have different gray level distributions. Weighted mean gray levels (WMGLs) in the chimpanzee showed a distinct pattern in which the 'knuckle-walking' regions (dorsal) and 'climbing' regions (palmar) are less mineralized, interpreted to reflect elevated remodeling rates, than the distal regions. Pongo pygmaeus exhibited the lowest WMGLs in the distal region, suggesting elevated remodeling rates in this region, which is loaded during hook grip hand postures associated with suspension and climbing. Differences among regions within metacarpal heads of the chimpanzee and orangutan specimens are significant (Kruskal-Wallis, p < 0.001). In humans, whose hands are used for manipulation as opposed to locomotion, mineralization density is much more uniform throughout the metacarpal head. WMGLs were significantly (p < 0.05) lower in subchondral compared to trabecular regions in all samples except humans. This micro-architectural approach offers a means of investigating joint loading patterns in primates and shows significant differences in metacarpal joint biomechanics among great apes and humans. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

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…

Can we trust the calculation of texture indices of CT images? A phantom study.

PubMed

Caramella, Caroline; Allorant, Adrien; Orlhac, Fanny; Bidault, Francois; Asselain, Bernard; Ammari, Samy; Jaranowski, Patricia; Moussier, Aurelie; Balleyguier, Corinne; Lassau, Nathalie; Pitre-Champagnat, Stephanie

2018-04-01

Texture analysis is an emerging tool in the field of medical imaging analysis. However, many issues have been raised in terms of its use in assessing patient images and it is crucial to harmonize and standardize this new imaging measurement tool. This study was designed to evaluate the reliability of texture indices of CT images on a phantom including a reproducibility study, to assess the discriminatory capacity of indices potentially relevant in CT medical images and to determine their redundancy. For the reproducibility and discriminatory analysis, eight identical CT acquisitions were performed on a phantom including one homogeneous insert and two close heterogeneous inserts. Texture indices were selected for their high reproducibility and capability of discriminating different textures. For the redundancy analysis, 39 acquisitions of the same phantom were performed using varying acquisition parameters and a correlation matrix was used to explore the 2 × 2 relationships. LIFEx software was used to explore 34 different parameters including first order and texture indices. Only eight indices of 34 exhibited high reproducibility and discriminated textures from each other. Skewness and kurtosis from histogram were independent from the six other indices but were intercorrelated, the other six indices correlated in diverse degrees (entropy, dissimilarity, and contrast of the co-occurrence matrix, contrast of the Neighborhood Gray Level difference matrix, SZE, ZLNU of the Gray-Level Size Zone Matrix). Care should be taken when using texture analysis as a tool to characterize CT images because changes in quantitation may be primarily due to internal variability rather than from real physio-pathological effects. Some textural indices appear to be sufficiently reliable and capable to discriminate close textures on CT images. © 2018 American Association of Physicists in Medicine.

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.

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.

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.

Application of texture analysis method for mammogram density classification

NASA Astrophysics Data System (ADS)

Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

Adaptive pixel-to-pixel projection intensity adjustment for measuring a shiny surface using orthogonal color fringe pattern projection

NASA Astrophysics Data System (ADS)

Chen, Chao; Gao, Nan; Wang, Xiangjun; Zhang, Zonghua

2018-05-01

Three-dimensional (3D) shape measurement based on fringe pattern projection techniques has been commonly used in various fields. One of the remaining challenges in fringe pattern projection is that camera sensor saturation may occur if there is a large range of reflectivity variation across the surface that causes measurement errors. To overcome this problem, a novel fringe pattern projection method is proposed to avoid image saturation and maintain high-intensity modulation for measuring shiny surfaces by adaptively adjusting the pixel-to-pixel projection intensity according to the surface reflectivity. First, three sets of orthogonal color fringe patterns and a sequence of uniform gray-level patterns with different gray levels are projected onto a measured surface by a projector. The patterns are deformed with respect to the object surface and captured by a camera from a different viewpoint. Subsequently, the optimal projection intensity at each pixel is determined by fusing different gray levels and transforming the camera pixel coordinate system into the projector pixel coordinate system. Finally, the adapted fringe patterns are created and used for 3D shape measurement. Experimental results on a flat checkerboard and shiny objects demonstrate that the proposed method can measure shiny surfaces with high accuracy.

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.

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.

Detecting functional magnetic resonance imaging activation in white matter: Interhemispheric transfer across the corpus callosum

PubMed Central

Mazerolle, Erin L; D'Arcy, Ryan CN; Beyea, Steven D

2008-01-01

Background It is generally believed that activation in functional magnetic resonance imaging (fMRI) is restricted to gray matter. Despite this, a number of studies have reported white matter activation, particularly when the corpus callosum is targeted using interhemispheric transfer tasks. These findings suggest that fMRI signals may not be neatly confined to gray matter tissue. In the current experiment, 4 T fMRI was employed to evaluate whether it is possible to detect white matter activation. We used an interhemispheric transfer task modelled after neurological studies of callosal disconnection. It was hypothesized that white matter activation could be detected using fMRI. Results Both group and individual data were considered. At liberal statistical thresholds (p < 0.005, uncorrected), group level activation was detected in the isthmus of the corpus callosum. This region connects the superior parietal cortices, which have been implicated previously in interhemispheric transfer. At the individual level, five of the 24 subjects (21%) had activation clusters that were located primarily within the corpus callosum. Consistent with the group results, the clusters of all five subjects were located in posterior callosal regions. The signal time courses for these clusters were comparable to those observed for task related gray matter activation. Conclusion The findings support the idea that, despite the inherent challenges, fMRI activation can be detected in the corpus callosum at the individual level. Future work is needed to determine whether the detection of this activation can be improved by utilizing higher spatial resolution, optimizing acquisition parameters, and analyzing the data with tissue specific models of the hemodynamic response. The ability to detect white matter fMRI activation expands the scope of basic and clinical brain mapping research, and provides a new approach for understanding brain connectivity. PMID:18789154

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.

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.

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.

Infrared image segmentation method based on spatial coherence histogram and maximum entropy

NASA Astrophysics Data System (ADS)

Liu, Songtao; Shen, Tongsheng; Dai, Yao

2014-11-01

In order to segment the target well and suppress background noises effectively, an infrared image segmentation method based on spatial coherence histogram and maximum entropy is proposed. First, spatial coherence histogram is presented by weighting the importance of the different position of these pixels with the same gray-level, which is obtained by computing their local density. Then, after enhancing the image by spatial coherence histogram, 1D maximum entropy method is used to segment the image. The novel method can not only get better segmentation results, but also have a faster computation time than traditional 2D histogram-based segmentation methods.

Characterization of coronary plaque regions in intravascular ultrasound images using a hybrid ensemble classifier.

PubMed

Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Shin, Eun Seok; Kim, Sung Min

2018-01-01

The purpose of this study was to propose a hybrid ensemble classifier to characterize coronary plaque regions in intravascular ultrasound (IVUS) images. Pixels were allocated to one of four tissues (fibrous tissue (FT), fibro-fatty tissue (FFT), necrotic core (NC), and dense calcium (DC)) through processes of border segmentation, feature extraction, feature selection, and classification. Grayscale IVUS images and their corresponding virtual histology images were acquired from 11 patients with known or suspected coronary artery disease using 20 MHz catheter. A total of 102 hybrid textural features including first order statistics (FOS), gray level co-occurrence matrix (GLCM), extended gray level run-length matrix (GLRLM), Laws, local binary pattern (LBP), intensity, and discrete wavelet features (DWF) were extracted from IVUS images. To select optimal feature sets, genetic algorithm was implemented. A hybrid ensemble classifier based on histogram and texture information was then used for plaque characterization in this study. The optimal feature set was used as input of this ensemble classifier. After tissue characterization, parameters including sensitivity, specificity, and accuracy were calculated to validate the proposed approach. A ten-fold cross validation approach was used to determine the statistical significance of the proposed method. Our experimental results showed that the proposed method had reliable performance for tissue characterization in IVUS images. The hybrid ensemble classification method outperformed other existing methods by achieving characterization accuracy of 81% for FFT and 75% for NC. In addition, this study showed that Laws features (SSV and SAV) were key indicators for coronary tissue characterization. The proposed method had high clinical applicability for image-based tissue characterization. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Gray matter network measures are associated with cognitive decline in mild cognitive impairment.

PubMed

Dicks, Ellen; Tijms, Betty M; Ten Kate, Mara; Gouw, Alida A; Benedictus, Marije R; Teunissen, Charlotte E; Barkhof, Frederik; Scheltens, Philip; van der Flier, Wiesje M

2018-01-01

Gray matter networks are disrupted in Alzheimer's disease and related to cognitive impairment. However, it is still unclear whether these disruptions are associated with cognitive decline over time. Here, we studied this question in a large sample of patients with mild cognitive impairment with extensive longitudinal neuropsychological assessments. Gray matter networks were extracted from baseline structural magnetic resonance imaging, and we tested associations of network measures and cognitive decline in Mini-Mental State Examination and 5 cognitive domains (i.e., memory, attention, executive function, visuospatial, and language). Disrupted network properties were cross-sectionally related to worse cognitive impairment. Longitudinally, lower small-world coefficient values were associated with a steeper decline in almost all domains. Lower betweenness centrality values correlated with a faster decline in Mini-Mental State Examination and memory, and at a regional level, these associations were specific for the precuneus, medial frontal, and temporal cortex. Furthermore, network measures showed additive value over established biomarkers in predicting cognitive decline. Our results suggest that gray matter network measures might have use in identifying patients who will show fast disease progression. Copyright © 2017 Elsevier Inc. All rights reserved.

Method used to test the imaging consistency of binocular camera's left-right optical system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Jie; Xue, Yaoke; Yang, Shaodong; Zhao, Hui

2016-09-01

To binocular camera, the consistency of optical parameters of the left and the right optical system is an important factor that will influence the overall imaging consistency. In conventional testing procedure of optical system, there lacks specifications suitable for evaluating imaging consistency. In this paper, considering the special requirements of binocular optical imaging system, a method used to measure the imaging consistency of binocular camera is presented. Based on this method, a measurement system which is composed of an integrating sphere, a rotary table and a CMOS camera has been established. First, let the left and the right optical system capture images in normal exposure time under the same condition. Second, a contour image is obtained based on the multiple threshold segmentation result and the boundary is determined using the slope of contour lines near the pseudo-contour line. Third, the constraint of gray level based on the corresponding coordinates of left-right images is established and the imaging consistency could be evaluated through standard deviation σ of the imaging grayscale difference D (x, y) between the left and right optical system. The experiments demonstrate that the method is suitable for carrying out the imaging consistency testing for binocular camera. When the standard deviation 3σ distribution of imaging gray difference D (x, y) between the left and right optical system of the binocular camera does not exceed 5%, it is believed that the design requirements have been achieved. This method could be used effectively and paves the way for the imaging consistency testing of the binocular camera.

A novel segmentation method for uneven lighting image with noise injection based on non-local spatial information and intuitionistic fuzzy entropy

NASA Astrophysics Data System (ADS)

Yu, Haiyan; Fan, Jiulun

2017-12-01

Local thresholding methods for uneven lighting image segmentation always have the limitations that they are very sensitive to noise injection and that the performance relies largely upon the choice of the initial window size. This paper proposes a novel algorithm for segmenting uneven lighting images with strong noise injection based on non-local spatial information and intuitionistic fuzzy theory. We regard an image as a gray wave in three-dimensional space, which is composed of many peaks and troughs, and these peaks and troughs can divide the image into many local sub-regions in different directions. Our algorithm computes the relative characteristic of each pixel located in the corresponding sub-region based on fuzzy membership function and uses it to replace its absolute characteristic (its gray level) to reduce the influence of uneven light on image segmentation. At the same time, the non-local adaptive spatial constraints of pixels are introduced to avoid noise interference with the search of local sub-regions and the computation of local characteristics. Moreover, edge information is also taken into account to avoid false peak and trough labeling. Finally, a global method based on intuitionistic fuzzy entropy is employed on the wave transformation image to obtain the segmented result. Experiments on several test images show that the proposed method has excellent capability of decreasing the influence of uneven illumination on images and noise injection and behaves more robustly than several classical global and local thresholding methods.

Assessment of spatial information for hyperspectral imaging of lesion

NASA Astrophysics Data System (ADS)

Yang, Xue; Li, Gang; Lin, Ling

2016-10-01

Multiple diseases such as breast tumor poses a great threat to women's health and life, while the traditional detection method is complex, costly and unsuitable for frequently self-examination, therefore, an inexpensive, convenient and efficient method for tumor self-inspection is needed urgently, and lesion localization is an important step. This paper proposes an self-examination method for positioning of a lesion. The method adopts transillumination to acquire the hyperspectral images and to assess the spatial information of lesion. Firstly, multi-wavelength sources are modulated with frequency division, which is advantageous to separate images of different wavelength, meanwhile, the source serves as fill light to each other to improve the sensitivity in the low-lightlevel imaging. Secondly, the signal-to-noise ratio of transmitted images after demodulation are improved by frame accumulation technology. Next, gray distributions of transmitted images are analyzed. The gray-level differences is constituted by the actual transmitted images and fitting transmitted images of tissue without lesion, which is to rule out individual differences. Due to scattering effect, there will be transition zones between tissue and lesion, and the zone changes with wavelength change, which will help to identify the structure details of lesion. Finally, image segmentation is adopted to extract the lesion and the transition zones, and the spatial features of lesion are confirmed according to the transition zones and the differences of transmitted light intensity distributions. Experiment using flat-shaped tissue as an example shows that the proposed method can extract the space information of lesion.

Diagnostic analysis of liver B ultrasonic texture features based on LM neural network

NASA Astrophysics Data System (ADS)

Chi, Qingyun; Hua, Hu; Liu, Menglin; Jiang, Xiuying

2017-03-01

In this study, B ultrasound images of 124 benign and malignant patients were randomly selected as the study objects. The B ultrasound images of the liver were treated by enhanced de-noising. By constructing the gray level co-occurrence matrix which reflects the information of each angle, Principal Component Analysis of 22 texture features were extracted and combined with LM neural network for diagnosis and classification. Experimental results show that this method is a rapid and effective diagnostic method for liver imaging, which provides a quantitative basis for clinical diagnosis of liver diseases.

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.

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.

Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

NASA Astrophysics Data System (ADS)

Wutsqa, D. U.; Marwah, M.

2017-06-01

In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

Image encryption using a synchronous permutation-diffusion technique

NASA Astrophysics Data System (ADS)

Enayatifar, Rasul; Abdullah, Abdul Hanan; Isnin, Ismail Fauzi; Altameem, Ayman; Lee, Malrey

2017-03-01

In the past decade, the interest on digital images security has been increased among scientists. A synchronous permutation and diffusion technique is designed in order to protect gray-level image content while sending it through internet. To implement the proposed method, two-dimensional plain-image is converted to one dimension. Afterward, in order to reduce the sending process time, permutation and diffusion steps for any pixel are performed in the same time. The permutation step uses chaotic map and deoxyribonucleic acid (DNA) to permute a pixel, while diffusion employs DNA sequence and DNA operator to encrypt the pixel. Experimental results and extensive security analyses have been conducted to demonstrate the feasibility and validity of this proposed image encryption method.

Simultaneous multiplexing and encoding of multiple images based on a double random phase encryption system

NASA Astrophysics Data System (ADS)

Alfalou, Ayman; Mansour, Ali

2009-09-01

Nowadays, protecting information is a major issue in any transmission system, as showed by an increasing number of research papers related to this topic. Optical encoding methods, such as a Double Random Phase encryption system i.e. DRP, are widely used and cited in the literature. DRP systems have very simple principle and they are easily applicable to most images (B&W, gray levels or color). Moreover, some applications require an enhanced encoding level based on multiencryption scheme and including biometric keys (as digital fingerprints). The enhancement should be done without increasing transmitted or stored information. In order to achieve that goal, a new approach for simultaneous multiplexing & encoding of several target images is developed in this manuscript. By introducing two additional security levels, our approach enhances the security level of a classic "DRP" system. Our first security level consists in using several independent image-keys (randomly and structurally) along with a new multiplexing algorithm. At this level, several target images (multiencryption) are used. This part can reduce needed information (encoding information). At the second level a standard DRP system is included. Finally, our approach can detect if any vandalism attempt has been done on transmitted encrypted images.

Magnetization Transfer Ratio Relates to Cognitive Impairment in Normal Elderly

PubMed Central

Seiler, Stephan; Pirpamer, Lukas; Hofer, Edith; Duering, Marco; Jouvent, Eric; Fazekas, Franz; Mangin, Jean-Francois; Chabriat, Hugues; Dichgans, Martin; Ropele, Stefan; Schmidt, Reinhold

2014-01-01

Magnetization transfer imaging (MTI) can detect microstructural brain tissue changes and may be helpful in determining age-related cerebral damage. We investigated the association between the magnetization transfer ratio (MTR) in gray and white matter (WM) and cognitive functioning in 355 participants of the Austrian stroke prevention family study (ASPS-Fam) aged 38–86 years. MTR maps were generated for the neocortex, deep gray matter structures, WM hyperintensities, and normal appearing WM (NAWM). Adjusted mixed models determined whole brain and lobar cortical MTR to be directly and significantly related to performance on tests of memory, executive function, and motor skills. There existed an almost linear dose-effect relationship. MTR of deep gray matter structures and NAWM correlated to executive functioning. All associations were independent of demographics, vascular risk factors, focal brain lesions, and cortex volume. Further research is needed to understand the basis of this association at the tissue level, and to determine the role of MTR in predicting cognitive decline and dementia. PMID:25309438

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

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.

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.

Cervical vertebral bone mineral density changes in adolescents during orthodontic treatment.

PubMed

Crawford, Bethany; Kim, Do-Gyoon; Moon, Eun-Sang; Johnson, Elizabeth; Fields, Henry W; Palomo, J Martin; Johnston, William M

2014-08-01

The cervical vertebral maturation (CVM) stages have been used to estimate facial growth status. In this study, we examined whether cone-beam computed tomography images can be used to detect changes of CVM-related parameters and bone mineral density distribution in adolescents during orthodontic treatment. Eighty-two cone-beam computed tomography images were obtained from 41 patients before (14.47 ± 1.42 years) and after (16.15 ± 1.38 years) orthodontic treatment. Two cervical vertebral bodies (C2 and C3) were digitally isolated from each image, and their volumes, means, and standard deviations of gray-level histograms were measured. The CVM stages and mandibular lengths were also estimated after converting the cone-beam computed tomography images. Significant changes for the examined variables were detected during the observation period (P ≤0.018) except for C3 vertebral body volume (P = 0.210). The changes of CVM stage had significant positive correlations with those of vertebral body volume (P ≤0.021). The change of the standard deviation of bone mineral density (variability) showed significant correlations with those of vertebral body volume and mandibular length for C2 (P ≤0.029). The means and variability of the gray levels account for bone mineral density and active remodeling, respectively. Our results indicate that bone mineral density distribution and the volume of the cervical vertebral body changed because of active bone remodeling during maturation. Copyright © 2014 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Cerebral Metabolic Rate of Oxygen (CMRO2 ) Mapping by Combining Quantitative Susceptibility Mapping (QSM) and Quantitative Blood Oxygenation Level-Dependent Imaging (qBOLD).

PubMed

Cho, Junghun; Kee, Youngwook; Spincemaille, Pascal; Nguyen, Thanh D; Zhang, Jingwei; Gupta, Ajay; Zhang, Shun; Wang, Yi

2018-03-07

To map the cerebral metabolic rate of oxygen (CMRO 2 ) by estimating the oxygen extraction fraction (OEF) from gradient echo imaging (GRE) using phase and magnitude of the GRE data. 3D multi-echo gradient echo imaging and perfusion imaging with arterial spin labeling were performed in 11 healthy subjects. CMRO 2 and OEF maps were reconstructed by joint quantitative susceptibility mapping (QSM) to process GRE phases and quantitative blood oxygen level-dependent (qBOLD) modeling to process GRE magnitudes. Comparisons with QSM and qBOLD alone were performed using ROI analysis, paired t-tests, and Bland-Altman plot. The average CMRO 2 value in cortical gray matter across subjects were 140.4 ± 14.9, 134.1 ± 12.5, and 184.6 ± 17.9 μmol/100 g/min, with corresponding OEFs of 30.9 ± 3.4%, 30.0 ± 1.8%, and 40.9 ± 2.4% for methods based on QSM, qBOLD, and QSM+qBOLD, respectively. QSM+qBOLD provided the highest CMRO 2 contrast between gray and white matter, more uniform OEF than QSM, and less noisy OEF than qBOLD. Quantitative CMRO 2 mapping that fits the entire complex GRE data is feasible by combining QSM analysis of phase and qBOLD analysis of magnitude. © 2018 International Society for Magnetic Resonance in Medicine.

Imaging Lenticular Autofluorescence in Older Subjects

PubMed Central

Charng, Jason; Tan, Rose; Luu, Chi D.; Sadigh, Sam; Stambolian, Dwight; Guymer, Robyn H.; Jacobson, Samuel G.; Cideciyan, Artur V.

2017-01-01

Purpose To evaluate whether a practical method of imaging lenticular autofluorescence (AF) can provide an individualized measure correlated with age-related lens yellowing in older subjects undergoing tests involving shorter wavelength lights. Methods Lenticular AF was imaged with 488-nm excitation using a confocal scanning laser ophthalmoscope (cSLO) routinely used for retinal AF imaging. There were 75 older subjects (ages 47–87) at two sites; a small cohort of younger subjects served as controls. At one site, the cSLO was equipped with an internal reference to allow quantitative AF measurements; at the other site, reduced-illuminance AF imaging (RAFI) was used. In a subset of subjects, lens density index was independently estimated from dark-adapted spectral sensitivities performed psychophysically. Results Lenticular AF intensity was significantly higher in the older eyes than the younger cohort when measured with the internal reference (59.2 ± 15.4 vs. 134.4 ± 31.7 gray levels; P < 0.05) as well as when recorded with RAFI without the internal reference (10.9 ± 1.5 vs. 26.1 ± 5.7 gray levels; P < 0.05). Lenticular AF was positively correlated with age; however, there could also be large differences between individuals of similar age. Lenticular AF intensity correlated well with lens density indices estimated from psychophysical measures. Conclusions Lenticular AF measured with a retinal cSLO can provide a practical and individualized measure of lens yellowing, and may be a good candidate to distinguish between preretinal and retinal deficits involving short-wavelength lights in older eyes. PMID:28973367

Military deployment correlates with smaller prefrontal gray matter volume and psychological symptoms in a subclinical population.

PubMed

Butler, O; Adolf, J; Gleich, T; Willmund, G; Zimmermann, P; Lindenberger, U; Gallinat, J; Kühn, S

2017-02-14

Research investigating the effects of trauma exposure on brain structure and function in adults has mainly focused on post-traumatic stress disorder (PTSD), whereas trauma-exposed individuals without a clinical diagnoses often serve as controls. However, this assumes a dichotomy between clinical and subclinical populations that may not be supported at the neural level. In the current study we investigate whether the effects of repeated or long-term stress exposure on brain structure in a subclinical sample are similar to previous PTSD neuroimaging findings. We assessed 27 combat trauma-exposed individuals by means of whole-brain voxel-based morphometry on 3 T magnetic resonance imaging scans and identified a negative association between duration of military deployment and gray matter volumes in ventromedial prefrontal cortex (vmPFC) and dorsal anterior cingulate cortex (ACC). We also found a negative relationship between deployment-related gray matter volumes and psychological symptoms, but not between military deployment and psychological symptoms. To our knowledge, this is the first whole-brain analysis showing that longer military deployment is associated with smaller regional brain volumes in combat-exposed individuals without PTSD. Notably, the observed gray matter associations resemble those previously identified in PTSD populations, and concern regions involved in emotional regulation and fear extinction. These findings question the current dichotomy between clinical and subclinical populations in PTSD neuroimaging research. Instead, neural correlates of both stress exposure and PTSD symptomatology may be more meaningfully investigated at a continuous level.

Military deployment correlates with smaller prefrontal gray matter volume and psychological symptoms in a subclinical population

PubMed Central

Butler, O; Adolf, J; Gleich, T; Willmund, G; Zimmermann, P; Lindenberger, U; Gallinat, J; Kühn, S

2017-01-01

Research investigating the effects of trauma exposure on brain structure and function in adults has mainly focused on post-traumatic stress disorder (PTSD), whereas trauma-exposed individuals without a clinical diagnoses often serve as controls. However, this assumes a dichotomy between clinical and subclinical populations that may not be supported at the neural level. In the current study we investigate whether the effects of repeated or long-term stress exposure on brain structure in a subclinical sample are similar to previous PTSD neuroimaging findings. We assessed 27 combat trauma-exposed individuals by means of whole-brain voxel-based morphometry on 3 T magnetic resonance imaging scans and identified a negative association between duration of military deployment and gray matter volumes in ventromedial prefrontal cortex (vmPFC) and dorsal anterior cingulate cortex (ACC). We also found a negative relationship between deployment-related gray matter volumes and psychological symptoms, but not between military deployment and psychological symptoms. To our knowledge, this is the first whole-brain analysis showing that longer military deployment is associated with smaller regional brain volumes in combat-exposed individuals without PTSD. Notably, the observed gray matter associations resemble those previously identified in PTSD populations, and concern regions involved in emotional regulation and fear extinction. These findings question the current dichotomy between clinical and subclinical populations in PTSD neuroimaging research. Instead, neural correlates of both stress exposure and PTSD symptomatology may be more meaningfully investigated at a continuous level. PMID:28195568

Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

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

Fave, Xenia, E-mail: xjfave@mdanderson.org; Fried, David; Mackin, Dennis

Purpose: Increasing evidence suggests radiomics features extracted from computed tomography (CT) images may be useful in prognostic models for patients with nonsmall cell lung cancer (NSCLC). This study was designed to determine whether such features can be reproducibly obtained from cone-beam CT (CBCT) images taken using medical Linac onboard-imaging systems in order to track them through treatment. Methods: Test-retest CBCT images of ten patients previously enrolled in a clinical trial were retrospectively obtained and used to determine the concordance correlation coefficient (CCC) for 68 different texture features. The volume dependence of each feature was also measured using the Spearman rankmore » correlation coefficient. Features with a high reproducibility (CCC > 0.9) that were not due to volume dependence in the patient test-retest set were further examined for their sensitivity to differences in imaging protocol, level of scatter, and amount of motion by using two phantoms. The first phantom was a texture phantom composed of rectangular cartridges to represent different textures. Features were measured from two cartridges, shredded rubber and dense cork, in this study. The texture phantom was scanned with 19 different CBCT imagers to establish the features’ interscanner variability. The effect of scatter on these features was studied by surrounding the same texture phantom with scattering material (rice and solid water). The effect of respiratory motion on these features was studied using a dynamic-motion thoracic phantom and a specially designed tumor texture insert of the shredded rubber material. The differences between scans acquired with different Linacs and protocols, varying amounts of scatter, and with different levels of motion were compared to the mean intrapatient difference from the test-retest image set. Results: Of the original 68 features, 37 had a CCC >0.9 that was not due to volume dependence. When the Linac manufacturer and imaging protocol were kept consistent, 4–13 of these 37 features passed our criteria for reproducibility more than 50% of the time, depending on the manufacturer-protocol combination. Almost all of the features changed substantially when scatter material was added around the phantom. For the dense cork, 23 features passed in the thoracic scans and 11 features passed in the head scans when the differences between one and two layers of scatter were compared. Using the same test for the shredded rubber, five features passed the thoracic scans and eight features passed the head scans. Motion substantially impacted the reproducibility of the features. With 4 mm of motion, 12 features from the entire volume and 14 features from the center slice measurements were reproducible. With 6–8 mm of motion, three features (Laplacian of Gaussian filtered kurtosis, gray-level nonuniformity, and entropy), from the entire volume and seven features (coarseness, high gray-level run emphasis, gray-level nonuniformity, sum-average, information measure correlation, scaled mean, and entropy) from the center-slice measurements were considered reproducible. Conclusions: Some radiomics features are robust to the noise and poor image quality of CBCT images when the imaging protocol is consistent, relative changes in the features are used, and patients are limited to those with less than 1 cm of motion.« less

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.

Testosterone affects language areas of the adult human brain

PubMed Central

Hahn, Andreas; Kranz, Georg S.; Sladky, Ronald; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Vanicek, Thomas; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F.

2016-01-01

Abstract Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high‐dose hormone application in adult female‐to‐male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel‐based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting‐state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone‐dependent neuroplastic adaptations in adulthood within language‐specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738–1748, 2016. © 2016 Wiley Periodicals, Inc. PMID:26876303

Testosterone affects language areas of the adult human brain.

PubMed

Hahn, Andreas; Kranz, Georg S; Sladky, Ronald; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Vanicek, Thomas; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F; Lanzenberger, Rupert

2016-05-01

Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high-dose hormone application in adult female-to-male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel-based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting-state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone-dependent neuroplastic adaptations in adulthood within language-specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738-1748, 2016. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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.

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

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

2D phase sensitive inversion recovery imaging to measure in-vivo spinal cord gray and white matter areas in clinically feasible acquisition times

PubMed Central

Papinutto, N.; Schlaeger, R.; Panara, V.; Caverzasi, E.; Ahn, S.; Johnson, K.J.; Zhu, A.H.; Stern, W.A.; Laub, G.; Hauser, S.L.; Henry, R.G.

2018-01-01

PURPOSE In-vivo assessment of spinal cord gray matter (GM) and white matter (WM) could become pivotal to study various neurological diseases, but it is challenging because of insufficient GM/WM contrast provided by conventional MRI. Here we present and assess a procedure for measurement of spinal cord total cross-sectional area (TCA) and GM areas based on phase sensitive inversion recovery imaging (PSIR). MATERIALS AND METHODS We acquired 2D PSIR images at 3T at each disc level of the spinal axis on 10 healthy subjects and measured TCA, cord diameters, WM and GM area, and GM area/TCA ratio. We secondly investigated 32 healthy subjects at 4 selected levels (C2–C3, C3–C4, T8–T9, T9–T10, total acquisition time <8 minutes) and generated normative reference values of TCA and GM areas. We assessed test-retest, intra- and inter-operator reliability of the acquisition strategy and measurement steps. RESULTS The measurement procedure based on 2D PSIR imaging allowed TCA and GM area assessments along the entire spinal cord axis. The tests we performed revealed high test-retest/intra-operator reliability (mean coefficient of variation (COV) at C2–C3: TCA=0.41%, GM area=2.75%) and inter-operator reliability of the measurements (mean COV on the 4 levels: TCA=0.44%, GM area= 4.20%; mean intra-class correlation coefficient: TCA=0.998, GM area=0.906). CONCLUSION 2D PSIR allows reliable in-vivo assessment of spinal cord TCA, GM and WM areas in clinically feasible acquisition times. The area measurements presented here are in agreement with previous MRI and post-mortem studies. PMID:25483607

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.

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.

Feature detection in satellite images using neural network technology

NASA Technical Reports Server (NTRS)

Augusteijn, Marijke F.; Dimalanta, Arturo S.

1992-01-01

A feasibility study of automated classification of satellite images is described. Satellite images were characterized by the textures they contain. In particular, the detection of cloud textures was investigated. The method of second-order gray level statistics, using co-occurrence matrices, was applied to extract feature vectors from image segments. Neural network technology was employed to classify these feature vectors. The cascade-correlation architecture was successfully used as a classifier. The use of a Kohonen network was also investigated but this architecture could not reliably classify the feature vectors due to the complicated structure of the classification problem. The best results were obtained when data from different spectral bands were fused.

Description of textures by a structural analysis.

PubMed

Tomita, F; Shirai, Y; Tsuji, S

1982-02-01

A structural analysis system for describing natural textures is introduced. The analyzer automatically extracts the texture elements in an input image, measures their properties, classifies them into some distinctive classes (one ``ground'' class and some ``figure'' classes), and computes the distributions of the gray level, the shape, and the placement of the texture elements in each class. These descriptions are used for classification of texture images. An analysis-by-synthesis method for evaluating texture analyzers is also presented. We propose a synthesizer which generates a texture image based on the descriptions. By comparing the reconstructed image with the original one, we can see what information is preserved and what is lost in the descriptions.

Edge detection techniques for iris recognition system

NASA Astrophysics Data System (ADS)

Tania, U. T.; Motakabber, S. M. A.; Ibrahimy, M. I.

2013-12-01

Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions

NASA Astrophysics Data System (ADS)

Zachiu, C.; Ries, M.; Ramaekers, P.; Guey, J.-L.; Moonen, C. T. W.; de Senneville, B. Denis

2017-10-01

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of  ˜1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions.

Real-time non-rigid target tracking for ultrasound-guided clinical interventions.

PubMed

Zachiu, C; Ries, M; Ramaekers, P; Guey, J-L; Moonen, C T W; de Senneville, B Denis

2017-10-04

Biological motion is a problem for non- or mini-invasive interventions when conducted in mobile/deformable organs due to the targeted pathology moving/deforming with the organ. This may lead to high miss rates and/or incomplete treatment of the pathology. Therefore, real-time tracking of the target anatomy during the intervention would be beneficial for such applications. Since the aforementioned interventions are often conducted under B-mode ultrasound (US) guidance, target tracking can be achieved via image registration, by comparing the acquired US images to a separate image established as positional reference. However, such US images are intrinsically altered by speckle noise, introducing incoherent gray-level intensity variations. This may prove problematic for existing intensity-based registration methods. In the current study we address US-based target tracking by employing the recently proposed EVolution registration algorithm. The method is, by construction, robust to transient gray-level intensities. Instead of directly matching image intensities, EVolution aligns similar contrast patterns in the images. Moreover, the displacement is computed by evaluating a matching criterion for image sub-regions rather than on a point-by-point basis, which typically provides more robust motion estimates. However, unlike similar previously published approaches, which assume rigid displacements in the image sub-regions, the EVolution algorithm integrates the matching criterion in a global functional, allowing the estimation of an elastic dense deformation. The approach was validated for soft tissue tracking under free-breathing conditions on the abdomen of seven healthy volunteers. Contact echography was performed on all volunteers, while three of the volunteers also underwent standoff echography. Each of the two modalities is predominantly specific to a particular type of non- or mini-invasive clinical intervention. The method demonstrated on average an accuracy of  ∼1.5 mm and submillimeter precision. This, together with a computational performance of 20 images per second make the proposed method an attractive solution for real-time target tracking during US-guided clinical interventions.

Digital photography for the light microscope: results with a gated, video-rate CCD camera and NIH-image software.

PubMed

Shaw, S L; Salmon, E D; Quatrano, R S

1995-12-01

In this report, we describe a relatively inexpensive method for acquiring, storing and processing light microscope images that combines the advantages of video technology with the powerful medium now termed digital photography. Digital photography refers to the recording of images as digital files that are stored, manipulated and displayed using a computer. This report details the use of a gated video-rate charge-coupled device (CCD) camera and a frame grabber board for capturing 256 gray-level digital images from the light microscope. This camera gives high-resolution bright-field, phase contrast and differential interference contrast (DIC) images but, also, with gated on-chip integration, has the capability to record low-light level fluorescent images. The basic components of the digital photography system are described, and examples are presented of fluorescence and bright-field micrographs. Digital processing of images to remove noise, to enhance contrast and to prepare figures for printing is discussed.

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.

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

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.

Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images

NASA Astrophysics Data System (ADS)

Nemoto, Mitsutaka; Nomura, Yukihiro; Hanaoka, Shohei; Masutani, Yoshitaka; Yoshikawa, Takeharu; Hayashi, Naoto; Yoshioka, Naoki; Ohtomo, Kuni

Anatomical point landmarks as most primitive anatomical knowledge are useful for medical image understanding. In this study, we propose a detection method for anatomical point landmark based on appearance models, which include gray-level statistical variations at point landmarks and their surrounding area. The models are built based on results of Principal Component Analysis (PCA) of sample data sets. In addition, we employed generative learning method by transforming ROI of sample data. In this study, we evaluated our method with 24 data sets of body trunk CT images and obtained 95.8 ± 7.3 % of the average sensitivity in 28 landmarks.

Impulse Noise Cancellation of Medical Images Using Wavelet Networks and Median Filters

PubMed Central

Sadri, Amir Reza; Zekri, Maryam; Sadri, Saeid; Gheissari, Niloofar

2012-01-01

This paper presents a new two-stage approach to impulse noise removal for medical images based on wavelet network (WN). The first step is noise detection, in which the so-called gray-level difference and average background difference are considered as the inputs of a WN. Wavelet Network is used as a preprocessing for the second stage. The second step is removing impulse noise with a median filter. The wavelet network presented here is a fixed one without learning. Experimental results show that our method acts on impulse noise effectively, and at the same time preserves chromaticity and image details very well. PMID:23493998

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.

Textural features of pretreatment 18F-FDG PET/CT images: prognostic significance in patients with advanced T-stage oropharyngeal squamous cell carcinoma.

PubMed

Cheng, Nai-Ming; Fang, Yu-Hua Dean; Chang, Joseph Tung-Chieh; Huang, Chung-Guei; Tsan, Din-Li; Ng, Shu-Hang; Wang, Hung-Ming; Lin, Chien-Yu; Liao, Chun-Ta; Yen, Tzu-Chen

2013-10-01

Previous studies have shown that total lesion glycolysis (TLG) may serve as a prognostic indicator in oropharyngeal squamous cell carcinoma (OPSCC). We sought to investigate whether the textural features of pretreatment (18)F-FDG PET/CT images can provide any additional prognostic information over TLG and clinical staging in patients with advanced T-stage OPSCC. We retrospectively analyzed the pretreatment (18)F-FDG PET/CT images of 70 patients with advanced T-stage OPSCC who had completed concurrent chemoradiotherapy, bioradiotherapy, or radiotherapy with curative intent. All of the patients had data on human papillomavirus (HPV) infection and were followed up for at least 24 mo or until death. A standardized uptake value (SUV) of 2.5 was taken as a cutoff for tumor boundary. The textural features of pretreatment (18)F-FDG PET/CT images were extracted from histogram analysis (SUV variance and SUV entropy), normalized gray-level cooccurrence matrix (uniformity, entropy, dissimilarity, contrast, homogeneity, inverse different moment, and correlation), and neighborhood gray-tone difference matrix (coarseness, contrast, busyness, complexity, and strength). Receiver-operating-characteristic curves were used to identify the optimal cutoff values for the textural features and TLG. Thirteen patients were HPV-positive. Multivariate Cox regression analysis showed that age, tumor TLG, and uniformity were independently associated with progression-free survival (PFS) and disease-specific survival (DSS). TLG, uniformity, and HPV positivity were significantly associated with overall survival (OS). A prognostic scoring system based on TLG and uniformity was derived. Patients who presented with TLG > 121.9 g and uniformity ≤ 0.138 experienced significantly worse PFS, DSS, and OS rates than those without (P < 0.001, < 0.001, and 0.002, respectively). Patients with TLG > 121.9 g or uniformity ≤ 0.138 were further divided according to age, and different PFS and DSS were observed. Uniformity extracted from the normalized gray-level cooccurrence matrix represents an independent prognostic predictor in patients with advanced T-stage OPSCC. A scoring system was developed and may serve as a risk-stratification strategy for guiding therapy.

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.

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.

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.

Parcellation of the human orbitofrontal cortex based on gray matter volume covariance.

PubMed

Liu, Huaigui; Qin, Wen; Qi, Haotian; Jiang, Tianzi; Yu, Chunshui

2015-02-01

The human orbitofrontal cortex (OFC) is an enigmatic brain region that cannot be parcellated reliably using diffusional and functional magnetic resonance imaging (fMRI) because there is signal dropout that results from an inherent defect in imaging techniques. We hypothesise that the OFC can be reliably parcellated into subregions based on gray matter volume (GMV) covariance patterns that are derived from artefact-free structural images. A total of 321 healthy young subjects were examined by high-resolution structural MRI. The OFC was parcellated into subregions-based GMV covariance patterns; and then sex and laterality differences in GMV covariance pattern of each OFC subregion were compared. The human OFC was parcellated into the anterior (OFCa), medial (OFCm), posterior (OFCp), intermediate (OFCi), and lateral (OFCl) subregions. This parcellation scheme was validated by the same analyses of the left OFC and the bilateral OFCs in male and female subjects. Both visual observation and quantitative comparisons indicated a unique GMV covariance pattern for each OFC subregion. These OFC subregions mainly covaried with the prefrontal and temporal cortices, cingulate cortex and amygdala. In addition, GMV correlations of most OFC subregions were similar across sex and laterality except for significant laterality difference in the OFCl. The right OFCl had stronger GMV correlation with the right inferior frontal cortex. Using high-resolution structural images, we established a reliable parcellation scheme for the human OFC, which may provide an in vivo guide for subregion-level studies of this region and improve our understanding of the human OFC at subregional levels. © 2014 Wiley Periodicals, Inc.

Episodic memory impairments in bipolar disorder are associated with functional and structural brain changes.

PubMed

Oertel-Knöchel, Viola; Reinke, Britta; Feddern, Richard; Knake, Annika; Knöchel, Christian; Prvulovic, David; Pantel, Johannes; Linden, David E J

2014-12-01

We combined multimodal functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging to probe abnormalities in brain circuits underpinning episodic memory performance deficits in patients with bipolar disorder (BD). We acquired whole-brain fMRI data in 21 patients with BD and a matched group of 20 healthy controls during a non-verbal episodic memory task, using abstract shapes. We also examined density of gray matter, using voxel-based morphometry (VBM), and integrity of connecting fiber tracts, using diffusion tensor imaging (DTI) and tract-based spatial statistics, for areas with significant activation differences. Patients with BD remembered less well than controls which shapes they had seen and had lower activation levels during the encoding stage of the task in the anterior cingulate gyrus, the precuneus/cuneus bilaterally, and the left lingual gyrus, and higher activation levels during the retrieval stage in the left temporo-parietal junction. Patients with BD showed reduced gray matter volumes in the left anterior cingulate, the precuneus/cuneus bilaterally, and the left temporo-parietal region in comparison with controls. DTI revealed increased radial, axial, and mean diffusivity in the left superior longitudinal fascicle in patients with BD compared with controls. Changes in task-related activation in frontal and parietal areas were associated with poorer episodic memory in patients with BD. Compared with data from single imaging modalities, integration of multimodal neuroimaging data enables the building of more complete neuropsychological models of mental disorders. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Reference tissue normalization in longitudinal (18)F-florbetapir positron emission tomography of late mild cognitive impairment.

PubMed

Shokouhi, Sepideh; Mckay, John W; Baker, Suzanne L; Kang, Hakmook; Brill, Aaron B; Gwirtsman, Harry E; Riddle, William R; Claassen, Daniel O; Rogers, Baxter P

2016-01-15

Semiquantitative methods such as the standardized uptake value ratio (SUVR) require normalization of the radiotracer activity to a reference tissue to monitor changes in the accumulation of amyloid-β (Aβ) plaques measured with positron emission tomography (PET). The objective of this study was to evaluate the effect of reference tissue normalization in a test-retest (18)F-florbetapir SUVR study using cerebellar gray matter, white matter (two different segmentation masks), brainstem, and corpus callosum as reference regions. We calculated the correlation between (18)F-florbetapir PET and concurrent cerebrospinal fluid (CSF) Aβ1-42 levels in a late mild cognitive impairment cohort with longitudinal PET and CSF data over the course of 2 years. In addition to conventional SUVR analysis using mean and median values of normalized brain radiotracer activity, we investigated a new image analysis technique-the weighted two-point correlation function (wS2)-to capture potentially more subtle changes in Aβ-PET data. Compared with the SUVRs normalized to cerebellar gray matter, all cerebral-to-white matter normalization schemes resulted in a higher inverse correlation between PET and CSF Aβ1-42, while the brainstem normalization gave the best results (high and most stable correlation). Compared with the SUVR mean and median values, the wS2 values were associated with the lowest coefficient of variation and highest inverse correlation to CSF Aβ1-42 levels across all time points and reference regions, including the cerebellar gray matter. The selection of reference tissue for normalization and the choice of image analysis method can affect changes in cortical (18)F-florbetapir uptake in longitudinal studies.

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.

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.

Intensity inhomogeneity compensation and tissue segmentation for magnetic resonance imaging with noise-suppressed multiplicative intrinsic component optimization

NASA Astrophysics Data System (ADS)

Dong, Huaipeng; Zhang, Qi; Shi, Jun

2017-12-01

Magnetic resonance (MR) images suffer from intensity inhomogeneity. Segmentation-based approaches can simultaneously achieve both intensity inhomogeneity compensation (IIC) and tissue segmentation for MR images with little noise, but they often fail for images polluted by severe noise. Here, we propose a noise-robust algorithm named noise-suppressed multiplicative intrinsic component optimization (NSMICO) for simultaneous IIC and tissue segmentation. Considering the spatial characteristics in an image, an adaptive nonlocal means filtering term is incorporated into the objective function of NSMICO to decrease image deterioration due to noise. Then, a fuzzy local factor term utilizing the spatial and gray-level relationship among local pixels is embedded into the objective function to reach a balance between noise suppression and detail preservation. Experimental results on synthetic natural and MR images with various levels of intensity inhomogeneity and noise, as well as in vivo clinical MR images, have demonstrated the effectiveness of the NSMICO and its superiority to three competing approaches. The NSMICO could be potentially valuable for MR image IIC and tissue segmentation.

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.

Optimal scan strategy for mega-pixel and kilo-gray-level OLED-on-silicon microdisplay.

PubMed

Ji, Yuan; Ran, Feng; Ji, Weigui; Xu, Meihua; Chen, Zhangjing; Jiang, Yuxi; Shen, Weixin

2012-06-10

The digital pixel driving scheme makes the organic light-emitting diode (OLED) microdisplays more immune to the pixel luminance variations and simplifies the circuit architecture and design flow compared to the analog pixel driving scheme. Additionally, it is easily applied in full digital systems. However, the data bottleneck becomes a notable problem as the number of pixels and gray levels grow dramatically. This paper will discuss the digital driving ability to achieve kilogray-levels for megapixel displays. The optimal scan strategy is proposed for creating ultra high gray levels and increasing light efficiency and contrast ratio. Two correction schemes are discussed to improve the gray level linearity. A 1280×1024×3 OLED-on-silicon microdisplay, with 4096 gray levels, is designed based on the optimal scan strategy. The circuit driver is integrated in the silicon backplane chip in the 0.35 μm 3.3 V-6 V dual voltage one polysilicon layer, four metal layers (1P4M) complementary metal-oxide semiconductor (CMOS) process with custom top metal. The design aspects of the optimal scan controller are also discussed. The test results show the gray level linearity of the correction schemes for the optimal scan strategy is acceptable by the human eye.

Analyzing Red and Gray Stages of Bark Beetle Attack in the San Bernardino National Forest Using Remote Sensing

NASA Astrophysics Data System (ADS)

Morgan, Andy J.

The San Bernardino National Forest (SBNF) has experienced periods of high, concentrated bark beetle epidemics in the late 1990's and into the 2000's. This increased activity has caused huge amounts of forest loss, resulting from disease introduced by bark beetles. Using remote sensing techniques and Landsat Thematic Mapper 5 (TM5) imagery, the spread of bark beetle diseased trees is mapped over a period from 1998 to 2008. Acreage of two attack stages (red and gray) were calculated from a level sliced classification method developed on data training sites. In each image using Normalized Difference Vegetation Index (NDVI) is the driver of forest health classifications. The results of the analysis are classification maps for each year, red acreage estimated for each study year, and gray attack acreage estimated for each study year. Additionally, for the period of 2001-2004, acreage was compared to those reported by the USDA with a thirteen percent lower mortality total in comparison to USDA federal land and a thirty-two percent lower total mortality (federal and non-federal) land in the SBNF.

Tradeoff between picture element dimensions and noncoherent averaging in side-looking airborne radar

NASA Technical Reports Server (NTRS)

Moore, R. K.

1979-01-01

An experiment was performed in which three synthetic-aperture images and one real-aperture image were successively degraded in spatial resolution, both retaining the same number of independent samples per pixel and using the spatial degradation to allow averaging of different numbers of independent samples within each pixel. The original and degraded images were provided to three interpreters familiar with both aerial photographs and radar images. The interpreters were asked to grade each image in terms of their ability to interpret various specified features on the image. The numerical interpretability grades were then used as a quantitative measure of the utility of the different kinds of image processing and different resolutions. The experiment demonstrated empirically that the interpretability is related exponentially to the SGL volume which is the product of azimuth, range, and gray-level resolution.

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.

Aortic valve bypass surgery in severe aortic valve stenosis: Insights from cardiac and brain magnetic resonance imaging.

PubMed

Mantini, Cesare; Caulo, Massimo; Marinelli, Daniele; Chiacchiaretta, Piero; Tartaro, Armando; Cotroneo, Antonio Raffaele; Di Giammarco, Gabriele

2018-04-13

To investigate and describe the distribution of aortic and cerebral blood flow (CBF) in patients with severe valvular aortic stenosis (AS) before and after aortic valve bypass (AVB) surgery. We enrolled 10 consecutive patients who underwent AVB surgery for severe AS. Cardiovascular magnetic resonance imaging (CMR) and brain magnetic resonance imaging were performed as baseline before surgery and twice after surgery. Quantitative flow measurements were obtained using 1.5-T magnetic resonance imaging (MRI) scanner phase-contrast images of the ascending aorta, descending thoracic aorta (3 cm proximally and distally from the conduit-to-aorta anastomosis), and ventricular outflow portion of the conduit. The evaluation of CBF was performed using 3.0-T MRI scanner arterial spin labeling (ASL) through sequences acquired at the gray matter, dorsal default-mode network, and sensorimotor levels. Conduit flow, expressed as the percentage of total antegrade flow through the conduit, was 63.5 ± 8% and 67.8 ± 7% on early and mid-term postoperative CMR, respectively (P < .05). Retrograde perfusion from the level of the conduit insertion in the descending thoracic aorta toward the aortic arch accounted for 6.9% of total cardiac output and 11% of total conduit flow. We did not observe any significant reduction in left ventricular stroke volume at postoperative evaluation compared with preoperative evaluation (P = .435). No differences were observed between preoperative and postoperative CBF at the gray matter, dorsal default-mode network, and sensorimotor levels (P = .394). After AVB surgery in patients with severe AS, cardiac output is split between the native left ventricular outflow tract and the apico-aortic bypass, with two-thirds of the total antegrade flow passing through the latter and one-third passing through the former. In our experience, CBF assessment confirms that the flow redistribution does not jeopardize cerebral blood supply. Copyright © 2018 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

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.

Military display performance parameters

NASA Astrophysics Data System (ADS)

Desjardins, Daniel D.; Meyer, Frederick

2012-06-01

The military display market is analyzed in terms of four of its segments: avionics, vetronics, dismounted soldier, and command and control. Requirements are summarized for a number of technology-driving parameters, to include luminance, night vision imaging system compatibility, gray levels, resolution, dimming range, viewing angle, video capability, altitude, temperature, shock and vibration, etc., for direct-view and virtual-view displays in cockpits and crew stations. Technical specifications are discussed for selected programs.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES.

PubMed

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-10-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES

PubMed Central

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-01-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors. PMID:28042512

Epileptic Seizure Detection Based on Time-Frequency Images of EEG Signals using Gaussian Mixture Model and Gray Level Co-Occurrence Matrix Features.

PubMed

Li, Yang; Cui, Weigang; Luo, Meilin; Li, Ke; Wang, Lina

2018-01-25

The electroencephalogram (EEG) signal analysis is a valuable tool in the evaluation of neurological disorders, which is commonly used for the diagnosis of epileptic seizures. This paper presents a novel automatic EEG signal classification method for epileptic seizure detection. The proposed method first employs a continuous wavelet transform (CWT) method for obtaining the time-frequency images (TFI) of EEG signals. The processed EEG signals are then decomposed into five sub-band frequency components of clinical interest since these sub-band frequency components indicate much better discriminative characteristics. Both Gaussian Mixture Model (GMM) features and Gray Level Co-occurrence Matrix (GLCM) descriptors are then extracted from these sub-band TFI. Additionally, in order to improve classification accuracy, a compact feature selection method by combining the ReliefF and the support vector machine-based recursive feature elimination (RFE-SVM) algorithm is adopted to select the most discriminative feature subset, which is an input to the SVM with the radial basis function (RBF) for classifying epileptic seizure EEG signals. The experimental results from a publicly available benchmark database demonstrate that the proposed approach provides better classification accuracy than the recently proposed methods in the literature, indicating the effectiveness of the proposed method in the detection of epileptic seizures.

[A graph cuts-based interactive method for segmentation of magnetic resonance images of meningioma].

PubMed

Li, Shuan-qiang; Feng, Qian-jin; Chen, Wu-fan; Lin, Ya-zhong

2011-06-01

For accurate segmentation of the magnetic resonance (MR) images of meningioma, we propose a novel interactive segmentation method based on graph cuts. The high dimensional image features was extracted, and for each pixel, the probabilities of its origin, either the tumor or the background regions, were estimated by exploiting the weighted K-nearest neighborhood classifier. Based on these probabilities, a new energy function was proposed. Finally, a graph cut optimal framework was used for the solution of the energy function. The proposed method was evaluated by application in the segmentation of MR images of meningioma, and the results showed that the method significantly improved the segmentation accuracy compared with the gray level information-based graph cut method.

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.

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

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.

Application of heterogeneous pulse coupled neural network in image quantization

NASA Astrophysics Data System (ADS)

Huang, Yi; Ma, Yide; Li, Shouliang; Zhan, Kun

2016-11-01

On the basis of the different strengths of synaptic connections between actual neurons, this paper proposes a heterogeneous pulse coupled neural network (HPCNN) algorithm to perform quantization on images. HPCNNs are developed from traditional pulse coupled neural network (PCNN) models, which have different parameters corresponding to different image regions. This allows pixels of different gray levels to be classified broadly into two categories: background regional and object regional. Moreover, an HPCNN also satisfies human visual characteristics. The parameters of the HPCNN model are calculated automatically according to these categories, and quantized results will be optimal and more suitable for humans to observe. At the same time, the experimental results of natural images from the standard image library show the validity and efficiency of our proposed quantization method.

Classification of Regional Radiographic Emphysematous Patterns Using Low-Attenuation Gap Length Matrix

NASA Astrophysics Data System (ADS)

Tan, Kok Liang; Tanaka, Toshiyuki; Nakamura, Hidetoshi; Shirahata, Toru; Sugiura, Hiroaki

The standard computer-tomography-based method for measuring emphysema uses percentage of area of low attenuation which is called the pixel index (PI). However, the PI method is susceptible to the problem of averaging effect and this causes the discrepancy between what the PI method describes and what radiologists observe. Knowing that visual recognition of the different types of regional radiographic emphysematous tissues in a CT image can be fuzzy, this paper proposes a low-attenuation gap length matrix (LAGLM) based algorithm for classifying the regional radiographic lung tissues into four emphysema types distinguishing, in particular, radiographic patterns that imply obvious or subtle bullous emphysema from those that imply diffuse emphysema or minor destruction of airway walls. Neural network is used for discrimination. The proposed LAGLM method is inspired by, but different from, former texture-based methods like gray level run length matrix (GLRLM) and gray level gap length matrix (GLGLM). The proposed algorithm is successfully validated by classifying 105 lung regions that are randomly selected from 270 images. The lung regions are hand-annotated by radiologists beforehand. The average four-class classification accuracies in the form of the proposed algorithm/PI/GLRLM/GLGLM methods are: 89.00%/82.97%/52.90%/51.36%, respectively. The p-values from the correlation analyses between the classification results of 270 images and pulmonary function test results are generally less than 0.01. The classification results are useful for a followup study especially for monitoring morphological changes with progression of pulmonary disease.

Contour Tracking with a Spatio-Temporal Intensity Moment.

PubMed

Demi, Marcello

2016-06-01

Standard edge detection operators such as the Laplacian of Gaussian and the gradient of Gaussian can be used to track contours in image sequences. When using edge operators, a contour, which is determined on a frame of the sequence, is simply used as a starting contour to locate the nearest contour on the subsequent frame. However, the strategy used to look for the nearest edge points may not work when tracking contours of non isolated gray level discontinuities. In these cases, strategies derived from the optical flow equation, which look for similar gray level distributions, appear to be more appropriate since these can work with a lower frame rate than that needed for strategies based on pure edge detection operators. However, an optical flow strategy tends to propagate the localization errors through the sequence and an additional edge detection procedure is essential to compensate for such a drawback. In this paper a spatio-temporal intensity moment is proposed which integrates the two basic functions of edge detection and tracking.

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.

Skeletal dosimetry: A hyperboloid representation of the bone-marrow interface to reduce voxel effects in three-dimensional images of trabecular bone

NASA Astrophysics Data System (ADS)

Rajon, Didier Alain

Radiation damage to the hematopoietic bone marrow is clearly defined as the limiting factor to the development of internal emitter therapies. Current dosimetry models rely on chord-length distributions measured through the complex microstructure of the trabecular bone regions of the skeleton in which most of the active marrow is located. Recently, Nuclear Magnetic Resonance (NMR) has been used to obtain high-resolution three-dimensional (3D) images of small trabecular bone samples. These images have been coupled with computer programs to estimate dosimetric parameters such as chord-length distributions, and energy depositions by monoenergetic electrons. This new technique is based on the assumption that each voxel of the image is assigned either to bone tissue or to marrow tissue after application of a threshold value. Previous studies showed that this assumption had important consequences on the outcome of the computer calculations. Both the chord-length distribution measurements and the energy deposition calculations are subject to voxel effects that are responsible for large discrepancies when applied to mathematical models of trabecular bone. The work presented in this dissertation proposes first a quantitative study of the voxel effects. Consensus is that the voxelized representation of surfaces should not be used as direct input to dosimetry computer programs. Instead we need a new technique to transform the interfaces into smooth surfaces. The Marching Cube (MC) algorithm was used and adapted to do this transformation. The initial image was used to generate a continuous gray-level field throughout the image. The interface between bone and marrow was then simulated by the iso-gray-level surface that corresponds to a predetermined threshold value. Calculations were then performed using this new representation. Excellent results were obtained for both the chord-length distribution and the energy deposition measurements. Voxel effects were reduced to an acceptable level and the discrepancies found when using the voxelized representation of the interface were reduced to a few percent. We conclude that this new model should be used every time one performs dosimetry estimates using NMR images of trabecular bone samples.

Brain segmentation and the generation of cortical surfaces

NASA Technical Reports Server (NTRS)

Joshi, M.; Cui, J.; Doolittle, K.; Joshi, S.; Van Essen, D.; Wang, L.; Miller, M. I.

1999-01-01

This paper describes methods for white matter segmentation in brain images and the generation of cortical surfaces from the segmentations. We have developed a system that allows a user to start with a brain volume, obtained by modalities such as MRI or cryosection, and constructs a complete digital representation of the cortical surface. The methodology consists of three basic components: local parametric modeling and Bayesian segmentation; surface generation and local quadratic coordinate fitting; and surface editing. Segmentations are computed by parametrically fitting known density functions to the histogram of the image using the expectation maximization algorithm [DLR77]. The parametric fits are obtained locally rather than globally over the whole volume to overcome local variations in gray levels. To represent the boundary of the gray and white matter we use triangulated meshes generated using isosurface generation algorithms [GH95]. A complete system of local parametric quadratic charts [JWM+95] is superimposed on the triangulated graph to facilitate smoothing and geodesic curve tracking. Algorithms for surface editing include extraction of the largest closed surface. Results for several macaque brains are presented comparing automated and hand surface generation. Copyright 1999 Academic Press.

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

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.

A real-time TV logo tracking method using template matching

NASA Astrophysics Data System (ADS)

Li, Zhi; Sang, Xinzhu; Yan, Binbin; Leng, Junmin

2012-11-01

A fast and accurate TV Logo detection method is presented based on real-time image filtering, noise eliminating and recognition of image features including edge and gray level information. It is important to accurately extract the optical template using the time averaging method from the sample video stream, and then different templates are used to match different logos in separated video streams with different resolution based on the topology features of logos. 12 video streams with different logos are used to verify the proposed method, and the experimental result demonstrates that the achieved accuracy can be up to 99%.

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

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.

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.

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.

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images

PubMed Central

Ramaswamy, Gomathy; Lombardo, Marco; Devaney, Nicholas

2014-01-01

Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM). PMID:24940551

LEDs as light source: examining quality of acquired images

NASA Astrophysics Data System (ADS)

Bachnak, Rafic; Funtanilla, Jeng; Hernandez, Jose

2004-05-01

Recent advances in technology have made light emitting diodes (LEDs) viable in a number of applications, including vehicle stoplights, traffic lights, machine-vision-inspection, illumination, and street signs. This paper presents the results of comparing images taken by a videoscope using two different light sources. One of the sources is the internal metal halide lamp and the other is a LED placed at the tip of the insertion tube. Images acquired using these two light sources were quantitatively compared using their histogram, intensity profile along a line segment, and edge detection. Also, images were qualitatively compared using image registration and transformation. The gray-level histogram, edge detection, image profile and image registration do not offer conclusive results. The LED light source, however, produces good images for visual inspection by an operator. The paper will present the results and discuss the usefulness and shortcomings of various comparison methods.

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images.

PubMed

Ramaswamy, Gomathy; Lombardo, Marco; Devaney, Nicholas

2014-06-01

Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM).

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.

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.

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.

Impaired Recognition and Regulation of Disgust Is Associated with Distinct but Partially Overlapping Patterns of Decreased Gray Matter Volume in the Ventroanterior Insula.

PubMed

Woolley, Josh D; Strobl, Eric V; Sturm, Virginia E; Shany-Ur, Tal; Poorzand, Pardis; Grossman, Scott; Nguyen, Lauren; Eckart, Janet A; Levenson, Robert W; Seeley, William W; Miller, Bruce L; Rankin, Katherine P

2015-10-01

The ventroanterior insula is implicated in the experience, expression, and recognition of disgust; however, whether this brain region is required for recognizing disgust or regulating disgusting behaviors remains unknown. We examined the brain correlates of the presence of disgusting behavior and impaired recognition of disgust using voxel-based morphometry in a sample of 305 patients with heterogeneous patterns of neurodegeneration. Permutation-based analyses were used to determine regions of decreased gray matter volume at a significance level p <= .05 corrected for family-wise error across the whole brain and within the insula. Patients with behavioral variant frontotemporal dementia and semantic variant primary progressive aphasia were most likely to exhibit disgusting behaviors and were, on average, the most impaired at recognizing disgust in others. Imaging analysis revealed that patients who exhibited disgusting behaviors had significantly less gray matter volume bilaterally in the ventral anterior insula. A region of interest analysis restricted to behavioral variant frontotemporal dementia and semantic variant primary progressive aphasia patients alone confirmed this result. Moreover, impaired recognition of disgust was associated with decreased gray matter volume in the bilateral ventroanterior and ventral middle regions of the insula. There was an area of overlap in the bilateral anterior insula where decreased gray matter volume was associated with both the presence of disgusting behavior and impairments in recognizing disgust. These findings suggest that regulating disgusting behaviors and recognizing disgust in others involve two partially overlapping neural systems within the insula. Moreover, the ventral anterior insula is required for both processes. Published by Elsevier Inc.

The informativeness of coefficients a and b of the soil line for the analysis of remote sensing materials

NASA Astrophysics Data System (ADS)

Rukhovich, D. I.; Rukhovich, A. D.; Rukhovich, D. D.; Simakova, M. S.; Kulyanitsa, A. L.; Bryzzhev, A. V.; Koroleva, P. V.

2016-08-01

The coefficients of the soil line are often taken into account in calculations of vegetation indices. These coefficients are usually calculated for the entire satellite image, or are taken as constants without any calculations. In both cases, the informativeness of these coefficients is low and insufficient for the needs of soil mapping. In our study, we calculated soil line coefficients at 8000 lattice points for the territory of Plavsk, Arsen'evsk, and Chern districts of Tula oblast on the basis of 34 Landsat 5, 7, and 8 images obtained in 1985-2014. In order to distinguish between the soil line calculated for a given image and the soil line calculated for lattice points on the basis of dozens of multitemporal images, we suggest that the latter can be referred to as the temporal soil line. The temporal soil line is described by a classical equation: NIR = RED a + b, where a is its slope relative to the horizontal axis (RED), and b is the Y-axis (NIR) intercept. Both coefficients were used to create soil maps. The verification of the maps was performed with the use of data on 1985 soil pits. The informativeness of these coefficients appeared to be sufficient for delineation of eight groups of soils of different taxonomic levels: soddy moderately podzolic soils, soddy slightly podzolic soils, soddy-podzolic soils, light gray forest soils, gray forest soils, dark gray forest soils, podzolized chernozems, and leached chernozems. The b coefficient proved to be more informative, as it allowed us to create the soil map precisely on its basis. In order to create the soil map on the basis of the a coefficient, we had to apply some threshold values of the b coefficient. The bare soil on each of Landsat scenes was separated with the help of the mask of agricultural fields and the notion of the spectral neighborhood of soil line (SNSL).

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

Remote sensing image denoising application by generalized morphological component analysis

NASA Astrophysics Data System (ADS)

Yu, Chong; Chen, Xiong

2014-12-01

In this paper, we introduced a remote sensing image denoising method based on generalized morphological component analysis (GMCA). This novel algorithm is the further extension of morphological component analysis (MCA) algorithm to the blind source separation framework. The iterative thresholding strategy adopted by GMCA algorithm firstly works on the most significant features in the image, and then progressively incorporates smaller features to finely tune the parameters of whole model. Mathematical analysis of the computational complexity of GMCA algorithm is provided. Several comparison experiments with state-of-the-art denoising algorithms are reported. In order to make quantitative assessment of algorithms in experiments, Peak Signal to Noise Ratio (PSNR) index and Structural Similarity (SSIM) index are calculated to assess the denoising effect from the gray-level fidelity aspect and the structure-level fidelity aspect, respectively. Quantitative analysis on experiment results, which is consistent with the visual effect illustrated by denoised images, has proven that the introduced GMCA algorithm possesses a marvelous remote sensing image denoising effectiveness and ability. It is even hard to distinguish the original noiseless image from the recovered image by adopting GMCA algorithm through visual effect.

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.

Color reproduction software for a digital still camera

NASA Astrophysics Data System (ADS)

Lee, Bong S.; Park, Du-Sik; Nam, Byung D.

1998-04-01

We have developed a color reproduction software for a digital still camera. The image taken by the camera was colorimetrically reproduced on the monitor after characterizing the camera and the monitor, and color matching between two devices. The reproduction was performed at three levels; level processing, gamma correction, and color transformation. The image contrast was increased after the level processing adjusting the level of dark and bright portions of the image. The relationship between the level processed digital values and the measured luminance values of test gray samples was calculated, and the gamma of the camera was obtained. The method for getting the unknown monitor gamma was proposed. As a result, the level processed values were adjusted by the look-up table created by the camera and the monitor gamma correction. For a color transformation matrix for the camera, 3 by 3 or 3 by 4 matrix was used, which was calculated by the regression between the gamma corrected values and the measured tristimulus values of each test color samples the various reproduced images were displayed on the dialogue box implemented in our software, which were generated according to four illuminations for the camera and three color temperatures for the monitor. An user can easily choose he best reproduced image comparing each others.

Low episodic memory performance in cognitively normal elderly subjects is associated with increased posterior cingulate gray matter N-acetylaspartate: a 1H MRSI study at 7 Tesla.

PubMed

Schreiner, Simon J; Kirchner, Thomas; Wyss, Michael; Van Bergen, Jiri M G; Quevenco, Frances C; Steininger, Stefanie C; Griffith, Erica Y; Meier, Irene; Michels, Lars; Gietl, Anton F; Leh, Sandra E; Brickman, Adam M; Hock, Christoph; Nitsch, Roger M; Pruessmann, Klaas P; Henning, Anke; Unschuld, Paul G

2016-12-01

Low episodic memory performance characterizes elderly subjects at increased risk for Alzheimer's disease (AD) and may reflect neuronal dysfunction within the posterior cingulate cortex and precuneus (PCP) region. To investigate a potential association between cerebral neurometabolism and low episodic memory in the absence of cognitive impairment, tissue-specific magnetic resonance spectroscopic imaging at ultrahigh field strength of 7 Tesla was used to investigate the PCP region in a healthy elderly study population (n = 30, age 70 ± 5.7 years, Mini-Mental State Examination 29.4 ± 4.1). The Verbal Learning and Memory Test (VLMT) was administered as part of a neuropsychological battery for assessment of episodic memory performance. Significant differences between PCP gray and white matter could be observed for glutamate-glutamine (p = 0.001), choline (p = 0.01), and myo-inositol (p = 0.02). Low Verbal Learning and Memory Test performance was associated with high N-acetylaspartate in PCP gray matter (p = 0.01) but not in PCP white matter. Our data suggest that subtle decreases in episodic memory performance in the elderly may be associated with increased levels of N-acetylaspartate as a reflection of increased mitochondrial energy capacity in PCP gray matter. Copyright © 2016 Elsevier Inc. All rights reserved.

Uncovering the Social Deficits in the Autistic Brain. A Source-Based Morphometric Study

PubMed Central

Grecucci, Alessandro; Rubicondo, Danilo; Siugzdaite, Roma; Surian, Luca; Job, Remo

2016-01-01

Autism is a neurodevelopmental disorder that mainly affects social interaction and communication. Evidence from behavioral and functional MRI studies supports the hypothesis that dysfunctional mechanisms involving social brain structures play a major role in autistic symptomatology. However, the investigation of anatomical abnormalities in the brain of people with autism has led to inconsistent results. We investigated whether specific brain regions, known to display functional abnormalities in autism, may exhibit mutual and peculiar patterns of covariance in their gray-matter concentrations. We analyzed structural MRI images of 32 young men affected by autistic disorder (AD) and 50 healthy controls. Controls were matched for sex, age, handedness. IQ scores were also monitored to avoid confounding. A multivariate Source-Based Morphometry (SBM) was applied for the first time on AD and controls to detect maximally independent networks of gray matter. Group comparison revealed a gray-matter source that showed differences in AD compared to controls. This network includes broad temporal regions involved in social cognition and high-level visual processing, but also motor and executive areas of the frontal lobe. Notably, we found that gray matter differences, as reflected by SBM, significantly correlated with social and behavioral deficits displayed by AD individuals and encoded via the Autism Diagnostic Observation Schedule scores. These findings provide support for current hypotheses about the neural basis of atypical social and mental states information processing in autism. PMID:27630538

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,…

Color calibration of liquid crystal displays

NASA Astrophysics Data System (ADS)

Cazes, Albert N.; Braudaway, Gordon W.; Christensen, James; Cordes, Michael; DeCain, Don; Lien, Shui-Chih A.; Mintzer, Frederick C.; Wright, Steven L.

1999-04-01

For more than a decade the Image Applications department at IBMs Watson Research Center has been involved in cultural and commercial imaging projects that demand high-fidelity color reproduction of precious objects like paintings, illuminated manuscripts or jewelry. Our primary display media have been high-resolution cathode ray tubes (CRT), but for the last three years our customers have been replacing them with liquid crystal displays (LCD). The color calibration model we have been using for the CRT is the one described in the literature. It assumes that the chromas of the primaries are independent of intensity, that the colors produced from them are additive and that the intensity of black is almost zero. We measured several models of LCDs and observed that they poorly satisfied these assumptions at medium to low intensities. This becomes noticeable if the image has dark areas or if the display is viewed under a weak ambient light. In this paper, we use a modified version of the CRT model to calibrate the LCD. First we measure four sets of red, green, blue and gray patches. THen we determine the correction factor needed to make, at each level,the sum of the primaries equal to the corresponding gray. Finally, we use these factors to modify the data of red, green and blue.

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.

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.

Identification of cortex in magnetic resonance images

NASA Astrophysics Data System (ADS)

VanMeter, John W.; Sandon, Peter A.

1992-06-01

The overall goal of the work described here is to make available to the neurosurgeon in the operating room an on-line, three-dimensional, anatomically labeled model of the patient brain, based on pre-operative magnetic resonance (MR) images. A stereotactic operating microscope is currently in experimental use, which allows structures that have been manually identified in MR images to be made available on-line. We have been working to enhance this system by combining image processing techniques applied to the MR data with an anatomically labeled 3-D brain model developed from the Talairach and Tournoux atlas. Here we describe the process of identifying cerebral cortex in the patient MR images. MR images of brain tissue are reasonably well described by material mixture models, which identify each pixel as corresponding to one of a small number of materials, or as being a composite of two materials. Our classification algorithm consists of three steps. First, we apply hierarchical, adaptive grayscale adjustments to correct for nonlinearities in the MR sensor. The goal of this preprocessing step, based on the material mixture model, is to make the grayscale distribution of each tissue type constant across the entire image. Next, we perform an initial classification of all tissue types according to gray level. We have used a sum of Gaussian's approximation of the histogram to perform this classification. Finally, we identify pixels corresponding to cortex, by taking into account the spatial patterns characteristic of this tissue. For this purpose, we use a set of matched filters to identify image locations having the appropriate configuration of gray matter (cortex), cerebrospinal fluid and white matter, as determined by the previous classification step.

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

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.

The level of detail required in a deformable phantom to accurately perform quality assurance of deformable image registration

NASA Astrophysics Data System (ADS)

Saenz, Daniel L.; Kim, Hojin; Chen, Josephine; Stathakis, Sotirios; Kirby, Neil

2016-09-01

The primary purpose of the study was to determine how detailed deformable image registration (DIR) phantoms need to adequately simulate human anatomy and accurately assess the quality of DIR algorithms. In particular, how many distinct tissues are required in a phantom to simulate complex human anatomy? Pelvis and head-and-neck patient CT images were used for this study as virtual phantoms. Two data sets from each site were analyzed. The virtual phantoms were warped to create two pairs consisting of undeformed and deformed images. Otsu’s method was employed to create additional segmented image pairs of n distinct soft tissue CT number ranges (fat, muscle, etc). A realistic noise image was added to each image. Deformations were applied in MIM Software (MIM) and Velocity deformable multi-pass (DMP) and compared with the known warping. Images with more simulated tissue levels exhibit more contrast, enabling more accurate results. Deformation error (magnitude of the vector difference between known and predicted deformation) was used as a metric to evaluate how many CT number gray levels are needed for a phantom to serve as a realistic patient proxy. Stabilization of the mean deformation error was reached by three soft tissue levels for Velocity DMP and MIM, though MIM exhibited a persisting difference in accuracy between the discrete images and the unprocessed image pair. A minimum detail of three levels allows a realistic patient proxy for use with Velocity and MIM deformation algorithms.

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.

In vivo placental MRI shape and textural features predict fetal growth restriction and postnatal outcome.

PubMed

Dahdouh, Sonia; Andescavage, Nickie; Yewale, Sayali; Yarish, Alexa; Lanham, Diane; Bulas, Dorothy; du Plessis, Adre J; Limperopoulos, Catherine

2018-02-01

To investigate the ability of three-dimensional (3D) MRI placental shape and textural features to predict fetal growth restriction (FGR) and birth weight (BW) for both healthy and FGR fetuses. We recruited two groups of pregnant volunteers between 18 and 39 weeks of gestation; 46 healthy subjects and 34 FGR. Both groups underwent fetal MR imaging on a 1.5 Tesla GE scanner using an eight-channel receiver coil. We acquired T2-weighted images on either the coronal or the axial plane to obtain MR volumes with a slice thickness of either 4 or 8 mm covering the full placenta. Placental shape features (volume, thickness, elongation) were combined with textural features; first order textural features (mean, variance, kurtosis, and skewness of placental gray levels), as well as, textural features computed on the gray level co-occurrence and run-length matrices characterizing placental homogeneity, symmetry, and coarseness. The features were used in two machine learning frameworks to predict FGR and BW. The proposed machine-learning based method using shape and textural features identified FGR pregnancies with 86% accuracy, 77% precision and 86% recall. BW estimations were 0.3 ± 13.4% (mean percentage error ± standard error) for healthy fetuses and -2.6 ± 15.9% for FGR. The proposed FGR identification and BW estimation methods using in utero placental shape and textural features computed on 3D MR images demonstrated high accuracy in our healthy and high-risk cohorts. Future studies to assess the evolution of each feature with regard to placental development are currently underway. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:449-458. © 2017 International Society for Magnetic Resonance in Medicine.

Decreased glutathione levels predict loss of brain volume in children and adolescents with first-episode psychosis in a two-year longitudinal study.

PubMed

Fraguas, David; Gonzalez-Pinto, Ana; Micó, Juan Antonio; Reig, Santiago; Parellada, Mara; Martínez-Cengotitabengoa, Mónica; Castro-Fornieles, Josefina; Rapado-Castro, Marta; Baeza, Immaculada; Janssen, Joost; Desco, Manuel; Leza, Juan Carlos; Arango, Celso

2012-05-01

Progressive loss of cortical gray matter (GM), as measured by magnetic resonance imaging, has been described early in the course of first-episode psychosis. This study aims to assess the relationship between oxidative balance and progression of cortical GM changes in a multicenter sample of first-episode early-onset psychosis (EOP) patients from baseline to two-year follow-up. A total of 48 patients (13 females, mean age 15.9±1.5 years) and 56 age- and gender-matched healthy controls (19 females, 15.3±1.5 years) were assessed. Magnetic resonance imaging (MRI) scans performed both at the time of the first psychotic episode and 2 years later were used for volumetric measurements of left and right gray matter regions (frontal, parietal, and temporal lobes) and total sulcal cerebrospinal fluid (CSF). Total glutathione (GSH) blood levels were determined at baseline. In patients, after controlling for possible confounding variables, lower baseline GSH levels were significantly associated with greater volume decrease in left frontal (B=0.034, 95% confidence interval (CI): 0.011 to 0.056, r=0.620, p=0.006), parietal (B=0.039, 95% CI: 0.020 to 0.059, r=0.739, p=0.001), temporal (B=0.026, 95% CI: 0.016 to 0.036, r=0.779, p<0.001), and total (B=0.022, 95% CI: 0.014 to 0.031, r=0.803, p<0.001) gray matter, and with greater increase in total CSF (B=-0.560, 95% CI: -0.270 to -0.850, r=-0.722, p=0.001). Controls did not show significant associations between brain volume changes and GSH levels. GSH deficit during the first psychotic episode was related to greater loss of cortical GM two years later in patients with first-episode EOP, suggesting that oxidative damage may contribute to the progressive loss of cortical GM found in patients with first-episode psychosis. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

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

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.

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.

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

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

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

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

Augmented reality system

NASA Astrophysics Data System (ADS)

Lin, Chien-Liang; Su, Yu-Zheng; Hung, Min-Wei; Huang, Kuo-Cheng

2010-08-01

In recent years, Augmented Reality (AR)[1][2][3] is very popular in universities and research organizations. The AR technology has been widely used in Virtual Reality (VR) fields, such as sophisticated weapons, flight vehicle development, data model visualization, virtual training, entertainment and arts. AR has characteristics to enhance the display output as a real environment with specific user interactive functions or specific object recognitions. It can be use in medical treatment, anatomy training, precision instrument casting, warplane guidance, engineering and distance robot control. AR has a lot of vantages than VR. This system developed combines sensors, software and imaging algorithms to make users feel real, actual and existing. Imaging algorithms include gray level method, image binarization method, and white balance method in order to make accurate image recognition and overcome the effects of light.

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.

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.

A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer.

PubMed

Neofytou, Marios S; Tanos, Vasilis; Pattichis, Marios S; Pattichis, Constantinos S; Kyriacou, Efthyvoulos C; Koutsouris, Dimitris D

2007-11-29

In the development of tissue classification methods, classifiers rely on significant differences between texture features extracted from normal and abnormal regions. Yet, significant differences can arise due to variations in the image acquisition method. For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i) the distance from the tissue (panoramic vs close up), (ii) difference in viewing angles and (iii) color correction. We investigate texture feature variability for a variety of targets encountered in clinical endoscopy. All images were captured at clinically optimum illumination and focus using 720 x 576 pixels and 24 bits color for: (i) a variety of testing targets from a color palette with a known color distribution, (ii) different viewing angles, (iv) two different distances from a calf endometrial and from a chicken cavity. Also, human images from the endometrium were captured and analysed. For texture feature analysis, three different sets were considered: (i) Statistical Features (SF), (ii) Spatial Gray Level Dependence Matrices (SGLDM), and (iii) Gray Level Difference Statistics (GLDS). All images were gamma corrected and the extracted texture feature values were compared against the texture feature values extracted from the uncorrected images. Statistical tests were applied to compare images from different viewing conditions so as to determine any significant differences. For the proposed acquisition procedure, results indicate that there is no significant difference in texture features between the panoramic and close up views and between angles. For a calibrated target image, gamma correction provided an acquired image that was a significantly better approximation to the original target image. In turn, this implies that the texture features extracted from the corrected images provided for better approximations to the original images. Within the proposed protocol, for human ROIs, we have found that there is a large number of texture features that showed significant differences between normal and abnormal endometrium. This study provides a standardized protocol for avoiding any significant texture feature differences that may arise due to variability in the acquisition procedure or the lack of color correction. After applying the protocol, we have found that significant differences in texture features will only be due to the fact that the features were extracted from different types of tissue (normal vs abnormal).

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.

[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).

Behavioral model of visual perception and recognition

NASA Astrophysics Data System (ADS)

Rybak, Ilya A.; Golovan, Alexander V.; Gusakova, Valentina I.

1993-09-01

In the processes of visual perception and recognition human eyes actively select essential information by way of successive fixations at the most informative points of the image. A behavioral program defining a scanpath of the image is formed at the stage of learning (object memorizing) and consists of sequential motor actions, which are shifts of attention from one to another point of fixation, and sensory signals expected to arrive in response to each shift of attention. In the modern view of the problem, invariant object recognition is provided by the following: (1) separated processing of `what' (object features) and `where' (spatial features) information at high levels of the visual system; (2) mechanisms of visual attention using `where' information; (3) representation of `what' information in an object-based frame of reference (OFR). However, most recent models of vision based on OFR have demonstrated the ability of invariant recognition of only simple objects like letters or binary objects without background, i.e. objects to which a frame of reference is easily attached. In contrast, we use not OFR, but a feature-based frame of reference (FFR), connected with the basic feature (edge) at the fixation point. This has provided for our model, the ability for invariant representation of complex objects in gray-level images, but demands realization of behavioral aspects of vision described above. The developed model contains a neural network subsystem of low-level vision which extracts a set of primary features (edges) in each fixation, and high- level subsystem consisting of `what' (Sensory Memory) and `where' (Motor Memory) modules. The resolution of primary features extraction decreases with distances from the point of fixation. FFR provides both the invariant representation of object features in Sensor Memory and shifts of attention in Motor Memory. Object recognition consists in successive recall (from Motor Memory) and execution of shifts of attention and successive verification of the expected sets of features (stored in Sensory Memory). The model shows the ability of recognition of complex objects (such as faces) in gray-level images invariant with respect to shift, rotation, and scale.

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.

Reversible watermarking for knowledge digest embedding and reliability control in medical images.

PubMed

Coatrieux, Gouenou; Le Guillou, Clara; Cauvin, Jean-Michel; Roux, Christian

2009-03-01

To improve medical image sharing in applications such as e-learning or remote diagnosis aid, we propose to make the image more usable by watermarking it with a digest of its associated knowledge. The aim of such a knowledge digest (KD) is for it to be used for retrieving similar images with either the same findings or differential diagnoses. It summarizes the symbolic descriptions of the image, the symbolic descriptions of the findings semiology, and the similarity rules that contribute to balancing the importance of previous descriptors when comparing images. Instead of modifying the image file format by adding some extra header information, watermarking is used to embed the KD in the pixel gray-level values of the corresponding images. When shared through open networks, watermarking also helps to convey reliability proofs (integrity and authenticity) of an image and its KD. The interest of these new image functionalities is illustrated in the updating of the distributed users' databases within the framework of an e-learning application demonstrator of endoscopic semiology.

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

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.

Detection of defects on apple using B-spline lighting correction method

NASA Astrophysics Data System (ADS)

Li, Jiangbo; Huang, Wenqian; Guo, Zhiming

To effectively extract defective areas in fruits, the uneven intensity distribution that was produced by the lighting system or by part of the vision system in the image must be corrected. A methodology was used to convert non-uniform intensity distribution on spherical objects into a uniform intensity distribution. A basically plane image with the defective area having a lower gray level than this plane was obtained by using proposed algorithms. Then, the defective areas can be easily extracted by a global threshold value. The experimental results with a 94.0% classification rate based on 100 apple images showed that the proposed algorithm was simple and effective. This proposed method can be applied to other spherical fruits.

Range image segmentation using Zernike moment-based generalized edge detector

NASA Technical Reports Server (NTRS)

Ghosal, S.; Mehrotra, R.

1992-01-01

The authors proposed a novel Zernike moment-based generalized step edge detection method which can be used for segmenting range and intensity images. A generalized step edge detector is developed to identify different kinds of edges in range images. These edge maps are thinned and linked to provide final segmentation. A generalized edge is modeled in terms of five parameters: orientation, two slopes, one step jump at the location of the edge, and the background gray level. Two complex and two real Zernike moment-based masks are required to determine all these parameters of the edge model. Theoretical noise analysis is performed to show that these operators are quite noise tolerant. Experimental results are included to demonstrate edge-based segmentation technique.

SVM-based classification of LV wall motion in cardiac MRI with the assessment of STE

NASA Astrophysics Data System (ADS)

Mantilla, Juan; Garreau, Mireille; Bellanger, Jean-Jacques; Paredes, José Luis

2015-01-01

In this paper, we propose an automated method to classify normal/abnormal wall motion in Left Ventricle (LV) function in cardiac cine-Magnetic Resonance Imaging (MRI), taking as reference, strain information obtained from 2D Speckle Tracking Echocardiography (STE). Without the need of pre-processing and by exploiting all the images acquired during a cardiac cycle, spatio-temporal profiles are extracted from a subset of radial lines from the ventricle centroid to points outside the epicardial border. Classical Support Vector Machines (SVM) are used to classify features extracted from gray levels of the spatio-temporal profile as well as their representations in the Wavelet domain under the assumption that the data may be sparse in that domain. Based on information obtained from radial strain curves in 2D-STE studies, we label all the spatio-temporal profiles that belong to a particular segment as normal if the peak systolic radial strain curve of this segment presents normal kinesis, or abnormal if the peak systolic radial strain curve presents hypokinesis or akinesis. For this study, short-axis cine- MR images are collected from 9 patients with cardiac dyssynchrony for which we have the radial strain tracings at the mid-papilary muscle obtained by 2D STE; and from one control group formed by 9 healthy subjects. The best classification performance is obtained with the gray level information of the spatio-temporal profiles using a RBF kernel with 91.88% of accuracy, 92.75% of sensitivity and 91.52% of specificity.

Evaluating fuzzy operators of an object-based image analysis for detecting landslides and their changes

NASA Astrophysics Data System (ADS)

Feizizadeh, Bakhtiar; Blaschke, Thomas; Tiede, Dirk; Moghaddam, Mohammad Hossein Rezaei

2017-09-01

This article presents a method of object-based image analysis (OBIA) for landslide delineation and landslide-related change detection from multi-temporal satellite images. It uses both spatial and spectral information on landslides, through spectral analysis, shape analysis, textural measurements using a gray-level co-occurrence matrix (GLCM), and fuzzy logic membership functionality. Following an initial segmentation step, particular combinations of various information layers were investigated to generate objects. This was achieved by applying multi-resolution segmentation to IRS-1D, SPOT-5, and ALOS satellite imagery in sequential steps of feature selection and object classification, and using slope and flow direction derivatives from a digital elevation model together with topographically-oriented gray level co-occurrence matrices. Fuzzy membership values were calculated for 11 different membership functions using 20 landslide objects from a landslide training data. Six fuzzy operators were used for the final classification and the accuracies of the resulting landslide maps were compared. A Fuzzy Synthetic Evaluation (FSE) approach was adapted for validation of the results and for an accuracy assessment using the landslide inventory database. The FSE approach revealed that the AND operator performed best with an accuracy of 93.87% for 2005 and 94.74% for 2011, closely followed by the MEAN Arithmetic operator, while the OR and AND (*) operators yielded relatively low accuracies. An object-based change detection was then applied to monitor landslide-related changes that occurred in northern Iran between 2005 and 2011. Knowledge rules to detect possible landslide-related changes were developed by evaluating all possible landslide-related objects for both time steps.

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.

New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis

NASA Astrophysics Data System (ADS)

Chaudhury, Baishali; Hall, Lawrence O.; Goldgof, Dmitry B.; Gatenby, Robert A.; Gillies, Robert; Drukteinis, Jennifer S.

2014-03-01

Magnetic Resonance Imaging (MRI) of breast cancer typically shows that tumors are heterogeneous with spatial variations in blood flow and cell density. Here, we examine the potential link between clinical tumor imaging and the underlying evolutionary dynamics behind heterogeneity in the cellular expression of estrogen receptors (ER) in breast cancer. We assume, in an evolutionary environment, that ER expression will only occur in the presence of significant concentrations of estrogen, which is delivered via the blood stream. Thus, we hypothesize, the expression of ER in breast cancer cells will correlate with blood flow on gadolinium enhanced breast MRI. To test this hypothesis, we performed quantitative analysis of blood flow on dynamic contrast enhanced MRI (DCE-MRI) and correlated it with the ER status of the tumor. Here we present our analytic methods, which utilize a novel algorithm to analyze 20 volumetric DCE-MRI breast cancer tumors. The algorithm generates post initial enhancement (PIE) maps from DCE-MRI and then performs texture features extraction from the PIE map, feature selection, and finally classification of tumors into ER positive and ER negative status. The combined gray level co-occurrence matrices, gray level run length matrices and local binary pattern histogram features allow quantification of breast tumor heterogeneity. The algorithm predicted ER expression with an accuracy of 85% using a Naive Bayes classifier in leave-one-out cross-validation. Hence, we conclude that our data supports the hypothesis that imaging characteristics can, through application of evolutionary principles, provide insights into the cellular and molecular properties of cancer cells.

SAR/LANDSAT image registration study

NASA Technical Reports Server (NTRS)

Murphrey, S. W. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Temporal registration of synthetic aperture radar data with LANDSAT-MSS data is both feasible (from a technical standpoint) and useful (from an information-content viewpoint). The greatest difficulty in registering aircraft SAR data to corrected LANDSAT-MSS data is control-point location. The differences in SAR and MSS data impact the selection of features that will serve as a good control points. The SAR and MSS data are unsuitable for automatic computer correlation of digital control-point data. The gray-level data can not be compared by the computer because of the different response characteristics of the MSS and SAR images.

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.

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.

Comparing object recognition from binary and bipolar edge images for visual prostheses.

PubMed

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2016-11-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition.

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.

Genetic programming approach to evaluate complexity of texture images

NASA Astrophysics Data System (ADS)

Ciocca, Gianluigi; Corchs, Silvia; Gasparini, Francesca

2016-11-01

We adopt genetic programming (GP) to define a measure that can predict complexity perception of texture images. We perform psychophysical experiments on three different datasets to collect data on the perceived complexity. The subjective data are used for training, validation, and test of the proposed measure. These data are also used to evaluate several possible candidate measures of texture complexity related to both low level and high level image features. We select four of them (namely roughness, number of regions, chroma variance, and memorability) to be combined in a GP framework. This approach allows a nonlinear combination of the measures and could give hints on how the related image features interact in complexity perception. The proposed complexity measure M exhibits Pearson correlation coefficients of 0.890 on the training set, 0.728 on the validation set, and 0.724 on the test set. M outperforms each of all the single measures considered. From the statistical analysis of different GP candidate solutions, we found that the roughness measure evaluated on the gray level image is the most dominant one, followed by the memorability, the number of regions, and finally the chroma variance.

Adapting to blur produced by ocular high-order aberrations

PubMed Central

Sawides, Lucie; de Gracia, Pablo; Dorronsoro, Carlos; Webster, Michael; Marcos, Susana

2011-01-01

The perceived focus of an image can be strongly biased by prior adaptation to a blurred or sharpened image. We examined whether these adaptation effects can occur for the natural patterns of retinal image blur produced by high-order aberrations (HOAs) in the optics of the eye. Focus judgments were measured for 4 subjects to estimate in a forced choice procedure (sharp/blurred) their neutral point after adaptation to different levels of blur produced by scaled increases or decreases in their HOAs. The optical blur was simulated by convolution of the PSFs from the 4 different HOA patterns, with Zernike coefficients (excluding tilt, defocus, and astigmatism) multiplied by a factor between 0 (diffraction limited) and 2 (double amount of natural blur). Observers viewed the images through an Adaptive Optics system that corrected their aberrations and made settings under neutral adaptation to a gray field or after adapting to 5 different blur levels. All subjects adapted to changes in the level of blur imposed by HOA regardless of which observer’s HOA was used to generate the stimuli, with the perceived neutral point proportional to the amount of blur in the adapting image. PMID:21712375

Adapting to blur produced by ocular high-order aberrations.

PubMed

Sawides, Lucie; de Gracia, Pablo; Dorronsoro, Carlos; Webster, Michael; Marcos, Susana

2011-06-28

The perceived focus of an image can be strongly biased by prior adaptation to a blurred or sharpened image. We examined whether these adaptation effects can occur for the natural patterns of retinal image blur produced by high-order aberrations (HOAs) in the optics of the eye. Focus judgments were measured for 4 subjects to estimate in a forced choice procedure (sharp/blurred) their neutral point after adaptation to different levels of blur produced by scaled increases or decreases in their HOAs. The optical blur was simulated by convolution of the PSFs from the 4 different HOA patterns, with Zernike coefficients (excluding tilt, defocus, and astigmatism) multiplied by a factor between 0 (diffraction limited) and 2 (double amount of natural blur). Observers viewed the images through an Adaptive Optics system that corrected their aberrations and made settings under neutral adaptation to a gray field or after adapting to 5 different blur levels. All subjects adapted to changes in the level of blur imposed by HOA regardless of which observer's HOA was used to generate the stimuli, with the perceived neutral point proportional to the amount of blur in the adapting image.

A unified tensor level set for image segmentation.

PubMed

Wang, Bin; Gao, Xinbo; Tao, Dacheng; Li, Xuelong

2010-06-01

This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt- and pepper-type noise. Second, considering the local geometrical features, e.g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

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.

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.…

Investigation of attenuation correction in SPECT using textural features, Monte Carlo simulations, and computational anthropomorphic models.

PubMed

Spirou, Spiridon V; Papadimitroulas, Panagiotis; Liakou, Paraskevi; Georgoulias, Panagiotis; Loudos, George

2015-09-01

To present and evaluate a new methodology to investigate the effect of attenuation correction (AC) in single-photon emission computed tomography (SPECT) using textural features analysis, Monte Carlo techniques, and a computational anthropomorphic model. The GATE Monte Carlo toolkit was used to simulate SPECT experiments using the XCAT computational anthropomorphic model, filled with a realistic biodistribution of (99m)Tc-N-DBODC. The simulated gamma camera was the Siemens ECAM Dual-Head, equipped with a parallel hole lead collimator, with an image resolution of 3.54 × 3.54 mm(2). Thirty-six equispaced camera positions, spanning a full 360° arc, were simulated. Projections were calculated after applying a ± 20% energy window or after eliminating all scattered photons. The activity of the radioisotope was reconstructed using the MLEM algorithm. Photon attenuation was accounted for by calculating the radiological pathlength in a perpendicular line from the center of each voxel to the gamma camera. Twenty-two textural features were calculated on each slice, with and without AC, using 16 and 64 gray levels. A mask was used to identify only those pixels that belonged to each organ. Twelve of the 22 features showed almost no dependence on AC, irrespective of the organ involved. In both the heart and the liver, the mean and SD were the features most affected by AC. In the liver, six features were affected by AC only on some slices. Depending on the slice, skewness decreased by 22-34% with AC, kurtosis by 35-50%, long-run emphasis mean by 71-91%, and long-run emphasis range by 62-95%. In contrast, gray-level non-uniformity mean increased by 78-218% compared with the value without AC and run percentage mean by 51-159%. These results were not affected by the number of gray levels (16 vs. 64) or the data used for reconstruction: with the energy window or without scattered photons. The mean and SD were the main features affected by AC. In the heart, no other feature was affected. In the liver, other features were affected, but the effect was slice dependent. The number of gray levels did not affect the results.

Relationship between aging and T1 relaxation time in deep gray matter: A voxel-based analysis.

PubMed

Okubo, Gosuke; Okada, Tomohisa; Yamamoto, Akira; Fushimi, Yasutaka; Okada, Tsutomu; Murata, Katsutoshi; Togashi, Kaori

2017-09-01

To investigate age-related changes in T 1 relaxation time in deep gray matter structures in healthy volunteers using magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE). In all, 70 healthy volunteers (aged 20-76, mean age 42.6 years) were scanned at 3T magnetic resonance imaging (MRI). A MP2RAGE sequence was employed to quantify T 1 relaxation times. After the spatial normalization of T 1 maps with the diffeomorphic anatomical registration using the exponentiated Lie algebra algorithm, voxel-based regression analysis was conducted. In addition, linear and quadratic regression analyses of regions of interest (ROIs) were also performed. With aging, voxel-based analysis (VBA) revealed significant T 1 value decreases in the ventral-inferior putamen, nucleus accumbens, and amygdala, whereas T 1 values significantly increased in the thalamus and white matter as well (P < 0.05 at cluster level, false discovery rate). ROI analysis revealed that T 1 values in the nucleus accumbens linearly decreased with aging (P = 0.0016), supporting the VBA result. T 1 values in the thalamus (P < 0.0001), substantia nigra (P = 0.0003), and globus pallidus (P < 0.0001) had a best fit to quadratic curves, with the minimum T 1 values observed between 30 and 50 years of age. Age-related changes in T 1 relaxation time vary by location in deep gray matter. 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:724-731. © 2017 International Society for Magnetic Resonance in Medicine.

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.

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

Application of remote sensing techniques to hydrography with emphasis on bathymetry. M.S. Thesis

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Meireles, D. S.

1980-01-01

Remote sensing techniques are utilized for the determination of hydrographic characteristics, with emphasis in bathymetry. Two sensor systems were utilized: the Metric Camera Wild RC-10 and the Multispectral Scanner of LANDSAT Satellite (MSS-LANDSAT). From photographs of the metric camera, data of photographic density of points with known depth are obtained. A correlation between the variables density x depth is calculated through a regression straight line. From this line, the depth of points with known photographic density is determined. The LANDSAT MSS images are interpreted automatically in the Iterative Multispectral Analysis System (I-100) with the obtention of point subareas with the same gray level. With some simplifications done, it is assumed that the depth of a point is directly related with its gray level. Subareas with points of the same depth are then determined and isobathymetric curves are drawn. The coast line is obtained through the sensor systems already mentioned. Advantages and limitations of the techniques and of the sensor systems utilized are discussed and the results are compared with ground truth.

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.

Shell feature: a new radiomics descriptor for predicting distant failure after radiotherapy in non-small cell lung cancer and cervix cancer

NASA Astrophysics Data System (ADS)

Hao, Hongxia; Zhou, Zhiguo; Li, Shulong; Maquilan, Genevieve; Folkert, Michael R.; Iyengar, Puneeth; Westover, Kenneth D.; Albuquerque, Kevin; Liu, Fang; Choy, Hak; Timmerman, Robert; Yang, Lin; Wang, Jing

2018-05-01

Distant failure is the main cause of human cancer-related mortalities. To develop a model for predicting distant failure in non-small cell lung cancer (NSCLC) and cervix cancer (CC) patients, a shell feature, consisting of outer voxels around the tumor boundary, was constructed using pre-treatment positron emission tomography (PET) images from 48 NSCLC patients received stereotactic body radiation therapy and 52 CC patients underwent external beam radiation therapy and concurrent chemotherapy followed with high-dose-rate intracavitary brachytherapy. The hypothesis behind this feature is that non-invasive and invasive tumors may have different morphologic patterns in the tumor periphery, in turn reflecting the differences in radiological presentations in the PET images. The utility of the shell was evaluated by the support vector machine classifier in comparison with intensity, geometry, gray level co-occurrence matrix-based texture, neighborhood gray tone difference matrix-based texture, and a combination of these four features. The results were assessed in terms of accuracy, sensitivity, specificity, and AUC. Collectively, the shell feature showed better predictive performance than all the other features for distant failure prediction in both NSCLC and CC cohorts.

Optimizing the balance between radiation dose and image quality in pediatric head CT: findings before and after intensive radiologic staff training.

PubMed

Paolicchi, Fabio; Faggioni, Lorenzo; Bastiani, Luca; Molinaro, Sabrina; Puglioli, Michele; Caramella, Davide; Bartolozzi, Carlo

2014-06-01

The purpose of this study was to assess the radiation dose and image quality of pediatric head CT examinations before and after radiologic staff training. Outpatients 1 month to 14 years old underwent 215 unenhanced head CT examinations before and after intensive training of staff radiologists and technologists in optimization of CT technique. Patients were divided into three age groups (0-4, 5-9, and 10-14 years), and CT dose index, dose-length product, tube voltage, and tube current-rotation time product values before and after training were retrieved from the hospital PACS. Gray matter conspicuity and contrast-to-noise ratio before and after training were calculated, and subjective image quality in terms of artifacts, gray-white matter differentiation, noise, visualization of posterior fossa structures, and need for repeat CT examination was visually evaluated by three neuroradiologists. The median CT dose index and dose-length product values were significantly lower after than before training in all age groups (27 mGy and 338 mGy ∙ cm vs 107 mGy and 1444 mGy ∙ cm in the 0- to 4-year-old group, 41 mGy and 483 mGy ∙ cm vs 68 mGy and 976 mGy ∙ cm in the 5- to 9-year-old group, and 51 mGy and 679 mGy ∙ cm vs 107 mGy and 1480 mGy ∙ cm in the 10- to 14-year-old group; p < 0.001). The tube voltage and tube current-time values after training were significantly lower than the levels before training (p < 0.001). Subjective posttraining image quality was not inferior to pretraining levels for any item except noise (p < 0.05), which, however, was never diagnostically unacceptable. Radiologic staff training can be effective in reducing radiation dose while preserving diagnostic image quality in pediatric head CT examinations.

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

Mateos, M-J; Brandan, M-E; Gastelum, A

Purpose: To evaluate the time evolution of texture parameters, based on the gray level co-occurrence matrix (GLCM), in subtracted images of 17 patients (10 malignant and 7 benign) subjected to contrast-enhanced digital mammography (CEDM). The goal is to determine the sensitivity of texture to iodine uptake at the lesion, and its correlation (or lack of) with mean-pixel-value (MPV). Methods: Acquisition of clinical images followed a single-energy CEDM protocol using Rh/Rh/48 kV plus external 0.5 cm Al from a Senographe DS unit. Prior to the iodine-based contrast medium (CM) administration a mask image was acquired; four CM images were obtained 1,more » 2, 3, and 5 minutes after CM injection. Temporal series were obtained by logarithmic subtraction of registered CM minus mask images.Regions of interest (ROI) for the lesion were drawn by a radiologist and the texture was analyzed. GLCM was evaluated at a 3 pixel distance, 0° angle, and 64 gray-levels. Pixels identified as registration errors were excluded from the computation. 17 texture parameters were chosen, classified according to similarity into 7 groups, and analyzed. Results: In all cases the texture parameters within a group have similar dynamic behavior. Two texture groups (associated to cluster and sum mean) show a strong correlation with MPV; their average correlation coefficient (ACC) is r{sup 2}=0.90. Other two groups (contrast, homogeneity) remain constant with time, that is, a low-sensitivity to CM uptake. Three groups (regularity, lacunarity and diagonal moment) are sensitive to CM uptake but less correlated with MPV; their ACC is r{sup 2}=0.78. Conclusion: This analysis has shown that, at least groups associated to regularity, lacunarity and diagonal moment offer dynamical information additional to the mean pixel value due to the presence of CM at the lesion. The next step will be the analysis in terms of the lesion pathology. Authors thank PAPIIT-IN105813 for support. Consejo Nacional de Ciencia Y Tecnologia, PAPIIT-IN105813.« less

SU-E-J-265: Feasibility Study of Texture Analysis for Prognosis of Local Tumor Recurrence Within 5-Years for Pharyngeal-Laryngeal Carcinoma Patients Received Radiotherapy Treatment

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

Huang, W; Tu, S

Purpose: Pharyngeal and laryngeal carcinomas (PLC) are among the top leading cancers in Asian populations. Typically the tumor may recur and progress in a short period of time if radiotherapy fails to deliver a successful treatment. Here we used image texture features extracted from images of computed tomography (CT) planning and conducted a retrospective study to evaluate whether texture analysis is a feasible approach to predict local tumor recurrence for PLC patients received radiotherapy treatment. Methods: CT planning images of 100 patients with PLC treated by radiotherapy at our facility between 2001 and 2010 are collected. These patients were receivedmore » two separate CT scans, before and mid-course of the treatment delivery. Before the radiotherapy, a CT scanning was used for the first treatment planning. A total of 30 fractions were used in the treatment and patients were scanned with a second CT around the end of the fifteenth delivery for an adaptive treatment planning. Only patients who were treated with intensity modulated radiation therapy and RapidArc were selected. Treatment planning software of Eclipse was used. The changes of texture parameters between two CT acquisitions were computed to determine whether they were correlated to the local tumor recurrence. The following texture parameters were used in the preliminary assessment: mean, variance, standard deviation, skewness, kurtosis, energy, entropy, inverse difference moment, cluster shade, inertia, cluster prominence, gray-level co-occurrence matrix, and gray-level run-length matrix. The study was reviewed and approved by the committee of our institutional review board. Results: Our calculations suggested the following texture parameters were correlated with the local tumor recurrence: skewness, kurtosis, entropy, and inertia (p<0.0.05). Conclusion: The preliminary results were positive. However some works remain crucial to be completed, including addition of texture parameters for different image features, sensitivity of tumor segmentation variations, and effect of image filtering.« less

Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies.

PubMed

Sanz-Requena, Roberto; Moratal, David; García-Sánchez, Diego Ramón; Bodí, Vicente; Rieta, José Joaquín; Sanchis, Juan Manuel

2007-03-01

Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media-adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove noise from the images without blurring the edges. Segmentation of media-adventitia contour is achieved using active contours (snakes). In particular, we use the gradient vector flow (GVF) as external force for the snakes. The detection of lumen border is obtained taking into account gray-level information of the inner part of the previously detected contours. A knowledge-based approach is used to determine which level of gray corresponds statistically to the different regions of interest: intima, plaque and lumen. The catheter region is automatically discarded. An estimate of plaque type is also given. Finally, 3D reconstruction of all detected regions is made. The suitability of this methodology has been verified for the analysis and visualization of plaque length, stenosis severity, automatic detection of the most problematic regions, calculus of plaque volumes and a preliminary estimation of plaque type obtaining for automatic measures of lumen and vessel area an average error smaller than 1mm(2) (equivalent aproximately to 10% of the average measure), for calculus of plaque and lumen volume errors smaller than 0.5mm(3) (equivalent approximately to 20% of the average measure) and for plaque type estimates a mismatch of less than 8% in the analysed frames.

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.

Altered voxel-wise gray matter structural brain networks in schizophrenia: Association with brain genetic expression pattern.

PubMed

Liu, Feng; Tian, Hongjun; Li, Jie; Li, Shen; Zhuo, Chuanjun

2018-05-04

Previous seed- and atlas-based structural covariance/connectivity analyses have demonstrated that patients with schizophrenia is accompanied by aberrant structural connection and abnormal topological organization. However, it remains unclear whether this disruption is present in unbiased whole-brain voxel-wise structural covariance networks (SCNs) and whether brain genetic expression variations are linked with network alterations. In this study, ninety-five patients with schizophrenia and 95 matched healthy controls were recruited and gray matter volumes were extracted from high-resolution structural magnetic resonance imaging scans. Whole-brain voxel-wise gray matter SCNs were constructed at the group level and were further analyzed by using graph theory method. Nonparametric permutation tests were employed for group comparisons. In addition, regression modes along with random effect analysis were utilized to explore the associations between structural network changes and gene expression from the Allen Human Brain Atlas. Compared with healthy controls, the patients with schizophrenia showed significantly increased structural covariance strength (SCS) in the right orbital part of superior frontal gyrus and bilateral middle frontal gyrus, while decreased SCS in the bilateral superior temporal gyrus and precuneus. The altered SCS showed reproducible correlations with the expression profiles of the gene classes involved in therapeutic targets and neurodevelopment. Overall, our findings not only demonstrate that the topological architecture of whole-brain voxel-wise SCNs is impaired in schizophrenia, but also provide evidence for the possible role of therapeutic targets and neurodevelopment-related genes in gray matter structural brain networks in schizophrenia.

Detection of pigment network in dermatoscopy images using texture analysis

PubMed Central

Anantha, Murali; Moss, Randy H.; Stoecker, William V.

2011-01-01

Dermatoscopy, also known as dermoscopy or epiluminescence microscopy (ELM), is a non-invasive, in vivo technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. ELM offers a completely new range of visual features. One such prominent feature is the pigment network. Two texture-based algorithms are developed for the detection of pigment network. These methods are applicable to various texture patterns in dermatoscopy images, including patterns that lack fine lines such as cobblestone, follicular, or thickened network patterns. Two texture algorithms, Laws energy masks and the neighborhood gray-level dependence matrix (NGLDM) large number emphasis, were optimized on a set of 155 dermatoscopy images and compared. Results suggest superiority of Laws energy masks for pigment network detection in dermatoscopy images. For both methods, a texel width of 10 pixels or approximately 0.22 mm is found for dermatoscopy images. PMID:15249068

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

A comparison of image processing techniques for bird recognition.

PubMed

Nadimpalli, Uma D; Price, Randy R; Hall, Steven G; Bomma, Pallavi

2006-01-01

Bird predation is one of the major concerns for fish culture in open ponds. A novel method for dispersing birds is the use of autonomous vehicles. Image recognition software can improve their efficiency. Several image processing techniques for recognition of birds have been tested. A series of morphological operations were implemented. We divided images into 3 types, Type 1, Type 2, and Type 3, based on the level of difficulty of recognizing birds. Type 1 images were clear; Type 2 images were medium clear, and Type 3 images were unclear. Local thresholding has been implemented using HSV (Hue, Saturation, and Value), GRAY, and RGB (Red, Green, and Blue) color models on all three sections of images and results were tabulated. Template matching using normal correlation and artificial neural networks (ANN) are the other methods that have been developed in this study in addition to image morphology. Template matching produced satisfactory results irrespective of the difficulty level of images, but artificial neural networks produced accuracies of 100, 60, and 50% on Type 1, Type 2, and Type 3 images, respectively. Correct classification rate can be increased by further training. Future research will focus on testing the recognition algorithms in natural or aquacultural settings on autonomous boats. Applications of such techniques to industrial, agricultural, or related areas are additional future possibilities.

Comparative study on the performance of textural image features for active contour segmentation.

PubMed

Moraru, Luminita; Moldovanu, Simona

2012-07-01

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.

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

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

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.

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

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

Gao, M; Fan, T; Duan, J

2015-06-15

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

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

Gender moderates the association between dorsal medial prefrontal cortex volume and depressive symptoms in a subclinical sample.

PubMed

Carlson, Joshua M; Depetro, Emily; Maxwell, Joshua; Harmon-Jones, Eddie; Hajcak, Greg

2015-08-30

Major depressive disorder is associated with lower medial prefrontal cortex volumes. The role that gender might play in moderating this relationship and what particular medial prefrontal cortex subregion(s) might be implicated is unclear. Magnetic resonance imaging was used to assess dorsal, ventral, and anterior cingulate regions of the medial prefrontal cortex in a normative sample of male and female adults. The Depression, Anxiety, and Stress Scale (DASS) was used to measure these three variables. Voxel-based morphometry was used to test for correlations between medial prefrontal gray matter volume and depressive traits. The dorsal medial frontal cortex was correlated with greater levels of depression, but not anxiety and stress. Gender moderates this effect: in males greater levels of depression were associated with lower dorsal medial prefrontal volumes, but in females no relationship was observed. The results indicate that even within a non-clinical sample, male participants with higher levels of depressive traits tend to have lower levels of gray matter volume in the dorsal medial prefrontal cortex. Our finding is consistent with low dorsal medial prefrontal volume contributing to the development of depression in males. Future longitudinal work is needed to substantiate this possibility. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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.

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

TU-AB-BRA-05: Repeatability of [F-18]-NaF PET Imaging Biomarkers for Bone Lesions: A Multicenter Study

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

Lin, C; Bradshaw, T; Perk, T

2015-06-15

Purpose: Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While therapeutic efficacy has been traditionally quantified by SUV metrics, imaging texture features have shown potential for use as quantitative biomarkers. In this study we evaluated the repeatability of quantitative {sup 18}F-NaF PET-derived SUV metrics and texture features in bone lesions from patients in a multicenter study. Methods: Twenty-nine metastatic castrate-resistant prostate cancer patients received whole-body test-retest NaF PET/CT scans from one of three harmonized imaging centers. Bone lesions of volume greater than 1.5 cm{sup 3} were identified and automatically segmented using a SUV>15 threshold. From eachmore » lesion, 55 NaF PET-derived texture features (including first-order, co-occurrence, grey-level run-length, neighbor gray-level, and neighbor gray-tone difference matrix) were extracted. The test-retest repeatability of each SUV metric and texture feature was assessed with Bland-Altman analysis. Results: A total of 315 bone lesions were evaluated. Of the traditional SUV metrics, the repeatability coefficient (RC) was 12.6 SUV for SUVmax, 2.5 SUV for SUVmean, and 4.3 cm{sup 3} for volume. Their respective intralesion coefficients of variation (COVs) were 12%, 17%, and 6%. Of the texture features, COV was lowest for entropy (0.03%) and highest for kurtosis (105%). Lesion intraclass correlation coefficient (ICC) was lowest for maximum correlation coefficient (ICC=0.848), and highest for entropy (ICC=0.985). Across imaging centers, repeatability of texture features and SUV varied. For example, across imaging centers, COV for SUVmax ranged between 11–23%. Conclusion: Many NaF PET-derived SUV metrics and texture features for bone lesions demonstrated high repeatability, such as SUVmax, entropy, and volume. Several imaging texture features demonstrated poor repeatability, such as SUVtotal and SUVstd. These results can be used to establish response criteria for NaF PET-based treatment response assessment. Prostate Cancer Foundation (PCF)« less

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.

Image Understanding. Proceedings of a Workshop (11th) Held at College Park, Maryland, April 30, 1980

DTIC Science & Technology

1980-04-30

space nearest connected pairs. The new change in disparity is evaluated, and tested to see whether it lies in the |^ - ff, i? + o\\ inter - val. When no...property values such as gray level and " busyness ". Figure 3a shows a house picture containing five principal types of regions—sky, grass, bushes...pixe1 based on those of its neighbors; see Figure 3c Similar Improvement is obtained when the busyness values are Iteratively smoothed, e.g. by

Nonlinear Time-Variant Response in an Avalanche Photodiode Array Based Laser Detection and Ranging System

DTIC Science & Technology

2007-03-01

the system is treated in a gray-box manner, with limited known parameters. The analytical approach which follows was used to identify the deviations be...effect spherical aberration, coma and astigmatism is to blur the image by introducing light from outside each pixel’s IFOV. Petzval field curvature and...difference between the two records is not the linear difference of the incident light levels. Even dark current subtraction must be treated with caution

Image processing and recognition for biological images

PubMed Central

Uchida, Seiichi

2013-01-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. PMID:23560739

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.

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.

Freezing effect on bread appearance evaluated by digital imaging

NASA Astrophysics Data System (ADS)

Zayas, Inna Y.

1999-01-01

In marketing channels, bread is sometimes delivered in a frozen sate for distribution. Changes occur in physical dimensions, crumb grain and appearance of slices. Ten loaves, twelve bread slices per loaf were scanned for digital image analysis and then frozen in a commercial refrigerator. The bread slices were stored for four weeks scanned again, permitted to thaw and scanned a third time. Image features were extracted, to determine shape, size and image texture of the slices. Different thresholds of grey levels were set to detect changes that occurred in crumb, images were binarized at these settings. The number of pixels falling into these gray level settings were determined for each slice. Image texture features of subimages of each slice were calculated to quantify slice crumb grain. The image features of the slice size showed shrinking of bread slices, as a results of freezing and storage, although shape of slices did not change markedly. Visible crumb texture changes occurred and these changes were depicted by changes in image texture features. Image texture features showed that slice crumb changed differently at the center of a slice compared to a peripheral area close to the crust. Image texture and slice features were sufficient for discrimination of slices before and after freezing and after thawing.

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

Simultaneous PET/MR imaging of the brain: feasibility of cerebral blood flow measurements with FAIR-TrueFISP arterial spin labeling MRI.

PubMed

Stegger, Lars; Martirosian, Petros; Schwenzer, Nina; Bisdas, Sotirios; Kolb, Armin; Pfannenberg, Christina; Claussen, Claus D; Pichler, Bernd; Schick, Fritz; Boss, Andreas

2012-11-01

Hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) with simultaneous data acquisition promises a comprehensive evaluation of cerebral pathophysiology on a molecular, anatomical, and functional level. Considering the necessary changes to the MR scanner design the feasibility of arterial spin labeling (ASL) is unclear. To evaluate whether cerebral blood flow imaging with ASL is feasible using a prototype PET/MRI device. ASL imaging of the brain with Flow-sensitive Alternating Inversion Recovery (FAIR) spin preparation and true fast imaging in steady precession (TrueFISP) data readout was performed in eight healthy volunteers sequentially on a prototype PET/MRI and a stand-alone MR scanner with 128 × 128 and 192 × 192 matrix sizes. Cerebral blood flow values for gray matter, signal-to-noise and contrast-to-noise ratios, and relative signal change were compared. Additionally, the feasibility of ASL as part of a clinical hybrid PET/MRI protocol was demonstrated in five patients with intracerebral tumors. Blood flow maps showed good delineation of gray and white matter with no discernible artifacts. The mean blood flow values of the eight volunteers on the PET/MR system were 51 ± 9 and 51 ± 7 mL/100 g/min for the 128 × 128 and 192 × 192 matrices (stand-alone MR, 57 ± 2 and 55 ± 5, not significant). The value for signal-to-noise (SNR) was significantly higher for the PET/MRI system using the 192 × 192 matrix size (P < 0.01), the relative signal change (δS) was significantly lower for the 192 × 192 matrix size (P = 0.02). ASL imaging as part of a clinical hybrid PET/MRI protocol could successfully be accomplished in all patients in diagnostic image quality. ASL brain imaging is feasible with a prototype hybrid PET/MRI scanner, thus adding to the value of this novel imaging technique.

Line drawing extraction from gray level images by feature integration

NASA Astrophysics Data System (ADS)

Yoo, Hoi J.; Crevier, Daniel; Lepage, Richard; Myler, Harley R.

1994-10-01

We describe procedures that extract line drawings from digitized gray level images, without use of domain knowledge, by modeling preattentive and perceptual organization functions of the human visual system. First, edge points are identified by standard low-level processing, based on the Canny edge operator. Edge points are then linked into single-pixel thick straight- line segments and circular arcs: this operation serves to both filter out isolated and highly irregular segments, and to lump the remaining points into a smaller number of structures for manipulation by later stages of processing. The next stages consist in linking the segments into a set of closed boundaries, which is the system's definition of a line drawing. According to the principles of Gestalt psychology, closure allows us to organize the world by filling in the gaps in a visual stimulation so as to perceive whole objects instead of disjoint parts. To achieve such closure, the system selects particular features or combinations of features by methods akin to those of preattentive processing in humans: features include gaps, pairs of straight or curved parallel lines, L- and T-junctions, pairs of symmetrical lines, and the orientation and length of single lines. These preattentive features are grouped into higher-level structures according to the principles of proximity, similarity, closure, symmetry, and feature conjunction. Achieving closure may require supplying missing segments linking contour concavities. Choices are made between competing structures on the basis of their overall compliance with the principles of closure and symmetry. Results include clean line drawings of curvilinear manufactured objects. The procedures described are part of a system called VITREO (viewpoint-independent 3-D recognition and extraction of objects).

Profiling pleural effusion cells by a diffraction imaging method

NASA Astrophysics Data System (ADS)

Al-Qaysi, Safaa; Hong, Heng; Wen, Yuhua; Lu, Jun Q.; Feng, Yuanming; Hu, Xin-Hua

2018-02-01

Assay of cells in pleural effusion (PE) is an important means of disease diagnosis. Conventional cytology of effusion samples, however, has low sensitivity and depends heavily on the expertise of cytopathologists. We applied a polarization diffraction imaging flow cytometry method on effusion cells to investigate their features. Diffraction imaging of the PE cell samples has been performed on 6000 to 12000 cells for each effusion cell sample of three patients. After prescreening to remove images by cellular debris and aggregated non-cellular particles, the image textures were extracted with a gray level co-occurrence matrix (GLCM) algorithm. The distribution of the imaged cells in the GLCM parameters space was analyzed by a Gaussian Mixture Model (GMM) to determine the number of clusters among the effusion cells. These results yield insight on textural features of diffraction images and related cellular morphology in effusion samples and can be used toward the development of a label-free method for effusion cells assay.

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.

An Efficient Semi-fragile Watermarking Scheme for Tamper Localization and Recovery

NASA Astrophysics Data System (ADS)

Hou, Xiang; Yang, Hui; Min, Lianquan

2018-03-01

To solve the problem that remote sensing images are vulnerable to be tampered, a semi-fragile watermarking scheme was proposed. Binary random matrix was used as the authentication watermark, which was embedded by quantizing the maximum absolute value of directional sub-bands coefficients. The average gray level of every non-overlapping 4×4 block was adopted as the recovery watermark, which was embedded in the least significant bit. Watermarking detection could be done directly without resorting to the original images. Experimental results showed our method was robust against rational distortions to a certain extent. At the same time, it was fragile to malicious manipulation, and realized accurate localization and approximate recovery of the tampered regions. Therefore, this scheme can protect the security of remote sensing image effectively.

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

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.

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.

Higher homocysteine associated with thinner cortical gray matter in 803 ADNI subjects

PubMed Central

Madsen, Sarah K.; Rajagopalan, Priya; Joshi, Shantanu H.; Toga, Arthur W.; Thompson, Paul M.

2014-01-01

A significant portion of our risk for dementia in old age is associated with lifestyle factors (diet, exercise, and cardiovascular health) that are modifiable, at least in principle. One such risk factor – high homocysteine levels in the blood – is known to increase risk for Alzheimer’s disease and vascular disorders. Here we set out to understand how homocysteine levels relate to 3D surface-based maps of cortical gray matter distribution (thickness, volume, surface area) computed from brain MRI in 803 elderly subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Individuals with higher plasma levels of homocysteine had lower gray matter thickness in bilateral frontal, parietal, occipital and right temporal regions; and lower gray matter volumes in left frontal, parietal, temporal, and occipital regions, after controlling for diagnosis, age, and sex, and after correcting for multiple comparisons. No significant within-group associations were found in cognitively healthy people, mild cognitive impairment, or Alzheimer’s disease. These regional differences in gray matter structure may be useful biomarkers to assess the effectiveness of interventions, such as vitamin B supplements, that aim to prevent homocysteine-related brain atrophy by normalizing homocysteine levels. PMID:25444607

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.

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.

Employing wavelet-based texture features in ammunition classification

NASA Astrophysics Data System (ADS)

Borzino, Ángelo M. C. R.; Maher, Robert C.; Apolinário, José A.; de Campos, Marcello L. R.

2017-05-01

Pattern recognition, a branch of machine learning, involves classification of information in images, sounds, and other digital representations. This paper uses pattern recognition to identify which kind of ammunition was used when a bullet was fired based on a carefully constructed set of gunshot sound recordings. To do this task, we show that texture features obtained from the wavelet transform of a component of the gunshot signal, treated as an image, and quantized in gray levels, are good ammunition discriminators. We test the technique with eight different calibers and achieve a classification rate better than 95%. We also compare the performance of the proposed method with results obtained by standard temporal and spectrographic techniques

Automated extraction of pleural effusion in three-dimensional thoracic CT images

NASA Astrophysics Data System (ADS)

Kido, Shoji; Tsunomori, Akinori

2009-02-01

It is important for diagnosis of pulmonary diseases to measure volume of accumulating pleural effusion in threedimensional thoracic CT images quantitatively. However, automated extraction of pulmonary effusion correctly is difficult. Conventional extraction algorithm using a gray-level based threshold can not extract pleural effusion from thoracic wall or mediastinum correctly, because density of pleural effusion in CT images is similar to those of thoracic wall or mediastinum. So, we have developed an automated extraction method of pulmonary effusion by use of extracting lung area with pleural effusion. Our method used a template of lung obtained from a normal lung for segmentation of lungs with pleural effusions. Registration process consisted of two steps. First step was a global matching processing between normal and abnormal lungs of organs such as bronchi, bones (ribs, sternum and vertebrae) and upper surfaces of livers which were extracted using a region-growing algorithm. Second step was a local matching processing between normal and abnormal lungs which were deformed by the parameter obtained from the global matching processing. Finally, we segmented a lung with pleural effusion by use of the template which was deformed by two parameters obtained from the global matching processing and the local matching processing. We compared our method with a conventional extraction method using a gray-level based threshold and two published methods. The extraction rates of pleural effusions obtained from our method were much higher than those obtained from other methods. Automated extraction method of pulmonary effusion by use of extracting lung area with pleural effusion is promising for diagnosis of pulmonary diseases by providing quantitative volume of accumulating pleural effusion.

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.

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.

Pesticide contamination of endangered gray bats and their food base in Boone County, Missouri, 1982

USGS Publications Warehouse

Clawson, R.L.; Clark, D.R.

1989-01-01

Gray bat guano from Devil's Icebox and Hunters Caves contained dieldrin at levels previously associated with gray bat mortality. Two of four gray bats found dead in Holton Cave had lethal brain concentrations of dieldrin. Twenty-five of 28 (86%) insect samples from bat foraging areas contained measurable dieldrin, heptachlor epoxide or both. Beetle samples were most heavily contaminated containing up to 2.2 ppm and 1.1 ppm heptachlor epoxide. The addition of Holton Cave brings to five the number of Missouri caves where gray bats have died of food chain pesticide poisoning.

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.

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.

Real-time detection of respiration rate with non-contact mode based on low-end imaging equipment

NASA Astrophysics Data System (ADS)

Jin, Xiaoli; Dong, Liquan; Zhao, Yuejin; Liu, Xiaohua; Liu, Ming; Yang, Lei; Liu, Weiyu; Zhao, Jingsheng; Xing, Jinhui

2013-09-01

Standard instrumentation for the assessment of respiration rate is large and based on invasive method, and not suitable for daily inspection. An optical, simple and non-contact measurement method to detect human respiration rate using lowend imaging equipment is discussed. This technology is based on the visible light absorption of blood, which contains many important physiological information of the cardiovascular system. The light absorption of facial area can be indirectly reflected to gray value of the corresponding area image. In this paper, we acquire the respiration rate through the video signal captured by low-end imaging equipment. Firstly, the color CCD captures the facial area below the eyes and every frame of the video can be separated into three RGB channels. The blue channel is extracted as the research object. Then, we calculate the mean gray value for each image and draw the mean gray curve along the time. Fourier transform can get the frequency spectrogram of the graph, which is filtered through the Fourier filter. The extreme point is the value of the respiratory rate. Finally, an available interface program is designed and we have some volunteers tested. The correlation coefficient between the experimental data and the data provided by a reference instrument is 0.98. The consistency of the experimental results is very well. This technology costs so low that it will be widely used in medical and daily respiration rate measurement.

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.

Greater cerebellar gray matter volume in car drivers: an exploratory voxel-based morphometry study

PubMed Central

Sakai, Hiroyuki; Ando, Takafumi; Sadato, Norihiro; Uchiyama, Yuji

2017-01-01

Previous functional neuroimaging studies have identified multiple brain areas associated with distinct aspects of car driving in simulated traffic environments. Few studies, however, have examined brain morphology associated with everyday car-driving experience in real traffic. Thus, the aim of the current study was to identify gray matter volume differences between drivers and non-drivers. We collected T1-weighted structural brain images from 73 healthy young adults (36 drivers and 37 non-drivers). We performed a whole-brain voxel-based morphometry analysis to examine between-group differences in regional gray matter volume. Compared with non-drivers, drivers showed significantly greater gray matter volume in the left cerebellar hemisphere, which has been associated with cognitive rather than motor functioning. In contrast, we found no brain areas with significantly greater gray matter volume in non-drivers compared with drivers. Our findings indicate that experience with everyday car driving in real traffic is associated with greater gray matter volume in the left cerebellar hemisphere. This brain area may be involved in abilities that are critical for driving a car, but are not commonly or frequently used during other daily activities. PMID:28417971

Investigation of mindfulness meditation practitioners with voxel-based morphometry

PubMed Central

Hölzel, Britta K.; Ott, Ulrich; Gard, Tim; Hempel, Hannes; Weygandt, Martin; Morgen, Katrin; Vaitl, Dieter

2008-01-01

Mindfulness meditators practice the non-judgmental observation of the ongoing stream of internal experiences as they arise. Using voxel-based morphometry, this study investigated MRI brain images of 20 mindfulness (Vipassana) meditators (mean practice 8.6 years; 2 h daily) and compared the regional gray matter concentration to that of non-meditators matched for sex, age, education and handedness. Meditators were predicted to show greater gray matter concentration in regions that are typically activated during meditation. Results confirmed greater gray matter concentration for meditators in the right anterior insula, which is involved in interoceptive awareness. This group difference presumably reflects the training of bodily awareness during mindfulness meditation. Furthermore, meditators had greater gray matter concentration in the left inferior temporal gyrus and right hippocampus. Both regions have previously been found to be involved in meditation. The mean value of gray matter concentration in the left inferior temporal gyrus was predictable by the amount of meditation training, corroborating the assumption of a causal impact of meditation training on gray matter concentration in this region. Results suggest that meditation practice is associated with structural differences in regions that are typically activated during meditation and in regions that are relevant for the task of meditation. PMID:19015095

Greater cerebellar gray matter volume in car drivers: an exploratory voxel-based morphometry study.

PubMed

Sakai, Hiroyuki; Ando, Takafumi; Sadato, Norihiro; Uchiyama, Yuji

2017-04-18

Previous functional neuroimaging studies have identified multiple brain areas associated with distinct aspects of car driving in simulated traffic environments. Few studies, however, have examined brain morphology associated with everyday car-driving experience in real traffic. Thus, the aim of the current study was to identify gray matter volume differences between drivers and non-drivers. We collected T1-weighted structural brain images from 73 healthy young adults (36 drivers and 37 non-drivers). We performed a whole-brain voxel-based morphometry analysis to examine between-group differences in regional gray matter volume. Compared with non-drivers, drivers showed significantly greater gray matter volume in the left cerebellar hemisphere, which has been associated with cognitive rather than motor functioning. In contrast, we found no brain areas with significantly greater gray matter volume in non-drivers compared with drivers. Our findings indicate that experience with everyday car driving in real traffic is associated with greater gray matter volume in the left cerebellar hemisphere. This brain area may be involved in abilities that are critical for driving a car, but are not commonly or frequently used during other daily activities.

Sub-Pixel Extraction of Laser Stripe Center Using an Improved Gray-Gravity Method †

PubMed Central

Li, Yuehua; Zhou, Jingbo; Huang, Fengshan; Liu, Lijian

2017-01-01

Laser stripe center extraction is a key step for the profile measurement of line structured light sensors (LSLS). To accurately obtain the center coordinates at sub-pixel level, an improved gray-gravity method (IGGM) was proposed. Firstly, the center points of the stripe were computed using the gray-gravity method (GGM) for all columns of the image. By fitting these points using the moving least squares algorithm, the tangential vector, the normal vector and the radius of curvature can be robustly obtained. One rectangular region could be defined around each of the center points. Its two sides that are parallel to the tangential vector could alter their lengths according to the radius of the curvature. After that, the coordinate for each center point was recalculated within the rectangular region and in the direction of the normal vector. The center uncertainty was also analyzed based on the Monte Carlo method. The obtained experimental results indicate that the IGGM is suitable for both the smooth stripes and the ones with sharp corners. The high accuracy center points can be obtained at a relatively low computation cost. The measured results of the stairs and the screw surface further demonstrate the effectiveness of the method. PMID:28394288

Brain Volume Differences Associated With Hearing Impairment in Adults

PubMed Central

Vriend, Chris; Heslenfeld, Dirk J.; Versfeld, Niek J.; Kramer, Sophia E.

2018-01-01

Speech comprehension depends on the successful operation of a network of brain regions. Processing of degraded speech is associated with different patterns of brain activity in comparison with that of high-quality speech. In this exploratory study, we studied whether processing degraded auditory input in daily life because of hearing impairment is associated with differences in brain volume. We compared T1-weighted structural magnetic resonance images of 17 hearing-impaired (HI) adults with those of 17 normal-hearing (NH) controls using a voxel-based morphometry analysis. HI adults were individually matched with NH adults based on age and educational level. Gray and white matter brain volumes were compared between the groups by region-of-interest analyses in structures associated with speech processing, and by whole-brain analyses. The results suggest increased gray matter volume in the right angular gyrus and decreased white matter volume in the left fusiform gyrus in HI listeners as compared with NH ones. In the HI group, there was a significant correlation between hearing acuity and cluster volume of the gray matter cluster in the right angular gyrus. This correlation supports the link between partial hearing loss and altered brain volume. The alterations in volume may reflect the operation of compensatory mechanisms that are related to decoding meaning from degraded auditory input. PMID:29557274

Differential regional gray matter volumes in patients with on-line game addiction and professional gamers.

PubMed

Han, Doug Hyun; Lyoo, In Kyoon; Renshaw, Perry F

2012-04-01

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. Copyright © 2012 Elsevier Ltd. All rights reserved.

Tinnitus Multimodal Imaging

DTIC Science & Technology

2016-12-01

images were segmented into gray and white matter images and spatially normalized to the MNI template (3 mm isotropic voxels) using the DARTEL toolbox in...AWARD NUMBER: W81XWH-13-1-0494 TITLE: Tinnitus Multimodal Imaging PRINCIPAL INVESTIGATOR: Steven Wan Cheung CONTRACTING ORGANIZATION... Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 DISTRIBUTION STATEMENT: Approved for Public Release; Distribution Unlimited

Image splitting and remapping method for radiological image compression

NASA Astrophysics Data System (ADS)

Lo, Shih-Chung B.; Shen, Ellen L.; Mun, Seong K.

1990-07-01

A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

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.

Structural Imaging and Parkinson's Disease: Moving Toward Quantitative Markers of Disease Progression.

PubMed

Sterling, N W; Lewis, M M; Du, G; Huang, X

2016-05-27

Parkinson's disease (PD) is a progressive age-related neurodegenerative disorder. Although the pathological hallmark of PD is dopaminergic cell death in the substantia nigra pars compacta, widespread neurodegenerative changes occur throughout the brain as disease progresses. Postmortem studies, for example, have demonstrated the presence of Lewy pathology, apoptosis, and loss of neurotransmitters and interneurons in both cortical and subcortical regions of PD patients. Many in vivo structural imaging studies have attempted to gauge PD-related pathology, particularly in gray matter, with the hope of identifying an imaging biomarker. Reports of brain atrophy in PD, however, have been inconsistent, most likely due to differences in the studied populations (i.e. different disease stages and/or clinical subtypes), experimental designs (i.e. cross-sectional vs. longitudinal), and image analysis methodologies (i.e. automatic vs. manual segmentation). This review attempts to summarize the current state of gray matter structural imaging research in PD in relationship to disease progression, reconciling some of the differences in reported results, and to identify challenges and future avenues.

Gray water recycle: Effect of pretreatment technologies on low pressure reverse osmosis treatment

USDA-ARS?s Scientific Manuscript database

Gray water can be a valuable source of water when properly treated to reduce the risks associated with chemical and microbial contamination to acceptable levels for the intended reuse application. In this study, the treatment of gray water using low pressure reverse osmosis (RO) filtration after pre...

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.

Structural imaging of the brain reveals decreased total brain and total gray matter volumes in obese but not in lean women with polycystic ovary syndrome compared to body mass index-matched counterparts.

PubMed

Ozgen Saydam, Basak; Has, Arzu Ceylan; Bozdag, Gurkan; Oguz, Kader Karli; Yildiz, Bulent Okan

2017-07-01

To detect differences in global brain volumes and identify relations between brain volume and appetite-related hormones in women with polycystic ovary syndrome (PCOS) compared to body mass index-matched controls. Forty subjects participated in this study. Cranial magnetic resonance imaging and measurements of fasting ghrelin, leptin and glucagon-like peptide 1 (GLP-1), as well as GLP-1 levels during mixed-meal tolerance test (MTT), were performed. Total brain volume and total gray matter volume (GMV) were decreased in obese PCOS compared to obese controls (p < 0.05 for both) whereas lean PCOS and controls did not show a significant difference. Secondary analyses of regional brain volumes showed decreases in GMV of the caudate nucleus, ventral diencephalon and hippocampus in obese PCOS compared to obese controls (p < 0.05 for all), whereas lean patients with PCOS had lower GMV in the amygdala than lean controls (p < 0.05). No significant relations were detected between structural differences and measured hormone levels at baseline or during MTT. This study, investigating structural brain alterations in PCOS, suggests volumetric reductions in global brain areas in obese women with PCOS. Functional studies with larger sample size are needed to determine physiopathological roles of these changes and potential effects of long-term medical management on brain structure of PCOS.

[RSF model optimization and its application to brain tumor segmentation in MRI].

PubMed

Cheng, Zhaoning; Song, Zhijian

2013-04-01

Magnetic resonance imaging (MRI) is usually obscure and non-uniform in gray, and the tumors inside are poorly circumscribed, hence the automatic tumor segmentation in MRI is very difficult. Region-scalable fitting (RSF) energy model is a new segmentation approach for some uneven grayscale images. However, the level set formulation (LSF) of RSF model is not suitable for the environment with different grey level distribution inside and outside the intial contour, and the complex intensity environment of MRI always makes it hard to get ideal segmentation results. Therefore, we improved the model by a new LSF and combined it with the mean shift method, which can be helpful for tumor segmentation and has better convergence and target direction. The proposed method has been utilized in a series of studies for real MRI images, and the results showed that it could realize fast, accurate and robust segmentations for brain tumors in MRI, which has great clinical significance.

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.

Homomorphic filtering textural analysis technique to reduce multiplicative noise in the 11Oba nano-doped liquid crystalline compounds

NASA Astrophysics Data System (ADS)

Madhav, B. T. P.; Pardhasaradhi, P.; Manepalli, R. K. N. R.; Pisipati, V. G. K. M.

2015-07-01

The compound undecyloxy benzoic acid (11Oba) exhibits nematic and smectic-C phases while a nano-doped undecyloxy benzoic acid with ZnO exhibits the same nematic and smectic-C phases with reduced clearing temperature as expected. The doping is done with 0.5% and 1% ZnO molecules. The clearing temperatures are reduced by approximately 4 ° and 6 °, respectively (differential scanning calorimeter data). While collecting the images from a polarizing microscope connected with hot stage and camera, the illumination and reflectance combined multiplicatively and the image quality was reduced to identify the exact phase in the compound. A novel technique of homomorphic filtering is used in this manuscript through which multiplicative noise components of the image are separated linearly in the frequency domain. This technique provides a frequency domain procedure to improve the appearance of an image by gray level range compression and contrast enhancement.

Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm

PubMed Central

Wang, Jie-sheng; Han, Shuang; Shen, Na-na; Li, Shu-xia

2014-01-01

For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed. Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix, and the shape characteristics based on the geometric theory of flotation froth images are extracted, respectively, as the input variables of the proposed soft-sensor model. Then the isometric mapping method is used to reduce the input dimension, the network size, and learning time of BP neural network. Finally, a shuffled cuckoo search algorithm is adopted to optimize the BP neural network soft-sensor model. Simulation results show that the model has better generalization results and prediction accuracy. PMID:25133210

Adaptable pattern recognition system for discriminating Melanocytic Nevi from Malignant Melanomas using plain photography images from different image databases.

PubMed

Kostopoulos, Spiros A; Asvestas, Pantelis A; Kalatzis, Ioannis K; Sakellaropoulos, George C; Sakkis, Theofilos H; Cavouras, Dionisis A; Glotsos, Dimitris T

2017-09-01

The aim of this study was to propose features that evaluate pictorial differences between melanocytic nevus (mole) and melanoma lesions by computer-based analysis of plain photography images and to design a cross-platform, tunable, decision support system to discriminate with high accuracy moles from melanomas in different publicly available image databases. Digital plain photography images of verified mole and melanoma lesions were downloaded from (i) Edinburgh University Hospital, UK, (Dermofit, 330moles/70 melanomas, under signed agreement), from 5 different centers (Multicenter, 63moles/25 melanomas, publicly available), and from the Groningen University, Netherlands (Groningen, 100moles/70 melanomas, publicly available). Images were processed for outlining the lesion-border and isolating the lesion from the surrounding background. Fourteen features were generated from each lesion evaluating texture (4), structure (5), shape (4) and color (1). Features were subjected to statistical analysis for determining differences in pictorial properties between moles and melanomas. The Probabilistic Neural Network (PNN) classifier, the exhaustive search features selection, the leave-one-out (LOO), and the external cross-validation (ECV) methods were used to design the PR-system for discriminating between moles and melanomas. Statistical analysis revealed that melanomas as compared to moles were of lower intensity, of less homogenous surface, had more dark pixels with intensities spanning larger spectra of gray-values, contained more objects of different sizes and gray-levels, had more asymmetrical shapes and irregular outlines, had abrupt intensity transitions from lesion to background tissue, and had more distinct colors. The PR-system designed by the Dermofit images scored on the Dermofit images, using the ECV, 94.1%, 82.9%, 96.5% for overall accuracy, sensitivity, specificity, on the Multicenter Images 92.0%, 88%, 93.7% and on the Groningen Images 76.2%, 73.9%, 77.8% respectively. The PR-system as designed by the Dermofit image database could be fine-tuned to classify with good accuracy plain photography moles/melanomas images of other databases employing different image capturing equipment and protocols. Copyright © 2017 Elsevier B.V. All rights reserved.

[Advantages and Application Prospects of Deep Learning in Image Recognition and Bone Age Assessment].

PubMed

Hu, T H; Wan, L; Liu, T A; Wang, M W; Chen, T; Wang, Y H

2017-12-01

Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech recognitions, and also has been extensively used in the fields of face recognition and information retrieval because of its special superiority. Bone X-ray images express different variations in black-white-gray gradations, which have image features of black and white contrasts and level differences. Based on these advantages of deep learning in image recognition, we combine it with the research of bone age assessment to provide basic datum for constructing a forensic automatic system of bone age assessment. This paper reviews the basic concept and network architectures of deep learning, and describes its recent research progress on image recognition in different research fields at home and abroad, and explores its advantages and application prospects in bone age assessment. Copyright© by the Editorial Department of Journal of Forensic Medicine.

Automatic detection method for mura defects on display film surface using modified Weber's law

NASA Astrophysics Data System (ADS)

Kim, Myung-Muk; Lee, Seung-Ho

2014-07-01

We propose a method that automatically detects mura defects on display film surfaces using a modified version of Weber's law. The proposed method detects mura defects regardless of their properties and shapes by identifying regions perceived by human vision as mura using the brightness of pixel and image distribution ratio of mura in an image histogram. The proposed detection method comprises five stages. In the first stage, the display film surface image is acquired and a gray-level shift performed. In the second and third stages, the image histogram is acquired and analyzed, respectively. In the fourth stage, the mura range is acquired. This is followed by postprocessing in the fifth stage. Evaluations of the proposed method conducted using 200 display film mura image samples indicate a maximum detection rate of ˜95.5%. Further, the results of application of the Semu index for luminance mura in flat panel display (FPD) image quality inspection indicate that the proposed method is more reliable than a popular conventional method.

Unsupervised texture image segmentation by improved neural network ART2

NASA Technical Reports Server (NTRS)

Wang, Zhiling; Labini, G. Sylos; Mugnuolo, R.; Desario, Marco

1994-01-01

We here propose a segmentation algorithm of texture image for a computer vision system on a space robot. An improved adaptive resonance theory (ART2) for analog input patterns is adapted to classify the image based on a set of texture image features extracted by a fast spatial gray level dependence method (SGLDM). The nonlinear thresholding functions in input layer of the neural network have been constructed by two parts: firstly, to reduce the effects of image noises on the features, a set of sigmoid functions is chosen depending on the types of the feature; secondly, to enhance the contrast of the features, we adopt fuzzy mapping functions. The cluster number in output layer can be increased by an autogrowing mechanism constantly when a new pattern happens. Experimental results and original or segmented pictures are shown, including the comparison between this approach and K-means algorithm. The system written in C language is performed on a SUN-4/330 sparc-station with an image board IT-150 and a CCD camera.

Comparing object recognition from binary and bipolar edge images for visual prostheses

PubMed Central

Jung, Jae-Hyun; Pu, Tian; Peli, Eli

2017-01-01

Visual prostheses require an effective representation method due to the limited display condition which has only 2 or 3 levels of grayscale in low resolution. Edges derived from abrupt luminance changes in images carry essential information for object recognition. Typical binary (black and white) edge images have been used to represent features to convey essential information. However, in scenes with a complex cluttered background, the recognition rate of the binary edge images by human observers is limited and additional information is required. The polarity of edges and cusps (black or white features on a gray background) carries important additional information; the polarity may provide shape from shading information missing in the binary edge image. This depth information may be restored by using bipolar edges. We compared object recognition rates from 16 binary edge images and bipolar edge images by 26 subjects to determine the possible impact of bipolar filtering in visual prostheses with 3 or more levels of grayscale. Recognition rates were higher with bipolar edge images and the improvement was significant in scenes with complex backgrounds. The results also suggest that erroneous shape from shading interpretation of bipolar edges resulting from pigment rather than boundaries of shape may confound the recognition. PMID:28458481

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.

Physical activity and inflammation: effects on gray-matter volume and cognitive decline in aging.

PubMed

Papenberg, Goran; Ferencz, Beata; Mangialasche, Francesca; Mecocci, Patrizia; Cecchetti, Roberta; Kalpouzos, Grégoria; Fratiglioni, Laura; Bäckman, Lars

2016-10-01

Physical activity has been positively associated with gray-matter integrity. In contrast, pro-inflammatory cytokines seem to have negative effects on the aging brain and have been related to dementia. It was investigated whether an inactive lifestyle and high levels of inflammation resulted in smaller gray-matter volumes and predicted cognitive decline across 6 years in a population-based study of older adults (n = 414). Self-reported physical activity (fitness-enhancing, health-enhancing, inadequate) was linked to gray-matter volume, such that individuals with inadequate physical activity had the least gray matter. There were no overall associations between different pro-and anti-inflammatory markers (IL-1β, IL-6, IL-10, IL-12p40, IL-12p70, G-CSF, and TNF-α) and gray-matter integrity. However, persons with inadequate activity and high levels of the pro-inflammatory marker IL-12p40 had smaller volumes of lateral prefrontal cortex and hippocampus and declined more on the Mini-Mental State Examination test over 6 years compared with physically inactive individuals with low levels of IL-12p40 and to more physically active persons, irrespective of their levels of IL-12p40. These patterns of data suggested that inflammation was particularly detrimental in inactive older adults and may exacerbate the negative effects of physical inactivity on brain and cognition in old age. Hum Brain Mapp 37:3462-3473, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Effect of cerebral spinal fluid suppression for diffusional kurtosis imaging.

PubMed

Yang, Alicia W; Jensen, Jens H; Hu, Caixia C; Tabesh, Ali; Falangola, Maria F; Helpern, Joseph A

2013-02-01

To evaluate the cerebral spinal fluid (CSF) partial volume effect on diffusional kurtosis imaging (DKI) metrics in white matter and cortical gray matter. Four healthy volunteers participated in this study. Standard DKI and fluid-attenuated inversion recovery (FLAIR) DKI experiments were performed using a twice-refocused-spin-echo diffusion sequence. The conventional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, D[symbol in text], D[symbol in text] together with DKI metrics of mean, axial, and radial kurtosis (MK, K[symbol in text], K[symbol in text], were measured and compared. Single image slices located above the lateral ventricles, with similar anatomical features for each subject, were selected to minimize the effect of CSF from the ventricles. In white matter, differences of less than 10% were observed between diffusion metrics measured with standard DKI and FLAIR-DKI sequences, suggesting minimal CSF contamination. For gray matter, conventional DTI metrics differed by 19% to 52%, reflecting significant CSF partial volume effects. Kurtosis metrics, however, changed by 11% or less, indicating greater robustness with respect to CSF contamination. Kurtosis metrics are less sensitive to CSF partial voluming in cortical gray matter than conventional diffusion metrics. The kurtosis metrics may then be more specific indicators of changes in tissue microstructure, provided the effect sizes for the changes are comparable. Copyright © 2012 Wiley Periodicals, Inc.

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

Gray matter morphological anomalies in the cerebellar vermis in first-episode schizophrenia patients with cognitive deficits.

PubMed

Wang, Jingjuan; Zhou, Li; Cui, Chunlei; Liu, Zhening; Lu, Jie

2017-11-22

Cognitive deficits are a core feature of early schizophrenia. However, the pathological foundations underlying cognitive deficits are still unknown. The present study examined the association between gray matter density and cognitive deficits in first-episode schizophrenia. Structural magnetic resonance imaging of the brain was performed in 34 first-episode schizophrenia patients and 21 healthy controls. Patients were divided into two subgroups according to working memory task performance. The three groups were well matched for age, gender, and education, and the two patient groups were also further matched for diagnosis, duration of illness, and antipsychotic treatment. Voxel-based morphometric analysis was performed to estimate changes in gray matter density in first-episode schizophrenia patients with cognitive deficits. The relationships between gray matter density and clinical outcomes were explored. Patients with cognitive deficits were found to have reduced gray matter density in the vermis and tonsil of cerebellum compared with patients without cognitive deficits and healthy controls, decreased gray matter density in left supplementary motor area, bilateral precentral gyrus compared with patients without cognitive deficits. Classifier results showed GMD in cerebellar vermis tonsil cluster could differentiate SZ-CD from controls, left supplementary motor area cluster could differentiate SZ-CD from SZ-NCD. Gray matter density values of the cerebellar vermis cluster in patients groups were positively correlated with cognitive severity. Decreased gray matter density in the vermis and tonsil of cerebellum may underlie early psychosis and serve as a candidate biomarker for schizophrenia with cognitive deficits.

Quantitative evaluation methods of skin condition based on texture feature parameters.

PubMed

Pang, Hui; Chen, Tianhua; Wang, Xiaoyi; Chang, Zhineng; Shao, Siqi; Zhao, Jing

2017-03-01

In order to quantitatively evaluate the improvement of the skin condition after using skin care products and beauty, a quantitative evaluation method for skin surface state and texture is presented, which is convenient, fast and non-destructive. Human skin images were collected by image sensors. Firstly, the median filter of the 3 × 3 window is used and then the location of the hairy pixels on the skin is accurately detected according to the gray mean value and color information. The bilinear interpolation is used to modify the gray value of the hairy pixels in order to eliminate the negative effect of noise and tiny hairs on the texture. After the above pretreatment, the gray level co-occurrence matrix (GLCM) is calculated. On the basis of this, the four characteristic parameters, including the second moment, contrast, entropy and correlation, and their mean value are calculated at 45 ° intervals. The quantitative evaluation model of skin texture based on GLCM is established, which can calculate the comprehensive parameters of skin condition. Experiments show that using this method evaluates the skin condition, both based on biochemical indicators of skin evaluation methods in line, but also fully consistent with the human visual experience. This method overcomes the shortcomings of the biochemical evaluation method of skin damage and long waiting time, also the subjectivity and fuzziness of the visual evaluation, which achieves the non-destructive, rapid and quantitative evaluation of skin condition. It can be used for health assessment or classification of the skin condition, also can quantitatively evaluate the subtle improvement of skin condition after using skin care products or stage beauty.

Delineation of early brain development from fetuses to infants with diffusion MRI and beyond.

PubMed

Ouyang, Minhui; Dubois, Jessica; Yu, Qinlin; Mukherjee, Pratik; Huang, Hao

2018-04-12

Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders. Copyright © 2018 Elsevier Inc. All rights reserved.

Thinner retinal layers are associated with changes in the visual pathway: A population-based study.

PubMed

Mutlu, Unal; Ikram, Mohammad K; Roshchupkin, Gennady V; Bonnemaijer, Pieter W M; Colijn, Johanna M; Vingerling, Johannes R; Niessen, Wiro J; Ikram, Mohammad A; Klaver, Caroline C W; Vernooij, Meike W

2018-06-23

Increasing evidence shows that thinner retinal nerve fiber layer (RNFL) and ganglion cell layer (GCL), assessed on optical coherence tomography (OCT), are reflecting global brain atrophy. Yet, little is known on the relation of these layers with specific brain regions. Using voxel-based analysis, we aimed to unravel specific brain regions associated with these retinal layers. We included 2,235 persons (mean age: 67.3 years, 55% women) from the Rotterdam Study (2007-2012) who had gradable retinal OCT images and brain magnetic resonance imaging (MRI) scans, including diffusion tensor (DT) imaging. Thicknesses of peripapillary RNFL and perimacular GCL were measured using an automated segmentation algorithm. Voxel-based morphometry protocols were applied to process DT-MRI data. We investigated the association between retinal layer thickness with voxel-wise gray matter density and white matter microstructure by performing linear regression models. We found that thinner RNFL and GCL were associated with lower gray matter density in the visual cortex, and with lower fractional anisotropy and higher mean diffusivity in white matter tracts that are part of the optic radiation. Furthermore, thinner GCL was associated with lower gray matter density of the thalamus. Thinner RNFL and GCL are associated with gray and white matter changes in the visual pathway suggesting that retinal thinning on OCT may be specifically associated with changes in the visual pathway rather than with changes in the global brain. These findings may serve as a basis for understanding visual symptoms in elderly patients, patients with Alzheimer's disease, or patients with posterior cortical atrophy. © 2018 Wiley Periodicals, Inc.

7 Tesla magnetic resonance imaging of caudal anterior cingulate and posterior cingulate cortex atrophy in patients with trigeminal neuralgia.

PubMed

Moon, Hyeong Cheol; Park, Chan-A; Jeon, Yeong-Jae; You, Soon Tae; Baek, Hyun Man; Lee, Youn Joo; Cho, Chul Beom; Cheong, Chae Joon; Park, Young Seok

2018-05-16

The cingulate cortex (CC) is a brain region that plays a key role in pain processing, but CC abnormalities are not unclear in patients with trigeminal neuralgia (TN). The purpose of this study was to determine the central causal mechanisms of TN and the surrounding brain structure in healthy controls and patients with TN using 7 Tesla (T) magnetic resonance imaging (MRI). Whole-brain parcellation in gray matter volume and thickness was assessed in 15 patients with TN and 16 healthy controls matched for sex, age, and regional variability using T1-weighted imaging. Regions of interest (ROIs) were measured in rostral anterior CC (rACC), caudal anterior CC (cACC) and posterior CC (PCC). We also investigated associations between gray matter volume or thickness and clinical symptoms, such as pain duration, Barrow Neurologic Institute (BNI) scores, offender vessel, and medications, in patients with TN. The cACC and PCC exhibited gray matter atrophy and reduced thickness between the TN and control groups. However, the rACC did not. Cortical volumes were negatively correlated with pain duration in transverse and inferior temporal areas, and thickness was also negatively correlated with pain duration in superior frontal and parietal areas. The cACC and PCC gray matter atrophy occurred in the patients with TN, and pain duration was associated with frontal, parietal, and temporal cortical regions. These results suggest that the cACC, PCC but not the rACC are associated with central pain mechanisms in TN. Copyright © 2018 Elsevier Inc. All rights reserved.

What’s special about task in dystonia? A voxel-based morphometry and diffusion weighted imaging study

PubMed Central

Ramdhani, Ritesh A.; Kumar, Veena; Velickovic, Miodrag; Frucht, Steven J.; Tagliati, Michele; Simonyan, Kristina

2014-01-01

Background Numerous brain imaging studies have demonstrated structural changes in the basal ganglia, thalamus, sensorimotor cortex and cerebellum across different forms of primary dystonia. However, our understanding of brain abnormalities contributing to the clinically well-described phenomenon of task-specificity in dystonia remained limited. Methods We used high-resolution MRI with voxel-based morphometry and diffusion tensor imaging with tract-based spatial statistics of fractional anisotropy to examine gray and white matter organization in two task-specific dystonia forms, writer’s cramp and laryngeal dystonia, and two non-task-specific dystonia forms, cervical dystonia and blepharospasm. Results A direct comparison between the both dystonia forms revealed that characteristic gray matter volumetric changes in task-specific dystonia involve the brain regions responsible for sensorimotor control during writing and speaking, such as primary somatosensory cortex, middle frontal gyrus, superior/inferior temporal gyrus, middle/posterior cingulate cortex, occipital cortex as well as the striatum and cerebellum (lobules VI-VIIa). These gray matter changes were accompanied by white matter abnormalities in the premotor cortex, middle/inferior frontal gyrus, genu of the corpus callosum, anterior limb/genu of the internal capsule, and putamen. Conversely, gray matter volumetric changes in non-task-specific group were limited to the left cerebellum (lobule VIIa) only, while white matter alterations were found to underlie the primary sensorimotor cortex, inferior parietal lobule and middle cingulate gyrus. Conclusion Distinct microstructural patterns in task-specific and non-task-specific dystonias may represent neuroimaging markers and provide evidence that these two dystonia subclasses likely follow divergent pathophysiological mechanisms precipitated by different triggers. PMID:24925463

Study of the Gray Scale, Polychromatic, Distortion Invariant Neural Networks Using the Ipa Model.

NASA Astrophysics Data System (ADS)

Uang, Chii-Maw

Research in the optical neural network field is primarily motivated by the fact that humans recognize objects better than the conventional digital computers and the massively parallel inherent nature of optics. This research represents a continuous effort during the past several years in the exploitation of using neurocomputing for pattern recognition. Based on the interpattern association (IPA) model and Hamming net model, many new systems and applications are introduced. A gray level discrete associative memory that is based on object decomposition/composition is proposed for recognizing gray-level patterns. This technique extends the processing ability from the binary mode to gray-level mode, and thus the information capacity is increased. Two polychromatic optical neural networks using color liquid crystal television (LCTV) panels for color pattern recognition are introduced. By introducing a color encoding technique in conjunction with the interpattern associative algorithm, a color associative memory was realized. Based on the color decomposition and composition technique, a color exemplar-based Hamming net was built for color image classification. A shift-invariant neural network is presented through use of the translation invariant property of the modulus of the Fourier transformation and the hetero-associative interpattern association (IPA) memory. To extract the main features, a quadrantal sampling method is used to sampled data and then replace the training patterns. Using the concept of hetero-associative memory to recall the distorted object. A shift and rotation invariant neural network using an interpattern hetero-association (IHA) model is presented. To preserve the shift and rotation invariant properties, a set of binarized-encoded circular harmonic expansion (CHE) functions at the Fourier domain is used as the training set. We use the shift and symmetric properties of the modulus of the Fourier spectrum to avoid the problem of centering the CHE functions. Almost all neural networks have the positive and negative weights, which increases the difficulty of optical implementation. A method to construct a unipolar IPA IWM is discussed. By searching the redundant interconnection links, an effective way that removes all negative links is discussed.

Haze in northeastern China

NASA Image and Video Library

2013-11-01

Chinese authorities shut down much of Harbin – a city of more than 10 million people – as unusually high levels of pollution shrouded the city and the surrounding region in mid-October, 2013. Measurements taken on October 20, 2013 scored the air quality index in the city at 500, the highest possible reading. Levels above 300 are considered hazardous to human health. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite acquired this true-color image of northeastern China on October 21. The brightest areas are fog, which is tinged with gray or yellow due to the air pollution. Other cloud-free areas have a pall of gray and brown smog that blots out the city and surrounding towns. Harbin lies under the Y-shaped patch of fog and smog in the south-central section of the image, completely obscured from view. Some neighborhoods experienced concentrations of fine particulate matter (PM 2.5) as high as 1,000 micrograms per cubic meter. For comparison the U.S. Environmental Protection Agency’s air quality standards state that PM 2.5 should remain below 35 micrograms per cubic meter. It is extremely rare for particulate levels to reach such high levels in the absence of a dust storm or forest fire. Chinese authorities grounded airplanes, shuttered thousands of schools and closed major roads in response to the surge in pollution. A few days after pollution levels started to rise, Harbin hospitals reported a 30 percent increase in admissions related to respiratory problems, and several Harbin pharmacies were sold out of pollution facemasks, according to media reports. Cold weather and lack of wind helped fuel the pollution outbreak, but human factors also played an important role. Wheat and corn farmers in the region light fires in the fall to burn off debris following the harvest. Also, city officials turned on Harbin’s city-wide, coal-powered heating system just prior to the pollution outbreak, according to China’s state-run Xinhua News Agency. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Regional Mosaic of Chaos and Gray Band on Europa

NASA Technical Reports Server (NTRS)

1997-01-01

This mosaic of part of Jupiter's moon, Europa, shows a region that is characterized by mottled (dark and splotchy) terrain. The images in this mosaic were obtained by Solid State Imaging (CCD) system on NASA's Galileo spacecraft during its eleventh orbit around Jupiter. North is to the top of the image, and the sun illuminates the scene from the right. Prior to obtaining these pictures, the age and origin of mottled terrain were not known. As seen here, the mottled appearance results from areas of the bright, icy crust that have been broken apart (known as 'chaos' terrain), exposing a darker underlying material. This terrain is typified by the area in the upper right-hand part of the image. The mottled terrain represents some of the most recent geologic activity on Europa. Also shown in this image is a smooth, gray band (lower part of image) representing a zone where the Europan crust has been fractured, separated, and filled in with material derived from the interior. The chaos terrain and the gray band show that this satellite has been subjected to intense geological deformation.

The mosaic, centered at 2.9 degrees south latitude and 234.1 degrees west longitude, covers an area of 365 kilometers by 335 kilometers (225 miles by 210 miles). The smallest distinguishable features in the image are about 460 meters (1500 feet) across. These images were obtained on November 6, 1997, when the Galileo spacecraft was approximately 21,700 kilometers (13,237 miles) from Europa.

The Jet Propulsion Laboratory, Pasadena, CA manages the mission for NASA's Office of Space Science, Washington, DC. JPL is a division of California Institute of Technology.

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo home page at URL http://galileo.jpl.nasa.gov. Background information and educational context can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.

PubMed

Milenković, Jana; Dalmış, Mehmet Ufuk; Žgajnar, Janez; Platel, Bram

2017-09-01

New ultrafast view-sharing sequences have enabled breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to be performed at high spatial and temporal resolution. The aim of this study is to evaluate the diagnostic potential of textural features that quantify the spatiotemporal changes of the contrast-agent uptake in computer-aided diagnosis of malignant and benign breast lesions imaged with high spatial and temporal resolution DCE-MRI. The proposed approach is based on the textural analysis quantifying the spatial variation of six dynamic features of the early-phase contrast-agent uptake of a lesion's largest cross-sectional area. The textural analysis is performed by means of the second-order gray-level co-occurrence matrix, gray-level run-length matrix and gray-level difference matrix. This yields 35 textural features to quantify the spatial variation of each of the six dynamic features, providing a feature set of 210 features in total. The proposed feature set is evaluated based on receiver operating characteristic (ROC) curve analysis in a cross-validation scheme for random forests (RF) and two support vector machine classifiers, with linear and radial basis function (RBF) kernel. Evaluation is done on a dataset with 154 breast lesions (83 malignant and 71 benign) and compared to a previous approach based on 3D morphological features and the average and standard deviation of the same dynamic features over the entire lesion volume as well as their average for the smaller region of the strongest uptake rate. The area under the ROC curve (AUC) obtained by the proposed approach with the RF classifier was 0.8997, which was significantly higher (P = 0.0198) than the performance achieved by the previous approach (AUC = 0.8704) on the same dataset. Similarly, the proposed approach obtained a significantly higher result for both SVM classifiers with RBF (P = 0.0096) and linear kernel (P = 0.0417) obtaining AUC of 0.8876 and 0.8548, respectively, compared to AUC values of previous approach of 0.8562 and 0.8311, respectively. The proposed approach based on 2D textural features quantifying spatiotemporal changes of the contrast-agent uptake significantly outperforms the previous approach based on 3D morphology and dynamic analysis in differentiating the malignant and benign breast lesions, showing its potential to aid clinical decision making. © 2017 American Association of Physicists in Medicine.

Association between background parenchymal enhancement of breast MRI and BIRADS rating change in the subsequent screening

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-03-01

Although breast magnetic resonance imaging (MRI) has been used as a breast cancer screening modality for high-risk women, its cancer detection yield remains low (i.e., <= 3%). Thus, increasing breast MRI screening efficacy and cancer detection yield is an important clinical issue in breast cancer screening. In this study, we investigated association between the background parenchymal enhancement (BPE) of breast MRI and the change of diagnostic (BIRADS) status in the next subsequent breast MRI screening. A dataset with 65 breast MRI screening cases was retrospectively assembled. All cases were rated BIRADS-2 (benign findings). In the subsequent screening, 4 cases were malignant (BIRADS-6), 48 remained BIRADS-2 and 13 were downgraded to negative (BIRADS-1). A computer-aided detection scheme was applied to process images of the first set of breast MRI screening. Total of 33 features were computed including texture feature and global BPE features. Texture features were computed from either a gray-level co-occurrence matrix or a gray level run length matrix. Ten global BPE features were also initially computed from two breast regions and bilateral difference between the left and right breasts. Box-plot based analysis shows positive association between texture features and BIRADS rating levels in the second screening. Furthermore, a logistic regression model was built using optimal features selected by a CFS based feature selection method. Using a leave-one-case-out based cross-validation method, classification yielded an overall 75% accuracy in predicting the improvement (or downgrade) of diagnostic status (to BIRAD-1) in the subsequent breast MRI screening. This study demonstrated potential of developing a new quantitative imaging marker to predict diagnostic status change in the short-term, which may help eliminate a high fraction of unnecessary repeated breast MRI screenings and increase the cancer detection yield.

Automatic extraction of via in the CT image of PCB

NASA Astrophysics Data System (ADS)

Liu, Xifeng; Hu, Yuwei

2018-04-01

In modern industry, the nondestructive testing of printed circuit board (PCB) can prevent effectively the system failure and is becoming more and more important. In order to detect the via in the PCB base on the CT image automatically accurately and reliably, a novel algorithm for via extraction based on weighting stack combining the morphologic character of via is designed. Every slice data in the vertical direction of the PCB is superimposed to enhanced vias target. The OTSU algorithm is used to segment the slice image. OTSU algorithm of thresholding gray level images is efficient for separating an image into two classes where two types of fairly distinct classes exist in the image. Randomized Hough Transform was used to locate the region of via in the segmented binary image. Then the 3D reconstruction of via based on sequence slice images was done by volume rendering. The accuracy of via positioning and detecting from a CT images of PCB was demonstrated by proposed algorithm. It was found that the method is good in veracity and stability for detecting of via in three dimensional.

Embedding intensity image into a binary hologram with strong noise resistant capability

NASA Astrophysics Data System (ADS)

Zhuang, Zhaoyong; Jiao, Shuming; Zou, Wenbin; Li, Xia

2017-11-01

A digital hologram can be employed as a host image for image watermarking applications to protect information security. Past research demonstrates that a gray level intensity image can be embedded into a binary Fresnel hologram by error diffusion method or bit truncation coding method. However, the fidelity of the retrieved watermark image from binary hologram is generally not satisfactory, especially when the binary hologram is contaminated with noise. To address this problem, we propose a JPEG-BCH encoding method in this paper. First, we employ the JPEG standard to compress the intensity image into a binary bit stream. Next, we encode the binary bit stream with BCH code to obtain error correction capability. Finally, the JPEG-BCH code is embedded into the binary hologram. By this way, the intensity image can be retrieved with high fidelity by a BCH-JPEG decoder even if the binary hologram suffers from serious noise contamination. Numerical simulation results show that the image quality of retrieved intensity image with our proposed method is superior to the state-of-the-art work reported.

SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom

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

Xie, Y; Wang, J; Wang, C

Purpose: To investigate the sensitivity of classic texture features to variations of MRI acquisition parameters. Methods: This study was performed on American College of Radiology (ACR) MRI Accreditation Program Phantom. MR imaging was acquired on a GE 750 3T scanner with XRM explain gradient, employing a T1-weighted images (TR/TE=500/20ms) with the following parameters as the reference standard: number of signal average (NEX) = 1, matrix size = 256×256, flip angle = 90°, slice thickness = 5mm. The effect of the acquisition parameters on texture features with and without non-uniformity correction were investigated respectively, while all the other parameters were keptmore » as reference standard. Protocol parameters were set as follows: (a). NEX = 0.5, 2 and 4; (b).Phase encoding steps = 128, 160 and 192; (c). Matrix size = 128×128, 192×192 and 512×512. 32 classic texture features were generated using the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from each image data set. Normalized range ((maximum-minimum)/mean) was calculated to determine variation among the scans with different protocol parameters. Results: For different NEX, 31 out of 32 texture features’ range are within 10%. For different phase encoding steps, 31 out of 32 texture features’ range are within 10%. For different acquisition matrix size without non-uniformity correction, 14 out of 32 texture features’ range are within 10%; for different acquisition matrix size with non-uniformity correction, 16 out of 32 texture features’ range are within 10%. Conclusion: Initial results indicated that those texture features that range within 10% are less sensitive to variations in T1-weighted MRI acquisition parameters. This might suggest that certain texture features might be more reliable to be used as potential biomarkers in MR quantitative image analysis.« less

NASA Spacecraft Images Wildfire Near Yosemite National Park

NASA Image and Video Library

2013-06-21

This image, acquired by NASA Terra spacecraft, is of the Carstens, Calif. wildfire which continues to burn in the foothills west of Yosemite National Park. Vegetation is displayed in green and burned and bare areas are dark to light gray.

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.

DART: a practical reconstruction algorithm for discrete tomography.

PubMed

Batenburg, Kees Joost; Sijbers, Jan

2011-09-01

In this paper, we present an iterative reconstruction algorithm for discrete tomography, called discrete algebraic reconstruction technique (DART). DART can be applied if the scanned object is known to consist of only a few different compositions, each corresponding to a constant gray value in the reconstruction. Prior knowledge of the gray values for each of the compositions is exploited to steer the current reconstruction towards a reconstruction that contains only these gray values. Based on experiments with both simulated CT data and experimental μCT data, it is shown that DART is capable of computing more accurate reconstructions from a small number of projection images, or from a small angular range, than alternative methods. It is also shown that DART can deal effectively with noisy projection data and that the algorithm is robust with respect to errors in the estimation of the gray values.

One Month of Oral Morphine Decreases Gray Matter Volume in the Right Amygdala of Individuals with Low Back Pain: Confirmation of Previously Reported Magnetic Resonance Imaging Results.

PubMed

Lin, Joanne C; Chu, Larry F; Stringer, Elizabeth Ann; Baker, Katharine S; Sayyid, Zahra N; Sun, John; Campbell, Kelsey A; Younger, Jarred W

2016-08-01

Prolonged exposure to opioids is known to produce neuroplastic changes in animals; however, few studies have investigated the effects of short-term prescription opioid use in humans. A previous study from our laboratory demonstrated a dosage-correlated volumetric decrease in the right amygdala of participants administered oral morphine daily for 1 month. The purpose of this current study was to replicate and extend the initial findings. Twenty-one participants with chronic low back pain were enrolled in this double-blind, placebo-controlled study. Participants were randomized to receive daily morphine (n = 11) or a matched placebo (n = 10) for 1 month. High-resolution anatomical images were acquired immediately before and after the treatment administration period. Morphological gray matter changes were investigated using tensor-based morphometry, and significant regions were subsequently tested for correlation with morphine dosage. Decreased gray matter volume was observed in several reward- and pain-related regions in the morphine group, including the bilateral amygdala, left inferior orbitofrontal cortex, and bilateral pre-supplementary motor areas. Morphine administration was also associated with significant gray matter increases in cingulate regions, including the mid cingulate, dorsal anterior cingulate, and ventral posterior cingulate. Many of the volumetric increases and decreases overlapped spatially with the previously reported changes. Individuals taking placebo for 1 month showed neither gray matter increases nor decreases. The results corroborate previous reports that rapid alterations occur in reward-related networks following short-term prescription opioid use. © 2015 American Academy of Pain Medicine.

Linear and curvilinear correlations of brain gray matter volume and density with age using voxel-based morphometry with the Akaike information criterion in 291 healthy children.

PubMed

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

2013-08-01

We examined linear and curvilinear correlations of gray matter volume and density in cortical and subcortical gray matter with age using magnetic resonance images (MRI) in a large number of healthy children. We applied voxel-based morphometry (VBM) and region-of-interest (ROI) analyses with the Akaike information criterion (AIC), which was used to determine the best-fit model by selecting which predictor terms should be included. We collected data on brain structural MRI in 291 healthy children aged 5-18 years. Structural MRI data were segmented and normalized using a custom template by applying the diffeomorphic anatomical registration using exponentiated lie algebra (DARTEL) procedure. Next, we analyzed the correlations of gray matter volume and density with age in VBM with AIC by estimating linear, quadratic, and cubic polynomial functions. Several regions such as the prefrontal cortex, the precentral gyrus, and cerebellum showed significant linear or curvilinear correlations between gray matter volume and age on an increasing trajectory, and between gray matter density and age on a decreasing trajectory in VBM and ROI analyses with AIC. Because the trajectory of gray matter volume and density with age suggests the progress of brain maturation, our results may contribute to clarifying brain maturation in healthy children from the viewpoint of brain structure. Copyright © 2012 Wiley Periodicals, Inc.

A summary of image segmentation techniques

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly

1993-01-01

Machine vision systems are often considered to be composed of two subsystems: low-level vision and high-level vision. Low level vision consists primarily of image processing operations performed on the input image to produce another image with more favorable characteristics. These operations may yield images with reduced noise or cause certain features of the image to be emphasized (such as edges). High-level vision includes object recognition and, at the highest level, scene interpretation. The bridge between these two subsystems is the segmentation system. Through segmentation, the enhanced input image is mapped into a description involving regions with common features which can be used by the higher level vision tasks. There is no theory on image segmentation. Instead, image segmentation techniques are basically ad hoc and differ mostly in the way they emphasize one or more of the desired properties of an ideal segmenter and in the way they balance and compromise one desired property against another. These techniques can be categorized in a number of different groups including local vs. global, parallel vs. sequential, contextual vs. noncontextual, interactive vs. automatic. In this paper, we categorize the schemes into three main groups: pixel-based, edge-based, and region-based. Pixel-based segmentation schemes classify pixels based solely on their gray levels. Edge-based schemes first detect local discontinuities (edges) and then use that information to separate the image into regions. Finally, region-based schemes start with a seed pixel (or group of pixels) and then grow or split the seed until the original image is composed of only homogeneous regions. Because there are a number of survey papers available, we will not discuss all segmentation schemes. Rather than a survey, we take the approach of a detailed overview. We focus only on the more common approaches in order to give the reader a flavor for the variety of techniques available yet present enough details to facilitate implementation and experimentation.

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.

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.

Infrared Spectroscopic Imaging for Prostate Pathology Practice

DTIC Science & Technology

2008-03-01

small data sets ( teens of attributes and few thousands of records) the matching process takes more than 85% of the overall execution time marginalizing...governs the execution time. For small data sets ( teens of attributes and few thousands of records) the matching process takes more than 85% of the...namely gray matter and white matter. These names derive simply from their appearance to the naked eye. Gray matter consists of cell bodies of nerve

Geographical Influences of an Emerging Network of Gang Rivalries

DTIC Science & Technology

2011-03-17

Hollenbeck in the N × M environment grid. The semi-permeable boundaries encoded in the model are displayed in the center image. The shades of gray of...intensity. Light shades of gray correspond to high density values near one and dark shades correspond to low densities near zero. The boundary crossing...Threshold Graphs ( GTG ) For comparison to the networks produced by our simulations, we constructed an instance of a Geograph- ical Threshold Graph ( GTG

Objective Quality Assessment for Color-to-Gray Image Conversion.

PubMed

Ma, Kede; Zhao, Tiesong; Zeng, Kai; Wang, Zhou

2015-12-01

Color-to-gray (C2G) image conversion is the process of transforming a color image into a grayscale one. Despite its wide usage in real-world applications, little work has been dedicated to compare the performance of C2G conversion algorithms. Subjective evaluation is reliable but is also inconvenient and time consuming. Here, we make one of the first attempts to develop an objective quality model that automatically predicts the perceived quality of C2G converted images. Inspired by the philosophy of the structural similarity index, we propose a C2G structural similarity (C2G-SSIM) index, which evaluates the luminance, contrast, and structure similarities between the reference color image and the C2G converted image. The three components are then combined depending on image type to yield an overall quality measure. Experimental results show that the proposed C2G-SSIM index has close agreement with subjective rankings and significantly outperforms existing objective quality metrics for C2G conversion. To explore the potentials of C2G-SSIM, we further demonstrate its use in two applications: 1) automatic parameter tuning for C2G conversion algorithms and 2) adaptive fusion of C2G converted images.