Airway extraction from 3D chest CT volumes based on iterative extension of VOI enhanced by cavity enhancement filter

NASA Astrophysics Data System (ADS)

Meng, Qier; Kitasaka, Takayuki; Oda, Masahiro; Mori, Kensaku

2017-03-01

Airway segmentation is an important step in analyzing chest CT volumes for computerized lung cancer detection, emphysema diagnosis, asthma diagnosis, and pre- and intra-operative bronchoscope navigation. However, obtaining an integrated 3-D airway tree structure from a CT volume is a quite challenging task. This paper presents a novel airway segmentation method based on intensity structure analysis and bronchi shape structure analysis in volume of interest (VOI). This method segments the bronchial regions by applying the cavity enhancement filter (CEF) to trace the bronchial tree structure from the trachea. It uses the CEF in each VOI to segment each branch and to predict the positions of VOIs which envelope the bronchial regions in next level. At the same time, a leakage detection is performed to avoid the leakage by analysing the pixel information and the shape information of airway candidate regions extracted in the VOI. Bronchial regions are finally obtained by unifying the extracted airway regions. The experiments results showed that the proposed method can extract most of the bronchial region in each VOI and led good results of the airway segmentation.

Evaluating the Impact of DNA Extraction Method on the Representation of Human Oral Bacterial and Fungal Communities

PubMed Central

Biswas, Kristi; Taylor, Michael W.; Gear, Kim

2017-01-01

The application of high-throughput, next-generation sequencing technologies has greatly improved our understanding of the human oral microbiome. While deciphering this diverse microbial community using such approaches is more accurate than traditional culture-based methods, experimental bias introduced during critical steps such as DNA extraction may compromise the results obtained. Here, we systematically evaluate four commonly used microbial DNA extraction methods (MoBio PowerSoil® DNA Isolation Kit, QIAamp® DNA Mini Kit, Zymo Bacterial/Fungal DNA Mini PrepTM, phenol:chloroform-based DNA isolation) based on the following criteria: DNA quality and yield, and microbial community structure based on Illumina amplicon sequencing of the V3–V4 region of the 16S rRNA gene of bacteria and the internal transcribed spacer (ITS) 1 region of fungi. Our results indicate that DNA quality and yield varied significantly with DNA extraction method. Representation of bacterial genera in plaque and saliva samples did not significantly differ across DNA extraction methods and DNA extraction method showed no effect on the recovery of fungal genera from plaque. By contrast, fungal diversity from saliva was affected by DNA extraction method, suggesting that not all protocols are suitable to study the salivary mycobiome. PMID:28099455

SD-MSAEs: Promoter recognition in human genome based on deep feature extraction.

PubMed

Xu, Wenxuan; Zhang, Li; Lu, Yaping

2016-06-01

The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different regions of DNA sequences. In this paper, we choose context feature and use a set of methods of SD to select the most effective n-mers distinguishing promoter regions from other DNA regions in human genome. Extracted from the total possible combinations of n-mers, we can get four sparse distributions based on promoter and non-promoters training samples. The informative n-mers are selected by optimizing the differentiating extents of these distributions. Specially, we combine the advantage of statistical divergence and multiple sparse auto-encoders (MSAEs) in deep learning to extract deep feature for promoter recognition. And then we apply multiple SVMs and a decision model to construct a human promoter recognition method called SD-MSAEs. Framework is flexible that it can integrate new feature extraction or new classification models freely. Experimental results show that our method has high sensitivity and specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

ACCELERATED SOLVENT EXTRACTION COMBINED WITH ...

EPA Pesticide Factsheets

A research project was initiated to address a recurring problem of elevated detection limits above required risk-based concentrations for the determination of semivolatile organic compounds in high moisture content solid samples. This project was initiated, in cooperation with the EPA Region 1 Laboratory, under the Regional Methods Program administered through the ORD Office of Science Policy. The aim of the project was to develop an approach for the rapid removal of water in high moisture content solids (e.g., wetland sediments) in preparation for analysis via Method 8270. Alternative methods for water removal have been investigated to enhance compound solid concentrations and improve extraction efficiency, with the use of pressure filtration providing a high-throughput alternative for removal of the majority of free water in sediments and sludges. In order to eliminate problems with phase separation during extraction of solids using Accelerated Solvent Extraction, a variation of a water-isopropanol extraction method developed at the USGS National Water Quality Laboratory in Denver, CO is being employed. The concentrations of target compounds in water-isopropanol extraction fluids are subsequently analyzed using an automated Solid Phase Extraction (SPE)-GC/MS method developed in our laboratory. The coupled approaches for dewatering, extraction, and target compound identification-quantitation provide a useful alternative to enhance sample throughput for Me

Segmentation of liver region with tumorous tissues

NASA Astrophysics Data System (ADS)

Zhang, Xuejun; Lee, Gobert; Tajima, Tetsuji; Kitagawa, Teruhiko; Kanematsu, Masayuki; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Hoshi, Hiroaki; Nawano, Shigeru; Shinozaki, Kenji

2007-03-01

Segmentation of an abnormal liver region based on CT or MR images is a crucial step in surgical planning. However, precisely carrying out this step remains a challenge due to either connectivities of the liver to other organs or the shape, internal texture, and homogeneity of liver that maybe extensively affected in case of liver diseases. Here, we propose a non-density based method for extracting the liver region containing tumor tissues by edge detection processing. False extracted regions are eliminated by a shape analysis method and thresholding processing. If the multi-phased images are available then the overall outcome of segmentation can be improved by subtracting two phase images, and the connectivities can be further eliminated by referring to the intensity on another phase image. Within an edge liver map, tumor candidates are identified by their different gray values relative to the liver. After elimination of the small and nonspherical over-extracted regions, the final liver region integrates the tumor region with the liver tissue. In our experiment, 40 cases of MDCT images were used and the result showed that our fully automatic method for the segmentation of liver region is effective and robust despite the presence of hepatic tumors within the liver.

Real-time text extraction based on the page layout analysis system

NASA Astrophysics Data System (ADS)

Soua, M.; Benchekroun, A.; Kachouri, R.; Akil, M.

2017-05-01

Several approaches were proposed in order to extract text from scanned documents. However, text extraction in heterogeneous documents stills a real challenge. Indeed, text extraction in this context is a difficult task because of the variation of the text due to the differences of sizes, styles and orientations, as well as to the complexity of the document region background. Recently, we have proposed the improved hybrid binarization based on Kmeans method (I-HBK)5 to extract suitably the text from heterogeneous documents. In this method, the Page Layout Analysis (PLA), part of the Tesseract OCR engine, is used to identify text and image regions. Afterwards our hybrid binarization is applied separately on each kind of regions. In one side, gamma correction is employed before to process image regions. In the other side, binarization is performed directly on text regions. Then, a foreground and background color study is performed to correct inverted region colors. Finally, characters are located from the binarized regions based on the PLA algorithm. In this work, we extend the integration of the PLA algorithm within the I-HBK method. In addition, to speed up the separation of text and image step, we employ an efficient GPU acceleration. Through the performed experiments, we demonstrate the high F-measure accuracy of the PLA algorithm reaching 95% on the LRDE dataset. In addition, we illustrate the sequential and the parallel compared PLA versions. The obtained results give a speedup of 3.7x when comparing the parallel PLA implementation on GPU GTX 660 to the CPU version.

Automatic extraction of planetary image features

NASA Technical Reports Server (NTRS)

LeMoigne-Stewart, Jacqueline J. (Inventor); Troglio, Giulia (Inventor); Benediktsson, Jon A. (Inventor); Serpico, Sebastiano B. (Inventor); Moser, Gabriele (Inventor)

2013-01-01

A method for the extraction of Lunar data and/or planetary features is provided. The feature extraction method can include one or more image processing techniques, including, but not limited to, a watershed segmentation and/or the generalized Hough Transform. According to some embodiments, the feature extraction method can include extracting features, such as, small rocks. According to some embodiments, small rocks can be extracted by applying a watershed segmentation algorithm to the Canny gradient. According to some embodiments, applying a watershed segmentation algorithm to the Canny gradient can allow regions that appear as close contours in the gradient to be segmented.

A new license plate extraction framework based on fast mean shift

NASA Astrophysics Data System (ADS)

Pan, Luning; Li, Shuguang

2010-08-01

License plate extraction is considered to be the most crucial step of Automatic license plate recognition (ALPR) system. In this paper, a region-based license plate hybrid detection method is proposed to solve practical problems under complex background in which existing large quantity of disturbing information. In this method, coarse license plate location is carried out firstly to get the head part of a vehicle. Then a new Fast Mean Shift method based on random sampling of Kernel Density Estimate (KDE) is adopted to segment the color vehicle images, in order to get candidate license plate regions. The remarkable speed-up it brings makes Mean Shift segmentation more suitable for this application. Feature extraction and classification is used to accurately separate license plate from other candidate regions. At last, tilted license plate regulation is used for future recognition steps.

An automatic system to detect and extract texts in medical images for de-identification

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

2010-03-01

Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

Reference-based source separation method for identification of brain regions involved in a reference state from intracerebral EEG

PubMed Central

Samadi, Samareh; Amini, Ladan; Cosandier-Rimélé, Delphine; Soltanian-Zadeh, Hamid; Jutten, Christian

2013-01-01

In this paper, we present a fast method to extract the sources related to interictal epileptiform state. The method is based on general eigenvalue decomposition using two correlation matrices during: 1) periods including interictal epileptiform discharges (IED) as a reference activation model and 2) periods excluding IEDs or abnormal physiological signals as background activity. After extracting the most similar sources to the reference or IED state, IED regions are estimated by using multiobjective optimization. The method is evaluated using both realistic simulated data and actual intracerebral electroencephalography recordings of patients suffering from focal epilepsy. These patients are seizure-free after the resective surgery. Quantitative comparisons of the proposed IED regions with the visually inspected ictal onset zones by the epileptologist and another method of identification of IED regions reveal good performance. PMID:23428609

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

An effective hand vein feature extraction method.

PubMed

Li, Haigang; Zhang, Qian; Li, Chengdong

2015-01-01

As a new authentication method developed years ago, vein recognition technology features the unique advantage of bioassay. This paper studies the specific procedure for the extraction of hand back vein characteristics. There are different positions used in the collecting process, so that a suitable intravenous regional orientation method is put forward, allowing the positioning area to be the same for all hand positions. In addition, to eliminate the pseudo vein area, the valley regional shape extraction operator can be improved and combined with multiple segmentation algorithms. The images should be segmented step by step, making the vein texture to appear clear and accurate. Lastly, the segmented images should be filtered, eroded, and refined. This process helps to filter the most of the pseudo vein information. Finally, a clear vein skeleton diagram is obtained, demonstrating the effectiveness of the algorithm. This paper presents a hand back vein region location method. This makes it possible to rotate and correct the image by working out the inclination degree of contour at the side of hand back.

Peripleural lung disease detection based on multi-slice CT images

NASA Astrophysics Data System (ADS)

Matsuhiro, M.; Suzuki, H.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2015-03-01

With the development of multi-slice CT technology, obtaining accurate 3D images of lung field in a short time become possible. To support that, a lot of image processing methods need to be developed. Detection peripleural lung disease is difficult due to its existence out of lung region, because lung extraction is often performed based on threshold processing. The proposed method uses thoracic inner region extracted by inner cavity of bone as well as air region, covers peripleural lung diseased cases such as lung nodule, calcification, pleural effusion and pleural plaque. We applied this method to 50 cases including 39 peripleural lung diseased cases. This method was able to detect 39 peripleural lung disease with 2.9 false positive per case.

A flower image retrieval method based on ROI feature.

PubMed

Hong, An-Xiang; Chen, Gang; Li, Jun-Li; Chi, Zhe-Ru; Zhang, Dan

2004-07-01

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

Influence of crisp values on the object-based data extraction procedure from LiDAR data

NASA Astrophysics Data System (ADS)

Tomljenovic, Ivan; Rousell, Adam

2014-05-01

Nowadays a plethora of approaches attempt to automate the process of object extraction from LiDAR data. However, the majority of these methods require the fusion of the LiDAR dataset with other information such as photogrammetric imagery. The approach that has been used as the basis for this paper is a novel method which makes use of human knowledge and the CNL modelling language to automatically extract buildings solely from LiDAR point cloud data in a transferable method. A number of rules are implemented to generate an artificial intelligence algorithm which is used for the object extraction. Although the single dataset method has been found to successfully extract building footprints from the point cloud dataset, at this initial stage it has one restriction that may limit its effectiveness - a number of the rules that are used are based on crisp boundary values. If, for example, the slope of the ground surface is used as a rule for determining objects then the slope value of a pixel would be assessed to determine if it is suitable for a building structure. This check would be performed by identifying whether the slope value is less than or greater than a threshold value. However, in reality such a crisp classification process is likely not to be a true reflection of real world scenarios. For example, using the crisp methods a difference of 1° in slope could result in one region in a dataset being deemed suitable and its neighboring region being seen as not suitable. It is likely however that there is in reality little difference in the actual suitability of these two neighboring regions. A more suitable classification process may be the use of fuzzy set theory whereby each region is seen as having degree of membership to a number of sets (or classifications). In the above example, the two regions would likely be seen as having very similar membership values to the different sets, although this is obviously dependent on factors such as the extent of each region. The purpose of this study is to identify to what extent the use of explicit boundary values has on the overall building footprint dataset extracted. By performing the analysis multiple times using differing threshold values for rules, it is possible to compare the resultant datasets and thus identify the impact of using such classification procedures. If a significant difference is found between the resultant datasets, this would highlight that the use of such crisp methods in the extraction processes may not be optimal and that a future enhancement to the method would be to consider the use of fuzzy classification methods.

Extraction of endoscopic images for biomedical figure classification

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; You, Daekeun; Chachra, Suchet; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.

2015-03-01

Modality filtering is an important feature in biomedical image searching systems and may significantly improve the retrieval performance of the system. This paper presents a new method for extracting endoscopic image figures from photograph images in biomedical literature, which are found to have highly diverse content and large variability in appearance. Our proposed method consists of three main stages: tissue image extraction, endoscopic image candidate extraction, and ophthalmic image filtering. For tissue image extraction we use image patch level clustering and MRF relabeling to detect images containing skin/tissue regions. Next, we find candidate endoscopic images by exploiting the round shape characteristics that commonly appear in these images. However, this step needs to compensate for images where endoscopic regions are not entirely round. In the third step we filter out the ophthalmic images which have shape characteristics very similar to the endoscopic images. We do this by using text information, specifically, anatomy terms, extracted from the figure caption. We tested and evaluated our method on a dataset of 115,370 photograph figures, and achieved promising precision and recall rates of 87% and 84%, respectively.

Sliding Window-Based Region of Interest Extraction for Finger Vein Images

PubMed Central

Yang, Lu; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2013-01-01

Region of Interest (ROI) extraction is a crucial step in an automatic finger vein recognition system. The aim of ROI extraction is to decide which part of the image is suitable for finger vein feature extraction. This paper proposes a finger vein ROI extraction method which is robust to finger displacement and rotation. First, we determine the middle line of the finger, which will be used to correct the image skew. Then, a sliding window is used to detect the phalangeal joints and further to ascertain the height of ROI. Last, for the corrective image with certain height, we will obtain the ROI by using the internal tangents of finger edges as the left and right boundary. The experimental results show that the proposed method can extract ROI more accurately and effectively compared with other methods, and thus improve the performance of finger vein identification system. Besides, to acquire the high quality finger vein image during the capture process, we propose eight criteria for finger vein capture from different aspects and these criteria should be helpful to some extent for finger vein capture. PMID:23507824

Simple and efficient method for region of interest value extraction from picture archiving and communication system viewer with optical character recognition software and macro program.

PubMed

Lee, Young Han; Park, Eun Hae; Suh, Jin-Suck

2015-01-01

The objectives are: 1) to introduce a simple and efficient method for extracting region of interest (ROI) values from a Picture Archiving and Communication System (PACS) viewer using optical character recognition (OCR) software and a macro program, and 2) to evaluate the accuracy of this method with a PACS workstation. This module was designed to extract the ROI values on the images of the PACS, and created as a development tool by using open-source OCR software and an open-source macro program. The principal processes are as follows: (1) capture a region of the ROI values as a graphic file for OCR, (2) recognize the text from the captured image by OCR software, (3) perform error-correction, (4) extract the values including area, average, standard deviation, max, and min values from the text, (5) reformat the values into temporary strings with tabs, and (6) paste the temporary strings into the spreadsheet. This principal process was repeated for the number of ROIs. The accuracy of this module was evaluated on 1040 recognitions from 280 randomly selected ROIs of the magnetic resonance images. The input times of ROIs were compared between conventional manual method and this extraction module-assisted input method. The module for extracting ROI values operated successfully using the OCR and macro programs. The values of the area, average, standard deviation, maximum, and minimum could be recognized and error-corrected with AutoHotkey-coded module. The average input times using the conventional method and the proposed module-assisted method were 34.97 seconds and 7.87 seconds, respectively. A simple and efficient method for ROI value extraction was developed with open-source OCR and a macro program. Accurate inputs of various numbers from ROIs can be extracted with this module. The proposed module could be applied to the next generation of PACS or existing PACS that have not yet been upgraded. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Segmentation of brain volume based on 3D region growing by integrating intensity and edge for image-guided surgery

NASA Astrophysics Data System (ADS)

Tsagaan, Baigalmaa; Abe, Keiichi; Goto, Masahiro; Yamamoto, Seiji; Terakawa, Susumu

2006-03-01

This paper presents a segmentation method of brain tissues from MR images, invented for our image-guided neurosurgery system under development. Our goal is to segment brain tissues for creating biomechanical model. The proposed segmentation method is based on 3-D region growing and outperforms conventional approaches by stepwise usage of intensity similarities between voxels in conjunction with edge information. Since the intensity and the edge information are complementary to each other in the region-based segmentation, we use them twice by performing a coarse-to-fine extraction. First, the edge information in an appropriate neighborhood of the voxel being considered is examined to constrain the region growing. The expanded region of the first extraction result is then used as the domain for the next processing. The intensity and the edge information of the current voxel only are utilized in the final extraction. Before segmentation, the intensity parameters of the brain tissues as well as partial volume effect are estimated by using expectation-maximization (EM) algorithm in order to provide an accurate data interpretation into the extraction. We tested the proposed method on T1-weighted MR images of brain and evaluated the segmentation effectiveness comparing the results with ground truths. Also, the generated meshes from the segmented brain volume by using mesh generating software are shown in this paper.

Text extraction method for historical Tibetan document images based on block projections

NASA Astrophysics Data System (ADS)

Duan, Li-juan; Zhang, Xi-qun; Ma, Long-long; Wu, Jian

2017-11-01

Text extraction is an important initial step in digitizing the historical documents. In this paper, we present a text extraction method for historical Tibetan document images based on block projections. The task of text extraction is considered as text area detection and location problem. The images are divided equally into blocks and the blocks are filtered by the information of the categories of connected components and corner point density. By analyzing the filtered blocks' projections, the approximate text areas can be located, and the text regions are extracted. Experiments on the dataset of historical Tibetan documents demonstrate the effectiveness of the proposed method.

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

NASA Astrophysics Data System (ADS)

Wu, T. Y.; Lin, S. F.

2013-10-01

Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Bubble structure evaluation method of sponge cake by using image morphology

NASA Astrophysics Data System (ADS)

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

2007-01-01

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

Acquiring 3-D information about thick objects from differential interference contrast images using texture extraction

NASA Astrophysics Data System (ADS)

Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

2010-07-01

The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.

Pseudophasic extraction method for the separation of ultra-fine minerals

DOEpatents

Chaiko, David J.

2002-01-01

An improved aqueous-based extraction method for the separation and recovery of ultra-fine mineral particles. The process operates within the pseudophase region of the conventional aqueous biphasic extraction system where a low-molecular-weight, water soluble polymer alone is used in combination with a salt and operates within the pseudo-biphase regime of the conventional aqueous biphasic extraction system. A combination of low molecular weight, mutually immiscible polymers are used with or without a salt. This method is especially suited for the purification of clays that are useful as rheological control agents and for the preparation of nanocomposites.

Extraction of liver volumetry based on blood vessel from the portal phase CT dataset

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Utsunomiya, Tohru; Shimada, Mitsuo

2012-02-01

At liver surgery planning stage, the liver volumetry would be essential for surgeons. Main problem at liver extraction is the wide variability of livers in shapes and sizes. Since, hepatic blood vessels structure varies from a person to another and covers liver region, the present method uses that information for extraction of liver in two stages. The first stage is to extract abdominal blood vessels in the form of hepatic and nonhepatic blood vessels. At the second stage, extracted vessels are used to control extraction of liver region automatically. Contrast enhanced CT datasets at only the portal phase of 50 cases is used. Those data include 30 abnormal livers. A reference for all cases is done through a comparison of two experts labeling results and correction of their inter-reader variability. Results of the proposed method agree with the reference at an average rate of 97.8%. Through application of different metrics mentioned at MICCAI workshop for liver segmentation, it is found that: volume overlap error is 4.4%, volume difference is 0.3%, average symmetric distance is 0.7 mm, Root mean square symmetric distance is 0.8 mm, and maximum distance is 15.8 mm. These results represent the average of overall data and show an improved accuracy compared to current liver segmentation methods. It seems to be a promising method for extraction of liver volumetry of various shapes and sizes.

Region of interest extraction based on multiscale visual saliency analysis for remote sensing images

NASA Astrophysics Data System (ADS)

Zhang, Yinggang; Zhang, Libao; Yu, Xianchuan

2015-01-01

Region of interest (ROI) extraction is an important component of remote sensing image processing. However, traditional ROI extraction methods are usually prior knowledge-based and depend on classification, segmentation, and a global searching solution, which are time-consuming and computationally complex. We propose a more efficient ROI extraction model for remote sensing images based on multiscale visual saliency analysis (MVS), implemented in the CIE L*a*b* color space, which is similar to visual perception of the human eye. We first extract the intensity, orientation, and color feature of the image using different methods: the visual attention mechanism is used to eliminate the intensity feature using a difference of Gaussian template; the integer wavelet transform is used to extract the orientation feature; and color information content analysis is used to obtain the color feature. Then, a new feature-competition method is proposed that addresses the different contributions of each feature map to calculate the weight of each feature image for combining them into the final saliency map. Qualitative and quantitative experimental results of the MVS model as compared with those of other models show that it is more effective and provides more accurate ROI extraction results with fewer holes inside the ROI.

Pelvic artery calcification detection on CT scans using convolutional neural networks

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Lu, Le; Yao, Jianhua; Bagheri, Mohammadhadi; Summers, Ronald M.

2017-03-01

Artery calcification is observed commonly in elderly patients, especially in patients with chronic kidney disease, and may affect coronary, carotid and peripheral arteries. Vascular calcification has been associated with many clinical outcomes. Manual identification of calcification in CT scans requires substantial expert interaction, which makes it time-consuming and infeasible for large-scale studies. Many works have been proposed for coronary artery calcification detection in cardiac CT scans. In these works, coronary artery extraction is commonly required for calcification detection. However, there are few works about abdominal or pelvic artery calcification detection. In this work, we present a method for automatic pelvic artery calcification detection on CT scan. This method uses the recent advanced faster region-based convolutional neural network (R-CNN) to directly identify artery calcification without a need for artery extraction since pelvic artery extraction itself is challenging. Our method first generates category-independent region proposals for each slice of the input CT scan using region proposal networks (RPN). Then, each region proposal is jointly classified and refined by softmax classifier and bounding box regressor. We applied the detection method to 500 images from 20 CT scans of patients for evaluation. The detection system achieved a 77.4% average precision and a 85% sensitivity at 1 false positive per image.

Change Detection in High-Resolution Remote Sensing Images Using Levene-Test and Fuzzy Evaluation

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Liu, H. J.

2018-04-01

High-resolution remote sensing images possess complex spatial structure and rich texture information, according to these, this paper presents a new method of change detection based on Levene-Test and Fuzzy Evaluation. It first got map-spots by segmenting two overlapping images which had been pretreated, extracted features such as spectrum and texture. Then, changed information of all map-spots which had been treated by the Levene-Test were counted to obtain the candidate changed regions, hue information (H component) was extracted through the IHS Transform and conducted change vector analysis combined with the texture information. Eventually, the threshold was confirmed by an iteration method, the subject degrees of candidate changed regions were calculated, and final change regions were determined. In this paper experimental results on multi-temporal ZY-3 high-resolution images of some area in Jiangsu Province show that: Through extracting map-spots of larger difference as the candidate changed regions, Levene-Test decreases the computing load, improves the precision of change detection, and shows better fault-tolerant capacity for those unchanged regions which are of relatively large differences. The combination of Hue-texture features and fuzzy evaluation method can effectively decrease omissions and deficiencies, improve the precision of change detection.

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

NASA Astrophysics Data System (ADS)

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

2005-12-01

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

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

PubMed Central

Qin, Lei; Snoussi, Hichem; Abdallah, Fahed

2014-01-01

We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences. PMID:24865883

Road extraction from aerial images using a region competition algorithm.

PubMed

Amo, Miriam; Martínez, Fernando; Torre, Margarita

2006-05-01

In this paper, we present a user-guided method based on the region competition algorithm to extract roads, and therefore we also provide some clues concerning the placement of the points required by the algorithm. The initial points are analyzed in order to find out whether it is necessary to add more initial points, and this process will be based on image information. Not only is the algorithm able to obtain the road centerline, but it also recovers the road sides. An initial simple model is deformed by using region growing techniques to obtain a rough road approximation. This model will be refined by region competition. The result of this approach is that it delivers the simplest output vector information, fully recovering the road details as they are on the image, without performing any kind of symbolization. Therefore, we tried to refine a general road model by using a reliable method to detect transitions between regions. This method is proposed in order to obtain information for feeding large-scale Geographic Information System.

Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

NASA Astrophysics Data System (ADS)

Y Yang, M.; Wang, J.; Zhang, Q.

2017-07-01

Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

High-performance Chinese multiclass traffic sign detection via coarse-to-fine cascade and parallel support vector machine detectors

NASA Astrophysics Data System (ADS)

Chang, Faliang; Liu, Chunsheng

2017-09-01

The high variability of sign colors and shapes in uncontrolled environments has made the detection of traffic signs a challenging problem in computer vision. We propose a traffic sign detection (TSD) method based on coarse-to-fine cascade and parallel support vector machine (SVM) detectors to detect Chinese warning and danger traffic signs. First, a region of interest (ROI) extraction method is proposed to extract ROIs using color contrast features in local regions. The ROI extraction can reduce scanning regions and save detection time. For multiclass TSD, we propose a structure that combines a coarse-to-fine cascaded tree with a parallel structure of histogram of oriented gradients (HOG) + SVM detectors. The cascaded tree is designed to detect different types of traffic signs in a coarse-to-fine process. The parallel HOG + SVM detectors are designed to do fine detection of different types of traffic signs. The experiments demonstrate the proposed TSD method can rapidly detect multiclass traffic signs with different colors and shapes in high accuracy.

Region-based automatic building and forest change detection on Cartosat-1 stereo imagery

NASA Astrophysics Data System (ADS)

Tian, J.; Reinartz, P.; d'Angelo, P.; Ehlers, M.

2013-05-01

In this paper a novel region-based method is proposed for change detection using space borne panchromatic Cartosat-1 stereo imagery. In the first step, Digital Surface Models (DSMs) from two dates are generated by semi-global matching. The geometric lateral resolution of the DSMs is 5 m × 5 m and the height accuracy is in the range of approximately 3 m (RMSE). In the second step, mean-shift segmentation is applied on the orthorectified images of two dates to obtain initial regions. A region intersection following a merging strategy is proposed to get minimum change regions and multi-level change vectors are extracted for these regions. Finally change detection is achieved by combining these features with weighted change vector analysis. The result evaluations demonstrate that the applied DSM generation method is well suited for Cartosat-1 imagery, and the extracted height values can largely improve the change detection accuracy, moreover it is shown that the proposed change detection method can be used robustly for both forest and industrial areas.

Dynamic Trajectory Extraction from Stereo Vision Using Fuzzy Clustering

NASA Astrophysics Data System (ADS)

Onishi, Masaki; Yoda, Ikushi

In recent years, many human tracking researches have been proposed in order to analyze human dynamic trajectory. These researches are general technology applicable to various fields, such as customer purchase analysis in a shopping environment and safety control in a (railroad) crossing. In this paper, we present a new approach for tracking human positions by stereo image. We use the framework of two-stepped clustering with k-means method and fuzzy clustering to detect human regions. In the initial clustering, k-means method makes middle clusters from objective features extracted by stereo vision at high speed. In the last clustering, c-means fuzzy method cluster middle clusters based on attributes into human regions. Our proposed method can be correctly clustered by expressing ambiguity using fuzzy clustering, even when many people are close to each other. The validity of our technique was evaluated with the experiment of trajectories extraction of doctors and nurses in an emergency room of a hospital.

Method to acquire regions of fruit, branch and leaf from image of red apple in orchard

NASA Astrophysics Data System (ADS)

Lv, Jidong; Xu, Liming

2017-07-01

This work proposed a method to acquire regions of fruit, branch and leaf from red apple image in orchard. To acquire fruit image, R-G image was extracted from the RGB image for corrosive working, hole filling, subregion removal, expansive working and opening operation in order. Finally, fruit image was acquired by threshold segmentation. To acquire leaf image, fruit image was subtracted from RGB image before extracting 2G-R-B image. Then, leaf image was acquired by subregion removal and threshold segmentation. To acquire branch image, dynamic threshold segmentation was conducted in the R-G image. Then, the segmented image was added to fruit image to acquire adding fruit image which was subtracted from RGB image with leaf image. Finally, branch image was acquired by opening operation, subregion removal and threshold segmentation after extracting the R-G image from the subtracting image. Compared with previous methods, more complete image of fruit, leaf and branch can be acquired from red apple image with this method.

Feasibility Research on Alternative Approaches for Sampling and Extraction Methods in the TO-4A Method for Pesticides in Ambient Air with Analysis by GC/MS and LC/MS/MS

EPA Science Inventory

This compilation of methods is the result of a Regional Methods project between the U.S. Environmental Protection Agency Region 4 and the EPA’s Office of Research and Development. The research leading to these methods was conducted in response to an observed need to update an EPA...

Age and gender estimation using Region-SIFT and multi-layered SVM

NASA Astrophysics Data System (ADS)

Kim, Hyunduk; Lee, Sang-Heon; Sohn, Myoung-Kyu; Hwang, Byunghun

2018-04-01

In this paper, we propose an age and gender estimation framework using the region-SIFT feature and multi-layered SVM classifier. The suggested framework entails three processes. The first step is landmark based face alignment. The second step is the feature extraction step. In this step, we introduce the region-SIFT feature extraction method based on facial landmarks. First, we define sub-regions of the face. We then extract SIFT features from each sub-region. In order to reduce the dimensions of features we employ a Principal Component Analysis (PCA) and a Linear Discriminant Analysis (LDA). Finally, we classify age and gender using a multi-layered Support Vector Machines (SVM) for efficient classification. Rather than performing gender estimation and age estimation independently, the use of the multi-layered SVM can improve the classification rate by constructing a classifier that estimate the age according to gender. Moreover, we collect a dataset of face images, called by DGIST_C, from the internet. A performance evaluation of proposed method was performed with the FERET database, CACD database, and DGIST_C database. The experimental results demonstrate that the proposed approach classifies age and performs gender estimation very efficiently and accurately.

TU-G-204-02: Automatic Sclerotic Bone Metastases Detection in the Pelvic Region From Dual Energy CT

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

Fehr, D; Schmidtlein, C; Hwang, S

Purpose: To automatically detect sclerotic bone metastases in the pelvic region using dual energy computed tomography (DECT). Methods: We developed a two stage algorithm to automatically detect sclerotic bone metastases in the pelvis from DECT for patients with multiple bone metastatic lesions and with hip implants. The first stage consists of extracting the bone and marrow regions by using a support vector machine (SVM) classifier. We employed a novel representation of the DECT images using multi-material decomposition, which represents each voxel as a mixture of different physical materials (e.g. bone+water+fat). Following the extraction of bone and marrow, in the secondmore » stage, a bi -histogram equalization method was employed to enhance the contrast to reveal the bone metastases. Next, meanshift segmentation was performed to separate the voxels by their intensity levels. Finally, shape-based filtering was performed to extract the possible locations of the metastatic lesions using multiple shape criteria. We used the following shape parameters: area, eccentricity, major and minor axis, perimeter and skeleton. Results: A radiologist with several years of experience with DECT manually labeled 64 regions consisting of metastatic lesions from 10 different patients. However, the patients had many more metastasic lesions throughout the pelvis. Our method correctly identified 46 of the marked 64 regions (72%). In addition, our method also identified several other lesions, which can then be validated by the radiologist. The missed lesions were typically very large elongated regions consisting of several islands of very small (<4mm) lesions. Conclusion: We developed an algorithm to automatically detect sclerotic lesions in the pelvic region from DECT. Preliminary assessment shows that our algorithm generated lesions agreeing with the radiologist generated candidate regions. Furthermore, our method reveals additional lesions that can be inspected by the radiologist, thereby, reducing radiologist effort in identifying all the lesions with poor contrast from the DECT images.« less

Algorithm based on regional separation for automatic grain boundary extraction using improved mean shift method

NASA Astrophysics Data System (ADS)

Zhenying, Xu; Jiandong, Zhu; Qi, Zhang; Yamba, Philip

2018-06-01

Metallographic microscopy shows that the vast majority of metal materials are composed of many small grains; the grain size of a metal is important for determining the tensile strength, toughness, plasticity, and other mechanical properties. In order to quantitatively evaluate grain size in metals, grain boundaries must be identified in metallographic images. Based on the phenomenon of grain boundary blurring or disconnection in metallographic images, this study develops an algorithm based on regional separation for automatically extracting grain boundaries by an improved mean shift method. Experimental observation shows that the grain boundaries obtained by the proposed algorithm are highly complete and accurate. This research has practical value because the proposed algorithm is suitable for grain boundary extraction from most metallographic images.

An assessment of the efficiency of fungal DNA extraction methods for maximizing the detection of medically important fungi using PCR.

PubMed

Karakousis, A; Tan, L; Ellis, D; Alexiou, H; Wormald, P J

2006-04-01

To date, no single reported DNA extraction method is suitable for the efficient extraction of DNA from all fungal species. The efficiency of extraction is of particular importance in PCR-based medical diagnostic applications where the quantity of fungus in a tissue biopsy may be limited. We subjected 16 medically relevant fungi to physical, chemical and enzymatic cell wall disruption methods which constitutes the first step in extracting DNA. Examination by light microscopy showed that grinding with mortar and pestle was the most efficient means of disrupting the rigid fungal cell walls of hyphae and conidia. We then trialled several published DNA isolation protocols to ascertain the most efficient method of extraction. Optimal extraction was achieved by incorporating a lyticase and proteinase K enzymatic digestion step and adapting a DNA extraction procedure from a commercial kit (MO BIO) to generate high yields of high quality DNA from all 16 species. DNA quality was confirmed by the successful PCR amplification of the conserved region of the fungal 18S small-subunit rRNA multicopy gene.

3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels

NASA Astrophysics Data System (ADS)

Huang, Shan; Liu, Xiabi; Han, Guanghui; Zhao, Xinming; Zhao, Yanfeng; Zhou, Chunwu

2018-02-01

The earlier detection of ground glass opacity (GGO) is of great importance since GGOs are more likely to be malignant than solid nodules. However, the detection of GGO is a difficult task in lung cancer screening. This paper proposes a novel GGO candidate extraction method, which performs multilevel thresholding on supervoxels in 3D lung CT images. Firstly, we segment the lung parenchyma based on Otsu algorithm. Secondly, the voxels which are adjacent in 3D discrete space and sharing similar grayscale are clustered into supervoxels. This procedure is used to enhance GGOs and reduce computational complexity. Thirdly, Hessian matrix is used to emphasize focal GGO candidates. Lastly, an improved adaptive multilevel thresholding method is applied on segmented clusters to extract GGO candidates. The proposed method was evaluated on a set of 19 lung CT scans containing 166 GGO lesions from the Lung CT Imaging Signs (LISS) database. The experimental results show that our proposed GGO candidate extraction method is effective, with a sensitivity of 100% and 26.3 of false positives per scan (665 GGO candidates, 499 non-GGO regions and 166 GGO regions). It can handle both focal GGOs and diffuse GGOs.

Scene text recognition in mobile applications by character descriptor and structure configuration.

PubMed

Yi, Chucai; Tian, Yingli

2014-07-01

Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

Automated tracking of a figure skater by using PTZ cameras

NASA Astrophysics Data System (ADS)

Haraguchi, Tomohiko; Taki, Tsuyoshi; Hasegawa, Junichi

2009-08-01

In this paper, a system for automated real-time tracking of a figure skater moving on an ice rink by using PTZ cameras is presented. This system is intended for support in training of skating, for example, as a tool for recording and evaluation of his/her motion performances. In the processing procedure of the system, an ice rink region is extracted first from a video image by region growing method, then one of hole components in the obtained rink region is extracted as a skater region. If there exists no hole component, a skater region is estimated from horizontal and vertical intensity projections of the rink region. Each camera is automatically panned and/or tilted so as to keep the skater region on almost the center of the image, and also zoomed so as to keep the height of the skater region within an appropriate range. In the experiments using 5 practical video images of skating, it was shown that the extraction rate of the skater region was almost 90%, and tracking with camera control was successfully done for almost all of the cases used here.

A Hybrid Method for Endocardial Contour Extraction of Right Ventricle in 4-Slices from 3D Echocardiography Dataset.

PubMed

Dawood, Faten A; Rahmat, Rahmita W; Kadiman, Suhaini B; Abdullah, Lili N; Zamrin, Mohd D

2014-01-01

This paper presents a hybrid method to extract endocardial contour of the right ventricular (RV) in 4-slices from 3D echocardiography dataset. The overall framework comprises four processing phases. In Phase I, the region of interest (ROI) is identified by estimating the cavity boundary. Speckle noise reduction and contrast enhancement were implemented in Phase II as preprocessing tasks. In Phase III, the RV cavity region was segmented by generating intensity threshold which was used for once for all frames. Finally, Phase IV is proposed to extract the RV endocardial contour in a complete cardiac cycle using a combination of shape-based contour detection and improved radial search algorithm. The proposed method was applied to 16 datasets of 3D echocardiography encompassing the RV in long-axis view. The accuracy of experimental results obtained by the proposed method was evaluated qualitatively and quantitatively. It has been done by comparing the segmentation results of RV cavity based on endocardial contour extraction with the ground truth. The comparative analysis results show that the proposed method performs efficiently in all datasets with overall performance of 95% and the root mean square distances (RMSD) measure in terms of mean ± SD was found to be 2.21 ± 0.35 mm for RV endocardial contours.

An Improved Text Localization Method for Natural Scene Images

NASA Astrophysics Data System (ADS)

Jiang, Mengdi; Cheng, Jianghua; Chen, Minghui; Ku, Xishu

2018-01-01

In order to extract text information effectively from natural scene image with complex background, multi-orientation perspective and multilingual languages, we present a new method based on the improved Stroke Feature Transform (SWT). Firstly, The Maximally Stable Extremal Region (MSER) method is used to detect text candidate regions. Secondly, the SWT algorithm is used in the candidate regions, which can improve the edge detection compared with tradition SWT method. Finally, the Frequency-tuned (FT) visual saliency is introduced to remove non-text candidate regions. The experiment results show that, the method can achieve good robustness for complex background with multi-orientation perspective, various characters and font sizes.

Influence of Humic Acids Extracted from Peat by Different Methods on Functional Activity of Macrophages in Vitro.

PubMed

Trofimova, E S; Zykova, M V; Ligacheva, A A; Sherstoboev, E Y; Zhdanov, V V; Belousov, M V; Yusubov, M S; Krivoshchekov, S V; Danilets, M G; Dygai, A M

2017-04-01

We studied activation of macrophages with humic acids extracted from peat of large deposits in the Tomsk region by two extraction methods: by hydroxide or sodium pyrophosphate. Humic acid of lowland peat types containing large amounts of aromatic carbon, phenolic and alcohol groups, carbohydrate residues and ethers, irrespectively of the extraction methods contained LPS admixture that probably determines their activating properties. Humic acid of upland peat types characterized by high content of carbonyl, carboxyl, and ester groups enhance NO production and reduce arginase expression, but these effects were minimized when sodium hydroxide was used as an extraction solvent. Pyrophosphate samples of the upland peat types were characterized by aromaticity and diversity of functional groups and have a significant advantage because of they induce specific endotoxin-independent stimulating action on antigen presenting cells.

Manipulation of the micro and macro-structure of beams extracted from cyclotrons

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

Laxdal, R.E.

1995-09-01

It is standard practice in cyclotrons to alter the extracted micro-pulse width by using center-region slits and/or by chopping the beam before injection. The macro-structure can also be varied by means of pulsed or sinusoidal deflection devices before injection and/or after extraction. All above methods, however, involve cutting away the unwanted beam, thus reducing the time-averaged intensity. This paper will focus on some methods used to alter the time structure of extracted beams without significant beam loss. For example radial gradients in the accelerating fields from rf cavities can be utilized to compress, expand or even split longitudinally the circulatingmore » particle bunches. The macro-structure of the extracted beam can be altered by employing resonant extraction methods and replacing the static magnetic bump with either a pulsed or a sinusoidal transverse perturbation. The methods are most suitable for H cyclotrons but may also be considered in a limited scope for cyclotrons using direct extraction. Results of computer simulations and beam tests on the TRIUMF 500 MeV H{sup {minus}} cyclotron will be presented.« less

Method of Grassland Information Extraction Based on Multi-Level Segmentation and Cart Model

NASA Astrophysics Data System (ADS)

Qiao, Y.; Chen, T.; He, J.; Wen, Q.; Liu, F.; Wang, Z.

2018-04-01

It is difficult to extract grassland accurately by traditional classification methods, such as supervised method based on pixels or objects. This paper proposed a new method combing the multi-level segmentation with CART (classification and regression tree) model. The multi-level segmentation which combined the multi-resolution segmentation and the spectral difference segmentation could avoid the over and insufficient segmentation seen in the single segmentation mode. The CART model was established based on the spectral characteristics and texture feature which were excavated from training sample data. Xilinhaote City in Inner Mongolia Autonomous Region was chosen as the typical study area and the proposed method was verified by using visual interpretation results as approximate truth value. Meanwhile, the comparison with the nearest neighbor supervised classification method was obtained. The experimental results showed that the total precision of classification and the Kappa coefficient of the proposed method was 95 % and 0.9, respectively. However, the total precision of classification and the Kappa coefficient of the nearest neighbor supervised classification method was 80 % and 0.56, respectively. The result suggested that the accuracy of classification proposed in this paper was higher than the nearest neighbor supervised classification method. The experiment certificated that the proposed method was an effective extraction method of grassland information, which could enhance the boundary of grassland classification and avoid the restriction of grassland distribution scale. This method was also applicable to the extraction of grassland information in other regions with complicated spatial features, which could avoid the interference of woodland, arable land and water body effectively.

Quantitative evaluation for small surface damage based on iterative difference and triangulation of 3D point cloud

NASA Astrophysics Data System (ADS)

Zhang, Yuyan; Guo, Quanli; Wang, Zhenchun; Yang, Degong

2018-03-01

This paper proposes a non-contact, non-destructive evaluation method for the surface damage of high-speed sliding electrical contact rails. The proposed method establishes a model of damage identification and calculation. A laser scanning system is built to obtain the 3D point cloud data of the rail surface. In order to extract the damage region of the rail surface, the 3D point cloud data are processed using iterative difference, nearest neighbours search and a data registration algorithm. The curvature of the point cloud data in the damage region is mapped to RGB color information, which can directly reflect the change trend of the curvature of the point cloud data in the damage region. The extracted damage region is divided into three prism elements by a method of triangulation. The volume and mass of a single element are calculated by the method of geometric segmentation. Finally, the total volume and mass of the damage region are obtained by the principle of superposition. The proposed method is applied to several typical injuries and the results are discussed. The experimental results show that the algorithm can identify damage shapes and calculate damage mass with milligram precision, which are useful for evaluating the damage in a further research stage.

An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.

PubMed

Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong

2016-01-01

Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels.

Extraction channel design based on an equivalent lumped parameter method for a SCC-250 MeV superconducting cyclotron

NASA Astrophysics Data System (ADS)

Zhang, Lige; Fan, Kuanjun; Hu, Shengwei; Li, Xiaofei; Mei, Zhiyuan; Zeng, Zhijie; Chen, Wei; Qin, Bin; Rao, Yinong

2018-07-01

A SCC-250 MeV cyclotron, producing a 250 MeV proton beam, is under development in Huazhong University of Science and Technology (HUST) for proton therapy. The magnetic flux density, as a function of radius, decreases rapidly in the beam extraction region, which increases the radial beam size continuously along the extraction orbit. In this paper, an extraction channel inside the SCC-250 MeV is designed to control the beam size using passive magnetic channels. An equivalent lumped parameter method is used to establish the model of the extraction channel in the complex fringe magnetic field of the main magnet. Then, the extraction channel is designed using the lattice design software MADX. The beam envelopes are verified using particle tracing method. The maximum radial size of 6.8 mm and axial size of 4.3 mm meet the requirements of the extraction from the SCC-250 MeV.

Text Line Detection from Rectangle Traffic Panels of Natural Scene

NASA Astrophysics Data System (ADS)

Wang, Shiyuan; Huang, Linlin; Hu, Jian

2018-01-01

Traffic sign detection and recognition is very important for Intelligent Transportation. Among traffic signs, traffic panel contains rich information. However, due to low resolution and blur in the rectangular traffic panel, it is difficult to extract the character and symbols. In this paper, we propose a coarse-to-fine method to detect the Chinese character on traffic panels from natural scenes. Given a traffic panel Color Quantization is applied to extract candidate regions of Chinese characters. Second, a multi-stage filter based on learning is applied to discard the non-character regions. Third, we aggregate the characters for text lines by Distance Metric Learning method. Experimental results on real traffic images from Baidu Street View demonstrate the effectiveness of the proposed method.

New auto-segment method of cerebral hemorrhage

NASA Astrophysics Data System (ADS)

Wang, Weijiang; Shen, Tingzhi; Dang, Hua

2007-12-01

A novel method for Computerized tomography (CT) cerebral hemorrhage (CH) image automatic segmentation is presented in the paper, which uses expert system that models human knowledge about the CH automatic segmentation problem. The algorithm adopts a series of special steps and extracts some easy ignored CH features which can be found by statistic results of mass real CH images, such as region area, region CT number, region smoothness and some statistic CH region relationship. And a seven steps' extracting mechanism will ensure these CH features can be got correctly and efficiently. By using these CH features, a decision tree which models the human knowledge about the CH automatic segmentation problem has been built and it will ensure the rationality and accuracy of the algorithm. Finally some experiments has been taken to verify the correctness and reasonable of the automatic segmentation, and the good correct ratio and fast speed make it possible to be widely applied into practice.

Line fitting based feature extraction for object recognition

NASA Astrophysics Data System (ADS)

Li, Bing

2014-06-01

Image feature extraction plays a significant role in image based pattern applications. In this paper, we propose a new approach to generate hierarchical features. This new approach applies line fitting to adaptively divide regions based upon the amount of information and creates line fitting features for each subsequent region. It overcomes the feature wasting drawback of the wavelet based approach and demonstrates high performance in real applications. For gray scale images, we propose a diffusion equation approach to map information-rich pixels (pixels near edges and ridge pixels) into high values, and pixels in homogeneous regions into small values near zero that form energy map images. After the energy map images are generated, we propose a line fitting approach to divide regions recursively and create features for each region simultaneously. This new feature extraction approach is similar to wavelet based hierarchical feature extraction in which high layer features represent global characteristics and low layer features represent local characteristics. However, the new approach uses line fitting to adaptively focus on information-rich regions so that we avoid the feature waste problems of the wavelet approach in homogeneous regions. Finally, the experiments for handwriting word recognition show that the new method provides higher performance than the regular handwriting word recognition approach.

Texture-based segmentation and analysis of emphysema depicted on CT images

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Lederman, Dror; Pu, Jiantao; Sciurba, Frank C.; Gur, David; Leader, J. Ken

2011-03-01

In this study we present a texture-based method of emphysema segmentation depicted on CT examination consisting of two steps. Step 1, a fractal dimension based texture feature extraction is used to initially detect base regions of emphysema. A threshold is applied to the texture result image to obtain initial base regions. Step 2, the base regions are evaluated pixel-by-pixel using a method that considers the variance change incurred by adding a pixel to the base in an effort to refine the boundary of the base regions. Visual inspection revealed a reasonable segmentation of the emphysema regions. There was a strong correlation between lung function (FEV1%, FEV1/FVC, and DLCO%) and fraction of emphysema computed using the texture based method, which were -0.433, -.629, and -0.527, respectively. The texture-based method produced more homogeneous emphysematous regions compared to simple thresholding, especially for large bulla, which can appear as speckled regions in the threshold approach. In the texture-based method, single isolated pixels may be considered as emphysema only if neighboring pixels meet certain criteria, which support the idea that single isolated pixels may not be sufficient evidence that emphysema is present. One of the strength of our complex texture-based approach to emphysema segmentation is that it goes beyond existing approaches that typically extract a single or groups texture features and individually analyze the features. We focus on first identifying potential regions of emphysema and then refining the boundary of the detected regions based on texture patterns.

Evaluation of Photoprotective Potential and Percutaneous Penetration by Photoacoustic Spectroscopy of the Schinus terebinthifolius Raddi Extract.

PubMed

Bulla, Milena K; Hernandes, Luzmarina; Baesso, Mauro L; Nogueira, Ana C; Bento, Antonio C; Bortoluzzi, Bruno B; Serra, Lara Z; Cortez, Diogenes A G

2015-01-01

Schinus terebinthifolius is a plant rich in phenolic compounds, which have antioxidant properties and can provide new opportunities for treatment and prevention of diseases mediated by ultraviolet radiation like photoaging and skin cancer. The aim of this study was to evaluate the photoprotective potential and ex vivo percutaneous penetration of the crude extract of Schinus terebinthifolius leaves. The extract was tested for antioxidant activity using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method and β-carotene bleaching test. The sun protection factor was also evaluated. The ex vivo skin permeation of the emulsion and gel formulations were assayed. Fractionation of the extract resulted in gallic acid, ethyl gallate and a mixture of flavonoids, suggesting derivatives of quercetin and myricetin. The phenolic content of the extract was 384.64 ± 2.60 mg GAE g(-1) extract. The antioxidant activity was superior to butylated hydroxytoluene, in DPPH method, and ascorbic acid and rutin, in β-carotene bleaching assay. The extract showed UV absorption with photoprotector potential in the UVB region. The photoacoustic spectroscopy measurements confirmed absorption in the UV region and topical application of the formulations caused no histological changes in the rats' skin. These results suggest that the crude extract of Schinus terebinthifolius leaves may be a promising natural sunscreen product. © 2015 The American Society of Photobiology.

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.

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.

Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

PubMed

Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

2017-09-01

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

Automated torso organ segmentation from 3D CT images using structured perceptron and dual decomposition

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Mori, Kensaku

2015-03-01

This paper presents a method for torso organ segmentation from abdominal CT images using structured perceptron and dual decomposition. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. This paper proposes an organ segmentation method using structured output learning. Our method utilizes a graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weights of the graphical model by structured perceptron and estimate the best organ label for a given image by dynamic programming and dual decomposition. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 4.4%. The DICE coefficients of left lung, right lung, heart, liver, spleen, pancreas, left kidney, right kidney, and gallbladder were 0.91, 0.95, 0.77, 0.81, 0.74, 0.08, 0.83, 0.84, and 0.03, respectively.

A SUSTAINABLE METHOD OF WATER EXTRACTION FOR SCHOOL-COMMUNITY GARDENS IN NIGER, WEST AFRICA

EPA Science Inventory

The challenge of this project is significant in the developing world, specifically in the Air Massif region of Niger, the poorest country in the world. A sustainable water extraction system is needed to irrigate community gardens. These gardens produce a basic need, food, for ...

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

PubMed

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lavenne, Franck; Le Bars, Didier; Costes, Nicolas

2013-08-15

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures. Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data. Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of atlases used. When all four atlases were used for the MAXPROB creation, the accuracy of morphometric segmentation approached that of the PROPAG method. PET measures extracted either via automatic methods or via the manually defined regions were strongly correlated, with no significant regional differences between methods. Intra-class correlation coefficients for test-retest data were over 0.87. Compared to single atlas extractions, multi-atlas methods improve the accuracy of region definition. They also perform comparably to manually defined regions for PET quantification. Multiple atlases of Macaca fascicularis brains are now available and allow reproducible and simplified analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Line segment extraction for large scale unorganized point clouds

NASA Astrophysics Data System (ADS)

Lin, Yangbin; Wang, Cheng; Cheng, Jun; Chen, Bili; Jia, Fukai; Chen, Zhonggui; Li, Jonathan

2015-04-01

Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction.

Extraction and Analysis of Traditional Chinese Medicine Crops Based on Multitemporal High Resolution Data-Taking Qiaocheng District of Bozhou as AN Example

NASA Astrophysics Data System (ADS)

Yu, H.; He, J.; Zhou, H.; Guan, F.; Li, L.; Ren, B.; Wang, Z.

2018-04-01

Remote sensing technology has become an important method to rapidly acquireing of planting layout and composition of regional crops.It is very important to accurately master the planting area of Chinese medicine crops in the Characteristic planting area because it relations to accurately master the cultivation of Chinese medicine crops, formulate related policies and adjustment of crop planting structure.The author puts forward a method of using remote sencing technology for momitoring Chinese medicine which has good applicability and generalization. This paper took Qiaocheng District of Bozhou as an example to Verify the feasibility of the method, providing a reference for solving the problem of interpretation and extraction of Chinese medicinal materials in the region.

Extraction of skin lesions from non-dermoscopic images for surgical excision of melanoma.

PubMed

Jafari, M Hossein; Nasr-Esfahani, Ebrahim; Karimi, Nader; Soroushmehr, S M Reza; Samavi, Shadrokh; Najarian, Kayvan

2017-06-01

Computerized prescreening of suspicious moles and lesions for malignancy is of great importance for assessing the need and the priority of the removal surgery. Detection can be done by images captured by standard cameras, which are more preferable due to low cost and availability. One important step in computerized evaluation is accurate detection of lesion's region, i.e., segmentation of an image into two regions as lesion and normal skin. In this paper, a new method based on deep neural networks is proposed for accurate extraction of a lesion region. The input image is preprocessed, and then, its patches are fed to a convolutional neural network. Local texture and global structure of the patches are processed in order to assign pixels to lesion or normal classes. A method for effective selection of training patches is proposed for more accurate detection of a lesion's border. Our results indicate that the proposed method could reach the accuracy of 98.7% and the sensitivity of 95.2% in segmentation of lesion regions over the dataset of clinical images. The experimental results of qualitative and quantitative evaluations demonstrate that our method can outperform other state-of-the-art algorithms exist in the literature.

Facial expression recognition under partial occlusion based on fusion of global and local features

NASA Astrophysics Data System (ADS)

Wang, Xiaohua; Xia, Chen; Hu, Min; Ren, Fuji

2018-04-01

Facial expression recognition under partial occlusion is a challenging research. This paper proposes a novel framework for facial expression recognition under occlusion by fusing the global and local features. In global aspect, first, information entropy are employed to locate the occluded region. Second, principal Component Analysis (PCA) method is adopted to reconstruct the occlusion region of image. After that, a replace strategy is applied to reconstruct image by replacing the occluded region with the corresponding region of the best matched image in training set, Pyramid Weber Local Descriptor (PWLD) feature is then extracted. At last, the outputs of SVM are fitted to the probabilities of the target class by using sigmoid function. For the local aspect, an overlapping block-based method is adopted to extract WLD features, and each block is weighted adaptively by information entropy, Chi-square distance and similar block summation methods are then applied to obtain the probabilities which emotion belongs to. Finally, fusion at the decision level is employed for the data fusion of the global and local features based on Dempster-Shafer theory of evidence. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the effectiveness and fault tolerance of this method.

Production of N[sup +] ions from a multicusp ion beam apparatus

DOEpatents

Kango Leung; Kunkel, W.B.; Walther, S.R.

1993-03-30

A method of generating a high purity (at least 98%) N[sup +] ion beam using a multicusp ion source having a chamber formed by a cylindrical chamber wall surrounded by a plurality of magnets, a filament centrally disposed in said chamber, a plasma electrode having an extraction orifice at one end of the chamber, a magnetic filter having two parallel magnets spaced from said plasma electrode and dividing the chamber into arc discharge and extraction regions. The method includes ionizing nitrogen gas in the arc discharge region of the chamber, maintaining the chamber wall at a positive voltage relative to the filament and at a magnitude for an optimum percentage of N[sup +] ions in the extracted ion beams, disposing a hot liner within the chamber and near the chamber wall to limit recombination of N[sup +] ions into the N[sub 2][sup +] ions, spacing the magnets of the magnetic filter from each other for optimum percentage of N[sup 3] ions in the extracted ion beams, and maintaining a relatively low pressure downstream of the extraction orifice and of a magnitude (preferably within the range of 3-8[times]10[sup [minus]4] torr) for an optimum percentage of N[sup +] ions in the extracted ion beam.

Medical Image Tamper Detection Based on Passive Image Authentication.

PubMed

Ulutas, Guzin; Ustubioglu, Arda; Ustubioglu, Beste; V Nabiyev, Vasif; Ulutas, Mustafa

2017-12-01

Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.

Detecting text in natural scenes with multi-level MSER and SWT

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Liu, Renjun

2018-04-01

The detection of the characters in the natural scene is susceptible to factors such as complex background, variable viewing angle and diverse forms of language, which leads to poor detection results. Aiming at these problems, a new text detection method was proposed, which consisted of two main stages, candidate region extraction and text region detection. At first stage, the method used multiple scale transformations of original image and multiple thresholds of maximally stable extremal regions (MSER) to detect the text regions which could detect character regions comprehensively. At second stage, obtained SWT maps by using the stroke width transform (SWT) algorithm to compute the candidate regions, then using cascaded classifiers to propose non-text regions. The proposed method was evaluated on the standard benchmark datasets of ICDAR2011 and the datasets that we made our own data sets. The experiment results showed that the proposed method have greatly improved that compared to other text detection methods.

An Effective Palmprint Recognition Approach for Visible and Multispectral Sensor Images.

PubMed

Gumaei, Abdu; Sammouda, Rachid; Al-Salman, Abdul Malik; Alsanad, Ahmed

2018-05-15

Among several palmprint feature extraction methods the HOG-based method is attractive and performs well against changes in illumination and shadowing of palmprint images. However, it still lacks the robustness to extract the palmprint features at different rotation angles. To solve this problem, this paper presents a hybrid feature extraction method, named HOG-SGF that combines the histogram of oriented gradients (HOG) with a steerable Gaussian filter (SGF) to develop an effective palmprint recognition approach. The approach starts by processing all palmprint images by David Zhang's method to segment only the region of interests. Next, we extracted palmprint features based on the hybrid HOG-SGF feature extraction method. Then, an optimized auto-encoder (AE) was utilized to reduce the dimensionality of the extracted features. Finally, a fast and robust regularized extreme learning machine (RELM) was applied for the classification task. In the evaluation phase of the proposed approach, a number of experiments were conducted on three publicly available palmprint databases, namely MS-PolyU of multispectral palmprint images and CASIA and Tongji of contactless palmprint images. Experimentally, the results reveal that the proposed approach outperforms the existing state-of-the-art approaches even when a small number of training samples are used.

Antioxidant components of Viburnum opulus L. determined by on-line HPLC-UV-ABTS radical scavenging and LC-UV-ESI-MS methods.

PubMed

Karaçelik, Ayça Aktaş; Küçük, Murat; İskefiyeli, Zeynep; Aydemir, Sezgin; De Smet, Seppe; Miserez, Bram; Sandra, Patrick

2015-05-15

Antioxidant activity of the juice and seed and skin extracts prepared with methanol, acetonitrile, and water of Viburnum opulus L. grown in Eastern Black Sea Region were studied with an on-line HPLC-ABTS method and off-line antioxidant methods, among which a linear positive correlation was observed. The fruit extracts were analysed with the HPLC-UV method optimised with 14 standard phenolics. Identification of the phenolic components in the juice was made using an HPLC-UV-ESI-MS method. Nineteen phenolic compounds in juice were identified by comparing the retention times and mass spectra with those of the standards and the phenolics reported in the literature. The major peaks in the juice belonged to coumaroyl-quinic acid, chlorogenic acid, procyanidin B2, and procyanidin trimer. Quite different antioxidant composition profiles were obtained from the extracts with the solvents of different polarities. The antioxidant activities of the seed extracts were higher than those of the skin extracts in general. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prostate cancer detection: Fusion of cytological and textural features.

PubMed

Nguyen, Kien; Jain, Anil K; Sabata, Bikash

2011-01-01

A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli) in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000×7,000 pixels) and 1 1 whole-slide test images (each of which has approximately 5,000×23,000 pixels). All images are at 20X magnification.

Prostate cancer detection: Fusion of cytological and textural features

PubMed Central

Nguyen, Kien; Jain, Anil K.; Sabata, Bikash

2011-01-01

A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli) in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000×7,000 pixels) and 1 1 whole-slide test images (each of which has approximately 5,000×23,000 pixels). All images are at 20X magnification. PMID:22811959

A new efficient method for color image compression based on visual attention mechanism

NASA Astrophysics Data System (ADS)

Shao, Xiaoguang; Gao, Kun; Lv, Lily; Ni, Guoqiang

2010-11-01

One of the key procedures in color image compression is to extract its region of interests (ROIs) and evaluate different compression ratios. A new non-uniform color image compression algorithm with high efficiency is proposed in this paper by using a biology-motivated selective attention model for the effective extraction of ROIs in natural images. When the ROIs have been extracted and labeled in the image, the subsequent work is to encode the ROIs and other regions with different compression ratios via popular JPEG algorithm. Furthermore, experiment results and quantitative and qualitative analysis in the paper show perfect performance when comparing with other traditional color image compression approaches.

The algorithm of fast image stitching based on multi-feature extraction

NASA Astrophysics Data System (ADS)

Yang, Chunde; Wu, Ge; Shi, Jing

2018-05-01

This paper proposed an improved image registration method combining Hu-based invariant moment contour information and feature points detection, aiming to solve the problems in traditional image stitching algorithm, such as time-consuming feature points extraction process, redundant invalid information overload and inefficiency. First, use the neighborhood of pixels to extract the contour information, employing the Hu invariant moment as similarity measure to extract SIFT feature points in those similar regions. Then replace the Euclidean distance with Hellinger kernel function to improve the initial matching efficiency and get less mismatching points, further, estimate affine transformation matrix between the images. Finally, local color mapping method is adopted to solve uneven exposure, using the improved multiresolution fusion algorithm to fuse the mosaic images and realize seamless stitching. Experimental results confirm high accuracy and efficiency of method proposed in this paper.

Extraction method of interfacial injected charges for SiC power MOSFETs

NASA Astrophysics Data System (ADS)

Wei, Jiaxing; Liu, Siyang; Li, Sheng; Song, Haiyang; Chen, Xin; Li, Ting; Fang, Jiong; Sun, Weifeng

2018-01-01

An improved novel extraction method which can characterize the injected charges along the gate oxide interface for silicon carbide (SiC) power metal-oxide-semiconductor field-effect transistors (MOSFETs) is proposed. According to the different interface situations of the channel region and the junction FET (JFET) region, the gate capacitance versus gate voltage (Cg-Vg) curve of the device can be divided into three relatively independent parts, through which the locations and the types of the charges injected in to the oxide above the interface can be distinguished. Moreover, the densities of these charges can also be calculated by the amplitudes of the shifts in the Cg-Vg curve. The correctness of this method is proved by TCAD simulations. Moreover, experiments on devices stressed by unclamped-inductive-switching (UIS) stress and negative bias temperature stress (NBTS) are performed to verify the validity of this method.

Blood vessel-based liver segmentation through the portal phase of a CT dataset

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Moriyama, Noriyuki; Utsunomiya, Toru; Shimada, Mitsuo

2013-02-01

Blood vessels are dispersed throughout the human body organs and carry unique information for each person. This information can be used to delineate organ boundaries. The proposed method relies on abdominal blood vessels (ABV) to segment the liver considering the potential presence of tumors through the portal phase of a CT dataset. ABV are extracted and classified into hepatic (HBV) and nonhepatic (non-HBV) with a small number of interactions. HBV and non-HBV are used to guide an automatic segmentation of the liver. HBV are used to individually segment the core region of the liver. This region and non-HBV are used to construct a boundary surface between the liver and other organs to separate them. The core region is classified based on extracted posterior distributions of its histogram into low intensity tumor (LIT) and non-LIT core regions. Non-LIT case includes normal part of liver, HBV, and high intensity tumors if exist. Each core region is extended based on its corresponding posterior distribution. Extension is completed when it reaches either a variation in intensity or the constructed boundary surface. The method was applied to 80 datasets (30 Medical Image Computing and Computer Assisted Intervention (MICCAI) and 50 non-MICCAI data) including 60 datasets with tumors. Our results for the MICCAI-test data were evaluated by sliver07 [1] with an overall score of 79.7, which ranks seventh best on the site (December 2013). This approach seems a promising method for extraction of liver volumetry of various shapes and sizes and low intensity hepatic tumors.

Thin Ice Area Extraction in the Seasonal Sea Ice Zones of the Northern Hemisphere Using Modis Data

NASA Astrophysics Data System (ADS)

Hayashi, K.; Naoki, K.; Cho, K.

2018-04-01

Sea ice has an important role of reflecting the solar radiation back into space. However, once the sea ice area melts, the area starts to absorb the solar radiation which accelerates the global warming. This means that the trend of global warming is likely to be enhanced in sea ice areas. In this study, the authors have developed a method to extract thin ice area using reflectance data of MODIS onboard Terra and Aqua satellites of NASA. The reflectance of thin sea ice in the visible region is rather low. Moreover, since the surface of thin sea ice is likely to be wet, the reflectance of thin sea ice in the near infrared region is much lower than that of visible region. Considering these characteristics, the authors have developed a method to extract thin sea ice areas by using the reflectance data of MODIS (NASA MYD09 product, 2017) derived from MODIS L1B. By using the scatter plots of the reflectance of Band 1 (620 nm-670 nm) and Band 2 (841 nm-876 nm)) of MODIS, equations for extracting thin ice area were derived. By using those equations, most of the thin ice areas which could be recognized from MODIS images were well extracted in the seasonal sea ice zones in the Northern Hemisphere, namely the Sea of Okhotsk, the Bering Sea and the Gulf of Saint Lawrence. For some limited areas, Landsat-8 OLI images were also used for validation.

Combining Feature Extraction Methods to Assist the Diagnosis of Alzheimer's Disease.

PubMed

Segovia, F; Górriz, J M; Ramírez, J; Phillips, C

2016-01-01

Neuroimaging data as (18)F-FDG PET is widely used to assist the diagnosis of Alzheimer's disease (AD). Looking for regions with hypoperfusion/ hypometabolism, clinicians may predict or corroborate the diagnosis of the patients. Modern computer aided diagnosis (CAD) systems based on the statistical analysis of whole neuroimages are more accurate than classical systems based on quantifying the uptake of some predefined regions of interests (ROIs). In addition, these new systems allow determining new ROIs and take advantage of the huge amount of information comprised in neuroimaging data. A major branch of modern CAD systems for AD is based on multivariate techniques, which analyse a neuroimage as a whole, considering not only the voxel intensities but also the relations among them. In order to deal with the vast dimensionality of the data, a number of feature extraction methods have been successfully applied. In this work, we propose a CAD system based on the combination of several feature extraction techniques. First, some commonly used feature extraction methods based on the analysis of the variance (as principal component analysis), on the factorization of the data (as non-negative matrix factorization) and on classical magnitudes (as Haralick features) were simultaneously applied to the original data. These feature sets were then combined by means of two different combination approaches: i) using a single classifier and a multiple kernel learning approach and ii) using an ensemble of classifier and selecting the final decision by majority voting. The proposed approach was evaluated using a labelled neuroimaging database along with a cross validation scheme. As conclusion, the proposed CAD system performed better than approaches using only one feature extraction technique. We also provide a fair comparison (using the same database) of the selected feature extraction methods.

Component spectra extraction from terahertz measurements of unknown mixtures.

PubMed

Li, Xian; Hou, D B; Huang, P J; Cai, J H; Zhang, G X

2015-10-20

The aim of this work is to extract component spectra from unknown mixtures in the terahertz region. To that end, a method, hard modeling factor analysis (HMFA), was applied to resolve terahertz spectral matrices collected from the unknown mixtures. This method does not require any expertise of the user and allows the consideration of nonlinear effects such as peak variations or peak shifts. It describes the spectra using a peak-based nonlinear mathematic model and builds the component spectra automatically by recombination of the resolved peaks through correlation analysis. Meanwhile, modifications on the method were made to take the features of terahertz spectra into account and to deal with the artificial baseline problem that troubles the extraction process of some terahertz spectra. In order to validate the proposed method, simulated wideband terahertz spectra of binary and ternary systems and experimental terahertz absorption spectra of amino acids mixtures were tested. In each test, not only the number of pure components could be correctly predicted but also the identified pure spectra had a good similarity with the true spectra. Moreover, the proposed method associated the molecular motions with the component extraction, making the identification process more physically meaningful and interpretable compared to other methods. The results indicate that the HMFA method with the modifications can be a practical tool for identifying component terahertz spectra in completely unknown mixtures. This work reports the solution to this kind of problem in the terahertz region for the first time, to the best of the authors' knowledge, and represents a significant advance toward exploring physical or chemical mechanisms of unknown complex systems by terahertz spectroscopy.

Comparison of six simple methods for extracting ribosomal and mitochondrial DNA from Toxocara and Toxascaris nematodes.

PubMed

Mikaeili, F; Kia, E B; Sharbatkhori, M; Sharifdini, M; Jalalizand, N; Heidari, Z; Zarei, Z; Stensvold, C R; Mirhendi, H

2013-06-01

Six simple methods for extraction of ribosomal and mitochondrial DNA from Toxocara canis, Toxocara cati and Toxascaris leonina were compared by evaluating the presence, appearance and intensity of PCR products visualized on agarose gels and amplified from DNA extracted by each of the methods. For each species, two isolates were obtained from the intestines of their respective hosts: T. canis and T. leonina from dogs, and T. cati from cats. For all isolates, total DNA was extracted using six different methods, including grinding, boiling, crushing, beating, freeze-thawing and the use of a commercial kit. To evaluate the efficacy of each method, the internal transcribed spacer (ITS) region and the cytochrome c oxidase subunit 1 (cox1) gene were chosen as representative markers for ribosomal and mitochondrial DNA, respectively. Among the six DNA extraction methods, the beating method was the most cost effective for all three species, followed by the commercial kit. Both methods produced high intensity bands on agarose gels and were characterized by no or minimal smear formation, depending on gene target; however, beating was less expensive. We therefore recommend the beating method for studies where costs need to be kept at low levels. Copyright © 2013 Elsevier Inc. All rights reserved.

Robust real-time extraction of respiratory signals from PET list-mode data.

PubMed

Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-05-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware. © 2018 Institute of Physics and Engineering in Medicine.

Robust real-time extraction of respiratory signals from PET list-mode data

NASA Astrophysics Data System (ADS)

Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-06-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.

Moving object localization using optical flow for pedestrian detection from a moving vehicle.

PubMed

Hariyono, Joko; Hoang, Van-Dung; Jo, Kang-Hyun

2014-01-01

This paper presents a pedestrian detection method from a moving vehicle using optical flows and histogram of oriented gradients (HOG). A moving object is extracted from the relative motion by segmenting the region representing the same optical flows after compensating the egomotion of the camera. To obtain the optical flow, two consecutive images are divided into grid cells 14 × 14 pixels; then each cell is tracked in the current frame to find corresponding cell in the next frame. Using at least three corresponding cells, affine transformation is performed according to each corresponding cell in the consecutive images, so that conformed optical flows are extracted. The regions of moving object are detected as transformed objects, which are different from the previously registered background. Morphological process is applied to get the candidate human regions. In order to recognize the object, the HOG features are extracted on the candidate region and classified using linear support vector machine (SVM). The HOG feature vectors are used as input of linear SVM to classify the given input into pedestrian/nonpedestrian. The proposed method was tested in a moving vehicle and also confirmed through experiments using pedestrian dataset. It shows a significant improvement compared with original HOG using ETHZ pedestrian dataset.

A Novel Selective Deep Eutectic Solvent Extraction Method for Versatile Determination of Copper in Sediment Samples by ICP-OES.

PubMed

Bağda, Esra; Altundağ, Huseyin; Tüzen, Mustafa; Soylak, Mustafa

2017-08-01

In the present study, a simple, mono step deep eutectic solvent (DES) extraction was developed for selective extraction of copper from sediment samples. The optimization of all experimental parameters, e.g. DES type, sample/DES ratio, contact time and temperature were performed with using BCR-280 R (lake sediment certified reference material). The limit of detection (LOD) and the limit of quantification (LOQ) were found as 1.2 and 3.97 µg L -1 , respectively. The RSD of the procedure was 7.5%. The proposed extraction method was applied to river and lake sediments sampled from Serpincik, Çeltek, Kızılırmak (Fadl and Tecer region of the river), Sivas-Turkey.

Regional water-quality analysis of 2,4-D and dicamba in river water using gas chromatography-isotope dilution mass spectrometry

USGS Publications Warehouse

Thurman, E.M.; Zimmerman, L.R.; Aga, D.S.; Gilliom, R.J.

2001-01-01

Gas chromatography with isotope dilution mass spectrometry (GC-MS) and enzyme-linked immunosorbent assay (ELISA) were used in regional National Water Quality Assessment studies of the herbicides, 2,4-D and dicamba, in river water across the United States. The GC-MS method involved solid-phase extraction, derivatized with deutemted 2,4-D, and analysis by selected ion monitoring. The ELISA method was applied after preconcentration with solid-phase extraction. The ELISA method was unreliable because of interference from humic substances that were also isolated by solid-phase extraction. Therefore, GC-MS was used to analyzed 80 samples from river water from 14 basins. The frequency of detection of dicamba (28%) was higher than that for 2,4-D (16%). Concentrations were higher for dicamba than for 2,4-D, ranging from less than the detection limit (<0.05 ??g/L) to 3.77 ??g/L, in spite of 5 times more annual use of 2,4-D as compared to dicamba. These results suggest that 2,4-D degrades more rapidly in the environment than dicamba.

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.

Evaluation of the application of ERTS-1 data to the regional land use planning process. [Northeast Wisconsin

NASA Technical Reports Server (NTRS)

Clapp, J. L. (Principal Investigator); Green, T., III; Hanson, G. F.; Kiefer, R. W.; Niemann, B. J., Jr.

1974-01-01

The author has identified the following significant results. Employing simple and economical extraction methods, ERTS can provide valuable data to the planners at the state or regional level with a frequency never before possible. Interactive computer methods of working directly with ERTS digital information show much promise for providing land use information at a more specific level, since the data format production rate of ERTS justifies improved methods of analysis.

Chinese License Plates Recognition Method Based on A Robust and Efficient Feature Extraction and BPNN Algorithm

NASA Astrophysics Data System (ADS)

Zhang, Ming; Xie, Fei; Zhao, Jing; Sun, Rui; Zhang, Lei; Zhang, Yue

2018-04-01

The prosperity of license plate recognition technology has made great contribution to the development of Intelligent Transport System (ITS). In this paper, a robust and efficient license plate recognition method is proposed which is based on a combined feature extraction model and BPNN (Back Propagation Neural Network) algorithm. Firstly, the candidate region of the license plate detection and segmentation method is developed. Secondly, a new feature extraction model is designed considering three sets of features combination. Thirdly, the license plates classification and recognition method using the combined feature model and BPNN algorithm is presented. Finally, the experimental results indicate that the license plate segmentation and recognition both can be achieved effectively by the proposed algorithm. Compared with three traditional methods, the recognition accuracy of the proposed method has increased to 95.7% and the consuming time has decreased to 51.4ms.

Automatic detection of magnetic flux emergings in the solar atmosphere from full-disk magnetogram sequences.

PubMed

Fu, Gang; Shih, Frank Y; Wang, Haimin

2008-11-01

In this paper, we present a novel method to detect Emerging Flux Regions (EFRs) in the solar atmosphere from consecutive full-disk Michelson Doppler Imager (MDI) magnetogram sequences. To our knowledge, this is the first developed technique for automatically detecting EFRs. The method includes several steps. First, the projection distortion on the MDI magnetograms is corrected. Second, the bipolar regions are extracted by applying multiscale circular harmonic filters. Third, the extracted bipolar regions are traced in consecutive MDI frames by Kalman filter as candidate EFRs. Fourth, the properties, such as positive and negative magnetic fluxes and distance between two polarities, are measured in each frame. Finally, a feature vector is constructed for each bipolar region using the measured properties, and the Support Vector Machine (SVM) classifier is applied to distinguish EFRs from other regions. Experimental results show that the detection rate of EFRs is 96.4% and of non-EFRs is 98.0%, and the false alarm rate is 25.7%, based on all the available MDI magnetograms in 2001 and 2002.

Comparison of Boiling and Robotics Automation Method in DNA Extraction for Metagenomic Sequencing of Human Oral Microbes.

PubMed

Yamagishi, Junya; Sato, Yukuto; Shinozaki, Natsuko; Ye, Bin; Tsuboi, Akito; Nagasaki, Masao; Yamashita, Riu

2016-01-01

The rapid improvement of next-generation sequencing performance now enables us to analyze huge sample sets with more than ten thousand specimens. However, DNA extraction can still be a limiting step in such metagenomic approaches. In this study, we analyzed human oral microbes to compare the performance of three DNA extraction methods: PowerSoil (a method widely used in this field), QIAsymphony (a robotics method), and a simple boiling method. Dental plaque was initially collected from three volunteers in the pilot study and then expanded to 12 volunteers in the follow-up study. Bacterial flora was estimated by sequencing the V4 region of 16S rRNA following species-level profiling. Our results indicate that the efficiency of PowerSoil and QIAsymphony was comparable to the boiling method. Therefore, the boiling method may be a promising alternative because of its simplicity, cost effectiveness, and short handling time. Moreover, this method was reliable for estimating bacterial species and could be used in the future to examine the correlation between oral flora and health status. Despite this, differences in the efficiency of DNA extraction for various bacterial species were observed among the three methods. Based on these findings, there is no "gold standard" for DNA extraction. In future, we suggest that the DNA extraction method should be selected on a case-by-case basis considering the aims and specimens of the study.

LIDAR Point Cloud Data Extraction and Establishment of 3D Modeling of Buildings

NASA Astrophysics Data System (ADS)

Zhang, Yujuan; Li, Xiuhai; Wang, Qiang; Liu, Jiang; Liang, Xin; Li, Dan; Ni, Chundi; Liu, Yan

2018-01-01

This paper takes the method of Shepard’s to deal with the original LIDAR point clouds data, and generate regular grid data DSM, filters the ground point cloud and non ground point cloud through double least square method, and obtains the rules of DSM. By using region growing method for the segmentation of DSM rules, the removal of non building point cloud, obtaining the building point cloud information. Uses the Canny operator to extract the image segmentation is needed after the edges of the building, uses Hough transform line detection to extract the edges of buildings rules of operation based on the smooth and uniform. At last, uses E3De3 software to establish the 3D model of buildings.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy.

PubMed

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-01-18

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in cellular media due to strong cross-talk between energetically separated detection channels.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy

NASA Astrophysics Data System (ADS)

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-03-01

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in cellular media due to strong cross-talk between energetically separated detection channels. Dedicated to Professor Kankan Bhattacharyya.

Machine Learning Classification Combining Multiple Features of A Hyper-Network of fMRI Data in Alzheimer's Disease

PubMed Central

Guo, Hao; Zhang, Fan; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

Exploring functional interactions among various brain regions is helpful for understanding the pathological underpinnings of neurological disorders. Brain networks provide an important representation of those functional interactions, and thus are widely applied in the diagnosis and classification of neurodegenerative diseases. Many mental disorders involve a sharp decline in cognitive ability as a major symptom, which can be caused by abnormal connectivity patterns among several brain regions. However, conventional functional connectivity networks are usually constructed based on pairwise correlations among different brain regions. This approach ignores higher-order relationships, and cannot effectively characterize the high-order interactions of many brain regions working together. Recent neuroscience research suggests that higher-order relationships between brain regions are important for brain network analysis. Hyper-networks have been proposed that can effectively represent the interactions among brain regions. However, this method extracts the local properties of brain regions as features, but ignores the global topology information, which affects the evaluation of network topology and reduces the performance of the classifier. This problem can be compensated by a subgraph feature-based method, but it is not sensitive to change in a single brain region. Considering that both of these feature extraction methods result in the loss of information, we propose a novel machine learning classification method that combines multiple features of a hyper-network based on functional magnetic resonance imaging in Alzheimer's disease. The method combines the brain region features and subgraph features, and then uses a multi-kernel SVM for classification. This retains not only the global topological information, but also the sensitivity to change in a single brain region. To certify the proposed method, 28 normal control subjects and 38 Alzheimer's disease patients were selected to participate in an experiment. The proposed method achieved satisfactory classification accuracy, with an average of 91.60%. The abnormal brain regions included the bilateral precuneus, right parahippocampal gyrus\\hippocampus, right posterior cingulate gyrus, and other regions that are known to be important in Alzheimer's disease. Machine learning classification combining multiple features of a hyper-network of functional magnetic resonance imaging data in Alzheimer's disease obtains better classification performance. PMID:29209156

DSA Image Blood Vessel Skeleton Extraction Based on Anti-concentration Diffusion and Level Set Method

NASA Astrophysics Data System (ADS)

Xu, Jing; Wu, Jian; Feng, Daming; Cui, Zhiming

Serious types of vascular diseases such as carotid stenosis, aneurysm and vascular malformation may lead to brain stroke, which are the third leading cause of death and the number one cause of disability. In the clinical practice of diagnosis and treatment of cerebral vascular diseases, how to do effective detection and description of the vascular structure of two-dimensional angiography sequence image that is blood vessel skeleton extraction has been a difficult study for a long time. This paper mainly discussed two-dimensional image of blood vessel skeleton extraction based on the level set method, first do the preprocessing to the DSA image, namely uses anti-concentration diffusion model for the effective enhancement and uses improved Otsu local threshold segmentation technology based on regional division for the image binarization, then vascular skeleton extraction based on GMM (Group marching method) with fast sweeping theory was actualized. Experiments show that our approach not only improved the time complexity, but also make a good extraction results.

Analysis of Fundus Fluorescein Angiogram Based on the Hessian Matrix of Directional Curvelet Sub-bands and Distance Regularized Level Set Evolution.

PubMed

Soltanipour, Asieh; Sadri, Saeed; Rabbani, Hossein; Akhlaghi, Mohammad Reza

2015-01-01

This paper presents a new procedure for automatic extraction of the blood vessels and optic disk (OD) in fundus fluorescein angiogram (FFA). In order to extract blood vessel centerlines, the algorithm of vessel extraction starts with the analysis of directional images resulting from sub-bands of fast discrete curvelet transform (FDCT) in the similar directions and different scales. For this purpose, each directional image is processed by using information of the first order derivative and eigenvalues obtained from the Hessian matrix. The final vessel segmentation is obtained using a simple region growing algorithm iteratively, which merges centerline images with the contents of images resulting from modified top-hat transform followed by bit plane slicing. After extracting blood vessels from FFA image, candidates regions for OD are enhanced by removing blood vessels from the FFA image, using multi-structure elements morphology, and modification of FDCT coefficients. Then, canny edge detector and Hough transform are applied to the reconstructed image to extract the boundary of candidate regions. At the next step, the information of the main arc of the retinal vessels surrounding the OD region is used to extract the actual location of the OD. Finally, the OD boundary is detected by applying distance regularized level set evolution. The proposed method was tested on the FFA images from angiography unit of Isfahan Feiz Hospital, containing 70 FFA images from different diabetic retinopathy stages. The experimental results show the accuracy more than 93% for vessel segmentation and more than 87% for OD boundary extraction.

Analysis of Fundus Fluorescein Angiogram Based on the Hessian Matrix of Directional Curvelet Sub-bands and Distance Regularized Level Set Evolution

PubMed Central

Soltanipour, Asieh; Sadri, Saeed; Rabbani, Hossein; Akhlaghi, Mohammad Reza

2015-01-01

This paper presents a new procedure for automatic extraction of the blood vessels and optic disk (OD) in fundus fluorescein angiogram (FFA). In order to extract blood vessel centerlines, the algorithm of vessel extraction starts with the analysis of directional images resulting from sub-bands of fast discrete curvelet transform (FDCT) in the similar directions and different scales. For this purpose, each directional image is processed by using information of the first order derivative and eigenvalues obtained from the Hessian matrix. The final vessel segmentation is obtained using a simple region growing algorithm iteratively, which merges centerline images with the contents of images resulting from modified top-hat transform followed by bit plane slicing. After extracting blood vessels from FFA image, candidates regions for OD are enhanced by removing blood vessels from the FFA image, using multi-structure elements morphology, and modification of FDCT coefficients. Then, canny edge detector and Hough transform are applied to the reconstructed image to extract the boundary of candidate regions. At the next step, the information of the main arc of the retinal vessels surrounding the OD region is used to extract the actual location of the OD. Finally, the OD boundary is detected by applying distance regularized level set evolution. The proposed method was tested on the FFA images from angiography unit of Isfahan Feiz Hospital, containing 70 FFA images from different diabetic retinopathy stages. The experimental results show the accuracy more than 93% for vessel segmentation and more than 87% for OD boundary extraction. PMID:26284170

Production of N.sup.+ ions from a multicusp ion beam apparatus

DOEpatents

Leung, Ka-Ngo; Kunkel, Wulf B.; Walther, Steven R.

1993-01-01

A method of generating a high purity (at least 98%) N.sup.+ ion beam using a multicusp ion source (10) having a chamber (11) formed by a cylindrical chamber wall (12) surrounded by a plurality of magnets (13), a filament (57) centrally disposed in said chamber, a plasma electrode (36) having an extraction orifice (41) at one end of the chamber, a magnetic filter having two parallel magnets (21, 22) spaced from said plasma electrode (36) and dividing the chamber (11) into arc discharge and extraction regions. The method includes ionizing nitrogen gas in the arc discharge region of the chamber (11), maintaining the chamber wall (12) at a positive voltage relative to the filament (57) and at a magnitude for an optimum percentage of N.sup.+ ions in the extracted ion beams, disposing a hot liner (45) within the chamber and near the chamber wall (12) to limit recombination of N.sup.+ ions into the N.sub.2.sup.+ ions, spacing the magnets (21, 22) of the magnetic filter from each other for optimum percentage of N.sup.3 ions in the extracted ion beams, and maintaining a relatively low pressure downstream of the extraction orifice and of a magnitude (preferably within the range of 3-8.times.10.sup.-4 torr) for an optimum percentage of N.sup.+ ions in the extracted ion beam.

Single-trial event-related potential extraction through one-unit ICA-with-reference

NASA Astrophysics Data System (ADS)

Lih Lee, Wee; Tan, Tele; Falkmer, Torbjörn; Leung, Yee Hong

2016-12-01

Objective. In recent years, ICA has been one of the more popular methods for extracting event-related potential (ERP) at the single-trial level. It is a blind source separation technique that allows the extraction of an ERP without making strong assumptions on the temporal and spatial characteristics of an ERP. However, the problem with traditional ICA is that the extraction is not direct and is time-consuming due to the need for source selection processing. In this paper, the application of an one-unit ICA-with-Reference (ICA-R), a constrained ICA method, is proposed. Approach. In cases where the time-region of the desired ERP is known a priori, this time information is utilized to generate a reference signal, which is then used for guiding the one-unit ICA-R to extract the source signal of the desired ERP directly. Main results. Our results showed that, as compared to traditional ICA, ICA-R is a more effective method for analysing ERP because it avoids manual source selection and it requires less computation thus resulting in faster ERP extraction. Significance. In addition to that, since the method is automated, it reduces the risks of any subjective bias in the ERP analysis. It is also a potential tool for extracting the ERP in online application.

Single-trial event-related potential extraction through one-unit ICA-with-reference.

PubMed

Lee, Wee Lih; Tan, Tele; Falkmer, Torbjörn; Leung, Yee Hong

2016-12-01

In recent years, ICA has been one of the more popular methods for extracting event-related potential (ERP) at the single-trial level. It is a blind source separation technique that allows the extraction of an ERP without making strong assumptions on the temporal and spatial characteristics of an ERP. However, the problem with traditional ICA is that the extraction is not direct and is time-consuming due to the need for source selection processing. In this paper, the application of an one-unit ICA-with-Reference (ICA-R), a constrained ICA method, is proposed. In cases where the time-region of the desired ERP is known a priori, this time information is utilized to generate a reference signal, which is then used for guiding the one-unit ICA-R to extract the source signal of the desired ERP directly. Our results showed that, as compared to traditional ICA, ICA-R is a more effective method for analysing ERP because it avoids manual source selection and it requires less computation thus resulting in faster ERP extraction. In addition to that, since the method is automated, it reduces the risks of any subjective bias in the ERP analysis. It is also a potential tool for extracting the ERP in online application.

A dual growing method for the automatic extraction of individual trees from mobile laser scanning data

NASA Astrophysics Data System (ADS)

Li, Lin; Li, Dalin; Zhu, Haihong; Li, You

2016-10-01

Street trees interlaced with other objects in cluttered point clouds of urban scenes inhibit the automatic extraction of individual trees. This paper proposes a method for the automatic extraction of individual trees from mobile laser scanning data, according to the general constitution of trees. Two components of each individual tree - a trunk and a crown can be extracted by the dual growing method. This method consists of coarse classification, through which most of artifacts are removed; the automatic selection of appropriate seeds for individual trees, by which the common manual initial setting is avoided; a dual growing process that separates one tree from others by circumscribing a trunk in an adaptive growing radius and segmenting a crown in constrained growing regions; and a refining process that draws a singular trunk from the interlaced other objects. The method is verified by two datasets with over 98% completeness and over 96% correctness. The low mean absolute percentage errors in capturing the morphological parameters of individual trees indicate that this method can output individual trees with high precision.

An Effective Palmprint Recognition Approach for Visible and Multispectral Sensor Images

PubMed Central

Sammouda, Rachid; Al-Salman, Abdul Malik; Alsanad, Ahmed

2018-01-01

Among several palmprint feature extraction methods the HOG-based method is attractive and performs well against changes in illumination and shadowing of palmprint images. However, it still lacks the robustness to extract the palmprint features at different rotation angles. To solve this problem, this paper presents a hybrid feature extraction method, named HOG-SGF that combines the histogram of oriented gradients (HOG) with a steerable Gaussian filter (SGF) to develop an effective palmprint recognition approach. The approach starts by processing all palmprint images by David Zhang’s method to segment only the region of interests. Next, we extracted palmprint features based on the hybrid HOG-SGF feature extraction method. Then, an optimized auto-encoder (AE) was utilized to reduce the dimensionality of the extracted features. Finally, a fast and robust regularized extreme learning machine (RELM) was applied for the classification task. In the evaluation phase of the proposed approach, a number of experiments were conducted on three publicly available palmprint databases, namely MS-PolyU of multispectral palmprint images and CASIA and Tongji of contactless palmprint images. Experimentally, the results reveal that the proposed approach outperforms the existing state-of-the-art approaches even when a small number of training samples are used. PMID:29762519

Semi-automated segmentation of solid and GGO nodules in lung CT images using vessel-likelihood derived from local foreground structure

NASA Astrophysics Data System (ADS)

Yaguchi, Atsushi; Okazaki, Tomoya; Takeguchi, Tomoyuki; Matsumoto, Sumiaki; Ohno, Yoshiharu; Aoyagi, Kota; Yamagata, Hitoshi

2015-03-01

Reflecting global interest in lung cancer screening, considerable attention has been paid to automatic segmentation and volumetric measurement of lung nodules on CT. Ground glass opacity (GGO) nodules deserve special consideration in this context, since it has been reported that they are more likely to be malignant than solid nodules. However, due to relatively low contrast and indistinct boundaries of GGO nodules, segmentation is more difficult for GGO nodules compared with solid nodules. To overcome this difficulty, we propose a method for accurately segmenting not only solid nodules but also GGO nodules without prior information about nodule types. First, the histogram of CT values in pre-extracted lung regions is modeled by a Gaussian mixture model and a threshold value for including high-attenuation regions is computed. Second, after setting up a region of interest around the nodule seed point, foreground regions are extracted by using the threshold and quick-shift-based mode seeking. Finally, for separating vessels from the nodule, a vessel-likelihood map derived from elongatedness of foreground regions is computed, and a region growing scheme starting from the seed point is applied to the map with the aid of fast marching method. Experimental results using an anthropomorphic chest phantom showed that our method yielded generally lower volumetric measurement errors for both solid and GGO nodules compared with other methods reported in preceding studies conducted using similar technical settings. Also, our method allowed reasonable segmentation of GGO nodules in low-dose images and could be applied to clinical CT images including part-solid nodules.

Method for Extraction and Multielement Analysis of Hypogymnia Physodes Samples from the Athabasca Oil Sands Region

EPA Science Inventory

A microwave-assisted digestion technique followed by ICPMS (inductively coupled plasma-mass spectrometry) analysis was used to measure concentrations of 43 elements in Hypogymnia physodes samples collected in the Athabasca Oil Sands Region (AOSR) of northern Alberta, Canad...

Fusion of monocular cues to detect man-made structures in aerial imagery

NASA Technical Reports Server (NTRS)

Shufelt, Jefferey; Mckeown, David M.

1991-01-01

The extraction of buildings from aerial imagery is a complex problem for automated computer vision. It requires locating regions in a scene that possess properties distinguishing them as man-made objects as opposed to naturally occurring terrain features. It is reasonable to assume that no single detection method can correctly delineate or verify buildings in every scene. A cooperative-methods paradigm is useful in approaching the building extraction problem. Using this paradigm, each extraction technique provides information which can be added or assimilated into an overall interpretation of the scene. Thus, the main objective is to explore the development of computer vision system that integrates the results of various scene analysis techniques into an accurate and robust interpretation of the underlying three dimensional scene. The problem of building hypothesis fusion in aerial imagery is discussed. Building extraction techniques are briefly surveyed, including four building extraction, verification, and clustering systems. A method for fusing the symbolic data generated by these systems is described, and applied to monocular image and stereo image data sets. Evaluation methods for the fusion results are described, and the fusion results are analyzed using these methods.

Extracting a Purely Non-rigid Deformation Field of a Single Structure

NASA Astrophysics Data System (ADS)

Demirci, Stefanie; Manstad-Hulaas, Frode; Navab, Nassir

During endovascular aortic repair (EVAR) treatment, the aortic shape is subject to severe deformation that is imposed by medical instruments such as guide wires, catheters, and the stent graft. The problem definition of deformable registration of images covering the entire abdominal region, however, is highly ill-posed. We present a new method for extracting the deformation of an aneurysmatic aorta. The outline of the procedure includes initial rigid alignment of two abdominal scans, segmentation of abdominal vessel trees, and automatic reduction of their centerline structures to one specified region of interest around the aorta. Our non-rigid registration procedure then only computes local non-rigid deformation and leaves out all remaining global rigid transformations. In order to evaluate our method, experiments for the extraction of aortic deformation fields are conducted on 15 patient datasets from endovascular aortic repair (EVAR) treatment. A visual assessment of the registration results were performed by two vascular surgeons and one interventional radiologist who are all experts in EVAR procedures.

Comparison of results from simple expressions for MOSFET parameter extraction

NASA Technical Reports Server (NTRS)

Buehler, M. G.; Lin, Y.-S.

1988-01-01

In this paper results are compared from a parameter extraction procedure applied to the linear, saturation, and subthreshold regions for enhancement-mode MOSFETs fabricated in a 3-micron CMOS process. The results indicate that the extracted parameters differ significantly depending on the extraction algorithm and the distribution of I-V data points. It was observed that KP values vary by 30 percent, VT values differ by 50 mV, and Delta L values differ by 1 micron. Thus for acceptance of wafers from foundries and for modeling purposes, the extraction method and data point distribution must be specified. In this paper measurement and extraction procedures that will allow a consistent evaluation of measured parameters are discussed.

Chemical Composition and Biological Activity of Extracts Obtained by Supercritical Extraction and Ethanolic Extraction of Brown, Green and Red Propolis Derived from Different Geographic Regions in Brazil

PubMed Central

Machado, Bruna Aparecida Souza; Silva, Rejane Pina Dantas; Barreto, Gabriele de Abreu; Costa, Samantha Serra; da Silva, Danielle Figuerêdo; Brandão, Hugo Neves; da Rocha, José Luiz Carneiro; Dellagostin, Odir Antônio; Henriques, João Antônio Pegas; Umsza-Guez, Marcelo Andres; Padilha, Francine Ferreira

2016-01-01

The variations in the chemical composition, and consequently, on the biological activity of the propolis, are associated with its type and geographic origin. Considering this fact, this study evaluated propolis extracts obtained by supercritical extraction (SCO2) and ethanolic extraction (EtOH), in eight samples of different types of propolis (red, green and brown), collected from different regions in Brazil. The content of phenolic compounds, flavonoids, in vitro antioxidant activity (DPPH and ABTS), Artepillin C, p-coumaric acid and antimicrobial activity against two bacteria were determined for all extracts. For the EtOH extracts, the anti-proliferative activity regarding the cell lines of B16F10, were also evaluated. Amongst the samples evaluated, the red propolis from the Brazilian Northeast (states of Sergipe and Alagoas) showed the higher biological potential, as well as the larger content of antioxidant compounds. The best results were shown for the extracts obtained through the conventional extraction method (EtOH). However, the highest concentrations of Artepillin C and p-coumaric acid were identified in the extracts from SCO2, indicating a higher selectivity for the extraction of these compounds. It was verified that the composition and biological activity of the Brazilian propolis vary significantly, depending on the type of sample and geographical area of collection. PMID:26745799

A modular method for the extraction of DNA and RNA, and the separation of DNA pools from diverse environmental sample types

PubMed Central

Lever, Mark A.; Torti, Andrea; Eickenbusch, Philip; Michaud, Alexander B.; Šantl-Temkiv, Tina; Jørgensen, Bo Barker

2015-01-01

A method for the extraction of nucleic acids from a wide range of environmental samples was developed. This method consists of several modules, which can be individually modified to maximize yields in extractions of DNA and RNA or separations of DNA pools. Modules were designed based on elaborate tests, in which permutations of all nucleic acid extraction steps were compared. The final modular protocol is suitable for extractions from igneous rock, air, water, and sediments. Sediments range from high-biomass, organic rich coastal samples to samples from the most oligotrophic region of the world's oceans and the deepest borehole ever studied by scientific ocean drilling. Extraction yields of DNA and RNA are higher than with widely used commercial kits, indicating an advantage to optimizing extraction procedures to match specific sample characteristics. The ability to separate soluble extracellular DNA pools without cell lysis from intracellular and particle-complexed DNA pools may enable new insights into the cycling and preservation of DNA in environmental samples in the future. A general protocol is outlined, along with recommendations for optimizing this general protocol for specific sample types and research goals. PMID:26042110

Improving the performance of lesion-based computer-aided detection schemes of breast masses using a case-based adaptive cueing method

NASA Astrophysics Data System (ADS)

Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Qian, Wei; Zheng, Bin

2016-03-01

Current commercialized CAD schemes have high false-positive (FP) detection rates and also have high correlations in positive lesion detection with radiologists. Thus, we recently investigated a new approach to improve the efficacy of applying CAD to assist radiologists in reading and interpreting screening mammograms. Namely, we developed a new global feature based CAD approach/scheme that can cue the warning sign on the cases with high risk of being positive. In this study, we investigate the possibility of fusing global feature or case-based scores with the local or lesion-based CAD scores using an adaptive cueing method. We hypothesize that the information from the global feature extraction (features extracted from the whole breast regions) are different from and can provide supplementary information to the locally-extracted features (computed from the segmented lesion regions only). On a large and diverse full-field digital mammography (FFDM) testing dataset with 785 cases (347 negative and 438 cancer cases with masses only), we ran our lesion-based and case-based CAD schemes "as is" on the whole dataset. To assess the supplementary information provided by the global features, we used an adaptive cueing method to adaptively adjust the original CAD-generated detection scores (Sorg) of a detected suspicious mass region based on the computed case-based score (Scase) of the case associated with this detected region. Using the adaptive cueing method, better sensitivity results were obtained at lower FP rates (<= 1 FP per image). Namely, increases of sensitivities (in the FROC curves) of up to 6.7% and 8.2% were obtained for the ROI and Case-based results, respectively.

Case study: using a nondestructive DNA extraction method to generate mtDNA sequences from historical chimpanzee specimens.

PubMed

Mohandesan, Elmira; Prost, Stefan; Hofreiter, Michael

2012-01-01

A major challenge for ancient DNA (aDNA) studies using museum specimens is that sampling procedures usually involve at least the partial destruction of each specimen used, such as the removal of skin, pieces of bone, or a tooth. Recently, a nondestructive DNA extraction method was developed for the extraction of amplifiable DNA fragments from museum specimens without appreciable damage to the specimen. Here, we examine the utility of this method by attempting DNA extractions from historic (older than 70 years) chimpanzee specimens. Using this method, we PCR-amplified part of the mitochondrial HVR-I region from 65% (56/86) of the specimens from which we attempted DNA extraction. However, we found a high incidence of multiple sequences in individual samples, suggesting substantial cross-contamination among samples, most likely originating from storage and handling in the museums. Consequently, reproducible sequences could be reconstructed from only 79% (44/56) of the successfully extracted samples, even after multiple extractions and amplifications. This resulted in an overall success rate of just over half (44/86 of samples, or 51% success), from which 39 distinct HVR-I haplotypes were recovered. We found a high incidence of C to T changes, arguing for both low concentrations of and substantial damage to the endogenous DNA. This chapter highlights both the potential and the limitations of nondestructive DNA extraction from museum specimens.

Mesh-free based variational level set evolution for breast region segmentation and abnormality detection using mammograms.

PubMed

Kashyap, Kanchan L; Bajpai, Manish K; Khanna, Pritee; Giakos, George

2018-01-01

Automatic segmentation of abnormal region is a crucial task in computer-aided detection system using mammograms. In this work, an automatic abnormality detection algorithm using mammographic images is proposed. In the preprocessing step, partial differential equation-based variational level set method is used for breast region extraction. The evolution of the level set method is done by applying mesh-free-based radial basis function (RBF). The limitation of mesh-based approach is removed by using mesh-free-based RBF method. The evolution of variational level set function is also done by mesh-based finite difference method for comparison purpose. Unsharp masking and median filtering is used for mammogram enhancement. Suspicious abnormal regions are segmented by applying fuzzy c-means clustering. Texture features are extracted from the segmented suspicious regions by computing local binary pattern and dominated rotated local binary pattern (DRLBP). Finally, suspicious regions are classified as normal or abnormal regions by means of support vector machine with linear, multilayer perceptron, radial basis, and polynomial kernel function. The algorithm is validated on 322 sample mammograms of mammographic image analysis society (MIAS) and 500 mammograms from digital database for screening mammography (DDSM) datasets. Proficiency of the algorithm is quantified by using sensitivity, specificity, and accuracy. The highest sensitivity, specificity, and accuracy of 93.96%, 95.01%, and 94.48%, respectively, are obtained on MIAS dataset using DRLBP feature with RBF kernel function. Whereas, the highest 92.31% sensitivity, 98.45% specificity, and 96.21% accuracy are achieved on DDSM dataset using DRLBP feature with RBF kernel function. Copyright © 2017 John Wiley & Sons, Ltd.

A comparison of the compositional differences between humic fractions isolated by the IHSS and exhaustive extraction procedures

NASA Astrophysics Data System (ADS)

Chang, R. R.; Mylotte, R.; Hayes, M. H. B.; Mclnerney, R.; Tzou, Y. M.

2014-03-01

Humic substances (HSs), consisting, on the basis of solubilities in aqueous acid and basic media, of humic acids (HAs), fulvic acids (FAs), and humin (Hu), are the major components of soil organic matter (SOM). Most studies of soil/natural organic matter (SOM/NOM) have been carried out on extracts of soils in dilute sodium hydroxide solutions, the solvent used to extract the Standards of the International Humic Substances Society (IHSS). However, Hu, the major component in the classical definition of HSs, is insoluble in aqueous base and is not isolated by the traditional IHSS method. Recently, a sequential exhaustive extraction (SEE) process has been shown to be capable of isolating and separating the major components of the classically defined HSs from the soils of the temperate and tropical regions. The SEE system was used in the present study to isolate the HA/FA and Hu fractions from a subtropical volcanic Taiwanese soil. Chemical and compositional properties of these extracts were then compared with similarly obtained isolates from soils from the different climatic regions. Increases in the aliphatic relative to aromatic carbon contents were observed for both the HA and FA fractions when the pH values of the extraction media were increased. HAs and FAs isolated using the SEE method have spectroscopic profiles similar to those from the IHSS isolate; however, the cumulative extraction efficiency (%) of the SEE method (65 %) for the volcanic soil was much higher than for the traditional IHSS method (33 %). When the residual volcanic soil, following extractions once, three, and eight times with 0.1 M NaOH were then extracted with dimethyl sulphoxide (DMSO) plus concentrated sulphuric acid (the final solvent in the SEE sequence) it was seen that the content of crystalline polymethylene hydrocarbon (33 ppm 13C-NMR resonance in the Hu (or DMSO/acid)) extract increased relative to the amorphous methylene (30 ppm). That highlights the difficulty in dissolving the more highly ordered hydrocarbon structures that would be expected to have closer associations with the mineral colloids. Although the SEE procedure isolated all of the HAs and FAs from the Yangmingshan soil, extractability of the Hu from the volcanic soil in the DMSO/acid solvent was low (21 %), and contrasted with the much higher yields from temperate and tropical regions. The decreased Hu extraction may arise from its associations with the extensive iron and aluminium hydroxide mineral colloids in the soil. The Hu from this sub-tropical soil was different from the Hus isolated from other soil types, indicating the need to isolate and characterise these recalcitrant organic material in order to understand the organic carbon components in soils in greater detail. Such results would indicate that more attention should be given to mineral colloids in soils, and to the organo/mineral associations that will have an important role in the stabilities of OM in the soil environment.

Using the Landsat 7 enhanced thematic mapper tasseled cap transformation to extract shoreline

USGS Publications Warehouse

Scott, J.W.

2003-01-01

A semiautomated method for objectively interpreting and extracting the land-water interface has been devised and used successfully to generate multiple shoreline data for the test States of Louisiana and Delaware. The method is based on the application of tasseled cap transformation coefficients derived by the EROS Data Center for Landsat 7 Enhanced Thematic Mapper Data, and is used in conjunction with ERDAS Imagine software. Shoreline data obtained using this method are cost effective compared with conventional mapping methods for State, regional, and national coastline applications. Attempts to attribute vector shoreline data with orthometric elevation values derived from tide observation stations, however, proved unsuccessful.

Near-infrared image formation and processing for the extraction of hand veins

NASA Astrophysics Data System (ADS)

Bouzida, Nabila; Hakim Bendada, Abdel; Maldague, Xavier P.

2010-10-01

The main objective of this work is to extract the hand vein network using a non-invasive technique in the near-infrared region (NIR). The visualization of the veins is based on a relevant feature of the blood in relation with certain wavelengths of the electromagnetic spectrum. In the present paper, we first introduce the image formation in the NIR spectral band. Then, the acquisition system will be presented as well as the method used for the image processing in order to extract the vein signature. Extractions of this pattern on the finger, on the wrist and on the dorsal hand are achieved after exposing the hand to an optical stimulation by reflection or transmission of light. We present meaningful results of the extracted vein pattern demonstrating the utility of the method for a clinical application like the diagnosis of vein disease, of primitive varicose vein and also for applications in vein biometrics.

A novel method of genomic DNA extraction for Cactaceae1

PubMed Central

Fehlberg, Shannon D.; Allen, Jessica M.; Church, Kathleen

2013-01-01

• Premise of the study: Genetic studies of Cactaceae can at times be impeded by difficult sampling logistics and/or high mucilage content in tissues. Simplifying sampling and DNA isolation through the use of cactus spines has not previously been investigated. • Methods and Results: Several protocols for extracting DNA from spines were tested and modified to maximize yield, amplification, and sequencing. Sampling of and extraction from spines resulted in a simplified protocol overall and complete avoidance of mucilage as compared to typical tissue extractions. Sequences from one nuclear and three plastid regions were obtained across eight genera and 20 species of cacti using DNA extracted from spines. • Conclusions: Genomic DNA useful for amplification and sequencing can be obtained from cactus spines. The protocols described here are valuable for any cactus species, but are particularly useful for investigators interested in sampling living collections, extensive field sampling, and/or conservation genetic studies. PMID:25202521

Feature Extraction and Selection Strategies for Automated Target Recognition

NASA Technical Reports Server (NTRS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Bioactive molecules in Kalanchoe pinnata leaves: extraction, purification, and identification.

PubMed

El Abdellaoui, Saïda; Destandau, Emilie; Toribio, Alix; Elfakir, Claire; Lafosse, Michel; Renimel, Isabelle; André, Patrice; Cancellieri, Perrine; Landemarre, Ludovic

2010-10-01

Kalanchoe pinnata (Lam.) Pers. (syn. Bryophyllum pinnatum; family Crassulaceae) is a popular plant used in traditional medicine in many temperate regions of the world and particularly in South America. In Guyana, the leaves are traditionally used as an anti-inflammatory and antiseptic to treat coughs, ulcers, and sores. The purpose of this study was to implement a method for targeting and identifying molecules with antimicrobial activity, which could replace chemical preservatives in cosmetic applications. The leaves were extracted by a method based on pressurized liquid extraction (PLE), using different solvents. A study of antimicrobial activity and cytotoxicity tests were performed to select the most interesting extract. To isolate one or more active molecules, the selected crude extract was fractionated by centrifugal partition chromatography (CPC) and then antimicrobial activity and cytotoxicity of each fraction were tested under the same procedure. The last step consisted of identifying the main compounds in the most active fraction by LC-MS/MS.

Blood flow, flow reserve, and glucose utilization in viable and nonviable myocardium in patients with ischemic cardiomyopathy

PubMed Central

Zhang, Xiaoli; Schindler, Thomas H.; Prior, John O.; Sayre, James; Dahlbom, Magnus; Huang, Sung-Cheng

2016-01-01

Purpose The aim of the study was to determine whether glucose uptake in viable myocardium of ischemic cardiomyopathy patients depends on rest myocardial blood flow (MBF) and the residual myocardial flow reserve (MFR). Methods Thirty-six patients with ischemic cardiomyopathy (left ventricular ejection fraction 25±10 %) were studied with 13N-ammonia and 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET). Twenty age-matched normals served as controls. Regional MBF was determined at rest and during dipyridamole hyperemia and regional FDG extraction was estimated from regional FDG to 13N-ammonia activity ratios. Results Rest MBF was reduced in viable (0.42±0.18 ml/min per g) and nonviable regions (0.32±0.09 ml/min per g) relative to remote regions (0.68±0.23 ml/min per g, p<0.001) and to normals (0.63±0.13 ml/min per g). Dipyridamole raised MBFs in controls, remote, viable, and nonviable regions. MBFs at rest (p<0.05) and stress (p<0.05) in viable regions were significantly higher than that in nonviable regions, while MFRs did not differ significantly (p>0.05). Compared to MFR in remote myocardium, MFRs in viable regions were similar (1.39±0.56 vs 1.70±0.45, p>0.05) but were significantly lower in nonviable regions (1.23±0.43, p<0.001). Moreover, the FDG and thus glucose extraction was higher in viable than in remote (1.40±0.14 vs 0.90±0.20, p<0.001) and in nonviable regions (1.13±0.21, p<0.001). The extraction of FDG in viable regions was independent of rest MBF but correlated inversely with MFRs (r=−0.424, p<0.05). No correlation between the FDG extraction and MFR was observed in nonviable regions. Conclusion As in the animal model, decreasing MFRs in viable myocardium are associated with increasing glucose extraction that likely reflects a metabolic adaptation of remodeling hibernating myocytes. PMID:23287994

Comparison of two extraction techniques, solid-phase microextraction versus continuous liquid-liquid extraction/solvent-assisted flavor evaporation, for the analysis of flavor compounds in gueuze lambic beer.

PubMed

Thompson-Witrick, Katherine A; Rouseff, Russell L; Cadawallader, Keith R; Duncan, Susan E; Eigel, William N; Tanko, James M; O'Keefe, Sean F

2015-03-01

Lambic is a beer style that undergoes spontaneous fermentation and is traditionally produced in the Payottenland region of Belgium, a valley on the Senne River west of Brussels. This region appears to have the perfect combination of airborne microorganisms required for lambic's spontaneous fermentation. Gueuze lambic is a substyle of lambic that is made by mixing young (approximately 1 year) and old (approximately 2 to 3 years) lambics with subsequent bottle conditioning. We compared 2 extraction techniques, solid-phase microextraction (SPME) and continuous liquid-liquid extraction/solvent-assisted flavor evaporation (CCLE/SAFE), for the isolation of volatile compounds in commercially produced gueuze lambic beer. Fifty-four volatile compounds were identified and could be divided into acids (14), alcohols (12), aldehydes (3), esters (20), phenols (3), and miscellaneous (2). SPME extracted a total of 40 volatile compounds, whereas CLLE/SAFE extracted 36 volatile compounds. CLLE/SAFE extracted a greater number of acids than SPME, whereas SPME was able to isolate a greater number of esters. Neither extraction technique proved to be clearly superior and both extraction methods can be utilized for the isolation of volatile compounds found in gueuze lambic beer. © 2015 Institute of Food Technologists®

Who Sleeps by Whom Revisited: A Method for Extracting the Moral Goods Implicit in Practice.

ERIC Educational Resources Information Center

Schweder, Richard A; And Others

1995-01-01

Explores the specific family practice of determining which family members share a bed or sleeping space. Discusses ways of extracting the moral principles implicit in the practice of arranging where family members sleep at night. Examines similarities and differences in the preferred moral goods of two culture regions--rural Hindu India and urban…

Extraction of gravitational waves in numerical relativity.

PubMed

Bishop, Nigel T; Rezzolla, Luciano

2016-01-01

A numerical-relativity calculation yields in general a solution of the Einstein equations including also a radiative part, which is in practice computed in a region of finite extent. Since gravitational radiation is properly defined only at null infinity and in an appropriate coordinate system, the accurate estimation of the emitted gravitational waves represents an old and non-trivial problem in numerical relativity. A number of methods have been developed over the years to "extract" the radiative part of the solution from a numerical simulation and these include: quadrupole formulas, gauge-invariant metric perturbations, Weyl scalars, and characteristic extraction. We review and discuss each method, in terms of both its theoretical background as well as its implementation. Finally, we provide a brief comparison of the various methods in terms of their inherent advantages and disadvantages.

a Landmark Extraction Method Associated with Geometric Features and Location Distribution

NASA Astrophysics Data System (ADS)

Zhang, W.; Li, J.; Wang, Y.; Xiao, Y.; Liu, P.; Zhang, S.

2018-04-01

Landmark plays an important role in spatial cognition and spatial knowledge organization. Significance measuring model is the main method of landmark extraction. It is difficult to take account of the spatial distribution pattern of landmarks because that the significance of landmark is built in one-dimensional space. In this paper, we start with the geometric features of the ground object, an extraction method based on the target height, target gap and field of view is proposed. According to the influence region of Voronoi Diagram, the description of target gap is established to the geometric representation of the distribution of adjacent targets. Then, segmentation process of the visual domain of Voronoi K order adjacent is given to set up target view under the multi view; finally, through three kinds of weighted geometric features, the landmarks are identified. Comparative experiments show that this method has a certain coincidence degree with the results of traditional significance measuring model, which verifies the effectiveness and reliability of the method and reduces the complexity of landmark extraction process without losing the reference value of landmark.

Optimizing conditions for the extraction of pigments in cochineals (Dactylopius coccus Costa) using response surface methodology.

PubMed

González, Mónica; Méndez, Jesús; Carnero, Aurelio; Lobo, M Gloria; Afonso, Ana

2002-11-20

A simple method was developed for the extraction and determination of color pigments in cochineals (Dactylopius coccus Costa). The procedure was based on the solvent extraction of pigments in insect samples using methanol:water (65:35, v:v) as extractant. Two-level factorial design was used in order to optimize the solvent extraction parameters: temperature, time, methanol concentration in the extractant mixture, and the number of extractions. The results suggest that the number of extractions is statistically the most significant factor. The separation and determination of the pigments was carried out by high-performance liquid chromatography with UV-visible detection. Because the absorption spectra of different pigments are different in the visible region, it is convenient to use a diode array detector to obtain chromatographic profiles that allow for the characterization of the extracted pigments.

Automated endoscopic navigation and advisory system from medical image

NASA Astrophysics Data System (ADS)

Kwoh, Chee K.; Khan, Gul N.; Gillies, Duncan F.

1999-05-01

In this paper, we present a review of the research conducted by our group to design an automatic endoscope navigation and advisory system. The whole system can be viewed as a two-layer system. The first layer is at the signal level, which consists of the processing that will be performed on a series of images to extract all the identifiable features. The information is purely dependent on what can be extracted from the 'raw' images. At the signal level, the first task is performed by detecting a single dominant feature, lumen. Few methods of identifying the lumen are proposed. The first method used contour extraction. Contours are extracted by edge detection, thresholding and linking. This method required images to be divided into overlapping squares (8 by 8 or 4 by 4) where line segments are extracted by using a Hough transform. Perceptual criteria such as proximity, connectivity, similarity in orientation, contrast and edge pixel intensity, are used to group edges both strong and weak. This approach is called perceptual grouping. The second method is based on a region extraction using split and merge approach using spatial domain data. An n-level (for a 2' by 2' image) quadtree based pyramid structure is constructed to find the most homogenous large dark region, which in most cases corresponds to the lumen. The algorithm constructs the quadtree from the bottom (pixel) level upward, recursively and computes the mean and variance of image regions corresponding to quadtree nodes. On reaching the root, the largest uniform seed region, whose mean corresponds to a lumen is selected that is grown by merging with its neighboring regions. In addition to the use of two- dimensional information in the form of regions and contours, three-dimensional shape can provide additional information that will enhance the system capabilities. Shape or depth information from an image is estimated by various methods. A particular technique suitable for endoscopy is the shape from shading, which is developed to obtain the relative depth of the colon surface in the image by assuming a point light source very close to the camera. If we assume the colon has a shape similar to a tube, then a reasonable approximation of the position of the center of the colon (lumen) will be a function of the direction in which the majority of the normal vectors of shape are pointing. The second layer is the control layer and at this level, a decision model must be built for endoscope navigation and advisory system. The system that we built is the models of probabilistic networks that create a basic, artificial intelligence system for navigation in the colon. We have constructed the probabilistic networks from correlated objective data using the maximum weighted spanning tree algorithm. In the construction of a probabilistic network, it is always assumed that the variables starting from the same parent are conditionally independent. However, this may not hold and will give rise to incorrect inferences. In these cases, we proposed the creation of a hidden node to modify the network topology, which in effect models the dependency of correlated variables, to solve the problem. The conditional probability matrices linking the hidden node to its neighbors are determined using a gradient descent method which minimizing the objective cost function. The error gradients can be treated as updating messages and ca be propagated in any direction throughout any singly connected network to adjust the network parameters. With the above two- level approach, we have been able to build an automated endoscope navigation and advisory system successfully.

Fully Convolutional Network Based Shadow Extraction from GF-2 Imagery

NASA Astrophysics Data System (ADS)

Li, Z.; Cai, G.; Ren, H.

2018-04-01

There are many shadows on the high spatial resolution satellite images, especially in the urban areas. Although shadows on imagery severely affect the information extraction of land cover or land use, they provide auxiliary information for building extraction which is hard to achieve a satisfactory accuracy through image classification itself. This paper focused on the method of building shadow extraction by designing a fully convolutional network and training samples collected from GF-2 satellite imagery in the urban region of Changchun city. By means of spatial filtering and calculation of adjacent relationship along the sunlight direction, the small patches from vegetation or bridges have been eliminated from the preliminary extracted shadows. Finally, the building shadows were separated. The extracted building shadow information from the proposed method in this paper was compared with the results from the traditional object-oriented supervised classification algorihtms. It showed that the deep learning network approach can improve the accuracy to a large extent.

A sensitive continuum analysis method for gamma ray spectra

NASA Technical Reports Server (NTRS)

Thakur, Alakh N.; Arnold, James R.

1993-01-01

In this work we examine ways to improve the sensitivity of the analysis procedure for gamma ray spectra with respect to small differences in the continuum (Compton) spectra. The method developed is applied to analyze gamma ray spectra obtained from planetary mapping by the Mars Observer spacecraft launched in September 1992. Calculated Mars simulation spectra and actual thick target bombardment spectra have been taken as test cases. The principle of the method rests on the extraction of continuum information from Fourier transforms of the spectra. We study how a better estimate of the spectrum from larger regions of the Mars surface will improve the analysis for smaller regions with poorer statistics. Estimation of signal within the continuum is done in the frequency domain which enables efficient and sensitive discrimination of subtle differences between two spectra. The process is compared to other methods for the extraction of information from the continuum. Finally we explore briefly the possible uses of this technique in other applications of continuum spectra.

Quantitative Analysis of First-Pass Contrast-Enhanced Myocardial Perfusion Multidetector CT Using a Patlak Plot Method and Extraction Fraction Correction During Adenosine Stress

NASA Astrophysics Data System (ADS)

Ichihara, Takashi; George, Richard T.; Silva, Caterina; Lima, Joao A. C.; Lardo, Albert C.

2011-02-01

The purpose of this study was to develop a quantitative method for myocardial blood flow (MBF) measurement that can be used to derive accurate myocardial perfusion measurements from dynamic multidetector computed tomography (MDCT) images by using a compartment model for calculating the first-order transfer constant (K1) with correction for the capillary transit extraction fraction (E). Six canine models of left anterior descending (LAD) artery stenosis were prepared and underwent first-pass contrast-enhanced MDCT perfusion imaging during adenosine infusion (0.14-0.21 mg/kg/min). K1 , which is the first-order transfer constant from left ventricular (LV) blood to myocardium, was measured using the Patlak plot method applied to time-attenuation curve data of the LV blood pool and myocardium. The results were compared against microsphere MBF measurements, and the extraction fraction of contrast agent was calculated. K1 is related to the regional MBF as K1=EF, E=(1-exp(-PS/F)), where PS is the permeability-surface area product and F is myocardial flow. Based on the above relationship, a look-up table from K1 to MBF can be generated and Patlak plot-derived K1 values can be converted to the calculated MBF. The calculated MBF and microsphere MBF showed a strong linear association. The extraction fraction in dogs as a function of flow (F) was E=(1-exp(-(0.2532F+0.7871)/F)) . Regional MBF can be measured accurately using the Patlak plot method based on a compartment model and look-up table with extraction fraction correction from K1 to MBF.

Emotion Discrimination Using Spatially Compact Regions of Interest Extracted from Imaging EEG Activity

PubMed Central

Padilla-Buritica, Jorge I.; Martinez-Vargas, Juan D.; Castellanos-Dominguez, German

2016-01-01

Lately, research on computational models of emotion had been getting much attention due to their potential for understanding the mechanisms of emotions and their promising broad range of applications that potentially bridge the gap between human and machine interactions. We propose a new method for emotion classification that relies on features extracted from those active brain areas that are most likely related to emotions. To this end, we carry out the selection of spatially compact regions of interest that are computed using the brain neural activity reconstructed from Electroencephalography data. Throughout this study, we consider three representative feature extraction methods widely applied to emotion detection tasks, including Power spectral density, Wavelet, and Hjorth parameters. Further feature selection is carried out using principal component analysis. For validation purpose, these features are used to feed a support vector machine classifier that is trained under the leave-one-out cross-validation strategy. Obtained results on real affective data show that incorporation of the proposed training method in combination with the enhanced spatial resolution provided by the source estimation allows improving the performed accuracy of discrimination in most of the considered emotions, namely: dominance, valence, and liking. PMID:27489541

Fabric defect detection based on faster R-CNN

NASA Astrophysics Data System (ADS)

Liu, Zhoufeng; Liu, Xianghui; Li, Chunlei; Li, Bicao; Wang, Baorui

2018-04-01

In order to effectively detect the defects for fabric image with complex texture, this paper proposed a novel detection algorithm based on an end-to-end convolutional neural network. First, the proposal regions are generated by RPN (regional proposal Network). Then, Fast Region-based Convolutional Network method (Fast R-CNN) is adopted to determine whether the proposal regions extracted by RPN is a defect or not. Finally, Soft-NMS (non-maximum suppression) and data augmentation strategies are utilized to improve the detection precision. Experimental results demonstrate that the proposed method can locate the fabric defect region with higher accuracy compared with the state-of- art, and has better adaptability to all kinds of the fabric image.

Can we estimate plasma density in ICP driver through electrical parameters in RF circuit?

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

Bandyopadhyay, M., E-mail: mainak@iter-india.org; Sudhir, Dass, E-mail: dass.sudhir@iter-india.org; Chakraborty, A., E-mail: arunkc@iter-india.org

2015-04-08

To avoid regular maintenance, invasive plasma diagnostics with probes are not included in the inductively coupled plasma (ICP) based ITER Neutral Beam (NB) source design. Even non-invasive probes like optical emission spectroscopic diagnostics are also not included in the present ITER NB design due to overall system design and interface issues. As a result, negative ion beam current through the extraction system in the ITER NB negative ion source is the only measurement which indicates plasma condition inside the ion source. However, beam current not only depends on the plasma condition near the extraction region but also on the perveancemore » condition of the ion extractor system and negative ion stripping. Nevertheless, inductively coupled plasma production region (RF driver region) is placed at distance (∼ 30cm) from the extraction region. Due to that, some uncertainties are expected to be involved if one tries to link beam current with plasma properties inside the RF driver. Plasma characterization in source RF driver region is utmost necessary to maintain the optimum condition for source operation. In this paper, a method of plasma density estimation is described, based on density dependent plasma load calculation.« less

A practical salient region feature based 3D multi-modality registration method for medical images

NASA Astrophysics Data System (ADS)

Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

2006-03-01

We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

[Investigation on pattern of quality control for Chinese materia medica based on famous-region drug and bioassay--the work reference].

PubMed

Yan, Dan; Xiao, Xiaohe

2011-05-01

Selection and standardization of the work reference are the technical issues to be faced with in the bioassay of Chinese materia medica. Taking the bioassay of Coptis chinensis. as an example, the manufacture process of the famous-region drugs extraction was explained from the aspects of original identification, routine examination, component analysis and bioassay. The common technologies were extracted, and the selection and standardization procedures of the work reference for the bioassay of Chinese materia medica were drawn up, so as to provide technical support for constructing a new mode and method of the quality control of Chinese materia medica based on the famous-region drugs and bioassay.

Application of Machine Learning in Urban Greenery Land Cover Extraction

NASA Astrophysics Data System (ADS)

Qiao, X.; Li, L. L.; Li, D.; Gan, Y. L.; Hou, A. Y.

2018-04-01

Urban greenery is a critical part of the modern city and the greenery coverage information is essential for land resource management, environmental monitoring and urban planning. It is a challenging work to extract the urban greenery information from remote sensing image as the trees and grassland are mixed with city built-ups. In this paper, we propose a new automatic pixel-based greenery extraction method using multispectral remote sensing images. The method includes three main steps. First, a small part of the images is manually interpreted to provide prior knowledge. Secondly, a five-layer neural network is trained and optimised with the manual extraction results, which are divided to serve as training samples, verification samples and testing samples. Lastly, the well-trained neural network will be applied to the unlabelled data to perform the greenery extraction. The GF-2 and GJ-1 high resolution multispectral remote sensing images were used to extract greenery coverage information in the built-up areas of city X. It shows a favourable performance in the 619 square kilometers areas. Also, when comparing with the traditional NDVI method, the proposed method gives a more accurate delineation of the greenery region. Due to the advantage of low computational load and high accuracy, it has a great potential for large area greenery auto extraction, which saves a lot of manpower and resources.

On the Detection of Coronal Dimmings and the Extraction of Their Characteristic Properties

NASA Astrophysics Data System (ADS)

Dissauer, K.; Veronig, A. M.; Temmer, M.; Podladchikova, T.; Vanninathan, K.

2018-03-01

Coronal dimmings are distinct phenomena associated with coronal mass ejections (CMEs). The study of coronal dimmings and the extraction of their characteristic parameters help us to obtain additional information regarding CMEs, especially on the initiation and early evolution of Earth-directed CMEs. We present a new approach to detect coronal dimming regions based on a thresholding technique applied on logarithmic base-ratio images. Characteristic dimming parameters describing the dynamics, morphology, magnetic properties, and the brightness of coronal dimming regions are extracted by cumulatively summing newly dimmed pixels over time. It is also demonstrated how core dimming regions are identified as a subset of the overall identified dimming region. We successfully apply our method to two well-observed coronal dimming events. For both events, the core dimming regions are identified and the spatial evolution of the dimming area reveals the expansion of the dimming region around these footpoints. We also show that in the early impulsive phase of the dimming expansion the total unsigned magnetic flux involved in the dimming regions is balanced and that up to 30% of this flux results from the localized core dimming regions. Furthermore, the onset in the profile of the area growth rate is cotemporal with the start of the associated flares and in one case also with the fast rise of the CME, indicating a strong relationship of coronal dimmings with both flares and CMEs.

Lung lobe segmentation based on statistical atlas and graph cuts

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2012-03-01

This paper presents a novel method that can extract lung lobes by utilizing probability atlas and multilabel graph cuts. Information about pulmonary structures plays very important role for decision of the treatment strategy and surgical planning. The human lungs are divided into five anatomical regions, the lung lobes. Precise segmentation and recognition of lung lobes are indispensable tasks in computer aided diagnosis systems and computer aided surgery systems. A lot of methods for lung lobe segmentation are proposed. However, these methods only target the normal cases. Therefore, these methods cannot extract the lung lobes in abnormal cases, such as COPD cases. To extract lung lobes in abnormal cases, this paper propose a lung lobe segmentation method based on probability atlas of lobe location and multilabel graph cuts. The process consists of three components; normalization based on the patient's physique, probability atlas generation, and segmentation based on graph cuts. We apply this method to six cases of chest CT images including COPD cases. Jaccard index was 79.1%.

The Efficiency of Random Forest Method for Shoreline Extraction from LANDSAT-8 and GOKTURK-2 Imageries

NASA Astrophysics Data System (ADS)

Bayram, B.; Erdem, F.; Akpinar, B.; Ince, A. K.; Bozkurt, S.; Catal Reis, H.; Seker, D. Z.

2017-11-01

Coastal monitoring plays a vital role in environmental planning and hazard management related issues. Since shorelines are fundamental data for environment management, disaster management, coastal erosion studies, modelling of sediment transport and coastal morphodynamics, various techniques have been developed to extract shorelines. Random Forest is one of these techniques which is used in this study for shoreline extraction.. This algorithm is a machine learning method based on decision trees. Decision trees analyse classes of training data creates rules for classification. In this study, Terkos region has been chosen for the proposed method within the scope of "TUBITAK Project (Project No: 115Y718) titled "Integration of Unmanned Aerial Vehicles for Sustainable Coastal Zone Monitoring Model - Three-Dimensional Automatic Coastline Extraction and Analysis: Istanbul-Terkos Example". Random Forest algorithm has been implemented to extract the shoreline of the Black Sea where near the lake from LANDSAT-8 and GOKTURK-2 satellite imageries taken in 2015. The MATLAB environment was used for classification. To obtain land and water-body classes, the Random Forest method has been applied to NIR bands of LANDSAT-8 (5th band) and GOKTURK-2 (4th band) imageries. Each image has been digitized manually and shorelines obtained for accuracy assessment. According to accuracy assessment results, Random Forest method is efficient for both medium and high resolution images for shoreline extraction studies.

Region-confined restoration method for motion-blurred star image of the star sensor under dynamic conditions.

PubMed

Ma, Liheng; Bernelli-Zazzera, Franco; Jiang, Guangwen; Wang, Xingshu; Huang, Zongsheng; Qin, Shiqiao

2016-06-10

Under dynamic conditions, the centroiding accuracy of the motion-blurred star image decreases and the number of identified stars reduces, which leads to the degradation of the attitude accuracy of the star sensor. To improve the attitude accuracy, a region-confined restoration method, which concentrates on the noise removal and signal to noise ratio (SNR) improvement of the motion-blurred star images, is proposed for the star sensor under dynamic conditions. A multi-seed-region growing technique with the kinematic recursive model for star image motion is given to find the star image regions and to remove the noise. Subsequently, a restoration strategy is employed in the extracted regions, taking the time consumption and SNR improvement into consideration simultaneously. Simulation results indicate that the region-confined restoration method is effective in removing noise and improving the centroiding accuracy. The identification rate and the average number of identified stars in the experiments verify the advantages of the region-confined restoration method.

Efficient video-equipped fire detection approach for automatic fire alarm systems

NASA Astrophysics Data System (ADS)

Kang, Myeongsu; Tung, Truong Xuan; Kim, Jong-Myon

2013-01-01

This paper proposes an efficient four-stage approach that automatically detects fire using video capabilities. In the first stage, an approximate median method is used to detect video frame regions involving motion. In the second stage, a fuzzy c-means-based clustering algorithm is employed to extract candidate regions of fire from all of the movement-containing regions. In the third stage, a gray level co-occurrence matrix is used to extract texture parameters by tracking red-colored objects in the candidate regions. These texture features are, subsequently, used as inputs of a back-propagation neural network to distinguish between fire and nonfire. Experimental results indicate that the proposed four-stage approach outperforms other fire detection algorithms in terms of consistently increasing the accuracy of fire detection in both indoor and outdoor test videos.

Quantitative extraction of the bedrock exposure rate based on unmanned aerial vehicle data and Landsat-8 OLI image in a karst environment

NASA Astrophysics Data System (ADS)

Wang, Hongyan; Li, Qiangzi; Du, Xin; Zhao, Longcai

2017-12-01

In the karst regions of southwest China, rocky desertification is one of the most serious problems in land degradation. The bedrock exposure rate is an important index to assess the degree of rocky desertification in karst regions. Because of the inherent merits of macro-scale, frequency, efficiency, and synthesis, remote sensing is a promising method to monitor and assess karst rocky desertification on a large scale. However, actual measurement of the bedrock exposure rate is difficult and existing remote-sensing methods cannot directly be exploited to extract the bedrock exposure rate owing to the high complexity and heterogeneity of karst environments. Therefore, using unmanned aerial vehicle (UAV) and Landsat-8 Operational Land Imager (OLI) data for Xingren County, Guizhou Province, quantitative extraction of the bedrock exposure rate based on multi-scale remote-sensing data was developed. Firstly, we used an object-oriented method to carry out accurate classification of UAVimages. From the results of rock extraction, the bedrock exposure rate was calculated at the 30 m grid scale. Parts of the calculated samples were used as training data; other data were used for model validation. Secondly, in each grid the band reflectivity of Landsat-8 OLI data was extracted and a variety of rock and vegetation indexes (e.g., NDVI and SAVI) were calculated. Finally, a network model was established to extract the bedrock exposure rate. The correlation coefficient of the network model was 0.855, that of the validation model was 0.677 and the root mean square error of the validation model was 0.073. This method is valuable for wide-scale estimation of bedrock exposure rate in karst environments. Using the quantitative inversion model, a distribution map of the bedrock exposure rate in Xingren County was obtained.

Analysis of wine volatile profile by purge-and-trap-gas chromatography-mass spectrometry. Application to the analysis of red and white wines from different Spanish regions.

PubMed

Aznar, Margarita; Arroyo, Teresa

2007-09-21

The purge-and-trap extraction method, coupled to a gas chromatograph with mass spectrometry detection, has been applied to the determination of 26 aromatic volatiles in wine. The method was optimized, validated and applied to the analyses of 40 red and white wines from 7 different Spanish regions. Principal components analyses of data showed the correlation between wines of similar origin.

Computer-aided detection of bladder mass within non-contrast-enhanced region of CT Urography (CTU)

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Weizer, Alon; Zhou, Chuan

2016-03-01

We are developing a computer-aided detection system for bladder cancer in CT urography (CTU). We have previously developed methods for detection of bladder masses within the contrast-enhanced region of the bladder. In this study, we investigated methods for detection of bladder masses within the non-contrast enhanced region. The bladder was first segmented using a newly developed deep-learning convolutional neural network in combination with level sets. The non-contrast-enhanced region was separated from the contrast-enhanced region with a maximum-intensityprojection- based method. The non-contrast region was smoothed and a gray level threshold was employed to segment the bladder wall and potential masses. The bladder wall was transformed into a straightened thickness profile, which was analyzed to identify lesion candidates as a prescreening step. The lesion candidates were segmented using our autoinitialized cascaded level set (AI-CALS) segmentation method, and 27 morphological features were extracted for each candidate. Stepwise feature selection with simplex optimization and leave-one-case-out resampling were used for training and validation of a false positive (FP) classifier. In each leave-one-case-out cycle, features were selected from the training cases and a linear discriminant analysis (LDA) classifier was designed to merge the selected features into a single score for classification of the left-out test case. A data set of 33 cases with 42 biopsy-proven lesions in the noncontrast enhanced region was collected. During prescreening, the system obtained 83.3% sensitivity at an average of 2.4 FPs/case. After feature extraction and FP reduction by LDA, the system achieved 81.0% sensitivity at 2.0 FPs/case, and 73.8% sensitivity at 1.5 FPs/case.

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories.

PubMed

Yang, Wei; Ai, Tinghua; Lu, Wei

2018-04-19

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality.

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories

PubMed Central

Yang, Wei

2018-01-01

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality. PMID:29671792

Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

PubMed Central

Lee, Gil-beom; Lee, Myeong-jin; Lee, Woo-Kyung; Park, Joo-heon; Kim, Tae-Hwan

2017-01-01

Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos. PMID:28327515

Learning-based meta-algorithm for MRI brain extraction.

PubMed

Shi, Feng; Wang, Li; Gilmore, John H; Lin, Weili; Shen, Dinggang

2011-01-01

Multiple-segmentation-and-fusion method has been widely used for brain extraction, tissue segmentation, and region of interest (ROI) localization. However, such studies are hindered in practice by their computational complexity, mainly coming from the steps of template selection and template-to-subject nonlinear registration. In this study, we address these two issues and propose a novel learning-based meta-algorithm for MRI brain extraction. Specifically, we first use exemplars to represent the entire template library, and assign the most similar exemplar to the test subject. Second, a meta-algorithm combining two existing brain extraction algorithms (BET and BSE) is proposed to conduct multiple extractions directly on test subject. Effective parameter settings for the meta-algorithm are learned from the training data and propagated to subject through exemplars. We further develop a level-set based fusion method to combine multiple candidate extractions together with a closed smooth surface, for obtaining the final result. Experimental results show that, with only a small portion of subjects for training, the proposed method is able to produce more accurate and robust brain extraction results, at Jaccard Index of 0.956 +/- 0.010 on total 340 subjects under 6-fold cross validation, compared to those by the BET and BSE even using their best parameter combinations.

Automatic segmentation of right ventricle on ultrasound images using sparse matrix transform and level set

NASA Astrophysics Data System (ADS)

Qin, Xulei; Cong, Zhibin; Halig, Luma V.; Fei, Baowei

2013-03-01

An automatic framework is proposed to segment right ventricle on ultrasound images. This method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform (SMT), a training model, and a localized region based level set. First, the sparse matrix transform extracts main motion regions of myocardium as eigenimages by analyzing statistical information of these images. Second, a training model of right ventricle is registered to the extracted eigenimages in order to automatically detect the main location of the right ventricle and the corresponding transform relationship between the training model and the SMT-extracted results in the series. Third, the training model is then adjusted as an adapted initialization for the segmentation of each image in the series. Finally, based on the adapted initializations, a localized region based level set algorithm is applied to segment both epicardial and endocardial boundaries of the right ventricle from the whole series. Experimental results from real subject data validated the performance of the proposed framework in segmenting right ventricle from echocardiography. The mean Dice scores for both epicardial and endocardial boundaries are 89.1%+/-2.3% and 83.6+/-7.3%, respectively. The automatic segmentation method based on sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.

Real-Time Lane Region Detection Using a Combination of Geometrical and Image Features

PubMed Central

Cáceres Hernández, Danilo; Kurnianggoro, Laksono; Filonenko, Alexander; Jo, Kang Hyun

2016-01-01

Over the past few decades, pavement markings have played a key role in intelligent vehicle applications such as guidance, navigation, and control. However, there are still serious issues facing the problem of lane marking detection. For example, problems include excessive processing time and false detection due to similarities in color and edges between traffic signs (channeling lines, stop lines, crosswalk, arrows, etc.). This paper proposes a strategy to extract the lane marking information taking into consideration its features such as color, edge, and width, as well as the vehicle speed. Firstly, defining the region of interest is a critical task to achieve real-time performance. In this sense, the region of interest is dependent on vehicle speed. Secondly, the lane markings are detected by using a hybrid color-edge feature method along with a probabilistic method, based on distance-color dependence and a hierarchical fitting model. Thirdly, the following lane marking information is extracted: the number of lane markings to both sides of the vehicle, the respective fitting model, and the centroid information of the lane. Using these parameters, the region is computed by using a road geometric model. To evaluate the proposed method, a set of consecutive frames was used in order to validate the performance. PMID:27869657

Automated anatomical labeling of bronchial branches extracted from CT datasets based on machine learning and combination optimization and its application to bronchoscope guidance.

PubMed

Mori, Kensaku; Ota, Shunsuke; Deguchi, Daisuke; Kitasaka, Takayuki; Suenaga, Yasuhito; Iwano, Shingo; Hasegawa, Yosihnori; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi

2009-01-01

This paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3D CT images based on machine learning and combination optimization. We also show applications of anatomical labeling on a bronchoscopy guidance system. This paper performs automated labeling by using machine learning and combination optimization. The actual procedure consists of four steps: (a) extraction of tree structures of the bronchus regions extracted from CT images, (b) construction of AdaBoost classifiers, (c) computation of candidate names for all branches by using the classifiers, (d) selection of best combination of anatomical names. We applied the proposed method to 90 cases of 3D CT datasets. The experimental results showed that the proposed method can assign correct anatomical names to 86.9% of the bronchial branches up to the sub-segmental lobe branches. Also, we overlaid the anatomical names of bronchial branches on real bronchoscopic views to guide real bronchoscopy.

Contrast enhancement of subcutaneous blood vessel images by means of visible and near-infrared hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Katrašnik, Jaka; Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2009-02-01

Visualization of subcutaneous veins is very difficult with the naked eye, but important for diagnosis of medical conditions and different medical procedures such as catheter insertion and blood withdrawal. Moreover, recent studies showed that the images of subcutaneous veins could be used for biometric identification. The majority of methods used for enhancing the contrast between the subcutaneous veins and surrounding tissue are based on simple imaging systems utilizing CMOS or CCD cameras with LED illumination capable of acquiring images from the near infrared spectral region, usually near 900 nm. However, such simplified imaging methods cannot exploit the full potential of the spectral information. In this paper, a new highly versatile method for enhancing the contrast of subcutaneous veins based on state-of-the-art high-resolution hyper-spectral imaging system utilizing the spectral region from 550 to 1700 nm is presented. First, a detailed analysis of the contrast between the subcutaneous veins and the surrounding tissue as a function of wavelength, for several different positions on the human arm, was performed in order to extract the spectral regions with the highest contrast. The highest contrast images were acquired at 1100 nm, however, combining the individual images from the extracted spectral regions by the proposed contrast enhancement method resulted in a single image with up to ten-fold better contrast. Therefore, the proposed method has proved to be a useful tool for visualization of subcutaneous veins.

Fusion method of SAR and optical images for urban object extraction

NASA Astrophysics Data System (ADS)

Jia, Yonghong; Blum, Rick S.; Li, Fangfang

2007-11-01

A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

Image analysis for skeletal evaluation of carpal bones

NASA Astrophysics Data System (ADS)

Ko, Chien-Chuan; Mao, Chi-Wu; Lin, Chi-Jen; Sun, Yung-Nien

1995-04-01

The assessment of bone age is an important field to the pediatric radiology. It provides very important information for treatment and prediction of skeletal growth in a developing child. So far, various computerized algorithms for automatically assessing the skeletal growth have been reported. Most of these methods made attempt to analyze the phalangeal growth. The most fundamental step in these automatic measurement methods is the image segmentation that extracts bones from soft-tissue and background. These automatic segmentation methods of hand radiographs can roughly be categorized into two main approaches that are edge and region based methods. This paper presents a region-based carpal-bone segmentation approach. It is organized into four stages: contrast enhancement, moment-preserving thresholding, morphological processing, and region-growing labeling.

A Highly Responsive Silicon Nanowire/Amplifier MOSFET Hybrid Biosensor

DTIC Science & Technology

2015-07-21

biosensor. The insets show a magnified view of the SiNW channel region (W = 55 nm). ( c ) Photograph of the biosensor chip fabricated via a top-down method...of the SiNW FET is 147 mV/decade. (b) VT and ( c ) ISINW at different pH levels; these values were extracted from Fig. 2a. VT was extracted using the...function of pH level in the hybrid biosensor. The extracted current change is 5.5 × 105 (=5.74 decade per pH). ( c ) Transient response of IMOSFET while

Effect of solvent polarity on the extraction of components of pharmaceutical plastic containers.

PubMed

Ahmad, Iqbal; Sabah, Arif; Anwar, Zubair; Arif, Aysha; Arsalan, Adeel; Qadeer, Kiran

2017-01-01

A study of the extraction of polymeric material and dyes from the pharmaceutical plastic containers using various organic solvents was conducted to evaluate the effect of polarity on the extraction process. The plastic containers used included semi-opaque, opaque, transparent and amber colored and the solvent used were acetonitrile, methanol, ethanol, acetone, dichloroethane, chloroform and water. The determination of extractable material was carried out by gravimetric and spectrometric methods. The yield of extractable materials from containers in 60 h was 0.10-1.29% (w/w) and the first-order rate constant (kobs) for the extraction of polymeric material ranged from 0.52-1.50 × 10-3 min -1 and for the dyes 6.43- 6.74 x10-3min-1. The values of (k obs ) were found to be an inverse function of solvent dielectric constant and decreased linearly with the solvent acceptor number. The extractable polymeric materials exhibited absorption in the 200-400 nm region and the dyes in the 300-500nm region. The rates of extraction of polymeric material and dyes from plastic containers were dependent on the solvent dielectric constant. The solvents of low polarity were more effective in the extraction of material indicating that the extracted material were of low polarity or have non-polar character. The dyes were soluble in acetone and chloroform. No plastic material was found to be extracted from the containers in aqueous solution.

Efficient Method for Scalable Registration of Remote Sensing Images

NASA Astrophysics Data System (ADS)

Prouty, R.; LeMoigne, J.; Halem, M.

2017-12-01

The goal of this project is to build a prototype of a resource-efficient pipeline that will provide registration within subpixel accuracy of multitemporal Earth science data. Accurate registration of Earth-science data is imperative to proper data integration and seamless mosaicing of data from multiple times, sensors, and/or observation geometries. Modern registration methods make use of many arithmetic operations and sometimes require complete knowledge of the image domain. As such, while sensors become more advanced and are able to provide higher-resolution data, the memory resources required to properly register these data become prohibitive. The proposed pipeline employs a region of interest extraction algorithm in order to extract image subsets with high local feature density. These image subsets are then used to generate local solutions to the global registration problem. The local solutions are then 'globalized' to determine the deformation model that best solves the registration problem. The region of interest extraction and globalization routines are tested for robustness among the variety of scene-types and spectral locations provided by Earth-observing instruments such as Landsat, MODIS, or ASTER.

Construction of Green Tide Monitoring System and Research on its Key Techniques

NASA Astrophysics Data System (ADS)

Xing, B.; Li, J.; Zhu, H.; Wei, P.; Zhao, Y.

2018-04-01

As a kind of marine natural disaster, Green Tide has been appearing every year along the Qingdao Coast, bringing great loss to this region, since the large-scale bloom in 2008. Therefore, it is of great value to obtain the real time dynamic information about green tide distribution. In this study, methods of optical remote sensing and microwave remote sensing are employed in Green Tide Monitoring Research. A specific remote sensing data processing flow and a green tide information extraction algorithm are designed, according to the optical and microwave data of different characteristics. In the aspect of green tide spatial distribution information extraction, an automatic extraction algorithm of green tide distribution boundaries is designed based on the principle of mathematical morphology dilation/erosion. And key issues in information extraction, including the division of green tide regions, the obtaining of basic distributions, the limitation of distribution boundary, and the elimination of islands, have been solved. The automatic generation of green tide distribution boundaries from the results of remote sensing information extraction is realized. Finally, a green tide monitoring system is built based on IDL/GIS secondary development in the integrated environment of RS and GIS, achieving the integration of RS monitoring and information extraction.

Airborne Infrared and Visible Image Fusion Combined with Region Segmentation

PubMed Central

Zuo, Yujia; Liu, Jinghong; Bai, Guanbing; Wang, Xuan; Sun, Mingchao

2017-01-01

This paper proposes an infrared (IR) and visible image fusion method introducing region segmentation into the dual-tree complex wavelet transform (DTCWT) region. This method should effectively improve both the target indication and scene spectrum features of fusion images, and the target identification and tracking reliability of fusion system, on an airborne photoelectric platform. The method involves segmenting the region in an IR image by significance, and identifying the target region and the background region; then, fusing the low-frequency components in the DTCWT region according to the region segmentation result. For high-frequency components, the region weights need to be assigned by the information richness of region details to conduct fusion based on both weights and adaptive phases, and then introducing a shrinkage function to suppress noise; Finally, the fused low-frequency and high-frequency components are reconstructed to obtain the fusion image. The experimental results show that the proposed method can fully extract complementary information from the source images to obtain a fusion image with good target indication and rich information on scene details. They also give a fusion result superior to existing popular fusion methods, based on eithers subjective or objective evaluation. With good stability and high fusion accuracy, this method can meet the fusion requirements of IR-visible image fusion systems. PMID:28505137

Airborne Infrared and Visible Image Fusion Combined with Region Segmentation.

PubMed

Zuo, Yujia; Liu, Jinghong; Bai, Guanbing; Wang, Xuan; Sun, Mingchao

2017-05-15

This paper proposes an infrared (IR) and visible image fusion method introducing region segmentation into the dual-tree complex wavelet transform (DTCWT) region. This method should effectively improve both the target indication and scene spectrum features of fusion images, and the target identification and tracking reliability of fusion system, on an airborne photoelectric platform. The method involves segmenting the region in an IR image by significance, and identifying the target region and the background region; then, fusing the low-frequency components in the DTCWT region according to the region segmentation result. For high-frequency components, the region weights need to be assigned by the information richness of region details to conduct fusion based on both weights and adaptive phases, and then introducing a shrinkage function to suppress noise; Finally, the fused low-frequency and high-frequency components are reconstructed to obtain the fusion image. The experimental results show that the proposed method can fully extract complementary information from the source images to obtain a fusion image with good target indication and rich information on scene details. They also give a fusion result superior to existing popular fusion methods, based on eithers subjective or objective evaluation. With good stability and high fusion accuracy, this method can meet the fusion requirements of IR-visible image fusion systems.

The United States Army Medical Department Journal, January - March 2009

DTIC Science & Technology

2009-03-01

and performing routine chemistry testing for moisture, protein, fat , and solids. Chemistry methods range from simple extractions for percent fat ...States and abroad. The risk for food and waterborne disease is greatest in regions with fractured public health and veterinary infrastructure, lack of a...surgery during the deployment. Two aural hematoma repairs, an extraction of an abscessed tooth, and a root canal on a fractured canine tooth were

Target matching based on multi-view tracking

NASA Astrophysics Data System (ADS)

Liu, Yahui; Zhou, Changsheng

2011-01-01

A feature matching method is proposed based on Maximally Stable Extremal Regions (MSER) and Scale Invariant Feature Transform (SIFT) to solve the problem of the same target matching in multiple cameras. Target foreground is extracted by using frame difference twice and bounding box which is regarded as target regions is calculated. Extremal regions are got by MSER. After fitted into elliptical regions, those regions will be normalized into unity circles and represented with SIFT descriptors. Initial matching is obtained from the ratio of the closest distance to second distance less than some threshold and outlier points are eliminated in terms of RANSAC. Experimental results indicate the method can reduce computational complexity effectively and is also adapt to affine transformation, rotation, scale and illumination.

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

NASA Astrophysics Data System (ADS)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

Using gradient-based ray and candidate shadow maps for environmental illumination distribution estimation

NASA Astrophysics Data System (ADS)

Eem, Changkyoung; Kim, Iksu; Hong, Hyunki

2015-07-01

A method to estimate the environmental illumination distribution of a scene with gradient-based ray and candidate shadow maps is presented. In the shadow segmentation stage, we apply a Canny edge detector to the shadowed image by using a three-dimensional (3-D) augmented reality (AR) marker of a known size and shape. Then the hierarchical tree of the connected edge components representing the topological relation is constructed, and the connected components are merged, taking their hierarchical structures into consideration. A gradient-based ray that is perpendicular to the gradient of the edge pixel in the shadow image can be used to extract the shadow regions. In the light source detection stage, shadow regions with both a 3-D AR marker and the light sources are partitioned into candidate shadow maps. A simple logic operation between each candidate shadow map and the segmented shadow is used to efficiently compute the area ratio between them. The proposed method successively extracts the main light sources according to their relative contributions on the segmented shadows. The proposed method can reduce unwanted effects due to the sampling positions in the shadow region and the threshold values in the shadow edge detection.

Nonlocal Intracranial Cavity Extraction

PubMed Central

Manjón, José V.; Eskildsen, Simon F.; Coupé, Pierrick; Romero, José E.; Collins, D. Louis; Robles, Montserrat

2014-01-01

Automatic and accurate methods to estimate normalized regional brain volumes from MRI data are valuable tools which may help to obtain an objective diagnosis and followup of many neurological diseases. To estimate such regional brain volumes, the intracranial cavity volume (ICV) is often used for normalization. However, the high variability of brain shape and size due to normal intersubject variability, normal changes occurring over the lifespan, and abnormal changes due to disease makes the ICV estimation problem challenging. In this paper, we present a new approach to perform ICV extraction based on the use of a library of prelabeled brain images to capture the large variability of brain shapes. To this end, an improved nonlocal label fusion scheme based on BEaST technique is proposed to increase the accuracy of the ICV estimation. The proposed method is compared with recent state-of-the-art methods and the results demonstrate an improved performance both in terms of accuracy and reproducibility while maintaining a reduced computational burden. PMID:25328511

Melt migration modeling in partially molten upper mantle

NASA Astrophysics Data System (ADS)

Ghods, Abdolreza

The objective of this thesis is to investigate the importance of melt migration in shaping major characteristics of geological features associated with the partial melting of the upper mantle, such as sea-floor spreading, continental flood basalts and rifting. The partial melting produces permeable partially molten rocks and a buoyant low viscosity melt. Melt migrates through the partially molten rocks, and transfers mass and heat. Due to its much faster velocity and appreciable buoyancy, melt migration has the potential to modify dynamics of the upwelling partially molten plumes. I develop a 2-D, two-phase flow model and apply it to investigate effects of melt migration on the dynamics and melt generation of upwelling mantle plumes and focusing of melt migration beneath mid-ocean ridges. Melt migration changes distribution of the melt-retention buoyancy force and therefore affects the dynamics of the upwelling plume. This is investigated by modeling a plume with a constant initial melt of 10% where no further melting is considered. Melt migration polarizes melt-retention buoyancy force into high and low melt fraction regions at the top and bottom portions of the plume and therefore results in formation of a more slender and faster upwelling plume. Allowing the plume to melt as it ascends through the upper mantle also produces a slender and faster plume. It is shown that melt produced by decompressional melting of the plume migrates to the upper horizons of the plume, increases the upwelling velocity and thus, the volume of melt generated by the plume. Melt migration produces a plume which lacks the mushroom shape observed for the plume models without melt migration. Melt migration forms a high melt fraction layer beneath the sloping base of the impermeable oceanic lithosphere. Using realistic conditions of melting, freezing and melt extraction, I examine whether the high melt fraction layer is able to focus melt from a wide partial melting zone to a narrow region beneath the observed neo-volcanic zone. My models consist of three parts; lithosphere, asthenosphere and a melt extraction region. It is shown that melt migrates vertically within the asthenosphere, and forms a high melt fraction layer beneath the sloping base of the impermeable lithosphere. Within the sloping high melt fraction layer, melt migrates laterally towards the ridge. In order to simulate melt migration via crustal fractures and cracks, melt is extracted from a melt extraction region extending to the base of the crust. Performance of the melt focusing mechanism is not significantly sensitive to the size of melt extraction region, melt extraction threshold and spreading rate. In all of the models, about half of the total melt production freezes beneath the cooling base of the lithosphere, and the rest is effectively focused towards the ridge and forms the crust. To meet the computational demand for a precise tracing of the deforming upwelling plume and including the chemical buoyancy of the partially molten zone in my models, a new numerical method is developed to solve the related pure advection equations. The numerical method is based on Second Moment numerical method of Egan and Mahoney [1972] which is improved to maintain a high numerical accuracy in shear and rotational flow fields. In comparison with previous numerical methods, my numerical method is a cost-effective, non-diffusive and shape preserving method, and it can also be used to trace a deforming body in compressible flow fields.

Nucleus and cytoplasm segmentation in microscopic images using K-means clustering and region growing

PubMed Central

Sarrafzadeh, Omid; Dehnavi, Alireza Mehri

2015-01-01

Background: Segmentation of leukocytes acts as the foundation for all automated image-based hematological disease recognition systems. Most of the time, hematologists are interested in evaluation of white blood cells only. Digital image processing techniques can help them in their analysis and diagnosis. Materials and Methods: The main objective of this paper is to detect leukocytes from a blood smear microscopic image and segment them into their two dominant elements, nucleus and cytoplasm. The segmentation is conducted using two stages of applying K-means clustering. First, the nuclei are segmented using K-means clustering. Then, a proposed method based on region growing is applied to separate the connected nuclei. Next, the nuclei are subtracted from the original image. Finally, the cytoplasm is segmented using the second stage of K-means clustering. Results: The results indicate that the proposed method is able to extract the nucleus and cytoplasm regions accurately and works well even though there is no significant contrast between the components in the image. Conclusions: In this paper, a method based on K-means clustering and region growing is proposed in order to detect leukocytes from a blood smear microscopic image and segment its components, the nucleus and the cytoplasm. As region growing step of the algorithm relies on the information of edges, it will not able to separate the connected nuclei more accurately in poor edges and it requires at least a weak edge to exist between the nuclei. The nucleus and cytoplasm segments of a leukocyte can be used for feature extraction and classification which leads to automated leukemia detection. PMID:26605213

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images

PubMed Central

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-01-01

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. PMID:28640236

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

PubMed

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Automated breast tissue density assessment using high order regional texture descriptors in mammography

NASA Astrophysics Data System (ADS)

Law, Yan Nei; Lieng, Monica Keiko; Li, Jingmei; Khoo, David Aik-Aun

2014-03-01

Breast cancer is the most common cancer and second leading cause of cancer death among women in the US. The relative survival rate is lower among women with a more advanced stage at diagnosis. Early detection through screening is vital. Mammography is the most widely used and only proven screening method for reliably and effectively detecting abnormal breast tissues. In particular, mammographic density is one of the strongest breast cancer risk factors, after age and gender, and can be used to assess the future risk of disease before individuals become symptomatic. A reliable method for automatic density assessment would be beneficial and could assist radiologists in the evaluation of mammograms. To address this problem, we propose a density classification method which uses statistical features from different parts of the breast. Our method is composed of three parts: breast region identification, feature extraction and building ensemble classifiers for density assessment. It explores the potential of the features extracted from second and higher order statistical information for mammographic density classification. We further investigate the registration of bilateral pairs and time-series of mammograms. The experimental results on 322 mammograms demonstrate that (1) a classifier using features from dense regions has higher discriminative power than a classifier using only features from the whole breast region; (2) these high-order features can be effectively combined to boost the classification accuracy; (3) a classifier using these statistical features from dense regions achieves 75% accuracy, which is a significant improvement from 70% accuracy obtained by the existing approaches.

Computer-aided detection of bladder masses in CT urography (CTU)

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Weizer, Alon; Samala, Ravi K.

2017-03-01

We are developing a computer-aided detection system for bladder cancer in CT urography (CTU). We have previously developed methods for detection of bladder masses within the contrast-enhanced and the non-contrastenhanced regions of the bladder individually. In this study, we investigated methods for detection of bladder masses within the entire bladder. The bladder was segmented using our method that combined deep-learning convolutional neural network with level sets. The non-contrast-enhanced region was separated from the contrast-enhanced region with a maximum-intensity-projection-based method. The non-contrast region was smoothed and gray level threshold was applied to the contrast and non-contrast regions separately to extract the bladder wall and potential masses. The bladder wall was transformed into a straightened thickness profile, which was analyzed to identify lesion candidates in a prescreening step. The candidates were mapped back to the 3D CT volume and segmented using our auto-initialized cascaded level set (AI-CALS) segmentation method. Twenty-seven morphological features were extracted for each candidate. A data set of 57 patients with 71 biopsy-proven bladder lesions was used, which was split into independent training and test sets: 42 training cases with 52 lesions, and 15 test cases with 19 lesions. Using the training set, feature selection was performed and a linear discriminant (LDA) classifier was designed to merge the selected features for classification of bladder lesions and false positives. The trained classifier was evaluated with the test set. FROC analysis showed that the system achieved a sensitivity of 86.5% at 3.3 FPs/case for the training set, and 84.2% at 3.7 FPs/case for the test set.

Quantitative assessment of tumour extraction from dermoscopy images and evaluation of computer-based extraction methods for an automatic melanoma diagnostic system.

PubMed

Iyatomi, Hitoshi; Oka, Hiroshi; Saito, Masataka; Miyake, Ayako; Kimoto, Masayuki; Yamagami, Jun; Kobayashi, Seiichiro; Tanikawa, Akiko; Hagiwara, Masafumi; Ogawa, Koichi; Argenziano, Giuseppe; Soyer, H Peter; Tanaka, Masaru

2006-04-01

The aims of this study were to provide a quantitative assessment of the tumour area extracted by dermatologists and to evaluate computer-based methods from dermoscopy images for refining a computer-based melanoma diagnostic system. Dermoscopic images of 188 Clark naevi, 56 Reed naevi and 75 melanomas were examined. Five dermatologists manually drew the border of each lesion with a tablet computer. The inter-observer variability was evaluated and the standard tumour area (STA) for each dermoscopy image was defined. Manual extractions by 10 non-medical individuals and by two computer-based methods were evaluated with STA-based assessment criteria: precision and recall. Our new computer-based method introduced the region-growing approach in order to yield results close to those obtained by dermatologists. The effectiveness of our extraction method with regard to diagnostic accuracy was evaluated. Two linear classifiers were built using the results of conventional and new computer-based tumour area extraction methods. The final diagnostic accuracy was evaluated by drawing the receiver operating curve (ROC) of each classifier, and the area under each ROC was evaluated. The standard deviations of the tumour area extracted by five dermatologists and 10 non-medical individuals were 8.9% and 10.7%, respectively. After assessment of the extraction results by dermatologists, the STA was defined as the area that was selected by more than two dermatologists. Dermatologists selected the melanoma area with statistically smaller divergence than that of Clark naevus or Reed naevus (P = 0.05). By contrast, non-medical individuals did not show this difference. Our new computer-based extraction algorithm showed superior performance (precision, 94.1%; recall, 95.3%) to the conventional thresholding method (precision, 99.5%; recall, 87.6%). These results indicate that our new algorithm extracted a tumour area close to that obtained by dermatologists and, in particular, the border part of the tumour was adequately extracted. With this refinement, the area under the ROC increased from 0.795 to 0.875 and the diagnostic accuracy showed an increase of approximately 20% in specificity when the sensitivity was 80%. It can be concluded that our computer-based tumour extraction algorithm extracted almost the same area as that obtained by dermatologists and provided improved computer-based diagnostic accuracy.

Development of pressurized subcritical water extraction combined with stir bar sorptive extraction for the analysis of organochlorine pesticides and chlorobenzenes in soils.

PubMed

Rodil, Rosario; Popp, Peter

2006-08-18

An analytical method for the determination of several organochlorine pesticides (OCPs) like hexachlorocyclohexanes (HCHs), cyclodiene derivates (dieldrin, aldrin, endrin, heptachlor, heptachlor epoxide, endrin aldehyde, endosulfan and ensodulfan sulphate) and DDX compounds (p,p'-DDE, p,p'-DDD and p,p'-DDT) as well as chlorobenzenes in soils has been developed. The procedure is based on pressurized subcritical water extraction (PSWE) followed by stir bar sorptive extraction (SBSE) and subsequent thermodesorption-gas chromatography/mass spectrometry analysis. Significant PSWE and SBSE parameters were optimized using spiked soil and water samples. For the PSWE of the organochlorine compounds, water modified with acetonitrile as the extraction solvent, at an extraction temperature of 120 degrees C, and three cycles of 10 min extraction proved to be optimal. Under optimized conditions, the figures of merit, such as precision, accuracy and detection limits were evaluated. The detection limits obtained for soil samples were in the range 0.002-4.7 ng/g. Recoveries between 4.1 and 85.2% were achieved from samples spiked at a concentration level of 25-155 ng/g. The main advantages of this method are the avoidance of clean-up and concentration procedures as well as the significant reduction of the required volume of organic solvents. The described method was applied to the determination of the pollutants in soil samples collected from a polluted area, the Bitterfeld region (Germany). The results obtained by PSWE-SBSE were in a good agreement with those obtained by a reference method, a conventional pressurized liquid extraction (PLE).

Macroalgae Extracts From Antarctica Have Antimicrobial and Anticancer Potential

PubMed Central

Martins, Rosiane M.; Nedel, Fernanda; Guimarães, Victoria B. S.; da Silva, Adriana F.; Colepicolo, Pio; de Pereira, Claudio M. P.; Lund, Rafael G.

2018-01-01

Background: Macroalgae are sources of bioactive compounds due to the large number of secondary metabolites they synthesize. The Antarctica region is characterized by extreme weather conditions and abundant aggregations of macroalgae. However, current knowledge on their biodiversity and their potential for bio-prospecting is still fledging. This study evaluates the antimicrobial and cytotoxic activity of different extracts of four macroalgae (Cystosphaera jacquinotii, Iridaea cordata, Himantothallus grandifolius, and Pyropia endiviifolia) from the Antarctic region against cancer and non-cancer cell lines. Methods: The antimicrobial activity of macroalgae was evaluated by the broth microdilution method. Extracts were assessed against Staphylococcus aureus ATCC 19095, Enterococcus faecalis ATCC 4083, Escherichia coli ATCC29214, Pseudomonas aeruginosa ATCC 9027, Candida albicans ATCC 62342, and the clinical isolates from the human oral cavity, namely, C. albicans (3), C. parapsilosis, C. glabrata, C. lipolytica, and C. famata. Cytotoxicity against human epidermoid carcinoma (A-431) and mouse embryonic fibroblast (NIH/3T3) cell lines was evaluated with MTT colorimetric assay. Results: An ethyl acetate extract of H. grandifolius showed noticeable antifungal activity against all fungal strains tested, including fluconazole-resistant samples. Cytotoxicity investigation with a cancer cell line revealed that the ethyl acetate extract of I. cordata was highly cytotoxic against A-431 cancer cell line, increasing the inhibitory ratio to 91.1 and 95.6% after 24 and 48 h exposure, respectively, for a concentration of 500 μg mL−1. Most of the algal extracts tested showed little or no cytotoxicity against fibroblasts. Conclusion: Data suggest that macroalgae extracts from Antarctica may represent a source of therapeutic agents. HIGHLIGHTS Different macroalgae samples from Antarctica were collected and the lyophilized biomass of each macroalgae was extracted sequentially with different solventsThe antimicrobial and anticancer potential of macroalgae extracts were evaluatedEthyl acetate extract of H. grandifolius showed noticeable antifungal activity against all the fungal strains tested, including fluconazole-resistant samplesEthyl acetate extract of I. cordata was highly cytotoxic against the A-431 cancer cell lineMost of the algal extracts tested showed little or no cytotoxicity against normal cell lines PMID:29568291

Finger-Vein Verification Based on Multi-Features Fusion

PubMed Central

Qin, Huafeng; Qin, Lan; Xue, Lian; He, Xiping; Yu, Chengbo; Liang, Xinyuan

2013-01-01

This paper presents a new scheme to improve the performance of finger-vein identification systems. Firstly, a vein pattern extraction method to extract the finger-vein shape and orientation features is proposed. Secondly, to accommodate the potential local and global variations at the same time, a region-based matching scheme is investigated by employing the Scale Invariant Feature Transform (SIFT) matching method. Finally, the finger-vein shape, orientation and SIFT features are combined to further enhance the performance. The experimental results on databases of 426 and 170 fingers demonstrate the consistent superiority of the proposed approach. PMID:24196433

DNA analysis of molluscs from a museum wet collection: a comparison of different extraction methods.

PubMed

Jaksch, Katharina; Eschner, Anita; Rintelen, Thomas V; Haring, Elisabeth

2016-07-18

DNA isolation and PCR amplification from molluscan taxa is considered as problematic because polysaccharides in tissue and mucus presumably co-precipitate with the DNA and inhibit the activity of DNA polymerase. In the present study we tested two common extraction methods on specimens from the mollusc collection of the Natural History Museum Vienna (NHMW). We analysed a broad variety of taxa covering a large temporal span (acquisition years 1877 to 1999), which distinguishes our study from previous ones where mostly fresh material was used. We also took other factors into account: effects of sample age, effects of formaldehyde treatment and taxon-specific problems. We used several primer combinations to amplify amplicons of different lengths of two mitochondrial genes: cytochrome c oxidase subunit 1 (COI) and 16S rRNA gene (16S). Overall PCR success was 43 % in the 576 extractions (including all primer combinations). The smallest amplicon (~240 bp) showed the best results (49 % positive reactions), followed by the 400 bp amplicon (40.5 %). Both short sections yielded significantly better results than the 700 bp long amplicon (27 %). Comparatively, the Gen-ial-First, All-tissue DNA-Kit-extraction method performed significantly better than Promega-Tissue and Hair Extraction Kit. Generally, PCR success is age-dependent. Nonetheless, we were able to obtain the longest amplicon even from 137-year-old material. Importantly, formaldehyde traces did not totally inhibit amplification success, although very high concentrations did. Museum material has gained importance for DNA analysis in recent years, especially for DNA barcoding projects. In some cases, however, the amplification of the standard barcoding region (partial sequence of the COI) is problematic with old material. Our study clearly shows that the COI barcoding region could be amplified in up to 49 % of PCRs (varying with amplicon length), which is, for museum samples, quite a high percentage. The difference between extraction methods was minimal and we recommend using an established kit for a first attempt because experience and routine in handling might be more important than slight performance differences of the various kits. Finally, we identify fixation, storage, sample conservation and documentation of the specimens' history rather than the DNA extraction method to be the most crucial factors for PCR success.

Automated Solar Flare Detection and Feature Extraction in High-Resolution and Full-Disk Hα Images

NASA Astrophysics Data System (ADS)

Yang, Meng; Tian, Yu; Liu, Yangyi; Rao, Changhui

2018-05-01

In this article, an automated solar flare detection method applied to both full-disk and local high-resolution Hα images is proposed. An adaptive gray threshold and an area threshold are used to segment the flare region. Features of each detected flare event are extracted, e.g. the start, peak, and end time, the importance class, and the brightness class. Experimental results have verified that the proposed method can obtain more stable and accurate segmentation results than previous works on full-disk images from Big Bear Solar Observatory (BBSO) and Kanzelhöhe Observatory for Solar and Environmental Research (KSO), and satisfying segmentation results on high-resolution images from the Goode Solar Telescope (GST). Moreover, the extracted flare features correlate well with the data given by KSO. The method may be able to implement a more complicated statistical analysis of Hα solar flares.

Enhanced Gender Recognition System Using an Improved Histogram of Oriented Gradient (HOG) Feature from Quality Assessment of Visible Light and Thermal Images of the Human Body.

PubMed

Nguyen, Dat Tien; Park, Kang Ryoung

2016-07-21

With higher demand from users, surveillance systems are currently being designed to provide more information about the observed scene, such as the appearance of objects, types of objects, and other information extracted from detected objects. Although the recognition of gender of an observed human can be easily performed using human perception, it remains a difficult task when using computer vision system images. In this paper, we propose a new human gender recognition method that can be applied to surveillance systems based on quality assessment of human areas in visible light and thermal camera images. Our research is novel in the following two ways: First, we utilize the combination of visible light and thermal images of the human body for a recognition task based on quality assessment. We propose a quality measurement method to assess the quality of image regions so as to remove the effects of background regions in the recognition system. Second, by combining the features extracted using the histogram of oriented gradient (HOG) method and the measured qualities of image regions, we form a new image features, called the weighted HOG (wHOG), which is used for efficient gender recognition. Experimental results show that our method produces more accurate estimation results than the state-of-the-art recognition method that uses human body images.

Enhanced Gender Recognition System Using an Improved Histogram of Oriented Gradient (HOG) Feature from Quality Assessment of Visible Light and Thermal Images of the Human Body

PubMed Central

Nguyen, Dat Tien; Park, Kang Ryoung

2016-01-01

With higher demand from users, surveillance systems are currently being designed to provide more information about the observed scene, such as the appearance of objects, types of objects, and other information extracted from detected objects. Although the recognition of gender of an observed human can be easily performed using human perception, it remains a difficult task when using computer vision system images. In this paper, we propose a new human gender recognition method that can be applied to surveillance systems based on quality assessment of human areas in visible light and thermal camera images. Our research is novel in the following two ways: First, we utilize the combination of visible light and thermal images of the human body for a recognition task based on quality assessment. We propose a quality measurement method to assess the quality of image regions so as to remove the effects of background regions in the recognition system. Second, by combining the features extracted using the histogram of oriented gradient (HOG) method and the measured qualities of image regions, we form a new image features, called the weighted HOG (wHOG), which is used for efficient gender recognition. Experimental results show that our method produces more accurate estimation results than the state-of-the-art recognition method that uses human body images. PMID:27455264

Digital image modification detection using color information and its histograms.

PubMed

Zhou, Haoyu; Shen, Yue; Zhu, Xinghui; Liu, Bo; Fu, Zigang; Fan, Na

2016-09-01

The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping blocks. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring. Copyright © 2016. Published by Elsevier Ireland Ltd.

Robust, non-invasive methods for metering groundwater well extraction in remote environments

NASA Astrophysics Data System (ADS)

Bulovic, Nevenka; Keir, Greg; McIntyre, Neil

2017-04-01

Quantifying the rate of extraction from groundwater wells can be essential for regional scale groundwater management and impact assessment. This is especially the case in regions heavily dependent on groundwater such as the semi-arid Surat and Bowen Basins in Queensland, Australia. Of the 30 000+ groundwater wells in this area, the majority of which are used for stock watering and domestic purposes, almost none have flow metering devices installed. As part of a research project to estimate regional groundwater extraction, we have undertaken a small scale flow metering program on a selected set of wells. Conventional in-line flow meters were unsuitable for our project, as both non-invasiveness and adaptability / suitability to a variety of discharge pipe characteristics was critical. We describe the use of two metering technologies not widely used in groundwater applications, non-invasive, clamp-on ultrasonic transit time flow meters and tipping bucket flow meters, as semi-permanent installations on discharge pipes of various artesian and sub-artesian groundwater wells. We present examples of detailed extraction rate time-series, which are of particular value in developing predictive models of water well extraction in data limited areas where water use dynamics and drivers are poorly understood. We conclude by discussing future project trajectories, which include expansion of the monitoring network through development of novel metering techniques and telemetry across large areas of poor connectivity.

DEVELOPMENT OF A SYSTEMATIC APPROACH TO ...

EPA Pesticide Factsheets

Risk assessment is a crucial component of the site remediation decision-making process. Some current EPA methods do not have detection limits low enough for risk assessment of many VOCs (e.g., EPA Region 3 Risk Based Concentration levels, EPA Region 9 Preliminary Remediation Goals, state-specified concentration levels). The magnitude of this problem was described in a paper recently presented at a University of Massachusetts Remediation Conference with the conclusion that the resolution of this issue is critical for valid human health and ecological risk assessments. Likewise, the difficulty of obtaining complete extraction of water-soluble VOCs and semi-volatile organic compounds (SVOCs) makes the generation of reliable and reproducible data a serious concern in site characterization and risk assessment programs.This poster presents findings of the development of an analytical method which uses thermal desorption combined with dual gas chromatography/mass spectrometry (GC/MS) to extract and accurately measure low levels of VOCs and SVOCs in soil and sediment samples with medium to high moisture content. Thermal extraction was selected for examination because the technique is simpler and more efficient than the present EPA purge-and-trap methods, and all water-soluble compounds are amenable to the procedure. Efforts were made to modify commonly used instrumentation (e.g., Archon

Identification of the critical depth-of-cut through a 2D image of the cutting region resulting from taper cutting of brittle materials

NASA Astrophysics Data System (ADS)

Gu, Wen; Zhu, Zhiwei; Zhu, Wu-Le; Lu, Leyao; To, Suet; Xiao, Gaobo

2018-05-01

An automatic identification method for obtaining the critical depth-of-cut (DoC) of brittle materials with nanometric accuracy and sub-nanometric uncertainty is proposed in this paper. With this method, a two-dimensional (2D) microscopic image of the taper cutting region is captured and further processed by image analysis to extract the margin of generated micro-cracks in the imaging plane. Meanwhile, an analytical model is formulated to describe the theoretical curve of the projected cutting points on the imaging plane with respect to a specified DoC during the whole cutting process. By adopting differential evolution algorithm-based minimization, the critical DoC can be identified by minimizing the deviation between the extracted margin and the theoretical curve. The proposed method is demonstrated through both numerical simulation and experimental analysis. Compared with conventional 2D- and 3D-microscopic-image-based methods, determination of the critical DoC in this study uses the envelope profile rather than the onset point of the generated cracks, providing a more objective approach with smaller uncertainty.

Object-oriented feature extraction approach for mapping supraglacial debris in Schirmacher Oasis using very high-resolution satellite data

NASA Astrophysics Data System (ADS)

Jawak, Shridhar D.; Jadhav, Ajay; Luis, Alvarinho J.

2016-05-01

Supraglacial debris was mapped in the Schirmacher Oasis, east Antarctica, by using WorldView-2 (WV-2) high resolution optical remote sensing data consisting of 8-band calibrated Gram Schmidt (GS)-sharpened and atmospherically corrected WV-2 imagery. This study is a preliminary attempt to develop an object-oriented rule set to extract supraglacial debris for Antarctic region using 8-spectral band imagery. Supraglacial debris was manually digitized from the satellite imagery to generate the ground reference data. Several trials were performed using few existing traditional pixel-based classification techniques and color-texture based object-oriented classification methods to extract supraglacial debris over a small domain of the study area. Multi-level segmentation and attributes such as scale, shape, size, compactness along with spectral information from the data were used for developing the rule set. The quantitative analysis of error was carried out against the manually digitized reference data to test the practicability of our approach over the traditional pixel-based methods. Our results indicate that OBIA-based approach (overall accuracy: 93%) for extracting supraglacial debris performed better than all the traditional pixel-based methods (overall accuracy: 80-85%). The present attempt provides a comprehensive improved method for semiautomatic feature extraction in supraglacial environment and a new direction in the cryospheric research.

Real-time 3D visualization of the thoraco-abdominal surface during breathing with body movement and deformation extraction.

PubMed

Povšič, K; Jezeršek, M; Možina, J

2015-07-01

Real-time 3D visualization of the breathing displacements can be a useful diagnostic tool in order to immediately observe the most active regions on the thoraco-abdominal surface. The developed method is capable of separating non-relevant torso movement and deformations from the deformations that are solely related to breathing. This makes it possible to visualize only the breathing displacements. The system is based on the structured laser triangulation principle, with simultaneous spatial and color data acquisition of the thoraco-abdominal region. Based on the tracking of the attached passive markers, the torso movement and deformation is compensated using rigid and non-rigid transformation models on the three-dimensional (3D) data. The total time of 3D data processing together with visualization equals 20 ms per cycle.In vitro verification of the rigid movement extraction was performed using the iterative closest point algorithm as a reference. Furthermore, a volumetric evaluation on a live subject was performed to establish the accuracy of the rigid and non-rigid model. The root mean square deviation between the measured and the reference volumes shows an error of  ±0.08 dm(3) for rigid movement extraction. Similarly, the error was calculated to be  ±0.02 dm(3) for torsional deformation extraction and  ±0.11 dm(3) for lateral bending deformation extraction. The results confirm that during the torso movement and deformation, the proposed method is sufficiently accurate to visualize only the displacements related to breathing. The method can be used, for example, during the breathing exercise on an indoor bicycle or a treadmill.

Development of Automated Tracking System with Active Cameras for Figure Skating

NASA Astrophysics Data System (ADS)

Haraguchi, Tomohiko; Taki, Tsuyoshi; Hasegawa, Junichi

This paper presents a system based on the control of PTZ cameras for automated real-time tracking of individual figure skaters moving on an ice rink. In the video images of figure skating, irregular trajectories, various postures, rapid movements, and various costume colors are included. Therefore, it is difficult to determine some features useful for image tracking. On the other hand, an ice rink has a limited area and uniform high intensity, and skating is always performed on ice. In the proposed system, an ice rink region is first extracted from a video image by the region growing method, and then, a skater region is extracted using the rink shape information. In the camera control process, each camera is automatically panned and/or tilted so that the skater region is as close to the center of the image as possible; further, the camera is zoomed to maintain the skater image at an appropriate scale. The results of experiments performed for 10 training scenes show that the skater extraction rate is approximately 98%. Thus, it was concluded that tracking with camera control was successful for almost all the cases considered in the study.

a R-Shiny Based Phenology Analysis System and Case Study Using Digital Camera Dataset

NASA Astrophysics Data System (ADS)

Zhou, Y. K.

2018-05-01

Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.

An improved method for pancreas segmentation using SLIC and interactive region merging

NASA Astrophysics Data System (ADS)

Zhang, Liyuan; Yang, Huamin; Shi, Weili; Miao, Yu; Li, Qingliang; He, Fei; He, Wei; Li, Yanfang; Zhang, Huimao; Mori, Kensaku; Jiang, Zhengang

2017-03-01

Considering the weak edges in pancreas segmentation, this paper proposes a new solution which integrates more features of CT images by combining SLIC superpixels and interactive region merging. In the proposed method, Mahalanobis distance is first utilized in SLIC method to generate better superpixel images. By extracting five texture features and one gray feature, the similarity measure between two superpixels becomes more reliable in interactive region merging. Furthermore, object edge blocks are accurately addressed by re-segmentation merging process. Applying the proposed method to four cases of abdominal CT images, we segment pancreatic tissues to verify the feasibility and effectiveness. The experimental results show that the proposed method can make segmentation accuracy increase to 92% on average. This study will boost the application process of pancreas segmentation for computer-aided diagnosis system.

A research of road centerline extraction algorithm from high resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhang, Yushan; Xu, Tingfa

2017-09-01

Satellite remote sensing technology has become one of the most effective methods for land surface monitoring in recent years, due to its advantages such as short period, large scale and rich information. Meanwhile, road extraction is an important field in the applications of high resolution remote sensing images. An intelligent and automatic road extraction algorithm with high precision has great significance for transportation, road network updating and urban planning. The fuzzy c-means (FCM) clustering segmentation algorithms have been used in road extraction, but the traditional algorithms did not consider spatial information. An improved fuzzy C-means clustering algorithm combined with spatial information (SFCM) is proposed in this paper, which is proved to be effective for noisy image segmentation. Firstly, the image is segmented using the SFCM. Secondly, the segmentation result is processed by mathematical morphology to remover the joint region. Thirdly, the road centerlines are extracted by morphology thinning and burr trimming. The average integrity of the centerline extraction algorithm is 97.98%, the average accuracy is 95.36% and the average quality is 93.59%. Experimental results show that the proposed method in this paper is effective for road centerline extraction.

Antioxidant, antimicrobial, antiparasitic, and cytotoxic properties of various Brazilian propolis extracts

PubMed Central

Barreto, Gabriele de Abreu; Costa, Samantha Serra; Andrade, Luciana Nalone; Amaral, Ricardo Guimarães; Carvalho, Adriana Andrade; Padilha, Francine Ferreira; Barbosa, Josiane Dantas Viana

2017-01-01

Propolis is known for its biological properties and its preparations have been continuously investigated in an attempt to solve the problem of their standardization, an issue that limits the use of propolis in food and pharmaceutical industries. The aim of this study was to evaluate in vitro antioxidant, antimicrobial, antiparasitic, and cytotoxic effects of extracts of red, green, and brown propolis from different regions of Brazil, obtained by ethanolic and supercritical extraction methods. We found that propolis extracts obtained by both these methods showed concentration-dependent antioxidant activity. The extracts obtained by ethanolic extraction showed higher antioxidant activity than that shown by the extracts obtained by supercritical extraction. Ethanolic extracts of red propolis exhibited up to 98% of the maximum antioxidant activity at the highest extract concentration. Red propolis extracts obtained by ethanolic and supercritical methods showed the highest levels of antimicrobial activity against several bacteria. Most extracts demonstrated antimicrobial activity against Staphylococcus aureus. None of the extracts analyzed showed activity against Escherichia coli or Candida albicans. An inhibitory effect of all tested ethanolic extracts on the growth of Trypanosoma cruzi Y strain epimastigotes was observed in the first 24 h. However, after 96 h, a persistent inhibitory effect was detected only for red propolis samples. Only ethanolic extracts of red propolis samples R01Et.B2 and R02Et.B2 showed a cytotoxic effect against all four cancer cell lines tested (HL-60, HCT-116, OVCAR-8, and SF-295), indicating that red propolis extracts have great cytotoxic potential. The biological effects of ethanolic extracts of red propolis revealed in the present study suggest that red propolis can be a potential alternative therapeutic treatment against Chagas disease and some types of cancer, although high activity of red propolis in vitro needs to be confirmed by future in vivo investigations. PMID:28358806

Antioxidant, antimicrobial, antiparasitic, and cytotoxic properties of various Brazilian propolis extracts.

PubMed

Dantas Silva, Rejane Pina; Machado, Bruna Aparecida Souza; Barreto, Gabriele de Abreu; Costa, Samantha Serra; Andrade, Luciana Nalone; Amaral, Ricardo Guimarães; Carvalho, Adriana Andrade; Padilha, Francine Ferreira; Barbosa, Josiane Dantas Viana; Umsza-Guez, Marcelo Andres

2017-01-01

Propolis is known for its biological properties and its preparations have been continuously investigated in an attempt to solve the problem of their standardization, an issue that limits the use of propolis in food and pharmaceutical industries. The aim of this study was to evaluate in vitro antioxidant, antimicrobial, antiparasitic, and cytotoxic effects of extracts of red, green, and brown propolis from different regions of Brazil, obtained by ethanolic and supercritical extraction methods. We found that propolis extracts obtained by both these methods showed concentration-dependent antioxidant activity. The extracts obtained by ethanolic extraction showed higher antioxidant activity than that shown by the extracts obtained by supercritical extraction. Ethanolic extracts of red propolis exhibited up to 98% of the maximum antioxidant activity at the highest extract concentration. Red propolis extracts obtained by ethanolic and supercritical methods showed the highest levels of antimicrobial activity against several bacteria. Most extracts demonstrated antimicrobial activity against Staphylococcus aureus. None of the extracts analyzed showed activity against Escherichia coli or Candida albicans. An inhibitory effect of all tested ethanolic extracts on the growth of Trypanosoma cruzi Y strain epimastigotes was observed in the first 24 h. However, after 96 h, a persistent inhibitory effect was detected only for red propolis samples. Only ethanolic extracts of red propolis samples R01Et.B2 and R02Et.B2 showed a cytotoxic effect against all four cancer cell lines tested (HL-60, HCT-116, OVCAR-8, and SF-295), indicating that red propolis extracts have great cytotoxic potential. The biological effects of ethanolic extracts of red propolis revealed in the present study suggest that red propolis can be a potential alternative therapeutic treatment against Chagas disease and some types of cancer, although high activity of red propolis in vitro needs to be confirmed by future in vivo investigations.

Accurate airway centerline extraction based on topological thinning using graph-theoretic analysis.

PubMed

Bian, Zijian; Tan, Wenjun; Yang, Jinzhu; Liu, Jiren; Zhao, Dazhe

2014-01-01

The quantitative analysis of the airway tree is of critical importance in the CT-based diagnosis and treatment of popular pulmonary diseases. The extraction of airway centerline is a precursor to identify airway hierarchical structure, measure geometrical parameters, and guide visualized detection. Traditional methods suffer from extra branches and circles due to incomplete segmentation results, which induce false analysis in applications. This paper proposed an automatic and robust centerline extraction method for airway tree. First, the centerline is located based on the topological thinning method; border voxels are deleted symmetrically to preserve topological and geometrical properties iteratively. Second, the structural information is generated using graph-theoretic analysis. Then inaccurate circles are removed with a distance weighting strategy, and extra branches are pruned according to clinical anatomic knowledge. The centerline region without false appendices is eventually determined after the described phases. Experimental results show that the proposed method identifies more than 96% branches and keep consistency across different cases and achieves superior circle-free structure and centrality.

Feature Selection in Order to Extract Multiple Sclerosis Lesions Automatically in 3D Brain Magnetic Resonance Images Using Combination of Support Vector Machine and Genetic Algorithm.

PubMed

Khotanlou, Hassan; Afrasiabi, Mahlagha

2012-10-01

This paper presents a new feature selection approach for automatically extracting multiple sclerosis (MS) lesions in three-dimensional (3D) magnetic resonance (MR) images. Presented method is applicable to different types of MS lesions. In this method, T1, T2, and fluid attenuated inversion recovery (FLAIR) images are firstly preprocessed. In the next phase, effective features to extract MS lesions are selected by using a genetic algorithm (GA). The fitness function of the GA is the Similarity Index (SI) of a support vector machine (SVM) classifier. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations. This algorithm is evaluated on 15 real 3D MR images using several measures. As a result, the SI between MS regions determined by the proposed method and radiologists was 87% on average. Experiments and comparisons with other methods show the effectiveness and the efficiency of the proposed approach.

Direct Extraction of Tumor Response Based on Ensemble Empirical Mode Decomposition for Image Reconstruction of Early Breast Cancer Detection by UWB.

PubMed

Li, Qinwei; Xiao, Xia; Wang, Liang; Song, Hang; Kono, Hayato; Liu, Peifang; Lu, Hong; Kikkawa, Takamaro

2015-10-01

A direct extraction method of tumor response based on ensemble empirical mode decomposition (EEMD) is proposed for early breast cancer detection by ultra-wide band (UWB) microwave imaging. With this approach, the image reconstruction for the tumor detection can be realized with only extracted signals from as-detected waveforms. The calibration process executed in the previous research for obtaining reference waveforms which stand for signals detected from the tumor-free model is not required. The correctness of the method is testified by successfully detecting a 4 mm tumor located inside the glandular region in one breast model and by the model located at the interface between the gland and the fat, respectively. The reliability of the method is checked by distinguishing a tumor buried in the glandular tissue whose dielectric constant is 35. The feasibility of the method is confirmed by showing the correct tumor information in both simulation results and experimental results for the realistic 3-D printed breast phantom.

Highway 3D model from image and lidar data

NASA Astrophysics Data System (ADS)

Chen, Jinfeng; Chu, Henry; Sun, Xiaoduan

2014-05-01

We present a new method of highway 3-D model construction developed based on feature extraction in highway images and LIDAR data. We describe the processing road coordinate data that connect the image frames to the coordinates of the elevation data. Image processing methods are used to extract sky, road, and ground regions as well as significant objects (such as signs and building fronts) in the roadside for the 3D model. LIDAR data are interpolated and processed to extract the road lanes as well as other features such as trees, ditches, and elevated objects to form the 3D model. 3D geometry reasoning is used to match the image features to the 3D model. Results from successive frames are integrated to improve the final model.

A maximally stable extremal region based scene text localization method

NASA Astrophysics Data System (ADS)

Xiao, Chengqiu; Ji, Lixin; Gao, Chao; Li, Shaomei

2015-07-01

Text localization in natural scene images is an important prerequisite for many content-based image analysis tasks. This paper proposes a novel text localization algorithm. Firstly, a fast pruning algorithm is designed to extract Maximally Stable Extremal Regions (MSER) as basic character candidates. Secondly, these candidates are filtered by using the properties of fitting ellipse and the distribution properties of characters to exclude most non-characters. Finally, a new extremal regions projection merging algorithm is designed to group character candidates into words. Experimental results show that the proposed method has an advantage in speed and achieve relatively high precision and recall rates than the latest published algorithms.

A bio-inspired method and system for visual object-based attention and segmentation

NASA Astrophysics Data System (ADS)

Huber, David J.; Khosla, Deepak

2010-04-01

This paper describes a method and system of human-like attention and object segmentation in visual scenes that (1) attends to regions in a scene in their rank of saliency in the image, (2) extracts the boundary of an attended proto-object based on feature contours, and (3) can be biased to boost the attention paid to specific features in a scene, such as those of a desired target object in static and video imagery. The purpose of the system is to identify regions of a scene of potential importance and extract the region data for processing by an object recognition and classification algorithm. The attention process can be performed in a default, bottom-up manner or a directed, top-down manner which will assign a preference to certain features over others. One can apply this system to any static scene, whether that is a still photograph or imagery captured from video. We employ algorithms that are motivated by findings in neuroscience, psychology, and cognitive science to construct a system that is novel in its modular and stepwise approach to the problems of attention and region extraction, its application of a flooding algorithm to break apart an image into smaller proto-objects based on feature density, and its ability to join smaller regions of similar features into larger proto-objects. This approach allows many complicated operations to be carried out by the system in a very short time, approaching real-time. A researcher can use this system as a robust front-end to a larger system that includes object recognition and scene understanding modules; it is engineered to function over a broad range of situations and can be applied to any scene with minimal tuning from the user.

Numerical analysis of electronegative plasma in the extraction region of negative hydrogen ion sources

NASA Astrophysics Data System (ADS)

Kuppel, S.; Matsushita, D.; Hatayama, A.; Bacal, M.

2011-01-01

This numerical study focuses on the physical mechanisms involved in the extraction of volume-produced H- ions from a steady state laboratory negative hydrogen ion source with one opening in the plasma electrode (PE) on which a dc-bias voltage is applied. A weak magnetic field is applied in the source plasma transversely to the extracted beam. The goal is to highlight the combined effects of the weak magnetic field and the PE bias voltage (upon the extraction process of H- ions and electrons). To do so, we focus on the behavior of electrons and volume-produced negative ions within a two-dimensional model using the particle-in-cell method. No collision processes are taken into account, except for electron diffusion across the magnetic field using a simple random-walk model at each time step of the simulation. The results show first that applying the magnetic field (without PE bias) enhances H- ion extraction, while it drastically decreases the extracted electron current. Secondly, the extracted H- ion current has a maximum when the PE bias is equal to the plasma potential, while the extracted electron current is significantly reduced by applying the PE bias. The underlying mechanism leading to the above results is the gradual opening by the PE bias of the equipotential lines towards the parts of the extraction region facing the PE. The shape of these lines is due originally to the electron trapping by the magnetic field.

Automatic extraction of nuclei centroids of mouse embryonic cells from fluorescence microscopy images.

PubMed

Bashar, Md Khayrul; Komatsu, Koji; Fujimori, Toshihiko; Kobayashi, Tetsuya J

2012-01-01

Accurate identification of cell nuclei and their tracking using three dimensional (3D) microscopic images is a demanding task in many biological studies. Manual identification of nuclei centroids from images is an error-prone task, sometimes impossible to accomplish due to low contrast and the presence of noise. Nonetheless, only a few methods are available for 3D bioimaging applications, which sharply contrast with 2D analysis, where many methods already exist. In addition, most methods essentially adopt segmentation for which a reliable solution is still unknown, especially for 3D bio-images having juxtaposed cells. In this work, we propose a new method that can directly extract nuclei centroids from fluorescence microscopy images. This method involves three steps: (i) Pre-processing, (ii) Local enhancement, and (iii) Centroid extraction. The first step includes two variations: first variation (Variant-1) uses the whole 3D pre-processed image, whereas the second one (Variant-2) modifies the preprocessed image to the candidate regions or the candidate hybrid image for further processing. At the second step, a multiscale cube filtering is employed in order to locally enhance the pre-processed image. Centroid extraction in the third step consists of three stages. In Stage-1, we compute a local characteristic ratio at every voxel and extract local maxima regions as candidate centroids using a ratio threshold. Stage-2 processing removes spurious centroids from Stage-1 results by analyzing shapes of intensity profiles from the enhanced image. An iterative procedure based on the nearest neighborhood principle is then proposed to combine if there are fragmented nuclei. Both qualitative and quantitative analyses on a set of 100 images of 3D mouse embryo are performed. Investigations reveal a promising achievement of the technique presented in terms of average sensitivity and precision (i.e., 88.04% and 91.30% for Variant-1; 86.19% and 95.00% for Variant-2), when compared with an existing method (86.06% and 90.11%), originally developed for analyzing C. elegans images.

Printed biofuel cells

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

Wang, Joseph; Windmiller, Joshua Ray; Jia, Wenzhao

2016-11-22

Methods, systems, and devices are disclosed for implementing a biofuel cell device for extracting energy from a biofuel. In one aspect, a biofuel cell device includes a substrate, an anode including a catalyst to facilitate the conversion of a fuel in a biological fluid in an oxidative process that releases electrons captured at the anode, thereby extracting energy from the fuel substance, a cathode configured on the substrate adjacent to the anode and separated from the anode by a spacing region, and a load electrically coupled to the anode and cathode via electrical interconnects to obtain the extracted energy asmore » electrical energy.« less

Cell nuclei segmentation in fluorescence microscopy images using inter- and intra-region discriminative information.

PubMed

Song, Yang; Cai, Weidong; Feng, David Dagan; Chen, Mei

2013-01-01

Automated segmentation of cell nuclei in microscopic images is critical to high throughput analysis of the ever increasing amount of data. Although cell nuclei are generally visually distinguishable for human, automated segmentation faces challenges when there is significant intensity inhomogeneity among cell nuclei or in the background. In this paper, we propose an effective method for automated cell nucleus segmentation using a three-step approach. It first obtains an initial segmentation by extracting salient regions in the image, then reduces false positives using inter-region feature discrimination, and finally refines the boundary of the cell nuclei using intra-region contrast information. This method has been evaluated on two publicly available datasets of fluorescence microscopic images with 4009 cells, and has achieved superior performance compared to popular state of the art methods using established metrics.

JMOSFET: A MOSFET parameter extractor with geometry-dependent terms

NASA Technical Reports Server (NTRS)

Buehler, M. G.; Moore, B. T.

1985-01-01

The parameters from metal-oxide-silicon field-effect transistors (MOSFETs) that are included on the Combined Release and Radiation Effects Satellite (CRRES) test chips need to be extracted to have a simple but comprehensive method that can be used in wafer acceptance, and to have a method that is sufficiently accurate that it can be used in integrated circuits. A set of MOSFET parameter extraction procedures that are directly linked to the MOSFET model equations and that facilitate the use of simple, direct curve-fitting techniques are developed. In addition, the major physical effects that affect MOSFET operation in the linear and saturation regions of operation for devices fabricated in 1.2 to 3.0 mm CMOS technology are included. The fitting procedures were designed to establish single values for such parameters as threshold voltage and transconductance and to provide for slope matching between the linear and saturation regions of the MOSFET output current-voltage curves. Four different sizes of transistors that cover a rectangular-shaped region of the channel length-width plane are analyzed.

A two-stage rule-constrained seedless region growing approach for mandibular body segmentation in MRI.

PubMed

Ji, Dong Xu; Foong, Kelvin Weng Chiong; Ong, Sim Heng

2013-09-01

Extraction of the mandible from 3D volumetric images is frequently required for surgical planning and evaluation. Image segmentation from MRI is more complex than CT due to lower bony signal-to-noise. An automated method to extract the human mandible body shape from magnetic resonance (MR) images of the head was developed and tested. Anonymous MR images data sets of the head from 12 subjects were subjected to a two-stage rule-constrained region growing approach to derive the shape of the body of the human mandible. An initial thresholding technique was applied followed by a 3D seedless region growing algorithm to detect a large portion of the trabecular bone (TB) regions of the mandible. This stage is followed with a rule-constrained 2D segmentation of each MR axial slice to merge the remaining portions of the TB regions with lower intensity levels. The two-stage approach was replicated to detect the cortical bone (CB) regions of the mandibular body. The TB and CB regions detected from the preceding steps were merged and subjected to a series of morphological processes for completion of the mandibular body region definition. Comparisons of the accuracy of segmentation between the two-stage approach, conventional region growing method, 3D level set method, and manual segmentation were made with Jaccard index, Dice index, and mean surface distance (MSD). The mean accuracy of the proposed method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of CRG is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of the 3D level set method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The proposed method shows improvement in accuracy over CRG and 3D level set. Accurate segmentation of the body of the human mandible from MR images is achieved with the proposed two-stage rule-constrained seedless region growing approach. The accuracy achieved with the two-stage approach is higher than CRG and 3D level set.

The Use of Blood Vessel–Derived Stem Cells for Meniscal Regeneration and Repair

PubMed Central

OSAWA, AKI; HARNER, CHRISTOPHER D.; GHARAIBEH, BURHAN; MATSUMOTO, TOMOYUKI; MIFUNE, YUTAKA; KOPF, SEBASTIAN; INGHAM, SHEILA J. M.; SCHREIBER, VERENA; USAS, ARVYDAS; HUARD, JOHNNY

2015-01-01

Purpose Surgical repairs of tears in the vascular region of the meniscus usually heal better than repairs performed in the avascular region; thus, we hypothesized that this region might possess a richer supply of vascular-derived stem cells than the avascular region. Methods In this study, we analyzed 6 menisci extracted from aborted human fetuses and 12 human lateral menisci extracted from adult human subjects undergoing total knee arthroplasty. Menisci were immunostained for CD34 (a stem cell marker) and CD146 (a pericyte marker) in situ, whereas other menisci were dissected into two regions (peripheral and inner) and used to isolate meniscus-derived cells by flow cytometry. Cell populations expressing CD34 and CD146 were tested for their multi-lineage differentiation potentials, including chondrogenic, osteogenic, and adipogenic lineages. Fetal peripheral meniscus cells were transplanted by intracapsular injection into the knee joints of an athymic rat meniscal tear model. Rat menisci were extracted and histologically evaluated after 4 wk posttransplantation. Results Immunohistochemistry and flow cytometric analyses demonstrated that a higher number of CD34- and CD146-positive cells were found in the peripheral region compared with the inner region. The CD34- and CD146-positive cells isolated from the vascular region of both fetal and adult menisci demonstrated multilineage differentiation capacities and were more potent than cells isolated from the inner (avascular) region. Fetal CD34- and CD146-positive cells transplanted into the athymic rat knee joint were recruited into the meniscal tear sites and contributed to meniscus repair. Conclusions The vascularized region of the meniscus contains more stem cells than the avascular region. These meniscal-derived stem cells were multi-potent and contributed to meniscal regeneration. PMID:23247715

Evaluating variation in human gut microbiota profiles due to DNA extraction method and inter-subject differences.

PubMed

Wagner Mackenzie, Brett; Waite, David W; Taylor, Michael W

2015-01-01

The human gut contains dense and diverse microbial communities which have profound influences on human health. Gaining meaningful insights into these communities requires provision of high quality microbial nucleic acids from human fecal samples, as well as an understanding of the sources of variation and their impacts on the experimental model. We present here a systematic analysis of commonly used microbial DNA extraction methods, and identify significant sources of variation. Five extraction methods (Human Microbiome Project protocol, MoBio PowerSoil DNA Isolation Kit, QIAamp DNA Stool Mini Kit, ZR Fecal DNA MiniPrep, phenol:chloroform-based DNA isolation) were evaluated based on the following criteria: DNA yield, quality and integrity, and microbial community structure based on Illumina amplicon sequencing of the V4 region of bacterial and archaeal 16S rRNA genes. Our results indicate that the largest portion of variation within the model was attributed to differences between subjects (biological variation), with a smaller proportion of variation associated with DNA extraction method (technical variation) and intra-subject variation. A comprehensive understanding of the potential impact of technical variation on the human gut microbiota will help limit preventable bias, enabling more accurate diversity estimates.

Combination of HPLC chromatogram and hypoglycemic effect identifies isoflavones as the principal active fraction of Belamcanda chinensis leaf extract in diabetes treatment.

PubMed

Chen, Yan; Wu, Chong-Ming; Dai, Rong-Ji; Li, Liang; Yu, Yu-Hong; Li, Yan; Meng, Wei-Wei; Zhang, Liang; Zhang, Yongqian; Deng, Yu-Lin

2011-02-15

In previous study, we demonstrated the hypoglycemic effect of aqueous extract of Belamcanda chinensis leaves in rats. Here, we separated the aqueous extract of B. chinensis leaves and investigated the spectrum-effect relationships between HPLC chromatograms and hypoglycemic activities of different isolates from B. chinensis leaf extract. Sequential solvent extraction with petroleum ether, chloroform, acetic ester and n-butanol provided several isolates showing similar hypoglycemic activities, making it difficult to discriminate the active fractions. Stepwise elution through HP20 macroporous resin by water, 40% and 95% ethanol provided isolates with distinct hypoglycemic activities, representing a simple, rapid and efficient preparative separation method. Combination of HPLC chromatogram and pharmacological effect targeted a hypoglycemic activity-related region in HPLC chromatogram. Each peak in this region was analyzed by UV spectrum scan. Most of them were flavonoids in which tectoridin and swertisin were known flavonoids with anti-diabetic activities. In together, this work provides a general model of combination of HPLC chromatography and pharmacological effect to study the spectrum-effect relationships of aqueous extract from B. chinensis leaves, which can be used to find principle components of B. chinensis on pharmacological activity. Copyright © 2011 Elsevier B.V. All rights reserved.

Automatic facial animation parameters extraction in MPEG-4 visual communication

NASA Astrophysics Data System (ADS)

Yang, Chenggen; Gong, Wanwei; Yu, Lu

2002-01-01

Facial Animation Parameters (FAPs) are defined in MPEG-4 to animate a facial object. The algorithm proposed in this paper to extract these FAPs is applied to very low bit-rate video communication, in which the scene is composed of a head-and-shoulder object with complex background. This paper addresses the algorithm to automatically extract all FAPs needed to animate a generic facial model, estimate the 3D motion of head by points. The proposed algorithm extracts human facial region by color segmentation and intra-frame and inter-frame edge detection. Facial structure and edge distribution of facial feature such as vertical and horizontal gradient histograms are used to locate the facial feature region. Parabola and circle deformable templates are employed to fit facial feature and extract a part of FAPs. A special data structure is proposed to describe deformable templates to reduce time consumption for computing energy functions. Another part of FAPs, 3D rigid head motion vectors, are estimated by corresponding-points method. A 3D head wire-frame model provides facial semantic information for selection of proper corresponding points, which helps to increase accuracy of 3D rigid object motion estimation.

Testing the application of Teflon/quartz soil solution samplers for DOM sampling in the Critical Zone: Field and laboratory approaches

NASA Astrophysics Data System (ADS)

Dolan, E. M.; Perdrial, J. N.; Vazquez, A.; Hernández, S.; Chorover, J.

2010-12-01

Elizabeth Dolan1,2, Julia Perdrial3, Angélica Vázquez-Ortega3, Selene Hernández-Ruiz3, Jon Chorover3 1Deptartment of Soil, Environmental, and Atmospheric Science, University of Missouri. 2Biosphere 2, University of Arizona. 3Deptartment of Soil, Water, and Environmental Science, University of Arizona. Abstract: The behavior of dissolved organic matter (DOM) in soil is important to many biogeochemical processes. Extraction methods to obtain DOM from the unsaturated zone remain a current focus of research as different methods can influence the type and concentration of DOM obtained. Thus, the present comparison study involves three methods for soil solution sampling to assess their impact on DOM quantity and quality: 1) aqueous soil extracts, 2) solution yielded from laboratory installed suction cup samplers and 3) solutions from field installed suction cup samplers. All samples were analyzed for dissolved organic carbon and total nitrogen concentrations. Moreover, DOM quality was analyzed using fluorescence, UV-Vis and FTIR spectroscopies. Results indicate higher DOC values for laboratory extracted DOM: 20 mg/L for aqueous soil extracts and 31 mg/L for lab installed samplers compared to 12 mg/L for field installed samplers. Large variations in C/N ratios were also observed ranging from 1.5 in laboratory extracted DOM to 11 in field samples. Fluorescence excitation-emission matrices of DOM solutions obtained for the laboratory extraction methods showed higher intensities in regions typical for fulvic and humic acid-like materials relative to those extracted in the field. Similarly, the molar absorptivity calculated from DOC concentration normalization of UV-Vis absorbance of the laboratory-derived solutions was significantly higher as well, indicating greater aromaticity. The observed differences can be attributed to soil disturbance associated with obtaining laboratory derived solution samples. Our results indicate that laboratory extraction methods are not comparable to in-situ field soil solution extraction in terms of DOM.

Detection of blur artifacts in histopathological whole-slide images of endomyocardial biopsies.

PubMed

Hang Wu; Phan, John H; Bhatia, Ajay K; Cundiff, Caitlin A; Shehata, Bahig M; Wang, May D

2015-01-01

Histopathological whole-slide images (WSIs) have emerged as an objective and quantitative means for image-based disease diagnosis. However, WSIs may contain acquisition artifacts that affect downstream image feature extraction and quantitative disease diagnosis. We develop a method for detecting blur artifacts in WSIs using distributions of local blur metrics. As features, these distributions enable accurate classification of WSI regions as sharp or blurry. We evaluate our method using over 1000 portions of an endomyocardial biopsy (EMB) WSI. Results indicate that local blur metrics accurately detect blurry image regions.

Highway extraction from high resolution aerial photography using a geometric active contour model

NASA Astrophysics Data System (ADS)

Niu, Xutong

Highway extraction and vehicle detection are two of the most important steps in traffic-flow analysis from multi-frame aerial photographs. The traditional method of deriving traffic flow trajectories relies on manual vehicle counting from a sequence of aerial photographs, which is tedious and time-consuming. This research presents a new framework for semi-automatic highway extraction. The basis of the new framework is an improved geometric active contour (GAC) model. This novel model seeks to minimize an objective function that transforms a problem of propagation of regular curves into an optimization problem. The implementation of curve propagation is based on level set theory. By using an implicit representation of a two-dimensional curve, a level set approach can be used to deal with topological changes naturally, and the output is unaffected by different initial positions of the curve. However, the original GAC model, on which the new model is based, only incorporates boundary information into the curve propagation process. An error-producing phenomenon called leakage is inevitable wherever there is an uncertain weak edge. In this research, region-based information is added as a constraint into the original GAC model, thereby, giving this proposed method the ability of integrating both boundary and region-based information during the curve propagation. Adding the region-based constraint eliminates the leakage problem. This dissertation applies the proposed augmented GAC model to the problem of highway extraction from high-resolution aerial photography. First, an optimized stopping criterion is designed and used in the implementation of the GAC model. It effectively saves processing time and computations. Second, a seed point propagation framework is designed and implemented. This framework incorporates highway extraction, tracking, and linking into one procedure. A seed point is usually placed at an end node of highway segments close to the boundary of the image or at a position where possible blocking may occur, such as at an overpass bridge or near vehicle crowds. These seed points can be automatically propagated throughout the entire highway network. During the process, road center points are also extracted, which introduces a search direction for solving possible blocking problems. This new framework has been successfully applied to highway network extraction from a large orthophoto mosaic. In the process, vehicles on the highway extracted from mosaic were detected with an 83% success rate.

Creation of the sole regional laser lead extraction program serving Atlantic Canada: initial experience

PubMed Central

Williams, Kenneth J.; O’Keefe, Scott; Légaré, Jean-Francois

2016-01-01

Background An increasing need for laser lead extraction has grown in parallel with the increase of implantation of pacing and defibrillating devices. We reviewed the initial experience of a regional laser-assisted lead extraction program serving Atlantic Canada. Methods We retrospectively reviewed the cases of all consecutive patients who underwent laser lead extraction at the Maritime Heart Centre in Halifax, NS, between 2006 and 2015. We conducted univariate and Kaplan–Meier survivorship analyses. Results During the 9-year study period, 108 consecutive patients underwent laser lead extractions (218 leads extracted). The most common indication for extraction was infection (84.3%). Most patients were older than 60 years (73.1%) and had leads chronically implanted; the explanted leads were an average of 7.5 ± 6.8 years old. Procedural and clinical success (resolution of preoperative symptoms) rates and mortality were 96.8%, 97.2%, and 0.9%, respectively. Sternotomy procedures were performed in 3 instances: once for vascular repair due to perforation and twice to ensure that all infected lead material was removed. No minor complications required surgical intervention. Survival after discharge was 98.4% at 30 days and 94% at 12 months. Conclusion Atlantic Canada’s sole surgical extraction centre achieved high extraction success with a low complication rate. Lead extraction in an operative setting provides for immediate surgical intervention and is essential for the survival of patients with complicated cases. Surgeons must weigh the risks versus benefits in patients older than 60 years who have chronically implanted leads (> 1 yr) and infection. PMID:26999473

Application of Modified Particle Swarm Optimization Method for Parameter Extraction of 2-D TEC Mapping

NASA Astrophysics Data System (ADS)

Toker, C.; Gokdag, Y. E.; Arikan, F.; Arikan, O.

2012-04-01

Ionosphere is a very important part of Space Weather. Modeling and monitoring of ionospheric variability is a major part of satellite communication, navigation and positioning systems. Total Electron Content (TEC), which is defined as the line integral of the electron density along a ray path, is one of the parameters to investigate the ionospheric variability. Dual-frequency GPS receivers, with their world wide availability and efficiency in TEC estimation, have become a major source of global and regional TEC modeling. When Global Ionospheric Maps (GIM) of International GPS Service (IGS) centers (http://iono.jpl.nasa.gov/gim.html) are investigated, it can be observed that regional ionosphere along the midlatitude regions can be modeled as a constant, linear or a quadratic surface. Globally, especially around the magnetic equator, the TEC surfaces resemble twisted and dispersed single centered or double centered Gaussian functions. Particle Swarm Optimization (PSO) proved itself as a fast converging and an effective optimization tool in various diverse fields. Yet, in order to apply this optimization technique into TEC modeling, the method has to be modified for higher efficiency and accuracy in extraction of geophysical parameters such as model parameters of TEC surfaces. In this study, a modified PSO (mPSO) method is applied to regional and global synthetic TEC surfaces. The synthetic surfaces that represent the trend and small scale variability of various ionospheric states are necessary to compare the performance of mPSO over number of iterations, accuracy in parameter estimation and overall surface reconstruction. The Cramer-Rao bounds for each surface type and model are also investigated and performance of mPSO are tested with respect to these bounds. For global models, the sample points that are used in optimization are obtained using IGS receiver network. For regional TEC models, regional networks such as Turkish National Permanent GPS Network (TNPGN-Active) receiver sites are used. The regional TEC models are grouped into constant (one parameter), linear (two parameters), and quadratic (six parameters) surfaces which are functions of latitude and longitude. Global models require seven parameters for single centered Gaussian and 13 parameters for double centered Gaussian function. The error criterion is the normalized percentage error for both the surface and the parameters. It is observed that mPSO is very successful in parameter extraction of various regional and global models. The normalized reconstruction error varies from 10-4 for constant surfaces to 10-3 for quadratic surfaces in regional models, sampled with regional networks. Even for the cases of a severe geomagnetic storm that affects measurements globally, with IGS network, the reconstruction error is on the order of 10-1 even though individual parameters have higher normalized errors. The modified PSO technique proved itself to be a useful tool for parameter extraction of more complicated TEC models. This study is supported by TUBITAK EEEAG under Grant No: 109E055.

Optimisation of 16S rRNA gut microbiota profiling of extremely low birth weight infants.

PubMed

Alcon-Giner, Cristina; Caim, Shabhonam; Mitra, Suparna; Ketskemety, Jennifer; Wegmann, Udo; Wain, John; Belteki, Gusztav; Clarke, Paul; Hall, Lindsay J

2017-11-02

Infants born prematurely, particularly extremely low birth weight infants (ELBW) have altered gut microbial communities. Factors such as maternal health, gut immaturity, delivery mode, and antibiotic treatments are associated with microbiota disturbances, and are linked to an increased risk of certain diseases such as necrotising enterocolitis. Therefore, there is a requirement to optimally characterise microbial profiles in this at-risk cohort, via standardisation of methods, particularly for studying the influence of microbiota therapies (e.g. probiotic supplementation) on community profiles and health outcomes. Profiling of faecal samples using the 16S rRNA gene is a cost-efficient method for large-scale clinical studies to gain insights into the gut microbiota and additionally allows characterisation of cohorts were sample quantities are compromised (e.g. ELBW infants). However, DNA extraction method, and the 16S rRNA region targeted can significantly change bacterial community profiles obtained, and so confound comparisons between studies. Thus, we sought to optimise a 16S rRNA profiling protocol to allow standardisation for studying ELBW infant faecal samples, with or without probiotic supplementation. Using ELBW faecal samples, we compared three different DNA extraction methods, and subsequently PCR amplified and sequenced three hypervariable regions of the 16S rRNA gene (V1 + V2 + V3), (V4 + V5) and (V6 + V7 + V8), and compared two bioinformatics approaches to analyse results (OTU and paired end). Paired shotgun metagenomics was used as a 'gold-standard'. Results indicated a longer bead-beating step was required for optimal bacterial DNA extraction and that sequencing regions (V1 + V2 + V3) and (V6 + V7 + V8) provided the most representative taxonomic profiles, which was confirmed via shotgun analysis. Samples sequenced using the (V4 + V5) region were found to be underrepresented in specific taxa including Bifidobacterium, and had altered diversity profiles. Both bioinformatics 16S rRNA pipelines used in this study (OTU and paired end) presented similar taxonomic profiles at genus level. We determined that DNA extraction from ELBW faecal samples, particularly those infants receiving probiotic supplementation, should include a prolonged beat-beating step. Furthermore, use of the 16S rRNA (V1 + V2 + V3) and (V6 + V7 + V8) regions provides reliable representation of ELBW microbiota profiles, while inclusion of the (V4 + V5) region may not be appropriate for studies where Bifidobacterium constitutes a resident microbiota member.

Medical image retrieval system using multiple features from 3D ROIs

NASA Astrophysics Data System (ADS)

Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming

2012-02-01

Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

Identification and extraction of the seaward edge of terrestrial vegetation using digital aerial photography

USGS Publications Warehouse

Harris, Melanie; Brock, John C.; Nayegandhi, A.; Duffy, M.; Wright, C.W.

2006-01-01

This report is created as part of the Aerial Data Collection and Creation of Products for Park Vital Signs Monitoring within the Northeast Region Coastal and Barrier Network project, which is a joint project between the National Park Service Inventory and Monitoring Program (NPS-IM), the National Aeronautics and Space Administration (NASA) Observational Sciences Branch, and the U.S. Geological Survey (USGS) Center for Coastal and Watershed Studies (CCWS). This report is one of a series that discusses methods for extracting topographic features from aerial survey data. It details step-by-step methods used to extract a spatially referenced digital line from aerial photography that represents the seaward edge of terrestrial vegetation along the coast of Assateague Island National Seashore (ASIS). One component of the NPS-IM/USGS/NASA project includes the collection of NASA aerial surveys over various NPS barrier islands and coastal parks throughout the National Park Service's Northeast Region. These aerial surveys consist of collecting optical remote sensing data from a variety of sensors, including the NASA Airborne Topographic Mapper (ATM), the NASA Experimental Advanced Airborne Research Lidar (EAARL), and down-looking digital mapping cameras.

A Unified Approach to Joint Regional/Teleseismic Calibration and Event Location with a 3D Earth Model

DTIC Science & Technology

2010-09-01

raytracing and travel-time calculation in 3D Earth models, such as the finite-difference eikonal method (e.g., Podvin and Lecomte, 1991), fast...by Reiter and Rodi (2009) in constructing JWM. Two teleseismic data sets were considered, both extracted from the EHB database (Engdahl et al...extracted from the updated EHB database distributed by the International Seismological Centre (http://www.isc.ac.uk/EHB/index.html). The new database

Target 3-D reconstruction of streak tube imaging lidar based on Gaussian fitting

NASA Astrophysics Data System (ADS)

Yuan, Qingyu; Niu, Lihong; Hu, Cuichun; Wu, Lei; Yang, Hongru; Yu, Bing

2018-02-01

Streak images obtained by the streak tube imaging lidar (STIL) contain the distance-azimuth-intensity information of a scanned target, and a 3-D reconstruction of the target can be carried out through extracting the characteristic data of multiple streak images. Significant errors will be caused in the reconstruction result by the peak detection method due to noise and other factors. So as to get a more precise 3-D reconstruction, a peak detection method based on Gaussian fitting of trust region is proposed in this work. Gaussian modeling is performed on the returned wave of single time channel of each frame, then the modeling result which can effectively reduce the noise interference and possesses a unique peak could be taken as the new returned waveform, lastly extracting its feature data through peak detection. The experimental data of aerial target is for verifying this method. This work shows that the peak detection method based on Gaussian fitting reduces the extraction error of the feature data to less than 10%; utilizing this method to extract the feature data and reconstruct the target make it possible to realize the spatial resolution with a minimum 30 cm in the depth direction, and improve the 3-D imaging accuracy of the STIL concurrently.

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

Xu, Q; Han, H; Xing, L

Purpose: Dictionary learning based method has attracted more and more attentions in low-dose CT due to the superior performance on suppressing noise and preserving structural details. Considering the structures and noise vary from region to region in one imaging object, we propose a region-specific dictionary learning method to improve the low-dose CT reconstruction. Methods: A set of normal-dose images was used for dictionary learning. Segmentations were performed on these images, so that the training patch sets corresponding to different regions can be extracted out. After that, region-specific dictionaries were learned from these training sets. For the low-dose CT reconstruction, amore » conventional reconstruction, such as filtered back-projection (FBP), was performed firstly, and then segmentation was followed to segment the image into different regions. Sparsity constraints of each region based on its dictionary were used as regularization terms. The regularization parameters were selected adaptively according to different regions. A low-dose human thorax dataset was used to evaluate the proposed method. The single dictionary based method was performed for comparison. Results: Since the lung region is very different from the other part of thorax, two dictionaries corresponding to lung region and the rest part of thorax respectively were learned to better express the structural details and avoid artifacts. With only one dictionary some artifact appeared in the body region caused by the spot atoms corresponding to the structures in the lung region. And also some structure in the lung regions cannot be recovered well by only one dictionary. The quantitative indices of the result by the proposed method were also improved a little compared to the single dictionary based method. Conclusion: Region-specific dictionary can make the dictionary more adaptive to different region characteristics, which is much desirable for enhancing the performance of dictionary learning based method.« less

Automatic detection of multi-level acetowhite regions in RGB color images of the uterine cervix

NASA Astrophysics Data System (ADS)

Lange, Holger

2005-04-01

Uterine cervical cancer is the second most common cancer among women worldwide. Colposcopy is a diagnostic method used to detect cancer precursors and cancer of the uterine cervix, whereby a physician (colposcopist) visually inspects the metaplastic epithelium on the cervix for certain distinctly abnormal morphologic features. A contrast agent, a 3-5% acetic acid solution, is used, causing abnormal and metaplastic epithelia to turn white. The colposcopist considers diagnostic features such as the acetowhite, blood vessel structure, and lesion margin to derive a clinical diagnosis. STI Medical Systems is developing a Computer-Aided-Diagnosis (CAD) system for colposcopy -- ColpoCAD, a complex image analysis system that at its core assesses the same visual features as used by colposcopists. The acetowhite feature has been identified as one of the most important individual predictors of lesion severity. Here, we present the details and preliminary results of a multi-level acetowhite region detection algorithm for RGB color images of the cervix, including the detection of the anatomic features: cervix, os and columnar region, which are used for the acetowhite region detection. The RGB images are assumed to be glare free, either obtained by cross-polarized image acquisition or glare removal pre-processing. The basic approach of the algorithm is to extract a feature image from the RGB image that provides a good acetowhite to cervix background ratio, to segment the feature image using novel pixel grouping and multi-stage region-growing algorithms that provide region segmentations with different levels of detail, to extract the acetowhite regions from the region segmentations using a novel region selection algorithm, and then finally to extract the multi-levels from the acetowhite regions using multiple thresholds. The performance of the algorithm is demonstrated using human subject data.

On consistent inter-view synthesis for autostereoscopic displays

NASA Astrophysics Data System (ADS)

Tran, Lam C.; Bal, Can; Pal, Christopher J.; Nguyen, Truong Q.

2012-03-01

In this paper we present a novel stereo view synthesis algorithm that is highly accurate with respect to inter-view consistency, thus to enabling stereo contents to be viewed on the autostereoscopic displays. The algorithm finds identical occluded regions within each virtual view and aligns them together to extract a surrounding background layer. The background layer for each occluded region is then used with an exemplar based inpainting method to synthesize all virtual views simultaneously. Our algorithm requires the alignment and extraction of background layers for each occluded region; however, these two steps are done efficiently with lower computational complexity in comparison to previous approaches using the exemplar based inpainting algorithms. Thus, it is more efficient than existing algorithms that synthesize one virtual view at a time. This paper also describes the implementation of a simplified GPU accelerated version of the approach and its implementation in CUDA. Our CUDA method has sublinear complexity in terms of the number of views that need to be generated, which makes it especially useful for generating content for autostereoscopic displays that require many views to operate. An objective of our work is to allow the user to change depth and viewing perspective on the fly. Therefore, to further accelerate the CUDA variant of our approach, we present a modified version of our method to warp the background pixels from reference views to a middle view to recover background pixels. We then use an exemplar based inpainting method to fill in the occluded regions. We use warping of the foreground from the reference images and background from the filled regions to synthesize new virtual views on the fly. Our experimental results indicate that the simplified CUDA implementation decreases running time by orders of magnitude with negligible loss in quality. [Figure not available: see fulltext.

Marker Registration Technique for Handwritten Text Marker in Augmented Reality Applications

NASA Astrophysics Data System (ADS)

Thanaborvornwiwat, N.; Patanukhom, K.

2018-04-01

Marker registration is a fundamental process to estimate camera poses in marker-based Augmented Reality (AR) systems. We developed AR system that creates correspondence virtual objects on handwritten text markers. This paper presents a new method for registration that is robust for low-content text markers, variation of camera poses, and variation of handwritten styles. The proposed method uses Maximally Stable Extremal Regions (MSER) and polygon simplification for a feature point extraction. The experiment shows that we need to extract only five feature points per image which can provide the best registration results. An exhaustive search is used to find the best matching pattern of the feature points in two images. We also compared performance of the proposed method to some existing registration methods and found that the proposed method can provide better accuracy and time efficiency.

Image-based Analysis of Emotional Facial Expressions in Full Face Transplants.

PubMed

Bedeloglu, Merve; Topcu, Çagdas; Akgul, Arzu; Döger, Ela Naz; Sever, Refik; Ozkan, Ozlenen; Ozkan, Omer; Uysal, Hilmi; Polat, Ovunc; Çolak, Omer Halil

2018-01-20

In this study, it is aimed to determine the degree of the development in emotional expression of full face transplant patients from photographs. Hence, a rehabilitation process can be planned according to the determination of degrees as a later work. As envisaged, in full face transplant cases, the determination of expressions can be confused or cannot be achieved as the healthy control group. In order to perform image-based analysis, a control group consist of 9 healthy males and 2 full-face transplant patients participated in the study. Appearance-based Gabor Wavelet Transform (GWT) and Local Binary Pattern (LBP) methods are adopted for recognizing neutral and 6 emotional expressions which consist of angry, scared, happy, hate, confused and sad. Feature extraction was carried out by using both methods and combination of these methods serially. In the performed expressions, the extracted features of the most distinct zones in the facial area where the eye and mouth region, have been used to classify the emotions. Also, the combination of these region features has been used to improve classifier performance. Control subjects and transplant patients' ability to perform emotional expressions have been determined with K-nearest neighbor (KNN) classifier with region-specific and method-specific decision stages. The results have been compared with healthy group. It has been observed that transplant patients don't reflect some emotional expressions. Also, there were confusions among expressions.

Preparation of Formalin-fixed Paraffin-embedded Tissue Cores for both RNA and DNA Extraction.

PubMed

Patel, Palak G; Selvarajah, Shamini; Boursalie, Suzanne; How, Nathan E; Ejdelman, Joshua; Guerard, Karl-Philippe; Bartlett, John M; Lapointe, Jacques; Park, Paul C; Okello, John B A; Berman, David M

2016-08-21

Formalin-fixed paraffin embedded tissue (FFPET) represents a valuable, well-annotated substrate for molecular investigations. The utility of FFPET in molecular analysis is complicated both by heterogeneous tissue composition and low yields when extracting nucleic acids. A literature search revealed a paucity of protocols addressing these issues, and none that showed a validated method for simultaneous extraction of RNA and DNA from regions of interest in FFPET. This method addresses both issues. Tissue specificity was achieved by mapping cancer areas of interest on microscope slides and transferring annotations onto FFPET blocks. Tissue cores were harvested from areas of interest using 0.6 mm microarray punches. Nucleic acid extraction was performed using a commercial FFPET extraction system, with modifications to homogenization, deparaffinization, and Proteinase K digestion steps to improve tissue digestion and increase nucleic acid yields. The modified protocol yields sufficient quantity and quality of nucleic acids for use in a number of downstream analyses, including a multi-analyte gene expression platform, as well as reverse transcriptase coupled real time PCR analysis of mRNA expression, and methylation-specific PCR (MSP) analysis of DNA methylation.

Gas chromatography-mass spectrometry of biofluids and extracts.

PubMed

Emwas, Abdul-Hamid M; Al-Talla, Zeyad A; Yang, Yang; Kharbatia, Najeh M

2015-01-01

Gas chromatography-mass spectrometry (GC-MS) has been widely used in metabonomics analyses of biofluid samples. Biofluids provide a wealth of information about the metabolism of the whole body and from multiple regions of the body that can be used to study general health status and organ function. Blood serum and blood plasma, for example, can provide a comprehensive picture of the whole body, while urine can be used to monitor the function of the kidneys, and cerebrospinal fluid (CSF) will provide information about the status of the brain and central nervous system (CNS). Different methods have been developed for the extraction of metabolites from biofluids, these ranging from solvent extracts, acids, heat denaturation, and filtration. These methods vary widely in terms of efficiency of protein removal and in the number of metabolites extracted. Consequently, for all biofluid-based metabonomics studies, it is vital to optimize and standardize all steps of sample preparation, including initial extraction of metabolites. In this chapter, recommendations are made of the optimum experimental conditions for biofluid samples for GC-MS, with a particular focus on blood serum and plasma samples.

Automated lung tumor segmentation for whole body PET volume based on novel downhill region growing

NASA Astrophysics Data System (ADS)

Ballangan, Cherry; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Feng, Dagan

2010-03-01

We propose an automated lung tumor segmentation method for whole body PET images based on a novel downhill region growing (DRG) technique, which regards homogeneous tumor hotspots as 3D monotonically decreasing functions. The method has three major steps: thoracic slice extraction with K-means clustering of the slice features; hotspot segmentation with DRG; and decision tree analysis based hotspot classification. To overcome the common problem of leakage into adjacent hotspots in automated lung tumor segmentation, DRG employs the tumors' SUV monotonicity features. DRG also uses gradient magnitude of tumors' SUV to improve tumor boundary definition. We used 14 PET volumes from patients with primary NSCLC for validation. The thoracic region extraction step achieved good and consistent results for all patients despite marked differences in size and shape of the lungs and the presence of large tumors. The DRG technique was able to avoid the problem of leakage into adjacent hotspots and produced a volumetric overlap fraction of 0.61 +/- 0.13 which outperformed four other methods where the overlap fraction varied from 0.40 +/- 0.24 to 0.59 +/- 0.14. Of the 18 tumors in 14 NSCLC studies, 15 lesions were classified correctly, 2 were false negative and 15 were false positive.

Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency.

PubMed

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-05-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Antioxidant Potential and DNA Damage Protection by the Slate Grey Saddle Mushroom, Helvella lacunosa (Ascomycetes), from Kashmir Himalaya (India).

PubMed

Shameem, Nowsheen; Kamili, Azra N; Ahmad, Mushtaq; Masoodi, F A; Parray, Javid A

2016-01-01

This study pertains to the radical scavenging potential of and DNA protection by Helvella lacunosa, an edible mushroom from Kashmir Himalaya (India). Different solvents, on the basis of their polarities, were used to extract all solvent-soluble bioactive compounds. Seven different antioxidant methods were also used to determine extensive radical scavenging activity. The mushroom ethanol extract and butanol extract showed effective scavenging activity of radicals at 95% and 89%, respectively. At 800 µg/mg, the ethanol extract was potent enough to protect DNA from degradation by hydroxyl radicals. It is evident from these findings that the presence of antioxidant substances signifies the use of H. lacunosa as food in the mountainous valleys of the Himalayan region.

Chemical composition and biological properties of Satureja avromanica Maroofi.

PubMed

Abdali, Elham; Javadi, Shima; Akhgari, Maryam; Hosseini, Seyran; Dastan, Dara

2017-03-01

Satureja avromanica is an indigenous plant which is frequently used as a spice in Avraman-Kurdistan region of Iran. The present study aimed to investigate the chemical composition, antimicrobial and antioxidant properties of the S. avromanica . In addition, rosmarinic acid and total phenolic content of S. avromanica was assessed by spectrophotometric method and HPTLC. The essential oil and methanolic extract were isolated by hydrodistillation and maceration methods, respectively. A total of 32 compounds representing 98.6% of the essential oil were identified by GC-MS and GC-FID. The main constituents were n -pentacosane (23.8%), spathulenol (11.5%), β-bourbonen (11.3%) and n -docosane (11.0%). The antibacterial activity of samples were carried out by disc diffusion method and evaluate the minimal inhibitory concentration (MIC) essential oil and methanolic extract were found to be effective against Staphylococcus aureus , Bacillus cereus and Bacillus pumilus . The highest scavenging activity was found for methanolic extract of S. avromanica (21.58 µg/mL) and the total phenolics of methanolic extract of S. avromanica was 95.3 mg GAE/g. The rosmarinic acid content of S. avromanica methanolic extract was 0.83 mg/g plant. Antioxidant activity and rosmarininc acid content of S. avromanica suggests that the essential oil and methanolic extract of S. avromanica has great potential for application as a natural antimicrobial and antioxidant agent to preserve food.

Tapping into the Hexagon spy imagery database: A new automated pipeline for geomorphic change detection

NASA Astrophysics Data System (ADS)

Maurer, Joshua; Rupper, Summer

2015-10-01

Declassified historical imagery from the Hexagon spy satellite database has near-global coverage, yet remains a largely untapped resource for geomorphic change studies. Unavailable satellite ephemeris data make DEM (digital elevation model) extraction difficult in terms of time and accuracy. A new fully-automated pipeline for DEM extraction and image orthorectification is presented which yields accurate results and greatly increases efficiency over traditional photogrammetric methods, making the Hexagon image database much more appealing and accessible. A 1980 Hexagon DEM is extracted and geomorphic change computed for the Thistle Creek Landslide region in the Wasatch Range of North America to demonstrate an application of the new method. Surface elevation changes resulting from the landslide show an average elevation decrease of 14.4 ± 4.3 m in the source area, an increase of 17.6 ± 4.7 m in the deposition area, and a decrease of 30.2 ± 5.1 m resulting from a new roadcut. Two additional applications of the method include volume estimates of material excavated during the Mount St. Helens volcanic eruption and the volume of net ice loss over a 34-year period for glaciers in the Bhutanese Himalayas. These results show the value of Hexagon imagery in detecting and quantifying historical geomorphic change, especially in regions where other data sources are limited.

Detection of protruding lesion in wireless capsule endoscopy videos of small intestine

NASA Astrophysics Data System (ADS)

Wang, Chengliang; Luo, Zhuo; Liu, Xiaoqi; Bai, Jianying; Liao, Guobin

2018-02-01

Wireless capsule endoscopy (WCE) is a developed revolutionary technology with important clinical benefits. But the huge image data brings a heavy burden to the doctors for locating and diagnosing the lesion images. In this paper, a novel and efficient approach is proposed to help clinicians to detect protruding lesion images in small intestine. First, since there are many possible disturbances such as air bubbles and so on in WCE video frames, which add the difficulty of efficient feature extraction, the color-saliency region detection (CSD) method is developed for extracting the potentially saliency region of interest (SROI). Second, a novel color channels modelling of local binary pattern operator (CCLBP) is proposed to describe WCE images, which combines grayscale and color angle. The CCLBP feature is more robust to variation of illumination and more discriminative for classification. Moreover, support vector machine (SVM) classifier with CCLBP feature is utilized to detect protruding lesion images. Experimental results on real WCE images demonstrate that proposed method has higher accuracy on protruding lesion detection than some art-of-state methods.

Finger tips detection for two handed gesture recognition

NASA Astrophysics Data System (ADS)

Bhuyan, M. K.; Kar, Mithun Kumar; Neog, Debanga Raj

2011-10-01

In this paper, a novel algorithm is proposed for fingertips detection in view of two-handed static hand pose recognition. In our method, finger tips of both hands are detected after detecting hand regions by skin color-based segmentation. At first, the face is removed in the image by using Haar classifier and subsequently, the regions corresponding to the gesturing hands are isolated by a region labeling technique. Next, the key geometric features characterizing gesturing hands are extracted for two hands. Finally, for all possible/allowable finger movements, a probabilistic model is developed for pose recognition. Proposed method can be employed in a variety of applications like sign language recognition and human-robot-interactions etc.

Identification and determination of the saikosaponins in Radix bupleuri by accelerated solvent extraction combined with rapid-resolution LC-MS.

PubMed

Yang, Yun-Yun; Tang, You-Zhi; Fan, Chun-Lin; Luo, Hui-Tai; Guo, Peng-Ran; Chen, Jian-Xin

2010-07-01

A method based on accelerated solvent extraction combined with rapid-resolution LC-MS for efficient extraction, rapid separation, online identification and accurate determination of the saikosaponins (SSs) in Radix bupleuri (RB) was developed. The RB samples were extracted by accelerated solvent extraction using 70% aqueous ethanol v/v as solvent, at a temperature of 120 degrees C and pressure of 100 bar, with 10 min of static extraction time and three extraction cycles. Rapid-resolution LC separation was performed by using a C(18) column at gradient elution of water (containing 0.5% formic acid) and acetonitrile, and the major constituents were well separated within 20 min. A TOF-MS and an IT-MS were used for online identification of the major constituents, and 27 SSs were identified or tentatively identified. Five major bioactive SSs (SSa, SSc, SSd, 6''-O-acetyl-SSa and 6''-O-acetyl-SSd) with obvious peak areas and good resolution were chosen as benchmark substances, and a triple quadrupole MS operating in multiple-reaction monitoring mode was used for their quantitative analysis. A total of 16 RB samples from different regions of China were analyzed. The results indicated that the method was rapid, efficient, accurate and suitable for use in the quality control of RB.

Nucleus and cytoplasm segmentation in microscopic images using K-means clustering and region growing.

PubMed

Sarrafzadeh, Omid; Dehnavi, Alireza Mehri

2015-01-01

Segmentation of leukocytes acts as the foundation for all automated image-based hematological disease recognition systems. Most of the time, hematologists are interested in evaluation of white blood cells only. Digital image processing techniques can help them in their analysis and diagnosis. The main objective of this paper is to detect leukocytes from a blood smear microscopic image and segment them into their two dominant elements, nucleus and cytoplasm. The segmentation is conducted using two stages of applying K-means clustering. First, the nuclei are segmented using K-means clustering. Then, a proposed method based on region growing is applied to separate the connected nuclei. Next, the nuclei are subtracted from the original image. Finally, the cytoplasm is segmented using the second stage of K-means clustering. The results indicate that the proposed method is able to extract the nucleus and cytoplasm regions accurately and works well even though there is no significant contrast between the components in the image. In this paper, a method based on K-means clustering and region growing is proposed in order to detect leukocytes from a blood smear microscopic image and segment its components, the nucleus and the cytoplasm. As region growing step of the algorithm relies on the information of edges, it will not able to separate the connected nuclei more accurately in poor edges and it requires at least a weak edge to exist between the nuclei. The nucleus and cytoplasm segments of a leukocyte can be used for feature extraction and classification which leads to automated leukemia detection.

Solid and Liquid Waste Drying Bag

NASA Technical Reports Server (NTRS)

Litwiller, Eric (Inventor); Hogan, John A. (Inventor); Fisher, John W. (Inventor)

2009-01-01

Method and system for processing waste from human activities, including solids, liquids and vapors. A fluid-impermeable bag, lined with a liquid-impermeable but vapor-permeable membrane, defining an inner bag, is provided. A vacuum force is provided to extract vapors so that the waste is moved toward a selected region in the inner bag, extracted vapors, including the waste vapors and vaporized portions of the waste liquids are transported across the membrane, and most or all of the solids remain within the liner. Extracted vapors are filtered, and sanitized components thereof are isolated and optionally stored. The solids remaining within the liner are optionally dried and isolated for ultimate disposal.

Content-based cell pathology image retrieval by combining different features

NASA Astrophysics Data System (ADS)

Zhou, Guangquan; Jiang, Lu; Luo, Limin; Bao, Xudong; Shu, Huazhong

2004-04-01

Content Based Color Cell Pathology Image Retrieval is one of the newest computer image processing applications in medicine. Recently, some algorithms have been developed to achieve this goal. Because of the particularity of cell pathology images, the result of the image retrieval based on single characteristic is not satisfactory. A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed. Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation and mathematics morphology. The features that include color, texture and morphologic features are extracted from single leukocyte to represent main attribute in the search query. The features are then normalized because the numerical value range and physical meaning of extracted features are different. Finally, the relevance feedback system is introduced. So that the system can automatically adjust the weights of different features and improve the results of retrieval system according to the feedback information. Retrieval results using the proposed method fit closely with human perception and are better than those obtained with the methods based on single feature.

Collection and processing of whole blood for transformation of peripheral blood mononuclear cells and extraction of DNA: the Type 1 Diabetes Genetics Consortium

PubMed Central

Rosinger, Silke; Nutland, Sarah; Mickelson, Eric; Varney, Michael D; Boehm, Bernard O; Olsem, Gary J; Hansen, John A; Nicholson, Ian; Hilner, Joan E; Perdue, Letitia H; Pierce, June J; Akolkar, Beena; Nierras, Concepcion; Steffes, Michael W

2010-01-01

Background and Purpose To yield large amounts of DNA for many genotype analyses and to provide a renewable source of DNA, the Type 1 Diabetes Genetics Consortium (T1DGC) harvested DNA and peripheral blood mononuclear cells (PBMCs) from individuals with type 1 diabetes and their family members in several regions of the world. Methods DNA repositories were established in Asia-Pacific, Europe, North America, and the United Kingdom. To address region-specific needs, different methods and sample processing techniques were used among the laboratories to extract and to quantify DNA and to establish Epstein-Barr virus transformed cell lines. Results More than 98% of the samples of PBMCs were successfully transformed. Approximately 20–25 µg of DNA were extracted per mL of whole blood. Extraction of DNA from the cell pack ranged from 92 to 165 µg per cell pack. In addition, the extracted DNA from whole blood or transformed cells was successfully utilized in each regional human leukocyte antigen genotyping laboratory and by several additional laboratories performing consortium-wide genotyping projects. Limitations Although the isolation of PBMCs was consistent among sites, the measurement of DNA was difficult to harmonize. Conclusions DNA repositories can be established in different regions of the world and produce similar amounts of high-quality DNA for a variety of high-throughput genotyping techniques. Furthermore, even with the distances and time necessary for transportation, highly efficient transformation of PBMCs is possible. For future studies/trials involving several laboratories in different locations, the T1DGC experience includes examples of protocols that may be applicable. In summary, T1DGC has developed protocols that would be of interest to any scientific organization attempting to overcome the logistical problems associated with studies/trials spanning multiple research facilities, located in different regions of the world. PMID:20595244

Variation in biogeochemical parameters across intertidal seagrass meadows in the central Great Barrier Reef region.

PubMed

Mellors, Jane; Waycott, Michelle; Marsh, Helene

2005-01-01

This survey provides baseline information on sediment characteristics, porewater, adsorbed and plant tissue nutrients from intertidal coastal seagrass meadows in the central region of the Great Barrier Reef World Heritage Area. Data collected from 11 locations, representative of intertidal coastal seagrass beds across the region, indicated that the chemical environment was typical of other tropical intertidal areas. Results using two different extraction methods highlight the need for caution when choosing an adsorbed phosphate extraction technique, as sediment type affects the analytical outcome. Comparison with published values indicates that the range of nutrient parameters measured is equivalent to those measured across tropical systems globally. However, the nutrient values in seagrass leaves and their molar ratios for Halophila ovalis and Halodule uninervis were much higher than the values from the literature from this and other regions, obtained using the same techniques, suggesting that these species act as nutrient sponges, in contrast with Zostera capricorni. The limited historical data from this region suggest that the nitrogen and phosphorus content of seagrass leaves has increased since the 1970s concomitant with changing land use practice.

Automatic bone outer contour extraction from B-modes ultrasound images based on local phase symmetry and quadratic polynomial fitting

NASA Astrophysics Data System (ADS)

Karlita, Tita; Yuniarno, Eko Mulyanto; Purnama, I. Ketut Eddy; Purnomo, Mauridhi Hery

2017-06-01

Analyzing ultrasound (US) images to get the shapes and structures of particular anatomical regions is an interesting field of study since US imaging is a non-invasive method to capture internal structures of a human body. However, bone segmentation of US images is still challenging because it is strongly influenced by speckle noises and it has poor image quality. This paper proposes a combination of local phase symmetry and quadratic polynomial fitting methods to extract bone outer contour (BOC) from two dimensional (2D) B-modes US image as initial steps of three-dimensional (3D) bone surface reconstruction. By using local phase symmetry, the bone is initially extracted from US images. BOC is then extracted by scanning one pixel on the bone boundary in each column of the US images using first phase features searching method. Quadratic polynomial fitting is utilized to refine and estimate the pixel location that fails to be detected during the extraction process. Hole filling method is then applied by utilize the polynomial coefficients to fill the gaps with new pixel. The proposed method is able to estimate the new pixel position and ensures smoothness and continuity of the contour path. Evaluations are done using cow and goat bones by comparing the resulted BOCs with the contours produced by manual segmentation and contours produced by canny edge detection. The evaluation shows that our proposed methods produces an excellent result with average MSE before and after hole filling at the value of 0.65.

Automated Identification of the Heart Wall Throughout the Entire Cardiac Cycle Using Optimal Cardiac Phase for Extracted Features

NASA Astrophysics Data System (ADS)

Takahashi, Hiroki; Hasegawa, Hideyuki; Kanai, Hiroshi

2011-07-01

In most methods for evaluation of cardiac function based on echocardiography, the heart wall is currently identified manually by an operator. However, this task is very time-consuming and suffers from inter- and intraobserver variability. The present paper proposes a method that uses multiple features of ultrasonic echo signals for automated identification of the heart wall region throughout an entire cardiac cycle. In addition, the optimal cardiac phase to select a frame of interest, i.e., the frame for the initiation of tracking, was determined. The heart wall region at the frame of interest in this cardiac phase was identified by the expectation-maximization (EM) algorithm, and heart wall regions in the following frames were identified by tracking each point classified in the initial frame as the heart wall region using the phased tracking method. The results for two subjects indicate the feasibility of the proposed method in the longitudinal axis view of the heart.

Automated detection of neovascularization for proliferative diabetic retinopathy screening.

PubMed

Roychowdhury, Sohini; Koozekanani, Dara D; Parhi, Keshab K

2016-08-01

Neovascularization is the primary manifestation of proliferative diabetic retinopathy (PDR) that can lead to acquired blindness. This paper presents a novel method that classifies neovascularizations in the 1-optic disc (OD) diameter region (NVD) and elsewhere (NVE) separately to achieve low false positive rates of neovascularization classification. First, the OD region and blood vessels are extracted. Next, the major blood vessel segments in the 1-OD diameter region are classified for NVD, and minor blood vessel segments elsewhere are classified for NVE. For NVD and NVE classifications, optimal region-based feature sets of 10 and 6 features, respectively, are used. The proposed method achieves classification sensitivity, specificity and accuracy for NVD and NVE of 74%, 98.2%, 87.6%, and 61%, 97.5%, 92.1%, respectively. Also, the proposed method achieves 86.4% sensitivity and 76% specificity for screening images with PDR from public and local data sets. Thus, the proposed NVD and NVE detection methods can play a key role in automated screening and prioritization of patients with diabetic retinopathy.

Effectiveness of Winkler Litter Extraction and Pitfall Traps in Sampling Ant Communities and Functional Groups in a Temperate Forest.

PubMed

Mahon, Michael B; Campbell, Kaitlin U; Crist, Thomas O

2017-06-01

Selection of proper sampling methods for measuring a community of interest is essential whether the study goals are to conduct a species inventory, environmental monitoring, or a manipulative experiment. Insect diversity studies often employ multiple collection methods at the expense of researcher time and funding. Ants (Formicidae) are widely used in environmental monitoring owing to their sensitivity to ecosystem changes. When sampling ant communities, two passive techniques are recommended in combination: pitfall traps and Winkler litter extraction. These recommendations are often based on studies from highly diverse tropical regions or when a species inventory is the goal. Studies in temperate regions often focus on measuring consistent community response along gradients of disturbance or among management regimes; therefore, multiple sampling methods may be unnecessary. We compared the effectiveness of pitfalls and Winkler litter extraction in an eastern temperate forest for measuring ant species richness, composition, and occurrence of ant functional groups in response to experimental manipulations of two key forest ecosystem drivers, white-tailed deer and an invasive shrub (Amur honeysuckle). We found no significant effect of sampling method on the outcome of the ecological experiment; however, we found differences between the two sampling methods in the resulting ant species richness and functional group occurrence. Litter samples approximated the overall combined species richness and composition, but pitfalls were better at sampling large-bodied (Camponotus) species. We conclude that employing both methods is essential only for species inventories or monitoring ants in the Cold-climate Specialists functional group. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The analysis and detection of hypernasality based on a formant extraction algorithm

NASA Astrophysics Data System (ADS)

Qian, Jiahui; Fu, Fanglin; Liu, Xinyi; He, Ling; Yin, Heng; Zhang, Han

2017-08-01

In the clinical practice, the effective assessment of cleft palate speech disorders is important. For hypernasal speech, the resonance between nasal cavity and oral cavity causes an additional nasal formant. Thus, the formant frequency is a crucial cue for the judgment of hypernasality in cleft palate speech. Due to the existence of nasal formant, the peak merger occurs to the spectrum of nasal speech more often. However, the peak merger could not be solved by classical linear prediction coefficient root extraction method. In this paper, a method is proposed to detect the additional nasal formant in low-frequency region and obtain the formant frequency. The experiment results show that the proposed method could locate the nasal formant preferably. Moreover, the formants are regarded as the extraction features to proceed the detection of hypernasality. 436 phonemes, which are collected from Hospital of Stomatology, are used to carry out the experiment. The detection accuracy of hypernasality in cleft palate speech is 95.2%.

Application of liquid-liquid microextraction for the effective separation and simultaneous determination of 11 pharmaceuticals in wastewater samples using HPLC-MS/MS.

PubMed

Diuzheva, Alina; Balogh, József; Jekő, József; Cziáky, Zoltán

2018-05-17

A dispersive liquid-liquid microextraction method for the simultaneous determination of 11 pharmaceuticals has been developed. The method is based on a microextraction procedure applied to wastewater samples from different regions of Hungary followed by high performance liquid chromatography with mass spectrometry. The effect of the nature of the extractant, dispersive solvent, different additives and extraction time were examined on the extraction efficiently of the dispersive liquid-liquid microextraction method. Under optimal conditions, the linearity for determining the pharmaceuticals was in the range of 1-500 ng mL -1 , with the correlation coefficients ranging from 0.9922 to 0.9995. The limits of detection and limits of quantification were in the range 0.31-6.65 and 0.93-22.18 ng mL -1 , respectively. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Template-based automatic extraction of the joint space of foot bones from CT scan

NASA Astrophysics Data System (ADS)

Park, Eunbi; Kim, Taeho; Park, Jinah

2016-03-01

Clean bone segmentation is critical in studying the joint anatomy for measuring the spacing between the bones. However, separation of the coupled bones in CT images is sometimes difficult due to ambiguous gray values coming from the noise and the heterogeneity of bone materials as well as narrowing of the joint space. For fine reconstruction of the individual local boundaries, manual operation is a common practice where the segmentation remains to be a bottleneck. In this paper, we present an automatic method for extracting the joint space by applying graph cut on Markov random field model to the region of interest (ROI) which is identified by a template of 3D bone structures. The template includes encoded articular surface which identifies the tight region of the high-intensity bone boundaries together with the fuzzy joint area of interest. The localized shape information from the template model within the ROI effectively separates the bones nearby. By narrowing the ROI down to the region including two types of tissue, the object extraction problem was reduced to binary segmentation and solved via graph cut. Based on the shape of a joint space marked by the template, the hard constraint was set by the initial seeds which were automatically generated from thresholding and morphological operations. The performance and the robustness of the proposed method are evaluated on 12 volumes of ankle CT data, where each volume includes a set of 4 tarsal bones (calcaneus, talus, navicular and cuboid).

Stable region for maxillary dental cast superimposition in adults, studied with the aid of stable miniscrews.

PubMed

Chen, G; Chen, S; Zhang, X Y; Jiang, R P; Liu, Y; Shi, F H; Xu, T M

2011-05-01

To identify a stable and reproducible reference region to superimpose serial maxillary dental models in adult extraction cases. Fifteen adult volunteers were enrolled. To reduce protrusion, bilateral maxillary first premolars were extracted in all volunteers. Each volunteer received six miniscrews, including two loaded miniscrews used to retract anterior teeth and four unloaded miniscrews. Impressions for maxillary models were taken at T1 (1 week after miniscrew placement) and T2 (17 months later). Dental models were created and then scanned using a laser scanner. Stability of the miniscrews was evaluated, and dental models were registered using stationary miniscrews. The palatal region, where deviation was within 0.5 mm in all subjects, was determined to be the stable region. Reproducibility of the new palatal region for 3D digital model superimposition was evaluated. Deviation of the medial 2/3 of the palatal region between the third rugae and the line in contact with the distal surface of the bilateral maxillary first molars was within 0.5 mm. Tooth movement of 15 subjects was measured to evaluate the validity of the new 3D superimposition method. Displacements were 8.18 ± 2.94 mm (central incisor) and 2.25 ± 0.73 mm (first molar) measured by miniscrew superimposition, while values of 7.81 ± 2.53 mm (central incisor) and 2.29 ± 1.03 mm (first molar) were measured using the 3D palatal vault regional superimposition method; no significant difference was observed. The medial 2/3 of the third rugae and the regional palatal vault dorsal to it is a stable region to register 3D digital models for evaluation of orthodontic tooth movement in adult patients. © 2011 John Wiley & Sons A/S.

Efficient region-based approach for blotch detection in archived video using texture information

NASA Astrophysics Data System (ADS)

Yous, Hamza; Serir, Amina

2017-03-01

We propose a method for blotch detection in archived videos by modeling their spatiotemporal properties. We introduce an adaptive spatiotemporal segmentation to extract candidate regions that can be classified as blotches. Then, the similarity between the preselected regions and their corresponding motion-compensated regions in the adjacent frames is assessed by means of motion trajectory estimation and textural information analysis. Perceived ground truth based on just noticeable contrast is employed for the evaluation of our approach against the state-of-the-art, and the reported results show a better performance for our approach.

GUMAP: A GUPIXWIN-compatible code for extracting regional spectra from nuclear microbeam list mode files

NASA Astrophysics Data System (ADS)

Russell, John L.; Campbell, John L.; Boyd, Nicholas I.; Dias, Johnny F.

2018-02-01

The newly developed GUMAP software creates element maps from OMDAQ list mode files, displays these maps individually or collectively, and facilitates on-screen definitions of specified regions from which a PIXE spectrum can be built. These include a free-hand region defined by moving the cursor. The regional charge is entered automatically into the spectrum file in a new GUPIXWIN-compatible format, enabling a GUPIXWIN analysis of the spectrum. The code defaults to the OMDAQ dead time treatment but also facilitates two other methods for dead time correction in sample regions with count rates different from the average.

An improved active contour model for glacial lake extraction

NASA Astrophysics Data System (ADS)

Zhao, H.; Chen, F.; Zhang, M.

2017-12-01

Active contour model is a widely used method in visual tracking and image segmentation. Under the driven of objective function, the initial curve defined in active contour model will evolve to a stable condition - a desired result in given image. As a typical region-based active contour model, C-V model has a good effect on weak boundaries detection and anti noise ability which shows great potential in glacial lake extraction. Glacial lake is a sensitive indicator for reflecting global climate change, therefore accurate delineate glacial lake boundaries is essential to evaluate hydrologic environment and living environment. However, the current method in glacial lake extraction mainly contains water index method and recognition classification method are diffcult to directly applied in large scale glacial lake extraction due to the diversity of glacial lakes and masses impacted factors in the image, such as image noise, shadows, snow and ice, etc. Regarding the abovementioned advantanges of C-V model and diffcults in glacial lake extraction, we introduce the signed pressure force function to improve the C-V model for adapting to processing of glacial lake extraction. To inspect the effect of glacial lake extraction results, three typical glacial lake development sites were selected, include Altai mountains, Centre Himalayas, South-eastern Tibet, and Landsat8 OLI imagery was conducted as experiment data source, Google earth imagery as reference data for varifying the results. The experiment consequence suggests that improved active contour model we proposed can effectively discriminate the glacial lakes from complex backgound with a higher Kappa Coefficient - 0.895, especially in some small glacial lakes which belongs to weak information in the image. Our finding provide a new approach to improved accuracy under the condition of large proportion of small glacial lakes and the possibility for automated glacial lake mapping in large-scale area.

Anticandidal, antibacterial, cytotoxic and antioxidant activities of Calendula arvensis flowers.

PubMed

Abudunia, A-M; Marmouzi, I; Faouzi, M E A; Ramli, Y; Taoufik, J; El Madani, N; Essassi, E M; Salama, A; Khedid, K; Ansar, M; Ibrahimi, A

2017-03-01

Calendula arvensis (CA) is one of the important plants used in traditional medicine in Morocco, due to its interesting chemical composition. The present study aimed to determine the anticandidal, antioxidant and antibacterial activities, and the effects of extracts of CA flowers on the growth of myeloid cancer cells. Also, to characterize the chemical composition of the plant. Flowers of CA were collected based on ethnopharmacological information from the villages around the region Rabat-Khemisset, Moroccco. The hexane and methanol extracts were obtained by soxhlet extraction, while aqueous extracts was obtained by maceration in cold water. CA extracts were assessed for antioxidant activity using four different methods (DPPH, FRAP, TEAC, β-carotene bleaching test). Furthermore, the phenolic and flavonoid contents were measured, also the antimicrobial activity has been evaluated by the well diffusion method using several bacterial and fungal strains. Finally, extracts cytotoxicity was assessed using MTT test. Phytochemical quantification of the methanolic and aqueous extracts revealed that they were rich with flavonoid and phenolic content and were found to possess considerable antioxidant activities. MIC values of methanolic extracts were 12.5-25μg/mL. While MIC values of hexanolic extracts were between 6.25-12.5μg/mL and were bacteriostatic for all bacteria while methanolic and aqueous extracts were bactericidal. In addition, the extracts exhibited no activity on Candida species except the methanolic extract, which showed antifungal activity onCandida tropicalis 1 and Candida famata 1. The methanolic and aqueous extracts also exhibited antimyeloid cancer activity (IC 50 of 31μg/mL). In our study, we conclude that the methanolic and aqueous extracts were a promising source of antioxidant, antimicrobial and cytotoxic agents. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

A novel no-reference objective stereoscopic video quality assessment method based on visual saliency analysis

NASA Astrophysics Data System (ADS)

Yang, Xinyan; Zhao, Wei; Ye, Long; Zhang, Qin

2017-07-01

This paper proposes a no-reference objective stereoscopic video quality assessment method with the motivation that making the effect of objective experiments close to that of subjective way. We believe that the image regions with different visual salient degree should not have the same weights when designing an assessment metric. Therefore, we firstly use GBVS algorithm to each frame pairs and separate both the left and right viewing images into the regions with strong, general and week saliency. Besides, local feature information like blockiness, zero-crossing and depth are extracted and combined with a mathematical model to calculate a quality assessment score. Regions with different salient degree are assigned with different weights in the mathematical model. Experiment results demonstrate the superiority of our method compared with the existed state-of-the-art no-reference objective Stereoscopic video quality assessment methods.

Pumpkin (Cucurbita maxima) seed proteins: sequential extraction processing and fraction characterization.

PubMed

Rezig, Leila; Chibani, Farhat; Chouaibi, Moncef; Dalgalarrondo, Michèle; Hessini, Kamel; Guéguen, Jacques; Hamdi, Salem

2013-08-14

Seed proteins extracted from Tunisian pumpkin seeds ( Cucurbita maxima ) were investigated for their solubility properties and sequentially extracted according to the Osborne procedure. The solubility of pumpkin proteins from seed flour was greatly influenced by pH changes and ionic strength, with higher values in the alkaline pH regions. It also depends on the seed defatting solvent. Protein solubility was decreased by using chloroform/methanol (CM) for lipid extraction instead of pentane (P). On the basis of differential solubility fractionation and depending on the defatting method, the alkali extract (AE) was the major fraction (42.1 (P), 22.3% (CM)) compared to the salt extract (8.6 (P), 7.5% (CM)). In salt, alkali, and isopropanol extracts, all essential amino acids with the exceptions of threonine and lysine met the minimum requirements for preschool children (FAO/WHO/UNU). The denaturation temperatures were 96.6 and 93.4 °C for salt and alkali extracts, respectively. Pumpkin protein extracts with unique protein profiles and higher denaturation temperatures could impart novel characteristics when used as food ingredients.

Classification of glioblastoma and metastasis for neuropathology intraoperative diagnosis: a multi-resolution textural approach to model the background

NASA Astrophysics Data System (ADS)

Ahmad Fauzi, Mohammad Faizal; Gokozan, Hamza Numan; Elder, Brad; Puduvalli, Vinay K.; Otero, Jose J.; Gurcan, Metin N.

2014-03-01

Brain cancer surgery requires intraoperative consultation by neuropathology to guide surgical decisions regarding the extent to which the tumor undergoes gross total resection. In this context, the differential diagnosis between glioblastoma and metastatic cancer is challenging as the decision must be made during surgery in a short time-frame (typically 30 minutes). We propose a method to classify glioblastoma versus metastatic cancer based on extracting textural features from the non-nuclei region of cytologic preparations. For glioblastoma, these regions of interest are filled with glial processes between the nuclei, which appear as anisotropic thin linear structures. For metastasis, these regions correspond to a more homogeneous appearance, thus suitable texture features can be extracted from these regions to distinguish between the two tissue types. In our work, we use the Discrete Wavelet Frames to characterize the underlying texture due to its multi-resolution capability in modeling underlying texture. The textural characterization is carried out in primarily the non-nuclei regions after nuclei regions are segmented by adapting our visually meaningful decomposition segmentation algorithm to this problem. k-nearest neighbor method was then used to classify the features into glioblastoma or metastasis cancer class. Experiment on 53 images (29 glioblastomas and 24 metastases) resulted in average accuracy as high as 89.7% for glioblastoma, 87.5% for metastasis and 88.7% overall. Further studies are underway to incorporate nuclei region features into classification on an expanded dataset, as well as expanding the classification to more types of cancers.

Extracting distribution and expansion of rubber plantations from Landsat imagery using the C5.0 decision tree method

NASA Astrophysics Data System (ADS)

Sun, Zhongchang; Leinenkugel, Patrick; Guo, Huadong; Huang, Chong; Kuenzer, Claudia

2017-04-01

Natural tropical rainforests in China's Xishuangbanna region have undergone dramatic conversion to rubber plantations in recent decades, resulting in altering the region's environment and ecological systems. Therefore, it is of great importance for local environmental and ecological protection agencies to research the distribution and expansion of rubber plantations. The objective of this paper is to monitor dynamic changes of rubber plantations in China's Xishuangbanna region based on multitemporal Landsat images (acquired in 1989, 2000, and 2013) using a C5.0-based decision-tree method. A practical and semiautomatic data processing procedure for mapping rubber plantations was proposed. Especially, haze removal and deshadowing were proposed to perform atmospheric and topographic correction and reduce the effects of haze, shadow, and terrain. Our results showed that the atmospheric and topographic correction could improve the extraction accuracy of rubber plantations, especially in mountainous areas. The overall classification accuracies were 84.2%, 83.9%, and 86.5% for the Landsat images acquired in 1989, 2000, and 2013, respectively. This study also found that the Landsat-8 images could provide significant improvement in the ability to identify rubber plantations. The extracted maps showed the selected study area underwent rapid conversion of natural and seminatural forest to a rubber plantations from 1989 to 2013. The rubber plantation area increased from 2.8% in 1989 to 17.8% in 2013, while the forest/woodland area decreased from 75.6% in 1989 to 44.8% in 2013. The proposed data processing procedure is a promising approach to mapping the spatial distribution and temporal dynamics of rubber plantations on a regional scale.

Isolation of entomopathogenic fungi from soils and Ixodes scapularis (Acari: Ixodidae) ticks: prevalence and methods.

PubMed

Tuininga, Amy R; Miller, Jessica L; Morath, Shannon U; Daniels, Thomas J; Falco, Richard C; Marchese, Michael; Sahabi, Sadia; Rosa, Dieshia; Stafford, Kirby C

2009-05-01

Entomopathogenic fungi are commonly found in forested soils that provide tick habitat, and many species are pathogenic to Ixodes scapularis Say, the blacklegged tick. As a first step to developing effective biocontrol strategies, the objective of this study was to determine the best methods to isolate entomopathogenic fungal species from field-collected samples of soils and ticks from an Eastern deciduous forest where I. scapularis is common. Several methods were assessed: (1) soils, leaf litter, and ticks were plated on two types of media; (2) soils were assayed for entomopathogenic fungi using the Galleria bait method; (3) DNA from internal transcribed spacer (ITS) regions of the nuclear ribosomal repeat was extracted from pure cultures obtained from soils, Galleria, and ticks and was amplified and sequenced; and (4) DNA was extracted directly from ticks, amplified, and sequenced. We conclude that (1) ticks encounter potentially entomopathogenic fungi more often in soil than in leaf litter, (2) many species of potentially entomopathogenic fungi found in the soil can readily be cultured, (3) the Galleria bait method is a sufficiently efficient method for isolation of these fungi from soils, and (4) although DNA extraction from ticks was not possible in this study because of small sample size, DNA extraction from fungi isolated from soils and from ticks was successful and provided clean sequences in 100 and 73% of samples, respectively. A combination of the above methods is clearly necessary for optimal characterization of entomopathogenic fungi associated with ticks in the environment.

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

NASA Technical Reports Server (NTRS)

Solarna, David; Moser, Gabriele; Le Moigne-Stewart, Jacqueline; Serpico, Sebastiano B.

2017-01-01

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Urban Boundary Extraction and Urban Sprawl Measurement Using High-Resolution Remote Sensing Images: a Case Study of China's Provincial

NASA Astrophysics Data System (ADS)

Wang, H.; Ning, X.; Zhang, H.; Liu, Y.; Yu, F.

2018-04-01

Urban boundary is an important indicator for urban sprawl analysis. However, methods of urban boundary extraction were inconsistent, and construction land or urban impervious surfaces was usually used to represent urban areas with coarse-resolution images, resulting in lower precision and incomparable urban boundary products. To solve above problems, a semi-automatic method of urban boundary extraction was proposed by using high-resolution image and geographic information data. Urban landscape and form characteristics, geographical knowledge were combined to generate a series of standardized rules for urban boundary extraction. Urban boundaries of China's 31 provincial capitals in year 2000, 2005, 2010 and 2015 were extracted with above-mentioned method. Compared with other two open urban boundary products, accuracy of urban boundary in this study was the highest. Urban boundary, together with other thematic data, were integrated to measure and analyse urban sprawl. Results showed that China's provincial capitals had undergone a rapid urbanization from year 2000 to 2015, with the area change from 6520 square kilometres to 12398 square kilometres. Urban area of provincial capital had a remarkable region difference and a high degree of concentration. Urban land became more intensive in general. Urban sprawl rate showed inharmonious with population growth rate. About sixty percent of the new urban areas came from cultivated land. The paper provided a consistent method of urban boundary extraction and urban sprawl measurement using high-resolution remote sensing images. The result of urban sprawl of China's provincial capital provided valuable urbanization information for government and public.

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

Differentiation of Glioblastoma and Lymphoma Using Feature Extraction and Support Vector Machine.

PubMed

Yang, Zhangjing; Feng, Piaopiao; Wen, Tian; Wan, Minghua; Hong, Xunning

2017-01-01

Differentiation of glioblastoma multiformes (GBMs) and lymphomas using multi-sequence magnetic resonance imaging (MRI) is an important task that is valuable for treatment planning. However, this task is a challenge because GBMs and lymphomas may have a similar appearance in MRI images. This similarity may lead to misclassification and could affect the treatment results. In this paper, we propose a semi-automatic method based on multi-sequence MRI to differentiate these two types of brain tumors. Our method consists of three steps: 1) the key slice is selected from 3D MRIs and region of interests (ROIs) are drawn around the tumor region; 2) different features are extracted based on prior clinical knowledge and validated using a t-test; and 3) features that are helpful for classification are used to build an original feature vector and a support vector machine is applied to perform classification. In total, 58 GBM cases and 37 lymphoma cases are used to validate our method. A leave-one-out crossvalidation strategy is adopted in our experiments. The global accuracy of our method was determined as 96.84%, which indicates that our method is effective for the differentiation of GBM and lymphoma and can be applied in clinical diagnosis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Vehicle detection in aerial surveillance using dynamic Bayesian networks.

PubMed

Cheng, Hsu-Yung; Weng, Chih-Chia; Chen, Yi-Ying

2012-04-01

We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.

Tampered Region Localization of Digital Color Images Based on JPEG Compression Noise

NASA Astrophysics Data System (ADS)

Wang, Wei; Dong, Jing; Tan, Tieniu

With the availability of various digital image edit tools, seeing is no longer believing. In this paper, we focus on tampered region localization for image forensics. We propose an algorithm which can locate tampered region(s) in a lossless compressed tampered image when its unchanged region is output of JPEG decompressor. We find the tampered region and the unchanged region have different responses for JPEG compression. The tampered region has stronger high frequency quantization noise than the unchanged region. We employ PCA to separate different spatial frequencies quantization noises, i.e. low, medium and high frequency quantization noise, and extract high frequency quantization noise for tampered region localization. Post-processing is involved to get final localization result. The experimental results prove the effectiveness of our proposed method.

Multi-focus image fusion using a guided-filter-based difference image.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Yang, Tingwu

2016-03-20

The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.

Automated kidney detection for 3D ultrasound using scan line searching

NASA Astrophysics Data System (ADS)

Noll, Matthias; Nadolny, Anne; Wesarg, Stefan

2016-04-01

Ultrasound (U/S) is a fast and non-expensive imaging modality that is used for the examination of various anatomical structures, e.g. the kidneys. One important task for automatic organ tracking or computer-aided diagnosis is the identification of the organ region. During this process the exact information about the transducer location and orientation is usually unavailable. This renders the implementation of such automatic methods exceedingly challenging. In this work we like to introduce a new automatic method for the detection of the kidney in 3D U/S images. This novel technique analyses the U/S image data along virtual scan lines. Here, characteristic texture changes when entering and leaving the symmetric tissue regions of the renal cortex are searched for. A subsequent feature accumulation along a second scan direction produces a 2D heat map of renal cortex candidates, from which the kidney location is extracted in two steps. First, the strongest candidate as well as its counterpart are extracted by heat map intensity ranking and renal cortex size analysis. This process exploits the heat map gap caused by the renal pelvis region. Substituting the renal pelvis detection with this combined cortex tissue feature increases the detection robustness. In contrast to model based methods that generate characteristic pattern matches, our method is simpler and therefore faster. An evaluation performed on 61 3D U/S data sets showed, that in 55 cases showing none or minor shadowing the kidney location could be correctly identified.

The ability of Abelmoschus manihot L. leaf extract in scavenging of free radical DPPH and total flavonoid determination

NASA Astrophysics Data System (ADS)

Sudewi, S.; Lolo, W. A.; Warongan, M.; Rifai, Y.; Rante, H.

2017-11-01

Abelmoschus manihot L. has reported to have flavonoids content. This study aims were to determine the ability of A. manihot extract in counteracting free radical DPPH and determine the content of total flavonoids. A. manihot leaf was taken from 2 regions in North Sulawesi, namely Tomohon and Kotamobagu. The maceration was carried out to extract the active compound in a 96% ethanol solvent. Free radical scavenging analysis was carried out by DPPH and determination of its total flavonoid in the extract was measured using spectrophotometri method. The results showed that A. manihot extract from Tomohon and Kotamobagu could counteract free radical of DPPH with value of free radical activity of 88.151 and 88.801 %, respectively. A. manihot leaf from Kotamobagu has higher total flavonoids content 61.763 mg/g compare to Tomohon 46.679 mg/g which presented as quercetin. A. manihot has antioxidant activity.

Automatic Delineation of the Myocardial Wall from CT Images via Shape Segmentation and Variational Region Growing

PubMed Central

Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen

2014-01-01

Prognosis and diagnosis of cardiac diseases frequently require quantitative evaluation of the ventricle volume, mass, and ejection fraction. The delineation of the myocardial wall is involved in all of these evaluations, which is a challenging task due to large variations in myocardial shapes and image quality. In this work, we present an automatic method for extracting the myocardial wall of the left and right ventricles from cardiac CT images. In the method, the left and right ventricles are located sequentially, in which each ventricle is detected by first identifying the endocardium and then segmenting the epicardium. To this end, the endocardium is localized by utilizing its geometric features obtained on-line from a CT image. After that, a variational region-growing model is employed to extract the epicardium of the ventricles. In particular, the location of the endocardium of the left ventricle is determined via using an active contour model on the blood-pool surface. To localize the right ventricle, the active contour model is applied on a heart surface extracted based on the left ventricle segmentation result. The robustness and accuracy of the proposed approach is demonstrated by experimental results from 33 human and 12 pig CT images. PMID:23744658

Rapid extraction and determination of 25 bioactive constituents in Alpinia oxyphylla using microwave extraction with ultra high performance liquid chromatography with tandem mass spectrometry.

PubMed

Sun, Zhi; Kong, Xiangzhen; Zuo, Lihua; Kang, Jian; Hou, Lei; Zhang, Xiaojian

2016-02-01

A novel and rapid microwave extraction and ultra high performance liquid chromatography with tandem mass spectrometry method was developed and validated for the simultaneous determination of 25 bioactive constituents (including two new constituents) in Fructus Alpinia oxyphylla. The optimized conditions of the microwave extraction was a microwave power of 300 W, extraction temperature of 80°C, solvent-to-solid ratio of 30 mL/g and extraction time of 8 min. Separation was achieved on a Waters ACQUITY UPLC(®) HSS C18 column (2.1 mm× 50 mm, 1.8 μm) using gradient elution with a mobile phase consisting of acetonitrile and 1 mM ammonium acetate at a flow rate of 0.2 mL/min. This is the first report of the simultaneous determination of 25 bioactive constituents in Fructus Alpinia oxyphylla by ultra high performance liquid chromatography with tandem mass spectrometry. The method was validated with good linearity, acceptable precision and accuracy. The validated method was successfully applied to determine the contents of 25 bioactive constituents in Fructus Alpinia oxyphylla from different sources and the analysis results were classified by hierarchical cluster analysis, which indicated the effect of different cultivation regions on the contents of constituents. This study provides powerful and practical guidance in the quality control of Alpinia oxyphylla and lays the foundation for further research of Alpinia oxyphylla. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The antiepileptic effect of Centella asiatica on the activities of Na+/K+, Mg2+ and Ca2+-ATPases in rat brain during pentylenetetrazol–induced epilepsy

PubMed Central

G., Visweswari; K., Siva Prasad; V., Lokanatha; Rajendra, W.

2010-01-01

Background: To study the anticonvulsant effect of different extracts of Centella asiatica (CA) in male albino rats with reference to Na+/K+, Mg2+ and Ca2+-ATPase activities. Materials and Methods: Male Wistar rats (150±25 g b.w.) were divided into seven groups of six each i.e. (a) control rats treated with saline, (b) pentylenetetrazol (PTZ)-induced epileptic group (60 mg/kg, i.p.), (c) epileptic group pretreated with n-hexane extract (n-HE), (d) epileptic group pretreated with chloroform extract (CE), (e) epileptic group pretreated with ethyl acetate extract (EAE), (f) epileptic group pretreated with n-butanol extract (n-BE), and (g) epileptic group pretreated with aqueous extract (AE). Results: The activities of three ATPases were decreased in different regions of brain during PTZ-induced epilepsy and were increased in epileptic rats pretreated with different extracts of CA except AE. Conclusion: The extracts of C. asiatica, except AE, possess anticonvulsant and neuroprotective activity and thus can be used for effective management in treatment of epileptic seizures. PMID:20711371

Enzyme inhibitory and radical scavenging effects of some antidiabetic plants of Turkey

PubMed Central

Orhan, Nilüfer; Hoçbaç, Sanem; Orhan, Didem Deliorman; Asian, Mustafa; Ergun, Fatma

2014-01-01

Objective(s): Ethnopharmacological field surveys demonstrated that many plants, such as Gentiana olivieri, Helichrysum graveolens, Helichrysum plicatum ssp. plicatum, Juniperus oxycedrus ssp. oxycedrus, Juniperus communis var. saxatilis, Viscum album (ssp. album, ssp. austriacum), are used as traditional medicine for diabetes in different regions of Anatolia. The present study was designed to evaluate the in vitro antidiabetic effects of some selected plants, tested in animal models recently. Materials and Methods: α-glucosidase and α-amylase enzyme inhibitory effects of the plant extracts were investigated and Acarbose was used as a reference drug. Additionally, radical scavenging capacities were determined using 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) ABTS radical cation scavenging assay and total phenolic content of the extracts were evaluated using Folin Ciocalteu method. Results: H. graveolens ethanol extract exhibited the highest inhibitory activity (55.7 % ± 2.2) on α-amylase enzyme. Additionally, J. oxycedrus hydro-alcoholic leaf extract had potent α-amylase inhibitory effect, while the hydro-alcoholic extract of J. communis fruit showed the highest α-glucosidase inhibitory activity (IC50: 4.4 μg/ml). Conclusion: Results indicated that, antidiabetic effect of hydro-alcoholic extracts of H. graveolens capitulums, J. communis fruit and J. oxycedrus leaf might arise from inhibition of digestive enzymes. PMID:25140204

Study of in vitro antimicrobial and antiproliferative activities of selected Saharan plants.

PubMed

Palici, Ionut F; Liktor-Busa, Erika; Zupkó, István; Touzard, Blaise; Chaieb, Mohamed; Urbán, Edit; Hohmann, Judit

2015-12-01

The aim of the present study was the evaluation of the antimicrobial and antiproliferative activities of selected Saharan species, which are applied in the traditional medicine but not studied thoroughly from chemical and pharmacological point of view. The studied plants, namely Anthyllis henoniana, Centropodia forskalii, Cornulaca monacantha, Ephedra alata var. alenda, Euphorbia guyoniana, Helianthemum confertum, Henophyton deserti, Moltkiopsis ciliata and Spartidium saharae were collected from remote areas of North Africa, especially from the Tunisian region of Sahara. After drying and applying the appropriate extraction methods, the plant extracts were tested in antimicrobial screening assay, performed on 19 Gram-positive and -negative strains of microbes. The inhibition zones produced by plant extracts were determined by disc-diffusion method. Remarkable antibacterial activities were exhibited by extracts of Ephedra alata var. alenda and Helianthemum confertum against B. subtilis, M. catarrhalis and methicillin-resistant and non-resistant S. aureus. Minimum inhibitory concentrations of these two species were also determined. Antiproliferative effects of the extracts were evaluated against 4 human adherent cell lines (HeLa, A431, A2780 and MCF7). Notable cell growth inhibition was found for extract of Helianthemum confertum and Euphorbia guyoniana. Our results provided data for selection of some plant species for further detailed pharmacological and phytochemical examinations.

In-line monitoring of extraction process of scutellarein from Erigeron breviscapus (vant.) Hand-Mazz based on qualitative and quantitative uses of near-infrared spectroscopy.

PubMed

Wu, Yongjiang; Jin, Ye; Ding, Haiying; Luan, Lianjun; Chen, Yong; Liu, Xuesong

2011-09-01

The application of near-infrared (NIR) spectroscopy for in-line monitoring of extraction process of scutellarein from Erigeron breviscapus (vant.) Hand-Mazz was investigated. For NIR measurements, two fiber optic probes designed to transmit NIR radiation through a 2 mm pathlength flow cell were utilized to collect spectra in real-time. High performance liquid chromatography (HPLC) was used as a reference method to determine scutellarein in extract solution. Partial least squares regression (PLSR) calibration model of Savitzky-Golay smoothing NIR spectra in the 5450-10,000 cm(-1) region gave satisfactory predictive results for scutellarein. The results showed that the correlation coefficients of calibration and cross validation were 0.9967 and 0.9811, respectively, and the root mean square error of calibration and cross validation were 0.044 and 0.105, respectively. Furthermore, both the moving block standard deviation (MBSD) method and conformity test were used to identify the end point of extraction process, providing real-time data and instant feedback about the extraction course. The results obtained in this study indicated that the NIR spectroscopy technique provides an efficient and environmentally friendly approach for fast determination of scutellarein and end point control of extraction process. Copyright © 2011 Elsevier B.V. All rights reserved.

Automatic diagnosis of malaria based on complete circle-ellipse fitting search algorithm.

PubMed

Sheikhhosseini, M; Rabbani, H; Zekri, M; Talebi, A

2013-12-01

Diagnosis of malaria parasitemia from blood smears is a subjective and time-consuming task for pathologists. The automatic diagnostic process will reduce the diagnostic time. Also, it can be worked as a second opinion for pathologists and may be useful in malaria screening. This study presents an automatic method for malaria diagnosis from thin blood smears. According to this fact that malaria life cycle is started by forming a ring around the parasite nucleus, the proposed approach is mainly based on curve fitting to detect parasite ring in the blood smear. The method is composed of six main phases: stain object extraction step, which extracts candidate objects that may be infected by malaria parasites. This phase includes stained pixel extraction step based on intensity and colour, and stained object segmentation by defining stained circle matching. Second step is preprocessing phase which makes use of nonlinear diffusion filtering. The process continues with detection of parasite nucleus from resulted image of previous step according to image intensity. Fourth step introduces a complete search process in which the circle search step identifies the direction and initial points for direct least-square ellipse fitting algorithm. Furthermore in the ellipse searching process, although parasite shape is completed undesired regions with high error value are removed and ellipse parameters are modified. Features are extracted from the parasite candidate region instead of whole candidate object in the fifth step. By employing this special feature extraction way, which is provided by special searching process, the necessity of employing clump splitting methods is removed. Also, defining stained circle matching process in the first step speeds up the whole procedure. Finally, a series of decision rules are applied on the extracted features to decide on the positivity or negativity of malaria parasite presence. The algorithm is applied on 26 digital images which are provided from thin blood smear films. The images are contained 1274 objects which may be infected by parasite or healthy. Applying the automatic identification of malaria on provided database showed a sensitivity of 82.28% and specificity of 98.02%. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Determination of Antibacterial and Antioxidant Potential of Some Medicinal Plants from Saurashtra Region, India

PubMed Central

Kaneria, M.; Baravalia, Y.; Vaghasiya, Y.; Chanda, S.

2009-01-01

Many plants used in Saurashtra folk medicine have been reported to exhibit high antibacterial and antioxidant activities. In the present study, some parts of five plants, Guazuma ulmifolia L., Manilkara zapota L., Melia azedarach L., Syzygium cumini L. and Wrightia tomentosa R.& S., were evaluated for their antibacterial activity, total phenol content, flavonoid content, 2,2-diphenyl-1-picrylhydrazyl free radical scavenging activity and phytochemical analysis, using successive extraction by cold percolation method with petroleum ether, ethyl acetate, methanol and water. In vitro antibacterial activity was evaluated against five bacterial strains viz. Bacillus subtilis, Staphylococcus aureus, Pseudomonas aeruginosa, Salmonella typhimurium and Enterobacter aerogenes by agar well diffusion method. Among the plants screened, W. tomentosa leaf and fruit showed the best antibacterial activity. The Gram-positive bacteria were more susceptible than Gram-negative bacteria. Methanol extract of M. zapota showed the best 2,2-diphenyl-1-picrylhydrazyl free radical scavenging activity. Highest total phenol content was shown by M. zapota and S. cumini in methanol extract, while highest flavonoid content was shown by W. tomentosa stem in petroleum ether extract and ethyl acetate extract. In all the plants, cardiac glycosides and triterpenes were more as compared to other phytoconstituents. PMID:20502546

Road Network Extraction from Dsm by Mathematical Morphology and Reasoning

NASA Astrophysics Data System (ADS)

Li, Yan; Wu, Jianliang; Zhu, Lin; Tachibana, Kikuo

2016-06-01

The objective of this research is the automatic extraction of the road network in a scene of the urban area from a high resolution digital surface model (DSM). Automatic road extraction and modeling from remote sensed data has been studied for more than one decade. The methods vary greatly due to the differences of data types, regions, resolutions et al. An advanced automatic road network extraction scheme is proposed to address the issues of tedium steps on segmentation, recognition and grouping. It is on the basis of a geometric road model which describes a multiple-level structure. The 0-dimension element is intersection. The 1-dimension elements are central line and side. The 2-dimension element is plane, which is generated from the 1-dimension elements. The key feature of the presented approach is the cross validation for the three road elements which goes through the entire procedure of their extraction. The advantage of our model and method is that linear elements of the road can be derived directly, without any complex, non-robust connection hypothesis. An example of Japanese scene is presented to display the procedure and the performance of the approach.

Separation of arteries and veins in the cerebral cortex using physiological oscillations by optical imaging of intrinsic signal

NASA Astrophysics Data System (ADS)

Hu, Dewen; Wang, Yucheng; Liu, Yadong; Li, Ming; Liu, Fayi

2010-05-01

An automated method is presented for artery-vein separation in cerebral cortical images recorded with optical imaging of the intrinsic signal. The vessel-type separation method is based on the fact that the spectral distribution of intrinsic physiological oscillations varies from arterial regions to venous regions. In arterial regions, the spectral power is higher in the heartbeat frequency (HF), whereas in venous regions, the spectral power is higher in the respiration frequency (RF). The separation method was begun by extracting the vascular network and its centerline. Then the spectra of the optical intrinsic signals were estimated by the multitaper method. A standard F-test was performed on each discrete frequency point to test the statistical significance at the given level. Four periodic physiological oscillations were examined: HF, RF, and two other eigenfrequencies termed F1 and F2. The separation of arteries and veins was implemented with the fuzzy c-means clustering method and the region-growing approach by utilizing the spectral amplitudes and power-ratio values of the four eigenfrequencies on the vasculature. Subsequently, independent spectral distributions in the arteries, veins, and capillary bed were estimated for comparison, which showed that the spectral distributions of the intrinsic signals were very distinct between the arterial and venous regions.

Separation of arteries and veins in the cerebral cortex using physiological oscillations by optical imaging of intrinsic signal.

PubMed

Hu, Dewen; Wang, Yucheng; Liu, Yadong; Li, Ming; Liu, Fayi

2010-01-01

An automated method is presented for artery-vein separation in cerebral cortical images recorded with optical imaging of the intrinsic signal. The vessel-type separation method is based on the fact that the spectral distribution of intrinsic physiological oscillations varies from arterial regions to venous regions. In arterial regions, the spectral power is higher in the heartbeat frequency (HF), whereas in venous regions, the spectral power is higher in the respiration frequency (RF). The separation method was begun by extracting the vascular network and its centerline. Then the spectra of the optical intrinsic signals were estimated by the multitaper method. A standard F-test was performed on each discrete frequency point to test the statistical significance at the given level. Four periodic physiological oscillations were examined: HF, RF, and two other eigenfrequencies termed F1 and F2. The separation of arteries and veins was implemented with the fuzzy c-means clustering method and the region-growing approach by utilizing the spectral amplitudes and power-ratio values of the four eigenfrequencies on the vasculature. Subsequently, independent spectral distributions in the arteries, veins, and capillary bed were estimated for comparison, which showed that the spectral distributions of the intrinsic signals were very distinct between the arterial and venous regions.

Estimating groundwater extraction in a data-sparse coal seam gas region, Australia

NASA Astrophysics Data System (ADS)

Keir, Greg; Bulovic, Nevenka; McIntyre, Neil

2017-04-01

The semi-arid Surat and Bowen Basins in central Queensland, Australia, are groundwater resources of both national and regional significance. Regional towns, agricultural industries and communities are heavily dependent on the 30 000+ groundwater supply bores for their existence; however groundwater extraction measurements are rare in this area and primarily limited to small irrigation regions. Accordingly, regional groundwater extraction is not well understood, and this may have implications for regional numerical groundwater modelling and impact assessments associated with recent coal seam gas developments. Here we present a novel statistical approach to model regional groundwater extraction that merges flow measurements / estimates with other more commonly available spatial datasets that may be of value, such as climate data, pasture data, surface water availability, etc. A three step modelling approach, combining a property scale magnitude model, a bore scale occurrence model, and a proportional distribution model within properties, is used to estimate bore extraction. We describe the process of model development and selection, and present extraction results on an aquifer-by-aquifer basis suitable for numerical groundwater modelling. Lastly, we conclude with recommendations for future research, particularly related to improvement of attribution of property-scale water demand, and temporal variability in water usage.

Evaluation of the antiplasmodial and leishmanicidal potential of Myrciaria dubia (Myrtaceae) extract.

PubMed

Correia, Vanessa Carolina de Sena; Lima, Nathália Oliveira; Oliveira, Flávio Augusto de Souza; Santos, Ana Paula de Azevedo Dos; Teles, Carolina Bioni Garcia; Oliveira, Waldesse Piragé de; Pimenta, And Raphael Sanzio

2016-01-01

Malaria and leishmaniasis are prevalent in tropical regions, which have environmental characteristics that are highly favorable to protozoa and vectors of these diseases; the transmission of these infections in sub-tropical regions, although recognized, represents only a small fraction of cases. Plants are constantly being used in the search for and acquisition of new drugs, and many compounds derived from them have been used to combat various diseases. In this study, we evaluated the action of the dichloromethanolic extract of Myrciaria dubia leaves against the protozoa Plasmodium falciparum, Leishmania amazonensis, Leishmania braziliensis, and Leishmania chagasi through bioassays. The extract from M. dubia was tested for its anti-P. falciparum activity in an anti-histidine-rich protein II immunosorbent assay. The antileishmanial assays were performed using the resazurin method, while cytotoxicity against human hepatoma (HepG2) strain was determined using the colorimetric MTT [3-(4, 5-dimethyl-2- thiazolyl)-2, 5-diphenyl-2H tetrazolium bromide] method. The M. dubia extract presented a half-maximal inhibitory concentration equal to 2.35 (1.05)μg/mL for P. falciparum, 190.73 (6.41) μg/mL for L. amazonensis, and greater than equal to 200µg/mL for L. chagasi and L. braziliensis strains. The cytotoxic concentration for 50% of the cells was above 500μg/mL for HepG2, indicating no toxicity and greater selectivity against parasites. The results obtained indicate the presence of antiplasmodial and leishmanicidal bioactive compounds in the dichloromethanolic extracts of M. dubia leaves, and point towards future studies to elucidate the mechanism of action for each physiological effect.

Computed Tomography-Based Biomarker for Longitudinal Assessment of Disease Burden in Pulmonary Tuberculosis.

PubMed

Gordaliza, P M; Muñoz-Barrutia, A; Via, L E; Sharpe, S; Desco, M; Vaquero, J J

2018-05-29

Computed tomography (CT) images enable capturing specific manifestations of tuberculosis (TB) that are undetectable using common diagnostic tests, which suffer from limited specificity. In this study, we aimed to automatically quantify the burden of Mycobacterium tuberculosis (Mtb) using biomarkers extracted from x-ray CT images. Nine macaques were aerosol-infected with Mtb and treated with various antibiotic cocktails. Chest CT scans were acquired in all animals at specific times independently of disease progression. First, a fully automatic segmentation of the healthy lungs from the acquired chest CT volumes was performed and air-like structures were extracted. Next, unsegmented pulmonary regions corresponding to damaged parenchymal tissue and TB lesions were included. CT biomarkers were extracted by classification of the probability distribution of the intensity of the segmented images into three tissue types: (1) Healthy tissue, parenchyma free from infection; (2) soft diseased tissue, and (3) hard diseased tissue. The probability distribution of tissue intensities was assumed to follow a Gaussian mixture model. The thresholds identifying each region were automatically computed using an expectation-maximization algorithm. The estimated longitudinal course of TB infection shows that subjects that have followed the same antibiotic treatment present a similar response (relative change in the diseased volume) with respect to baseline. More interestingly, the correlation between the diseased volume (soft tissue + hard tissue), which was manually delineated by an expert, and the automatically extracted volume with the proposed method was very strong (R 2  ≈ 0.8). We present a methodology that is suitable for automatic extraction of a radiological biomarker from CT images for TB disease burden. The method could be used to describe the longitudinal evolution of Mtb infection in a clinical trial devoted to the design of new drugs.

Antioxidant activity and total phenolic and flavonoids content variations of leaves extracts of white Horehound (Marrubium vulgare Linné) from three geographical origins.

PubMed

Bouterfas, K; Mehdadi, Z; Elaoufi, M M; Latreche, A; Benchiha, W

2016-11-01

To elucidate the effect of the sampling location of Marrubium vulgare L. leaves on phenolic contents and antioxidant proprieties of flavonoids extracts. M. vulgare L. leaves were collected from three different geographical locations belonging to northwest Algeria: Tessala (mountain region), M'sila forest (coastal region), and Ain Skhouna (steppe region). The flavonoid extraction was achieved using organic solvents with different polarities (methanol, chloroform, ethyl acetate, and hexane). Folin-Ciocalteu colorimetric method was used for quantification of total phenolic contents, and aluminum chloride assay for quantification of total flavonoid contents. The antioxidant properties of flavonoids extract were studied by free l,l-diphenyl-2-picrylhydrazyl radical-scavenging technique. Total phenolic and flavonoids concentrations varied respectively between 40.7 and 160mg gallic acid equivalents/g and 27.4 and 66.3mg catechin equivalents/g. The DPPH free radical-scavenging activity shows that the antioxidant activity of the flavonoid extracts varied significantly (P<0.001) depending on the type of the organic solvent used, and the sampling location. The methanol, chloroform and ethyl acetate extracts exhibited the highest percentages of inhibition unlike to the aqueous and hexane extracts. These percentages are ranged from 54.8 to 98.8% at 1000μg/mL. In general, M'sila forest flavonoids extracts showed the highest free radical inhibition capacity; followed by those of Ain Skhouna and Tessala Mountain. The inhibitory concentration 50 (IC 50 ) ranged from 33.7 to 774μg/mL and often exceeded those recorded by phenolic standards (ascorbic acid, gallic acid, caffeic acid, tannic acid and catechin). The phytochemical screening revealed the presence of some flavonoid classes, such as flavans and flavanols. The results suggested a potent antioxidant activity of M. vulgare flavonoids extracts, which may find its application in feature research for the food and the pharmacological industries. Copyright © 2016 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Extracting the regional common-mode component of GPS station position time series from dense continuous network

NASA Astrophysics Data System (ADS)

Tian, Yunfeng; Shen, Zheng-Kang

2016-02-01

We develop a spatial filtering method to remove random noise and extract the spatially correlated transients (i.e., common-mode component (CMC)) that deviate from zero mean over the span of detrended position time series of a continuous Global Positioning System (CGPS) network. The technique utilizes a weighting scheme that incorporates two factors—distances between neighboring sites and their correlations of long-term residual position time series. We use a grid search algorithm to find the optimal thresholds for deriving the CMC that minimizes the root-mean-square (RMS) of the filtered residual position time series. Comparing to the principal component analysis technique, our method achieves better (>13% on average) reduction of residual position scatters for the CGPS stations in western North America, eliminating regional transients of all spatial scales. It also has advantages in data manipulation: less intervention and applicable to a dense network of any spatial extent. Our method can also be used to detect CMC irrespective of its origins (i.e., tectonic or nontectonic), if such signals are of particular interests for further study. By varying the filtering distance range, the long-range CMC related to atmospheric disturbance can be filtered out, uncovering CMC associated with transient tectonic deformation. A correlation-based clustering algorithm is adopted to identify stations cluster that share the common regional transient characteristics.

Reprint of "Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency".

PubMed

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-08-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Object-oriented segmentation and classification of forest gap based on QuickBird remote sensing image.

PubMed

Mao, Xue Gang; Du, Zi Han; Liu, Jia Qian; Chen, Shu Xin; Hou, Ji Yu

2018-01-01

Traditional field investigation and artificial interpretation could not satisfy the need of forest gaps extraction at regional scale. High spatial resolution remote sensing image provides the possibility for regional forest gaps extraction. In this study, we used object-oriented classification method to segment and classify forest gaps based on QuickBird high resolution optical remote sensing image in Jiangle National Forestry Farm of Fujian Province. In the process of object-oriented classification, 10 scales (10-100, with a step length of 10) were adopted to segment QuickBird remote sensing image; and the intersection area of reference object (RA or ) and intersection area of segmented object (RA os ) were adopted to evaluate the segmentation result at each scale. For segmentation result at each scale, 16 spectral characteristics and support vector machine classifier (SVM) were further used to classify forest gaps, non-forest gaps and others. The results showed that the optimal segmentation scale was 40 when RA or was equal to RA os . The accuracy difference between the maximum and minimum at different segmentation scales was 22%. At optimal scale, the overall classification accuracy was 88% (Kappa=0.82) based on SVM classifier. Combining high resolution remote sensing image data with object-oriented classification method could replace the traditional field investigation and artificial interpretation method to identify and classify forest gaps at regional scale.

National Oceanic and Atmospheric Administration hydrographic survey data used in a U.S. Geological Survey regional geologic framework study along the Delmarva Peninsula

USGS Publications Warehouse

Pendleton, Elizabeth A.; Brothers, Laura L.; Thieler, E. Robert; Danforth, William W.; Parker, Castle E.

2014-01-01

The U.S. Geological Survey obtained raw Reson multibeam data files from Science Applications International Corporation and the National Oceanic and Atmospheric Administration for 20 hydrographic surveys and extracted backscatter data using the Fledermaus Geocoder Toolbox from Quality Positioning Service. The backscatter mosaics produced by the U.S. Geological Survey for the inner continental shelf of the Delmarva Peninsula using National Oceanic and Atmospheric Administration data increased regional geophysical surveying efficiency, collaboration among government agencies, and the area over which geologic data can be interpreted by the U.S. Geological Survey. This report describes the methods by which the backscatter data were extracted and processed and includes backscatter mosaics and interpolated bathymetric surfaces.

Active surface model improvement by energy function optimization for 3D segmentation.

PubMed

Azimifar, Zohreh; Mohaddesi, Mahsa

2015-04-01

This paper proposes an optimized and efficient active surface model by improving the energy functions, searching method, neighborhood definition and resampling criterion. Extracting an accurate surface of the desired object from a number of 3D images using active surface and deformable models plays an important role in computer vision especially medical image processing. Different powerful segmentation algorithms have been suggested to address the limitations associated with the model initialization, poor convergence to surface concavities and slow convergence rate. This paper proposes a method to improve one of the strongest and recent segmentation algorithms, namely the Decoupled Active Surface (DAS) method. We consider a gradient of wavelet edge extracted image and local phase coherence as external energy to extract more information from images and we use curvature integral as internal energy to focus on high curvature region extraction. Similarly, we use resampling of points and a line search for point selection to improve the accuracy of the algorithm. We further employ an estimation of the desired object as an initialization for the active surface model. A number of tests and experiments have been done and the results show the improvements with regards to the extracted surface accuracy and computational time of the presented algorithm compared with the best and recent active surface models. Copyright © 2015 Elsevier Ltd. All rights reserved.

Finger-vein and fingerprint recognition based on a feature-level fusion method

NASA Astrophysics Data System (ADS)

Yang, Jinfeng; Hong, Bofeng

2013-07-01

Multimodal biometrics based on the finger identification is a hot topic in recent years. In this paper, a novel fingerprint-vein based biometric method is proposed to improve the reliability and accuracy of the finger recognition system. First, the second order steerable filters are used here to enhance and extract the minutiae features of the fingerprint (FP) and finger-vein (FV). Second, the texture features of fingerprint and finger-vein are extracted by a bank of Gabor filter. Third, a new triangle-region fusion method is proposed to integrate all the fingerprint and finger-vein features in feature-level. Thus, the fusion features contain both the finger texture-information and the minutiae triangular geometry structure. Finally, experimental results performed on the self-constructed finger-vein and fingerprint databases are shown that the proposed method is reliable and precise in personal identification.

Finger vein recognition based on finger crease location

NASA Astrophysics Data System (ADS)

Lu, Zhiying; Ding, Shumeng; Yin, Jing

2016-07-01

Finger vein recognition technology has significant advantages over other methods in terms of accuracy, uniqueness, and stability, and it has wide promising applications in the field of biometric recognition. We propose using finger creases to locate and extract an object region. Then we use linear fitting to overcome the problem of finger rotation in the plane. The method of modular adaptive histogram equalization (MAHE) is presented to enhance image contrast and reduce computational cost. To extract the finger vein features, we use a fusion method, which can obtain clear and distinguishable vein patterns under different conditions. We used the Hausdorff average distance algorithm to examine the recognition performance of the system. The experimental results demonstrate that MAHE can better balance the recognition accuracy and the expenditure of time compared with three other methods. Our resulting equal error rate throughout the total procedure was 3.268% in a database of 153 finger vein images.

Author name recognition in degraded journal images

NASA Astrophysics Data System (ADS)

de Bodard de la Jacopière, Aliette; Likforman-Sulem, Laurence

2006-01-01

A method for extracting names in degraded documents is presented in this article. The documents targeted are images of photocopied scientific journals from various scientific domains. Due to the degradation, there is poor OCR recognition, and pieces of other articles appear on the sides of the image. The proposed approach relies on the combination of a low-level textual analysis and an image-based analysis. The textual analysis extracts robust typographic features, while the image analysis selects image regions of interest through anchor components. We report results on the University of Washington benchmark database.

Fly Diversity Revealed by PCR-RFLP of Mitochondrial DNA

ERIC Educational Resources Information Center

Asraoui, Jimmy F.; Sayar, Nancy P.; Knio, Khouzama M.; Smith, Colin A.

2008-01-01

In this article, we describe an inexpensive, two-session undergraduate laboratory activity that introduces important molecular biology methods in the context of biodiversity. In the first session, students bring tentatively identified flies (order Diptera, true flies) to the laboratory, extract DNA, and amplify a region of the mitochondrial gene…

Detection and Monitoring of Oil Spills Using Moderate/High-Resolution Remote Sensing Images.

PubMed

Li, Ying; Cui, Can; Liu, Zexi; Liu, Bingxin; Xu, Jin; Zhu, Xueyuan; Hou, Yongchao

2017-07-01

Current marine oil spill detection and monitoring methods using high-resolution remote sensing imagery are quite limited. This study presented a new bottom-up and top-down visual saliency model. We used Landsat 8, GF-1, MAMS, HJ-1 oil spill imagery as dataset. A simplified, graph-based visual saliency model was used to extract bottom-up saliency. It could identify the regions with high visual saliency object in the ocean. A spectral similarity match model was used to obtain top-down saliency. It could distinguish oil regions and exclude the other salient interference by spectrums. The regions of interest containing oil spills were integrated using these complementary saliency detection steps. Then, the genetic neural network was used to complete the image classification. These steps increased the speed of analysis. For the test dataset, the average running time of the entire process to detect regions of interest was 204.56 s. During image segmentation, the oil spill was extracted using a genetic neural network. The classification results showed that the method had a low false-alarm rate (high accuracy of 91.42%) and was able to increase the speed of the detection process (fast runtime of 19.88 s). The test image dataset was composed of different types of features over large areas in complicated imaging conditions. The proposed model was proved to be robust in complex sea conditions.

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems.

PubMed

Oh, Sang-Il; Kang, Hang-Bong

2017-01-22

To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN). The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI) pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR) sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226 × 370 image, whereas the original selective search method extracted approximately 10 6 × n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset.

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN). The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI) pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR) sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226×370 image, whereas the original selective search method extracted approximately 106×n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset. PMID:28117742

An optimized protocol for DNA extraction in plants with a high content of secondary metabolites, based on leaves of Mimosa tenuiflora (Willd.) Poir. (Leguminosae).

PubMed

Arruda, S R; Pereira, D G; Silva-Castro, M M; Brito, M G; Waldschmidt, A M

2017-07-06

Some species are characterized by a high content of tannins, alkaloids, and phenols in their leaves. These secondary metabolites are released during DNA extraction and might hinder molecular studies based on PCR (polymerase chain reaction). To provide an efficient method to extract DNA, Mimosa tenuiflora, an important leguminous plant from Brazilian semiarid region used in popular medicine and as a source of fuelwood or forage, was used. Eight procedures previously reported for plants were tested and adapted from leaf tissues of M. tenuiflora stored at -20°C. The optimized procedure in this study encompassed the utilization of phenol during deproteinization, increased concentrations of cetyltrimethylammonium bromide and sodium chloride, and a shorter period and lower temperature of incubation concerning other methods. The extracted DNA did not present degradation, and amplification via PCR was successful using ISSR, trnL, ITS, and ETS primers. Besides M. tenuiflora, this procedure was also tested and proved to be efficient in genetic studies of other plant species.

Analysis of alterative cleavage and polyadenylation by 3′ region extraction and deep sequencing

PubMed Central

Hoque, Mainul; Ji, Zhe; Zheng, Dinghai; Luo, Wenting; Li, Wencheng; You, Bei; Park, Ji Yeon; Yehia, Ghassan; Tian, Bin

2012-01-01

Alternative cleavage and polyadenylation (APA) leads to mRNA isoforms with different coding sequences (CDS) and/or 3′ untranslated regions (3′UTRs). Using 3′ Region Extraction And Deep Sequencing (3′READS), a method which addresses the internal priming and oligo(A) tail issues that commonly plague polyA site (pA) identification, we comprehensively mapped pAs in the mouse genome, thoroughly annotating 3′ ends of genes and revealing over five thousand pAs (~8% of total) flanked by A-rich sequences, which have hitherto been overlooked. About 79% of mRNA genes and 66% of long non-coding RNA (lncRNA) genes have APA; but these two gene types have distinct usage patterns for pAs in introns and upstream exons. Promoter-distal pAs become relatively more abundant during embryonic development and cell differentiation, a trend affecting pAs in both 3′-most exons and upstream regions. Upregulated isoforms generally have stronger pAs, suggesting global modulation of the 3′ end processing activity in development and differentiation. PMID:23241633

Infrared dim small target segmentation method based on ALI-PCNN model

NASA Astrophysics Data System (ADS)

Zhao, Shangnan; Song, Yong; Zhao, Yufei; Li, Yun; Li, Xu; Jiang, Yurong; Li, Lin

2017-10-01

Pulse Coupled Neural Network (PCNN) is improved by Adaptive Lateral Inhibition (ALI), while a method of infrared (IR) dim small target segmentation based on ALI-PCNN model is proposed in this paper. Firstly, the feeding input signal is modulated by lateral inhibition network to suppress background. Then, the linking input is modulated by ALI, and linking weight matrix is generated adaptively by calculating ALI coefficient of each pixel. Finally, the binary image is generated through the nonlinear modulation and the pulse generator in PCNN. The experimental results show that the segmentation effect as well as the values of contrast across region and uniformity across region of the proposed method are better than the OTSU method, maximum entropy method, the methods based on conventional PCNN and visual attention, and the proposed method has excellent performance in extracting IR dim small target from complex background.

Generating region proposals for histopathological whole slide image retrieval.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu; Shi, Jun

2018-06-01

Content-based image retrieval is an effective method for histopathological image analysis. However, given a database of huge whole slide images (WSIs), acquiring appropriate region-of-interests (ROIs) for training is significant and difficult. Moreover, histopathological images can only be annotated by pathologists, resulting in the lack of labeling information. Therefore, it is an important and challenging task to generate ROIs from WSI and retrieve image with few labels. This paper presents a novel unsupervised region proposing method for histopathological WSI based on Selective Search. Specifically, the WSI is over-segmented into regions which are hierarchically merged until the WSI becomes a single region. Nucleus-oriented similarity measures for region mergence and Nucleus-Cytoplasm color space for histopathological image are specially defined to generate accurate region proposals. Additionally, we propose a new semi-supervised hashing method for image retrieval. The semantic features of images are extracted with Latent Dirichlet Allocation and transformed into binary hashing codes with Supervised Hashing. The methods are tested on a large-scale multi-class database of breast histopathological WSIs. The results demonstrate that for one WSI, our region proposing method can generate 7.3 thousand contoured regions which fit well with 95.8% of the ROIs annotated by pathologists. The proposed hashing method can retrieve a query image among 136 thousand images in 0.29 s and reach precision of 91% with only 10% of images labeled. The unsupervised region proposing method can generate regions as predictions of lesions in histopathological WSI. The region proposals can also serve as the training samples to train machine-learning models for image retrieval. The proposed hashing method can achieve fast and precise image retrieval with small amount of labels. Furthermore, the proposed methods can be potentially applied in online computer-aided-diagnosis systems. Copyright © 2018 Elsevier B.V. All rights reserved.

A novel approach for fire recognition using hybrid features and manifold learning-based classifier

NASA Astrophysics Data System (ADS)

Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

2018-03-01

Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

Bi-model processing for early detection of breast tumor in CAD system

NASA Astrophysics Data System (ADS)

Mughal, Bushra; Sharif, Muhammad; Muhammad, Nazeer

2017-06-01

Early screening of skeptical masses in mammograms may reduce mortality rate among women. This rate can be further reduced upon developing the computer-aided diagnosis system with decrease in false assumptions in medical informatics. This method highlights the early tumor detection in digitized mammograms. For improving the performance of this system, a novel bi-model processing algorithm is introduced. It divides the region of interest into two parts, the first one is called pre-segmented region (breast parenchyma) and other is the post-segmented region (suspicious region). This system follows the scheme of the preprocessing technique of contrast enhancement that can be utilized to segment and extract the desired feature of the given mammogram. In the next phase, a hybrid feature block is presented to show the effective performance of computer-aided diagnosis. In order to assess the effectiveness of the proposed method, a database provided by the society of mammographic images is tested. Our experimental outcomes on this database exhibit the usefulness and robustness of the proposed method.

A novel visual saliency analysis model based on dynamic multiple feature combination strategy

NASA Astrophysics Data System (ADS)

Lv, Jing; Ye, Qi; Lv, Wen; Zhang, Libao

2017-06-01

The human visual system can quickly focus on a small number of salient objects. This process was known as visual saliency analysis and these salient objects are called focus of attention (FOA). The visual saliency analysis mechanism can be used to extract the salient regions and analyze saliency of object in an image, which is time-saving and can avoid unnecessary costs of computing resources. In this paper, a novel visual saliency analysis model based on dynamic multiple feature combination strategy is introduced. In the proposed model, we first generate multi-scale feature maps of intensity, color and orientation features using Gaussian pyramids and the center-surround difference. Then, we evaluate the contribution of all feature maps to the saliency map according to the area of salient regions and their average intensity, and attach different weights to different features according to their importance. Finally, we choose the largest salient region generated by the region growing method to perform the evaluation. Experimental results show that the proposed model cannot only achieve higher accuracy in saliency map computation compared with other traditional saliency analysis models, but also extract salient regions with arbitrary shapes, which is of great value for the image analysis and understanding.

Isolation of Entomopathogenic Fungi From Soils and Ixodes scapularis (Acari: Ixodidae) Ticks: Prevalence and Methods

PubMed Central

Tuininga, Amy R.; Miller, Jessica L.; Morath, Shannon U.; Daniels, Thomas J.; Falco, Richard C.; Marchese, Michael; Sahabi, Sadia; Rosa, Dieshia; Stafford, Kirby C.

2009-01-01

Entomopathogenic fungi are commonly found in forested soils that provide tick habitat, and many species are pathogenic to Ixodes scapularis Say, the blacklegged tick. As a first step to developing effective biocontrol strategies, the objective of this study was to determine the best methods to isolate entomopathogenic fungal species from field-collected samples of soils and ticks from an Eastern deciduous forest where I. scapularis is common. Several methods were assessed: (1) soils, leaf litter, and ticks were plated on two types of media; (2) soils were assayed for entomopathogenic fungi using the Galleria bait method; (3) DNA from internal transcribed spacer (ITS) regions of the nuclear ribosomal repeat was extracted from pure cultures obtained from soils, Galleria, and ticks and was amplified and sequenced; and (4) DNA was extracted directly from ticks, amplified, and sequenced. We conclude that (1) ticks encounter potentially entomopathogenic fungi more often in soil than in leaf litter, (2) many species of potentially entomopathogenic fungi found in the soil can readily be cultured, (3) the Galleria bait method is a sufficiently efficient method for isolation of these fungi from soils, and (4) although DNA extraction from ticks was not possible in this study because of small sample size, DNA extraction from fungi isolated from soils and from ticks was successful and provided clean sequences in 100 and 73% of samples, respectively. A combination of the above methods is clearly necessary for optimal characterization of entomopathogenic fungi associated with ticks in the environment. PMID:19496427

Waterbodies Extraction from LANDSAT8-OLI Imagery Using Awater Indexs-Guied Stochastic Fully-Connected Conditional Random Field Model and the Support Vector Machine

NASA Astrophysics Data System (ADS)

Wang, X.; Xu, L.

2018-04-01

One of the most important applications of remote sensing classification is water extraction. The water index (WI) based on Landsat images is one of the most common ways to distinguish water bodies from other land surface features. But conventional WI methods take into account spectral information only form a limited number of bands, and therefore the accuracy of those WI methods may be constrained in some areas which are covered with snow/ice, clouds, etc. An accurate and robust water extraction method is the key to the study at present. The support vector machine (SVM) using all bands spectral information can reduce for these classification error to some extent. Nevertheless, SVM which barely considers spatial information is relatively sensitive to noise in local regions. Conditional random field (CRF) which considers both spatial information and spectral information has proven to be able to compensate for these limitations. Hence, in this paper, we develop a systematic water extraction method by taking advantage of the complementarity between the SVM and a water index-guided stochastic fully-connected conditional random field (SVM-WIGSFCRF) to address the above issues. In addition, we comprehensively evaluate the reliability and accuracy of the proposed method using Landsat-8 operational land imager (OLI) images of one test site. We assess the method's performance by calculating the following accuracy metrics: Omission Errors (OE) and Commission Errors (CE); Kappa coefficient (KP) and Total Error (TE). Experimental results show that the new method can improve target detection accuracy under complex and changeable environments.

Method for contour extraction for object representation

DOEpatents

Skourikhine, Alexei N.; Prasad, Lakshman

2005-08-30

Contours are extracted for representing a pixelated object in a background pixel field. An object pixel is located that is the start of a new contour for the object and identifying that pixel as the first pixel of the new contour. A first contour point is then located on the mid-point of a transition edge of the first pixel. A tracing direction from the first contour point is determined for tracing the new contour. Contour points on mid-points of pixel transition edges are sequentially located along the tracing direction until the first contour point is again encountered to complete tracing the new contour. The new contour is then added to a list of extracted contours that represent the object. The contour extraction process associates regions and contours by labeling all the contours belonging to the same object with the same label.

Molluscicidal and ovicidal activities of plant extracts of the Piperaceae on Biomphalaria glabrata (Say, 1818).

PubMed

Rapado, L N; Nakano, E; Ohlweiler, F P; Kato, M J; Yamaguchi, L F; Pereira, C A B; Kawano, T

2011-03-01

Schistosomiasis is a tropical disease caused by Schistosoma and occurs in 54 countries, mainly in South America, the Caribbean region, Africa and the eastern Mediterranean. Currently, 5 to 6 million Brazilian people are infected and 30,000 are under infection risk. Typical of poor regions, this disease is associated with the lack of basic sanitation and very frequently to the use of contaminated water in agriculture, housework and leisure. One of the most efficient methods of controlling the disease is application of molluscicides to eliminate or to reduce the population of the intermediate host snail Biomphalaria glabrata. Studies on molluscicidal activity of plant extracts have been stimulated by issues such as environmental preservation, high cost and recurrent resistance of snails to synthetic molluscicides. The aim of this study was to determine the molluscicide action of extracts from Piperaceae species on adult and embryonic stages of B. glabrata. Fifteen extracts from 13 Piperaceae species were obtained from stems, leaves and roots. Toxicity of extracts was evaluated against snails at two different concentrations (500 and 100 ppm) and those causing 100% mortality at 100 ppm concentration were selected to obtain the LC₉₀ (lethal concentration of 90% mortality). Piper aduncum, P. crassinervium, P. cuyabanum, P. diospyrifolium and P. hostmannianum gave 100% mortality of adult snails at concentrations ranging from 10 to 60 ppm. These extracts were also assayed on embryonic stages of B. glabrata and those from P. cuyabanum and P. hostmannianum showed 100% ovicidal action at 20 ppm.

Autonomous navigation method for substation inspection robot based on travelling deviation

NASA Astrophysics Data System (ADS)

Yang, Guoqing; Xu, Wei; Li, Jian; Fu, Chongguang; Zhou, Hao; Zhang, Chuanyou; Shao, Guangting

2017-06-01

A new method of edge detection is proposed in substation environment, which can realize the autonomous navigation of the substation inspection robot. First of all, the road image and information are obtained by using an image acquisition device. Secondly, the noise in the region of interest which is selected in the road image, is removed with the digital image processing algorithm, the road edge is extracted by Canny operator, and the road boundaries are extracted by Hough transform. Finally, the distance between the robot and the left and the right boundaries is calculated, and the travelling distance is obtained. The robot's walking route is controlled according to the travel deviation and the preset threshold. Experimental results show that the proposed method can detect the road area in real time, and the algorithm has high accuracy and stable performance.

Novel face-detection method under various environments

NASA Astrophysics Data System (ADS)

Jing, Min-Quan; Chen, Ling-Hwei

2009-06-01

We propose a method to detect a face with different poses under various environments. On the basis of skin color information, skin regions are first extracted from an input image. Next, the shoulder part is cut out by using shape information and the head part is then identified as a face candidate. For a face candidate, a set of geometric features is applied to determine if it is a profile face. If not, then a set of eyelike rectangles extracted from the face candidate and the lighting distribution are used to determine if the face candidate is a nonprofile face. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses, and races. The detection rate for the HHI face database is 93.68%. For the Champion face database, the detection rate is 95.15%.

Pedestrian detection in thermal images: An automated scale based region extraction with curvelet space validation

NASA Astrophysics Data System (ADS)

Lakshmi, A.; Faheema, A. G. J.; Deodhare, Dipti

2016-05-01

Pedestrian detection is a key problem in night vision processing with a dozen of applications that will positively impact the performance of autonomous systems. Despite significant progress, our study shows that performance of state-of-the-art thermal image pedestrian detectors still has much room for improvement. The purpose of this paper is to overcome the challenge faced by the thermal image pedestrian detectors, which employ intensity based Region Of Interest (ROI) extraction followed by feature based validation. The most striking disadvantage faced by the first module, ROI extraction, is the failed detection of cloth insulted parts. To overcome this setback, this paper employs an algorithm and a principle of region growing pursuit tuned to the scale of the pedestrian. The statistics subtended by the pedestrian drastically vary with the scale and deviation from normality approach facilitates scale detection. Further, the paper offers an adaptive mathematical threshold to resolve the problem of subtracting the background while extracting cloth insulated parts as well. The inherent false positives of the ROI extraction module are limited by the choice of good features in pedestrian validation step. One such feature is curvelet feature, which has found its use extensively in optical images, but has as yet no reported results in thermal images. This has been used to arrive at a pedestrian detector with a reduced false positive rate. This work is the first venture made to scrutinize the utility of curvelet for characterizing pedestrians in thermal images. Attempt has also been made to improve the speed of curvelet transform computation. The classification task is realized through the use of the well known methodology of Support Vector Machines (SVMs). The proposed method is substantiated with qualified evaluation methodologies that permits us to carry out probing and informative comparisons across state-of-the-art features, including deep learning methods, with six standard and in-house databases. With reference to deep learning, our algorithm exhibits comparable performance. More important is that it has significant lower requirements in terms of compute power and memory, thus making it more relevant for depolyment in resource constrained platforms with significant size, weight and power constraints.

Blood Vessel Extraction in Color Retinal Fundus Images with Enhancement Filtering and Unsupervised Classification

PubMed Central

2017-01-01

Retinal blood vessels have a significant role in the diagnosis and treatment of various retinal diseases such as diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. For this reason, retinal vasculature extraction is important in order to help specialists for the diagnosis and treatment of systematic diseases. In this paper, a novel approach is developed to extract retinal blood vessel network. Our method comprises four stages: (1) preprocessing stage in order to prepare dataset for segmentation; (2) an enhancement procedure including Gabor, Frangi, and Gauss filters obtained separately before a top-hat transform; (3) a hard and soft clustering stage which includes K-means and Fuzzy C-means (FCM) in order to get binary vessel map; and (4) a postprocessing step which removes falsely segmented isolated regions. The method is tested on color retinal images obtained from STARE and DRIVE databases which are available online. As a result, Gabor filter followed by K-means clustering method achieves 95.94% and 95.71% of accuracy for STARE and DRIVE databases, respectively, which are acceptable for diagnosis systems. PMID:29065611

A Local DCT-II Feature Extraction Approach for Personal Identification Based on Palmprint

NASA Astrophysics Data System (ADS)

Choge, H. Kipsang; Oyama, Tadahiro; Karungaru, Stephen; Tsuge, Satoru; Fukumi, Minoru

Biometric applications based on the palmprint have recently attracted increased attention from various researchers. In this paper, a method is presented that differs from the commonly used global statistical and structural techniques by extracting and using local features instead. The middle palm area is extracted after preprocessing for rotation, position and illumination normalization. The segmented region of interest is then divided into blocks of either 8×8 or 16×16 pixels in size. The type-II Discrete Cosine Transform (DCT) is applied to transform the blocks into DCT space. A subset of coefficients that encode the low to medium frequency components is selected using the JPEG-style zigzag scanning method. Features from each block are subsequently concatenated into a compact feature vector and used in palmprint verification experiments with palmprints from the PolyU Palmprint Database. Results indicate that this approach achieves better results than many conventional transform-based methods, with an excellent recognition accuracy above 99% and an Equal Error Rate (EER) of less than 1.2% in palmprint verification.

Novel vehicle detection system based on stacked DoG kernel and AdaBoost

PubMed Central

Kang, Hyun Ho; Lee, Seo Won; You, Sung Hyun

2018-01-01

This paper proposes a novel vehicle detection system that can overcome some limitations of typical vehicle detection systems using AdaBoost-based methods. The performance of the AdaBoost-based vehicle detection system is dependent on its training data. Thus, its performance decreases when the shape of a target differs from its training data, or the pattern of a preceding vehicle is not visible in the image due to the light conditions. A stacked Difference of Gaussian (DoG)–based feature extraction algorithm is proposed to address this issue by recognizing common characteristics, such as the shadow and rear wheels beneath vehicles—of vehicles under various conditions. The common characteristics of vehicles are extracted by applying the stacked DoG shaped kernel obtained from the 3D plot of an image through a convolution method and investigating only certain regions that have a similar patterns. A new vehicle detection system is constructed by combining the novel stacked DoG feature extraction algorithm with the AdaBoost method. Experiments are provided to demonstrate the effectiveness of the proposed vehicle detection system under different conditions. PMID:29513727

Contact effects analyzed by a parameter extraction method based on a single bottom-gate/top-contact organic thin-film transistor

NASA Astrophysics Data System (ADS)

Takagaki, Shunsuke; Yamada, Hirofumi; Noda, Kei

2018-03-01

Contact effects in organic thin-film transistors (OTFTs) were examined by using our previously proposed parameter extraction method from the electrical characteristics of a single staggered-type device. Gate-voltage-dependent contact resistance and channel mobility in the linear regime were evaluated for bottom-gate/top-contact (BGTC) pentacene TFTs with active layers of different thicknesses, and for pentacene TFTs with contact-doped layers prepared by coevaporation of pentacene and tetrafluorotetracyanoquinodimethane (F4TCNQ). The extracted parameters suggested that the influence of the contact resistance becomes more prominent with the larger active-layer thickness, and that contact-doping experiments give rise to a drastic decrease in the contact resistance and a concurrent considerable improvement in the channel mobility. Additionally, the estimated energy distributions of trap density in the transistor channel probably reflect the trap filling with charge carriers injected into the channel regions. The analysis results in this study confirm the effectiveness of our proposed method, with which we can investigate contact effects and circumvent the influences of characteristic variations in OTFT fabrication.

News on Collectivity in PbPb Collisions at CMS

NASA Astrophysics Data System (ADS)

Moon, Dong Ho

2017-04-01

The flow anisotropies with the Fourier coefficients (n = 2, 3) for the charged particles produced in PbPb collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV is studied with the CMS detector. In order to extract the Fourier coefficients, several methods were used, such as the scalar product method or multi-particle cumulant method. The results cover both of the low-pT region (1 < pT < 3 GeV/c) associated with hydrodynamic flow phenomena and the high-pT region where anisotropic azimuthal distributions may reflect the path-length dependence of the parton energy loss in the created medium for the seven bins of collision centrality, spanning the rang of 0-60% most-central events.

Estimating the number of people in crowded scenes

NASA Astrophysics Data System (ADS)

Kim, Minjin; Kim, Wonjun; Kim, Changick

2011-01-01

This paper presents a method to estimate the number of people in crowded scenes without using explicit object segmentation or tracking. The proposed method consists of three steps as follows: (1) extracting space-time interest points using eigenvalues of the local spatio-temporal gradient matrix, (2) generating crowd regions based on space-time interest points, and (3) estimating the crowd density based on the multiple regression. In experimental results, the efficiency and robustness of our proposed method are demonstrated by using PETS 2009 dataset.

Extraction of Trypanosoma cruzi DNA from food: a contribution to the elucidation of acute Chagas disease outbreaks.

PubMed

Ferreira, Renata Trotta Barroso; Melandre, Aline Martins; Cabral, Maria Luiza; Branquinho, Maria Regina; Cardarelli-Leite, Paola

2016-04-01

Before 2004, the occurrence of acute Chagas disease (ACD) by oral transmission associated with food was scarcely known or investigated. Originally sporadic and circumstantial, ACD occurrences have now become frequent in the Amazon region, with recently related outbreaks spreading to several Brazilian states. These cases are associated with the consumption of açai juice by waste reservoir animals or insect vectors infected with Trypanosoma cruzi in endemic areas. Although guidelines for processing the fruit to minimize contamination through microorganisms and parasites exist, açai-based products must be assessed for quality, for which the demand for appropriate methodologies must be met. Dilutions ranging from 5 to 1,000 T. cruzi CL Brener cells were mixed with 2mL of acai juice. Four Extraction of T. cruzi DNA methods were used on the fruit, and the cetyltrimethyl ammonium bromide (CTAB) method was selected according to JRC, 2005. DNA extraction by the CTAB method yielded satisfactory results with regard to purity and concentration for use in PCR. Overall, the methods employed proved that not only extraction efficiency but also high sensitivity in amplification was important. The method for T. cruzi detection in food is a powerful tool in the epidemiological investigation of outbreaks as it turns epidemiological evidence into supporting data that serve to confirm T. cruzi infection in the foods. It also facilitates food quality control and assessment of good manufacturing practices involving acai-based products.

Predicting Future Morphological Changes of Lesions from Radiotracer Uptake in 18F-FDG-PET Images

PubMed Central

Bagci, Ulas; Yao, Jianhua; Miller-Jaster, Kirsten; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on 18F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 18F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75±1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUVmax (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUVmax. We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16). PMID:23431398

Soil phosphorus forms and profile distributions in the tidal river network region in the Yellow River Delta estuary.

PubMed

Yu, Junbao; Qu, Fanzhu; Wu, Huifeng; Meng, Ling; Du, Siyao; Xie, Baohua

2014-01-01

Modified Hedley fraction method was used to study the forms and profile distribution in the tidal river network region subjected to rapid deposition and hydrologic disturbance in the Yellow River Delta (YRD) estuary, eastern China. The results showed that the total P (Pt) ranged from 612.1 to 657.8 mg kg(-1). Dilute HCl extractable inorganic P (Pi) was the predominant form in all profiles, both as absolute values and as a percentage of total extracted Pi. The NaOH extractable organic P (Po) was the predominant form of total extracted Po, while Bicarb-Pi and C.HCl-Po were the lowest fractions of total extracted Pi and Po in all the P forms. The Resin-P concentrations were high in the top soil layer and decreased with depth. The Pearson correlation matrix indicated that Resin-P, Bicarb-Pi, NaOH-Pi, and C.HCl-Pi were strongly positively correlated with salinity, TOC, Ca, Al, and Fe but negatively correlated with pH. The significant correlation of any studied form of organic P (Bicarb-Po, NaOH-Po, and C.HCl-Po) with geochemical properties were not observed in the study. Duncan multiple-range test indicated that the P forms and distribution heterogeneity in the profiles could be attributed to the influences of vegetation cover and hydrologic disturbance.

Methods and Devices for Micro-Isolation, Extraction, and/or Analysis of Microscale Components

NASA Technical Reports Server (NTRS)

Wade, Lawrence A. (Inventor); Kartalov, Emil P. (Inventor); Taylor, Clive (Inventor); Shibata, Darryl (Inventor)

2014-01-01

Provided herein are devices and methods for the micro-isolation of biological cellular material. A micro-isolation apparatus described can comprise a photomask that protects regions of interest against DNA-destroying illumination. The micro-isolation apparatus can further comprise photosensitive material defining access wells following illumination and subsequent developing of the photosensitive material. The micro-isolation apparatus can further comprise a chambered microfluidic device comprising channels providing access to wells defined in photosensitive material. The micro-isolation apparatus can comprise a chambered microfluidic device without access wells defined in photosensitive material where valves control the flow of gases or liquids through the channels of the microfluidic device. Also included are methods for selectively isolating cellular material using the apparatuses described herein, as are methods for biochemical analysis of individual regions of interest of cellular material using the devices described herein. Further included are methods of making masking arrays useful for the methods described herein.

Foreground extraction for moving RGBD cameras

NASA Astrophysics Data System (ADS)

Junejo, Imran N.; Ahmed, Naveed

2017-02-01

In this paper, we propose a simple method to perform foreground extraction for a moving RGBD camera. These cameras have now been available for quite some time. Their popularity is primarily due to their low cost and ease of availability. Although the field of foreground extraction or background subtraction has been explored by the computer vision researchers since a long time, the depth-based subtraction is relatively new and has not been extensively addressed as of yet. Most of the current methods make heavy use of geometric reconstruction, making the solutions quite restrictive. In this paper, we make a novel use RGB and RGBD data: from the RGB frame, we extract corner features (FAST) and then represent these features with the histogram of oriented gradients (HoG) descriptor. We train a non-linear SVM on these descriptors. During the test phase, we make used of the fact that the foreground object has distinct depth ordering with respect to the rest of the scene. That is, we use the positively classified FAST features on the test frame to initiate a region growing to obtain the accurate segmentation of the foreground object from just the RGBD data. We demonstrate the proposed method of a synthetic datasets, and demonstrate encouraging quantitative and qualitative results.

Capillary electrophoresis of Big-Dye terminator sequencing reactions for human mtDNA Control Region haplotyping in the identification of human remains.

PubMed

Montesino, Marta; Prieto, Lourdes

2012-01-01

Cycle sequencing reaction with Big-Dye terminators provides the methodology to analyze mtDNA Control Region amplicons by means of capillary electrophoresis. DNA sequencing with ddNTPs or terminators was developed by (1). The progressive automation of the method by combining the use of fluorescent-dye terminators with cycle sequencing has made it possible to increase the sensibility and efficiency of the method and hence has allowed its introduction into the forensic field. PCR-generated mitochondrial DNA products are the templates for sequencing reactions. Different set of primers can be used to generate amplicons with different sizes according to the quality and quantity of the DNA extract providing sequence data for different ranges inside the Control Region.

Free-Form Region Description with Second-Order Pooling.

PubMed

Carreira, João; Caseiro, Rui; Batista, Jorge; Sminchisescu, Cristian

2015-06-01

Semantic segmentation and object detection are nowadays dominated by methods operating on regions obtained as a result of a bottom-up grouping process (segmentation) but use feature extractors developed for recognition on fixed-form (e.g. rectangular) patches, with full images as a special case. This is most likely suboptimal. In this paper we focus on feature extraction and description over free-form regions and study the relationship with their fixed-form counterparts. Our main contributions are novel pooling techniques that capture the second-order statistics of local descriptors inside such free-form regions. We introduce second-order generalizations of average and max-pooling that together with appropriate non-linearities, derived from the mathematical structure of their embedding space, lead to state-of-the-art recognition performance in semantic segmentation experiments without any type of local feature coding. In contrast, we show that codebook-based local feature coding is more important when feature extraction is constrained to operate over regions that include both foreground and large portions of the background, as typical in image classification settings, whereas for high-accuracy localization setups, second-order pooling over free-form regions produces results superior to those of the winning systems in the contemporary semantic segmentation challenges, with models that are much faster in both training and testing.

Iris Matching Based on Personalized Weight Map.

PubMed

Dong, Wenbo; Sun, Zhenan; Tan, Tieniu

2011-09-01

Iris recognition typically involves three steps, namely, iris image preprocessing, feature extraction, and feature matching. The first two steps of iris recognition have been well studied, but the last step is less addressed. Each human iris has its unique visual pattern and local image features also vary from region to region, which leads to significant differences in robustness and distinctiveness among the feature codes derived from different iris regions. However, most state-of-the-art iris recognition methods use a uniform matching strategy, where features extracted from different regions of the same person or the same region for different individuals are considered to be equally important. This paper proposes a personalized iris matching strategy using a class-specific weight map learned from the training images of the same iris class. The weight map can be updated online during the iris recognition procedure when the successfully recognized iris images are regarded as the new training data. The weight map reflects the robustness of an encoding algorithm on different iris regions by assigning an appropriate weight to each feature code for iris matching. Such a weight map trained by sufficient iris templates is convergent and robust against various noise. Extensive and comprehensive experiments demonstrate that the proposed personalized iris matching strategy achieves much better iris recognition performance than uniform strategies, especially for poor quality iris images.

Component-resolved microarray analysis of IgE sensitization profiles to Felis catus major allergen molecules in Russian cat-allergic patients.

PubMed

Dolgova, Anna Sergeevna; Sudina, Anna Evgenevna; Cherkashina, Anna Sergeevna; Stukolova, Olga Alekseevna

We aimed to determine the profile of IgE reactivity to three major cat allergens, Fel d 1, Fel d 2 and Fel d 4, in cat-allergic patients in the Moscow region in Russia. sIgE levels to recombinant proteins expressed in Escherichia coli (Fel d 1 and Fel d 4) and to Fel d 2 protein purified from cat serum were measured using a microarray method developed in our laboratory. Sera from 174 anonymous subjects with a positive reaction (≥0.35 IU/mL) to cat dander extract (e1, ImmunoCAP) and 56 negative controls were used for IgE testing. Fel d 1 was recognized by 92.5%, Fel d 2 by 29.9% and Fel d 4 by 39.1% of the tested patient sera. The sensitivity to these three proteins was approximately 98% compared to cat dander extract (correlation coefficient to ImmunoCAP is 0.94 with PPV = 0.99 and NPV = 0.95). These predictive values appeared to be even more statistically significant than the divergence between the ISAC IgE test and the extract-based singleplex ImmunoCAP. The combination of the three investigated proteins (Fel d 1, Fel d 2 and Fel d 4) is suitable for in vitro molecular (serological) diagnosis of cat allergy in this region as a complement to cat dander extract. Moreover, with this method, we found distinction between Fel d 2 and other Feline sIgEs formation.

Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data

PubMed Central

Prieto, Sandra P.; Lai, Keith K.; Laryea, Jonathan A.; Mizell, Jason S.; Muldoon, Timothy J.

2016-01-01

Abstract. Qualitative screening for colorectal polyps via fiber bundle microendoscopy imaging has shown promising results, with studies reporting high rates of sensitivity and specificity, as well as low interobserver variability with trained clinicians. A quantitative image quality control and image feature extraction algorithm (QFEA) was designed to lessen the burden of training and provide objective data for improved clinical efficacy of this method. After a quantitative image quality control step, QFEA extracts field-of-view area, crypt area, crypt circularity, and crypt number per image. To develop and validate this QFEA, a training set of microendoscopy images was collected from freshly resected porcine colon epithelium. The algorithm was then further validated on ex vivo image data collected from eight human subjects, selected from clinically normal appearing regions distant from grossly visible tumor in surgically resected colorectal tissue. QFEA has proven flexible in application to both mosaics and individual images, and its automated crypt detection sensitivity ranges from 71 to 94% despite intensity and contrast variation within the field of view. It also demonstrates the ability to detect and quantify differences in grossly normal regions among different subjects, suggesting the potential efficacy of this approach in detecting occult regions of dysplasia. PMID:27335893

Innovative Methods of Anthropogenic Landscape Reconstruction in the Urbanized Oil and Gas Region Environment

NASA Astrophysics Data System (ADS)

Shabatura, L. N.; Bauer, N. V.; Speranskaya, N. I.; Iatsevich, O. E.

2016-10-01

The article deals with the problems of the urbanized environment appearing as a result of intensive region developing. The state neglect towards people affects the population life quality of the of oil and gas extraction areas as well as problems resolving, and it provokes enormous losses for manufacturing and the whole region. The environment influences the person behaviour, one's perception and space understanding. The city environment is considered as the human existence space influencing on it directly, so it is necessary to renovate it. The authentic region developing cannot be reduced to "pure" economics (for not to be deserted), but needs to be fully mastered. To renovate the destroyed landscapes, it is necessary to use the landscape design methods making a cultural landscape. They help to increase the natural components of the city environment and to make it more harmonious, more harmless, more comfortable for residents.

Efficient graph-cut tattoo segmentation

NASA Astrophysics Data System (ADS)

Kim, Joonsoo; Parra, Albert; Li, He; Delp, Edward J.

2015-03-01

Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related crimes. Many tattoo image retrieval systems have been described. In a retrieval system tattoo segmentation is an important step for retrieval accuracy since segmentation removes background information in a tattoo image. Existing segmentation methods do not extract the tattoo very well when the background includes textures and color similar to skin tones. In this paper we describe a tattoo segmentation approach by determining skin pixels in regions near the tattoo. In these regions graph-cut segmentation using a skin color model and a visual saliency map is used to find skin pixels. After segmentation we determine which set of skin pixels are connected with each other that form a closed contour including a tattoo. The regions surrounded by the closed contours are considered tattoo regions. Our method segments tattoos well when the background includes textures and color similar to skin.

Visualization and Quantification of Rotor Tip Vortices in Helicopter Flows

NASA Technical Reports Server (NTRS)

Kao, David L.; Ahmad, Jasim U.; Holst, Terry L.

2015-01-01

This paper presents an automated approach for effective extraction, visualization, and quantification of vortex core radii from the Navier-Stokes simulations of a UH-60A rotor in forward flight. We adopt a scaled Q-criterion to determine vortex regions and then perform vortex core profiling in these regions to calculate vortex core radii. This method provides an efficient way of visualizing and quantifying the blade tip vortices. Moreover, the vortices radii are displayed graphically in a plane.

Ultra-trace analysis of furanic compounds in transformer/rectifier oils with water extraction and high-performance liquid chromatography.

PubMed

Lin, Monica; Lin, Kham; Lin, Amanda; Gras, Ronda; Luong, Jim

2016-07-01

A novel approach for the determination of parts-per-billion level of 5-hydroxymethyl-2-furaldehyde, furfuryl alcohol, furfural, 2-furyl methyl ketone, and 5-methylfurfural in transformer or rectifier oils has been successfully innovated and implemented. Various extraction methods including solid-phase extraction, liquid-liquid extraction using methanol, acetonitrile, and water were studied. Water was by far the most efficient solvent for use as an extraction medium. Separation of the analytes was conducted using a 4.6 mm × 250 mm × 3.5 μm Agilent Zorbax column while detection and quantitation were conducted with a variable wavelength UV detector. Detection limits of all furans were at 1 ppb v/v with linear ranges range from 5 to 1000 ppb v/v with correlation coefficients of 0.997 or better. A relative standard deviation of at most 2.4% at 1000 ppb v/v and 7.3% at 5 ppb v/v and a recovery from 43% to 90% depending on the analyte monitored were obtained. The method was purposely designed to be environmental friendly with water as an extraction medium. Also, the method uses 80% water and 20% acetonitrile with a mere 0.2 mL/min of acetonitrile in an acetonitrile/water mixture as mobile phase. The analytical technique has been demonstrated to be highly reliable with low cost of ownership, suitable for deployment in quality control labs or in regions where available analytical resources and solvents are difficult to procure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discrimination of gender using facial image with expression change

NASA Astrophysics Data System (ADS)

Kuniyada, Jun; Fukuda, Takahiro; Terada, Kenji

2005-12-01

By carrying out marketing research, the managers of large-sized department stores or small convenience stores obtain the information such as ratio of men and women of visitors and an age group, and improve their management plan. However, these works are carried out in the manual operations, and it becomes a big burden to small stores. In this paper, the authors propose a method of men and women discrimination by extracting difference of the facial expression change from color facial images. Now, there are a lot of methods of the automatic recognition of the individual using a motion facial image or a still facial image in the field of image processing. However, it is very difficult to discriminate gender under the influence of the hairstyle and clothes, etc. Therefore, we propose the method which is not affected by personality such as size and position of facial parts by paying attention to a change of an expression. In this method, it is necessary to obtain two facial images with an expression and an expressionless. First, a region of facial surface and the regions of facial parts such as eyes, nose, and mouth are extracted in the facial image with color information of hue and saturation in HSV color system and emphasized edge information. Next, the features are extracted by calculating the rate of the change of each facial part generated by an expression change. In the last step, the values of those features are compared between the input data and the database, and the gender is discriminated. In this paper, it experimented for the laughing expression and smile expression, and good results were provided for discriminating gender.

A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer.

PubMed

Echegaray, Sebastian; Nair, Viswam; Kadoch, Michael; Leung, Ann; Rubin, Daniel; Gevaert, Olivier; Napel, Sandy

2016-12-01

Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts. We propose a new paradigm, called "digital biopsy," that allows for the collection of intensity- and texture-based features from these regions at least 1 order of magnitude faster than the current manual or semiautomated methods. A radiologist reviewed automated segmentations of lung nodules from 100 preoperative volume computed tomography scans of patients with non-small cell lung cancer, and manually adjusted the nodule boundaries in each section, to be used as a reference standard, requiring up to 45 minutes per nodule. We also asked a different expert to generate a digital biopsy for each patient using a paintbrush tool to paint a contiguous region of each tumor over multiple cross-sections, a procedure that required an average of <3 minutes per nodule. We simulated additional digital biopsies using morphological procedures. Finally, we compared the features extracted from these digital biopsies with our reference standard using intraclass correlation coefficient (ICC) to characterize robustness. Comparing the reference standard segmentations to our digital biopsies, we found that 84/94 features had an ICC >0.7; comparing erosions and dilations, using a sphere of 1.5-mm radius, of our digital biopsies to the reference standard segmentations resulted in 41/94 and 53/94 features, respectively, with ICCs >0.7. We conclude that many intensity- and texture-based features remain consistent between the reference standard and our method while substantially reducing the amount of operator time required.

Pavement crack detection combining non-negative feature with fast LoG in complex scene

NASA Astrophysics Data System (ADS)

Wang, Wanli; Zhang, Xiuhua; Hong, Hanyu

2015-12-01

Pavement crack detection is affected by much interference in the realistic situation, such as the shadow, road sign, oil stain, salt and pepper noise etc. Due to these unfavorable factors, the exist crack detection methods are difficult to distinguish the crack from background correctly. How to extract crack information effectively is the key problem to the road crack detection system. To solve this problem, a novel method for pavement crack detection based on combining non-negative feature with fast LoG is proposed. The two key novelties and benefits of this new approach are that 1) using image pixel gray value compensation to acquisit uniform image, and 2) combining non-negative feature with fast LoG to extract crack information. The image preprocessing results demonstrate that the method is indeed able to homogenize the crack image with more accurately compared to existing methods. A large number of experimental results demonstrate the proposed approach can detect the crack regions more correctly compared with traditional methods.

Automated detection of abnormalities in paranasal sinus on dental panoramic radiographs by using contralateral subtraction technique based on mandible contour

NASA Astrophysics Data System (ADS)

Mori, Shintaro; Hara, Takeshi; Tagami, Motoki; Muramatsu, Chicako; Kaneda, Takashi; Katsumata, Akitoshi; Fujita, Hiroshi

2013-02-01

Inflammation in paranasal sinus sometimes becomes chronic to take long terms for the treatment. The finding is important for the early treatment, but general dentists may not recognize the findings because they focus on teeth treatments. The purpose of this study was to develop a computer-aided detection (CAD) system for the inflammation in paranasal sinus on dental panoramic radiographs (DPRs) by using the mandible contour and to demonstrate the potential usefulness of the CAD system by means of receiver operating characteristic analysis. The detection scheme consists of 3 steps: 1) Contour extraction of mandible, 2) Contralateral subtraction, and 3) Automated detection. The Canny operator and active contour model were applied to extract the edge at the first step. At the subtraction step, the right region of the extracted contour image was flipped to compare with the left region. Mutual information between two selected regions was obtained to estimate the shift parameters of image registration. The subtraction images were generated based on the shift parameter. Rectangle regions of left and right paranasal sinus on the subtraction image were determined based on the size of mandible. The abnormal side of the regions was determined by taking the difference between the averages of each region. Thirteen readers were responded to all cases without and with the automated results. The averaged AUC of all readers was increased from 0.69 to 0.73 with statistical significance (p=0.032) when the automated detection results were provided. In conclusion, the automated detection method based on contralateral subtraction technique improves readers' interpretation performance of inflammation in paranasal sinus on DPRs.

Lake Ontario Shore Protection Study: Literature Review Report.

DTIC Science & Technology

1979-07-01

Rochester Region - Extracted from IJC, May 1976 31 Recreational Facilities and Lake Ontario State Parkway Expressways - Existing and Proposed...Throughout Areas of the Lake Ontario Western and Central Basins and the Genesee and Oswego River Basins - Extracted from the Genesee/Finger Lakes Regional...Planning Board, Nov. 1972 32 Recreational Facilities of the Rochester to St. Lawrence Region - Extracted from IJC, May 1976 33 Aquatic Vegetation

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

PubMed

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

2017-03-01

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

A marker-based watershed method for X-ray image segmentation.

PubMed

Zhang, Xiaodong; Jia, Fucang; Luo, Suhuai; Liu, Guiying; Hu, Qingmao

2014-03-01

Digital X-ray images are the most frequent modality for both screening and diagnosis in hospitals. To facilitate subsequent analysis such as quantification and computer aided diagnosis (CAD), it is desirable to exclude image background. A marker-based watershed segmentation method was proposed to segment background of X-ray images. The method consisted of six modules: image preprocessing, gradient computation, marker extraction, watershed segmentation from markers, region merging and background extraction. One hundred clinical direct radiograph X-ray images were used to validate the method. Manual thresholding and multiscale gradient based watershed method were implemented for comparison. The proposed method yielded a dice coefficient of 0.964±0.069, which was better than that of the manual thresholding (0.937±0.119) and that of multiscale gradient based watershed method (0.942±0.098). Special means were adopted to decrease the computational cost, including getting rid of few pixels with highest grayscale via percentile, calculation of gradient magnitude through simple operations, decreasing the number of markers by appropriate thresholding, and merging regions based on simple grayscale statistics. As a result, the processing time was at most 6s even for a 3072×3072 image on a Pentium 4 PC with 2.4GHz CPU (4 cores) and 2G RAM, which was more than one time faster than that of the multiscale gradient based watershed method. The proposed method could be a potential tool for diagnosis and quantification of X-ray images. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

COMPARISON OF PRESSURIZED LIQUID EXTRACTION AND MATRIX SOLID PHASE DISPERSION FOR THE MEASUREMENT OF SEMI-VOLATILE ORGANIC COMPOUND ACCUMULATION IN TADPOLES

EPA Science Inventory

Analytical methods capable of trace measurement of semi-volatile organic compounds (SOCs) are necessary to assess the exposure of tadpoles to contaminants as a result of long-range and regional atmospheric transport and deposition. The following study compares the results of two ...

Mapping analysis of scaffold/matrix attachment regions (s/MARs) from two different mammalian cell lines

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

Pilus, Nur Shazwani Mohd; Ahmad, Azrin; Yusof, Nurul Yuziana Mohd

Scaffold/matrix attachment regions (S/MARs) are potential element that can be integrated into expression vector to increase expression of recombinant protein. Many studies on S/MAR have been done but none has revealed the distribution of S/MAR in a genome. In this study, we have isolated S/MAR sequences from HEK293 and Chinese hamster ovary cell lines (CHO DG44) using two different methods utilizing 2 M NaCl and lithium-3,5-diiodosalicylate (LIS). The isolated S/MARs were sequenced using Next Generation Sequencing (NGS) platform. Based on reference mapping analysis against human genome database, a total of 8,994,856 and 8,412,672 contigs of S/MAR sequences were retrieved frommore » 2M NaCl and LIS extraction of HEK293 respectively. On the other hand, reference mapping analysis of S/MAR derived from CHO DG44 against our own CHO DG44 database have generated a total of 7,204,348 and 4,672,913 contigs from 2 M NaCl and LIS extraction method respectively.« less

Chemical composition of Argentinean propolis collected in extreme regions and its relation with antimicrobial and antioxidant activities.

PubMed

Vera, Nancy; Solorzano, Eliana; Ordoñez, Roxana; Maldonado, Luis; Bedascarrasbure, Enrique; Isla, María I

2011-06-01

This paper reveals, for the first time, the functional properties of propolis from an extreme region of Argentine (El Rincón, Province of Catamarca, Argentina), as well as the isolation and identification of bioactive compounds. The antioxidant activity was determined by the ABTS method and beta-carotene bleaching. The antibacterial activity was determined on methicillin resistant Staphylococcus aureus (MRSA) by the microdilution method and bioautographic assays. Twelve compounds were isolated and identified by NMR spectroscopy. The main bioactive compounds were 2',4'-dihydroxy-3'-methoxychalcone (3), 2',4'-dihydroxychalcone (9), 2',4',4-trihydroxy-6'- methoxychalcone (8), 5-hydroxy-4',7-dimethoxyflavone (4), 4',5-dihydroxy-3,7,8-trimethoxyflavone (10) and 7-hydroxy- 5,8-dimethoxyflavone (11). All compounds were active against clinical isolates (MIC50 10 microg/mL) and displayed antioxidant activity (SC50 values of 20 microg/mL). The MIC and SC50 values of the isolated compounds were lower than those obtained with crude propolis extracts, chloroform sub-extracts and isolated fractions.

3D Feature Extraction for Unstructured Grids

NASA Technical Reports Server (NTRS)

Silver, Deborah

1996-01-01

Visualization techniques provide tools that help scientists identify observed phenomena in scientific simulation. To be useful, these tools must allow the user to extract regions, classify and visualize them, abstract them for simplified representations, and track their evolution. Object Segmentation provides a technique to extract and quantify regions of interest within these massive datasets. This article explores basic algorithms to extract coherent amorphous regions from two-dimensional and three-dimensional scalar unstructured grids. The techniques are applied to datasets from Computational Fluid Dynamics and those from Finite Element Analysis.

Some new classification methods for hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Du, Pei-jun; Chen, Yun-hao; Jones, Simon; Ferwerda, Jelle G.; Chen, Zhi-jun; Zhang, Hua-peng; Tan, Kun; Yin, Zuo-xia

2006-10-01

Hyperspectral Remote Sensing (HRS) is one of the most significant recent achievements of Earth Observation Technology. Classification is the most commonly employed processing methodology. In this paper three new hyperspectral RS image classification methods are analyzed. These methods are: Object-oriented FIRS image classification, HRS image classification based on information fusion and HSRS image classification by Back Propagation Neural Network (BPNN). OMIS FIRS image is used as the example data. Object-oriented techniques have gained popularity for RS image classification in recent years. In such method, image segmentation is used to extract the regions from the pixel information based on homogeneity criteria at first, and spectral parameters like mean vector, texture, NDVI and spatial/shape parameters like aspect ratio, convexity, solidity, roundness and orientation for each region are calculated, finally classification of the image using the region feature vectors and also using suitable classifiers such as artificial neural network (ANN). It proves that object-oriented methods can improve classification accuracy since they utilize information and features both from the point and the neighborhood, and the processing unit is a polygon (in which all pixels are homogeneous and belong to the class). HRS image classification based on information fusion, divides all bands of the image into different groups initially, and extracts features from every group according to the properties of each group. Three levels of information fusion: data level fusion, feature level fusion and decision level fusion are used to HRS image classification. Artificial Neural Network (ANN) can perform well in RS image classification. In order to promote the advances of ANN used for HIRS image classification, Back Propagation Neural Network (BPNN), the most commonly used neural network, is used to HRS image classification.

Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum

NASA Astrophysics Data System (ADS)

Wang, Ruofan; Wang, Jiang; Li, Shunan; Yu, Haitao; Deng, Bin; Wei, Xile

2015-01-01

In this paper, we have combined experimental neurophysiologic recording and statistical analysis to investigate the nonlinear characteristic and the cognitive function of the brain. Spectrum and bispectrum analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease (AD) patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared to the control group, the relative power spectral density of AD group is significantly higher in the theta frequency band, while lower in the alpha frequency bands. In addition, median frequency of spectrum is decreased, and spectral entropy ratio of these two frequency bands undergoes drastic changes at the P3 electrode in the central-parietal brain region, implying that the electrophysiological behavior in AD brain is much slower and less irregular. In order to explore the nonlinear high order information, bispectral analysis which measures the complexity of phase-coupling is further applied to P3 electrode in the whole frequency band. It is demonstrated that less bispectral peaks appear and the amplitudes of peaks fall, suggesting a decrease of non-Gaussianity and nonlinearity of EEG in ADs. Notably, the application of this method to five brain regions shows higher concentration of the weighted center of bispectrum and lower complexity reflecting phase-coupling by bispectral entropy. Based on spectrum and bispectrum analyses, six efficient features are extracted and then applied to discriminate AD from the normal in the five brain regions. The classification results indicate that all these features could differentiate AD patients from the normal controls with a maximum accuracy of 90.2%. Particularly, different brain regions are sensitive to different features. Moreover, the optimal combination of features obtained by discriminant analysis may improve the classification accuracy. These results demonstrate the great promise for scape EEG spectral and bispectral features as a potential effective method for detection of AD, which may facilitate our understanding of the pathological mechanism of the disease.

Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum.

PubMed

Wang, Ruofan; Wang, Jiang; Li, Shunan; Yu, Haitao; Deng, Bin; Wei, Xile

2015-01-01

In this paper, we have combined experimental neurophysiologic recording and statistical analysis to investigate the nonlinear characteristic and the cognitive function of the brain. Spectrum and bispectrum analyses are proposed to extract multiple effective features of electroencephalograph (EEG) signals from Alzheimer's disease (AD) patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared to the control group, the relative power spectral density of AD group is significantly higher in the theta frequency band, while lower in the alpha frequency bands. In addition, median frequency of spectrum is decreased, and spectral entropy ratio of these two frequency bands undergoes drastic changes at the P3 electrode in the central-parietal brain region, implying that the electrophysiological behavior in AD brain is much slower and less irregular. In order to explore the nonlinear high order information, bispectral analysis which measures the complexity of phase-coupling is further applied to P3 electrode in the whole frequency band. It is demonstrated that less bispectral peaks appear and the amplitudes of peaks fall, suggesting a decrease of non-Gaussianity and nonlinearity of EEG in ADs. Notably, the application of this method to five brain regions shows higher concentration of the weighted center of bispectrum and lower complexity reflecting phase-coupling by bispectral entropy. Based on spectrum and bispectrum analyses, six efficient features are extracted and then applied to discriminate AD from the normal in the five brain regions. The classification results indicate that all these features could differentiate AD patients from the normal controls with a maximum accuracy of 90.2%. Particularly, different brain regions are sensitive to different features. Moreover, the optimal combination of features obtained by discriminant analysis may improve the classification accuracy. These results demonstrate the great promise for scape EEG spectral and bispectral features as a potential effective method for detection of AD, which may facilitate our understanding of the pathological mechanism of the disease.

Research of seafloor topographic analyses for a staged mineral exploration

NASA Astrophysics Data System (ADS)

Ikeda, M.; Kadoshima, K.; Koizumi, Y.; Yamakawa, T.; Asakawa, E.; Sumi, T.; Kose, M.

2016-12-01

J-MARES (Research and Development Partnership for Next Generation Technology of Marine Resources Survey, JAPAN) has been designing a low-cost and high-efficiency exploration system for seafloor hydrothermal massive sulfide (SMS) deposits in "Cross-ministerial Strategic Innovation Promotion Program (SIP)" granted by the Cabinet Office, Government of Japan since 2014. We proposed the multi-stage approach, which is designed from the regional scaled to the detail scaled survey stages through semi-detail scaled, focusing a prospective area by seafloor topographic analyses. We applied this method to the area of more than 100km x 100km around Okinawa Trough, including some well-known mineralized deposits. In the regional scale survey, we assume survey areas are more than 100 km x 100km. Then the spatial resolution of topography data should be bigger than 100m. The 500 m resolution data which is interpolated into 250 m resolution was used for extracting depression and performing principal component analysis (PCA) by the wavelength obtained from frequency analysis. As the result, we have successfully extracted the areas having the topographic features quite similar to well-known mineralized deposits. In the semi-local survey stage, we use the topography data obtained by bathymetric survey using multi-narrow beam echo-sounder. The 30m-resolution data was used for extracting depression, relative-large mounds, hills, lineaments as fault, and also for performing frequency analysis. As the result, wavelength as principal component constituting in the target area was extracted by PCA of wavelength obtained from frequency analysis. Therefore, color image was composited by using the second principal component (PC2) to the forth principal component (PC4) in which the continuity of specific wavelength was observed, and consistent with extracted lineaments. In addition, well-known mineralized deposits were discriminated in the same clusters by using clustering from PC2 to PC4.We applied the results described above to a new area, and successfully extract the quite similar area in vicinity to one of the well-known mineralized deposits. So we are going to verify the extracted areas by using geophysical methods, such as vertical cable seismic and time-domain EM survey, developed in this SIP project.

A neural network approach to lung nodule segmentation

NASA Astrophysics Data System (ADS)

Hu, Yaoxiu; Menon, Prahlad G.

2016-03-01

Computed tomography (CT) imaging is a sensitive and specific lung cancer screening tool for the high-risk population and shown to be promising for detection of lung cancer. This study proposes an automatic methodology for detecting and segmenting lung nodules from CT images. The proposed methods begin with thorax segmentation, lung extraction and reconstruction of the original shape of the parenchyma using morphology operations. Next, a multi-scale hessian-based vesselness filter is applied to extract lung vasculature in lung. The lung vasculature mask is subtracted from the lung region segmentation mask to extract 3D regions representing candidate pulmonary nodules. Finally, the remaining structures are classified as nodules through shape and intensity features which are together used to train an artificial neural network. Up to 75% sensitivity and 98% specificity was achieved for detection of lung nodules in our testing dataset, with an overall accuracy of 97.62%+/-0.72% using 11 selected features as input to the neural network classifier, based on 4-fold cross-validation studies. Receiver operator characteristics for identifying nodules revealed an area under curve of 0.9476.

Differential nuclear scaffold/matrix attachment marks expressed genes.

PubMed

Linnemann, Amelia K; Platts, Adrian E; Krawetz, Stephen A

2009-02-15

It is well established that nuclear architecture plays a key role in poising regions of the genome for transcription. This may be achieved using scaffold/matrix attachment regions (S/MARs) that establish loop domains. However, the relationship between changes in the physical structure of the genome as mediated by attachment to the nuclear scaffold/matrix and gene expression is not clearly understood. To define the role of S/MARs in organizing our genome and to resolve the often contradictory loci-specific studies, we have surveyed the S/MARs in HeLa S3 cells on human chromosomes 14-18 by array comparative genomic hybridization. Comparison of LIS (lithium 3,5-diiodosalicylate) extraction to identify SARs and 2 m NaCl extraction to identify MARs revealed that approximately one-half of the sites were in common. The results presented in this study suggest that SARs 5' of a gene are associated with transcript presence whereas MARs contained within a gene are associated with silenced genes. The varied functions of the S/MARs as revealed by the different extraction methods highlights their unique functional contribution.

Differential nuclear scaffold/matrix attachment marks expressed genes†

PubMed Central

Linnemann, Amelia K.; Platts, Adrian E.; Krawetz, Stephen A.

2009-01-01

It is well established that nuclear architecture plays a key role in poising regions of the genome for transcription. This may be achieved using scaffold/matrix attachment regions (S/MARs) that establish loop domains. However, the relationship between changes in the physical structure of the genome as mediated by attachment to the nuclear scaffold/matrix and gene expression is not clearly understood. To define the role of S/MARs in organizing our genome and to resolve the often contradictory loci-specific studies, we have surveyed the S/MARs in HeLa S3 cells on human chromosomes 14–18 by array comparative genomic hybridization. Comparison of LIS (lithium 3,5-diiodosalicylate) extraction to identify SARs and 2 m NaCl extraction to identify MARs revealed that approximately one-half of the sites were in common. The results presented in this study suggest that SARs 5′ of a gene are associated with transcript presence whereas MARs contained within a gene are associated with silenced genes. The varied functions of the S/MARs as revealed by the different extraction methods highlights their unique functional contribution. PMID:19017725

Evaluation of antileishmanial, cytotoxic and antioxidant activities of essential oils extracted from plants issued from the leishmaniasis-endemic region of Sned (Tunisia).

PubMed

Ahmed, S Ben Hadj; Sghaier, R M; Guesmi, F; Kaabi, B; Mejri, M; Attia, H; Laouini, D; Smaali, I

2011-07-01

In this study, we tested 10 essential oils (EOs) extracted from 10 plants issued from Sned region (Tunisia) to evaluate both their leishmanicidal effects against Leishmania major and L. infantum, and their cytotoxicity against murine macrophage cell line RAW 264.7 (ATCC, TIB-71). The antioxidant activity was also monitored by the DDPH method, while the chemical composition of active EO was assessed by GC-MS analysis. The results showed that the EOs obtained from Thymus hirtus sp. algeriensis (rich on monoterpenoids, especially linalool at 17.62% and camphor at 13.82%) is significantly active against both L. major and L. infantum, whereas Ruta chalepensis EO (rich on 2-undecanone at 84.28%) is only active against L. infantum. Both oil extracts showed low cytotoxicity towards murine macrophages. The characteristic ratios (IC₈₀ Raw264.7 cells/IC₅₀ L. infantum and IC₈₀ Raw264.7 cells/IC₅₀ L. major) were, respectively, 2.7 and 1.57 for T. hirtus sp. algeriensis, and 1.34 and 0.19 for R. chalepensis. However, when measuring the antioxidant effects (DDPH method), the two latter EOs presented a moderate 2,2-diphenyl-2-picrylhydrazyl hydrate scavenging effects compared to EOs from Eucaliptus globulus, Pinus halepensis, Pituranthos tortuosus, Rosmarinus officinalis, Tetraclinis articulata or to BHT.

Investigation of relationships between parameters of solar nano-flares and solar activity

NASA Astrophysics Data System (ADS)

Safari, Hossein; Javaherian, Mohsen; Kaki, Bardia

2016-07-01

Solar flares are one of the important coronal events which are originated in solar magnetic activity. They release lots of energy during the interstellar medium, right after the trigger. Flare prediction can play main role in avoiding eventual damages on the Earth. Here, to interpret solar large-scale events (e.g., flares), we investigate relationships between small-scale events (nano-flares) and large-scale events (e.g., flares). In our method, by using simulations of nano-flares based on Monte Carlo method, the intensity time series of nano-flares are simulated. Then, the solar full disk images taken at 171 angstrom recorded by SDO/AIA are employed. Some parts of the solar disk (quiet Sun (QS), coronal holes (CHs), and active regions (ARs)) are cropped and the time series of these regions are extracted. To compare the simulated intensity time series of nano-flares with the intensity time series of real data extracted from different parts of the Sun, the artificial neural networks is employed. Therefore, we are able to extract physical parameters of nano-flares like both kick and decay rate lifetime, and the power of their power-law distributions. The procedure of variations in the power value of power-law distributions within QS, CH is similar to AR. Thus, by observing the small part of the Sun, we can follow the procedure of solar activity.

Development of extraction method for characterization of free and bonded polyphenols in barley (Hordeum vulgare L.) grown in Czech Republic using liquid chromatography-tandem mass spectrometry.

PubMed

Arigò, Adriana; Česla, Petr; Šilarová, Petra; Calabrò, Maria Luisa; Česlová, Lenka

2018-04-15

Complete characterizations of free and bonded phenolic compounds, presented in four cultivars of barley from two regions of Czech Republic, were achieved, using optimized solvent extraction and liquid chromatography coupled with tandem mass spectrometry. The optimization of extraction of free polyphenols was performed using Box-Behnken design and response surface methodology. The intra-day and extra-day precision of developed method were below 6% and 12%, respectively. The isolation of polyphenols bonded to the cell wall structure was carried out by a hydrolysis process. In all cultivars, p-hydroxybenzoic, p-coumaric and ferulic acids were the most abundant compounds. Their average amounts in barley samples were 17.6, 15.2 and 54.4% (m/m), respectively. The highest amount of these compounds was found in the bonded form, proving the importance of this procedure for the correct characterization of total polyphenols in food matrices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of Buried Objects in GPR Using Amplitude Modulated Signals Extracted from Multiresolution Monogenic Signal Analysis

PubMed Central

Qiao, Lihong; Qin, Yao; Ren, Xiaozhen; Wang, Qifu

2015-01-01

It is necessary to detect the target reflections in ground penetrating radar (GPR) images, so that surface metal targets can be identified successfully. In order to accurately locate buried metal objects, a novel method called the Multiresolution Monogenic Signal Analysis (MMSA) system is applied in ground penetrating radar (GPR) images. This process includes four steps. First the image is decomposed by the MMSA to extract the amplitude component of the B-scan image. The amplitude component enhances the target reflection and suppresses the direct wave and reflective wave to a large extent. Then we use the region of interest extraction method to locate the genuine target reflections from spurious reflections by calculating the normalized variance of the amplitude component. To find the apexes of the targets, a Hough transform is used in the restricted area. Finally, we estimate the horizontal and vertical position of the target. In terms of buried object detection, the proposed system exhibits promising performance, as shown in the experimental results. PMID:26690146

Dynamic cardiac PET imaging: extraction of time-activity curves using ICA and a generalized Gaussian distribution model.

PubMed

Mabrouk, Rostom; Dubeau, François; Bentabet, Layachi

2013-01-01

Kinetic modeling of metabolic and physiologic cardiac processes in small animals requires an input function (IF) and a tissue time-activity curves (TACs). In this paper, we present a mathematical method based on independent component analysis (ICA) to extract the IF and the myocardium's TACs directly from dynamic positron emission tomography (PET) images. The method assumes a super-Gaussian distribution model for the blood activity, and a sub-Gaussian distribution model for the tissue activity. Our appreach was applied on 22 PET measurement sets of small animals, which were obtained from the three most frequently used cardiac radiotracers, namely: desoxy-fluoro-glucose ((18)F-FDG), [(13)N]-ammonia, and [(11)C]-acetate. Our study was extended to PET human measurements obtained with the Rubidium-82 ((82) Rb) radiotracer. The resolved mathematical IF values compare favorably to those derived from curves extracted from regions of interest (ROI), suggesting that the procedure presents a reliable alternative to serial blood sampling for small-animal cardiac PET studies.

Comparison of a modified phenol/chloroform and commercial-kit methods for extracting DNA from horse fecal material.

PubMed

Janabi, Ali H D; Kerkhof, Lee J; McGuinness, Lora R; Biddle, Amy S; McKeever, Kenneth H

2016-10-01

There are many choices for methods of extracting bacterial DNA for Next Generation Sequencing (NGS) from fecal samples. Here, we compare our modifications of a phenol/chloroform extraction method plus an inhibitor removal solution (C3) (ph/Chl+C3) to the PowerFecal® DNA Isolation Kit (MoBio-K). DNA quality and quantity coupled to NGS results were used to assess differences in relative abundance, Shannon diversity index, unique species, and principle coordinate analysis (PCoA) between biological replicates. Six replicate samples, taken from a single ball of horse feces manually collected from the rectum, were subjected to each extraction method. The Ph/Chl+C3 method produced 100× higher DNA yields with less shearing than the MoBio-K method. To assess the methods, the two method samples were sent for sequencing of the bacterial V3-V4 region of 16S rRNA gene using the Illumina MiSeq platform. The relative abundance of Bacteroidetes was greater and there were more unique species assigned to this group in MoBio-K than in Ph/Chl+C3 (P<0.05). In contrast, Firmicutes had greater relative abundance and more unique species in Ph/Chl+C3 extracts than in MoBio-K (P<0.05). The other major bacterial phyla were equally abundant in samples using both extraction methods. Alpha diversity and Shannon Weaver indices showed greater evenness of bacterial distribution in Ph/Chl+C3 compared with MoBio-K (P<0.05), but there was no difference in the OTU richness. Principle coordinate analysis (PCoA) indicated a distinct separation between the two methods (P<0.05) and tighter clustering (less variability) in Ph/Chl+C3 than in MoBio-K. These results suggest that the Ph/Chl+C3 may be preferred for research to identify specific Firmicutes taxa such as Clostridium, and Bacillus. However; MoBio-K may be a better choice for projects focusing on Bacteroidetes abundance. The Ph/Chl+C3 method required less time, but has some safety concerns associated with exposure and disposal of phenol and chloroform. While the MoBio-K may be better choice for researchers with less access to safety equipment like a fume hood. Copyright © 2016 Elsevier B.V. All rights reserved.

[Research on suitable distribution of Paris yunnanensis based on remote sensing and GIS].

PubMed

Luo, Yao; Dong, Yong-Bo; Zhu, Cong; Peng, Wen-Fu; Fang, Qing-Mao; Xu, Xin-Liang

2017-11-01

Paris yunnanensis is a kind of rare medicinal herb, having a very high medicinal value. Studying its suitable ecological condition can provide a basis for its rational exploitation, artificial cultivation, and sustainable utilization. A practicable method in this paper has been proposed to research the suitable regional distribution of P. yunnanensis in Sichuan province. By the case study of P. yunnanensis in Sichuan province, and according to related literatures, the suitable ecological condition of P. yunnanensis such as altitude, mean annual temperature (MAT), annual precipitation, regional slope, slope ranges, vegetative cover, and soil types was analyzed following remote sensing (RS) and GIS.The appropriate distribution regionof P. yunnanensis and its area were extracted based on RS and GIS technology,combing with the information of the field validation data. The results showed that the concentrated distribution regions in counties of Sichuan province were, Liangshan prefecture, Aba prefecture, Sertar county of Ganzi prefecture, Panzhihua city, Ya'an city, Chengdu city, Meishan city, Leshan city, Yibin city, Neijiang city, Luzhou city, Bazhong city, Nanchong city, Guangyuan city and other cities and counties area.The suitable distribution area in Sichuan is about 7 338 km², accounting for 3.02% of the total study regional area. The analysis result has high consistency with the filed validation data, and the research method for P. yunnanensis distribution region based onspatial overlay analysis and the extracted the information of land usage and ecological factors following the RS and GIS is reliable. Copyright© by the Chinese Pharmaceutical Association.

Cancer risk to First Nations’ people from exposure to polycyclic aromatic hydrocarbons near in-situ bitumen extraction in Cold Lake, Alberta

PubMed Central

2014-01-01

Background The Alberta oil sands are an important economic resource in Canada, but there is growing concern over the environmental and health effects as a result of contaminant releases and exposures. Recent studies have shown a temporal and spatial trend of increased polycyclic aromatic hydrocarbon (PAH) concentrations in sediments and snowpack near the Athabasca oil sands operations (i.e., open pit mines), but thus far similar studies have not been done for the Cold Lake region where steam assisted gravity drainage (in situ) extraction is performed. Methods Many PAHs are known mutagenic carcinogens, and this study measured soil and atmospheric concentrations of PAHs in the Cold Lake region to assess the excess lifetime cancer risk posed to the First Nations’ inhabitants of the region. Using both deterministic and probabilistic risk assessment methods, excess lifetime cancer risks were calculated for exposures from inhalation or inadvertent soil ingestion. Results The mean excess cancer risk for First Nations’ people through ingestion who engage in traditional wilderness activities in the Cold Lake region was 0.02 new cases per 100,000 with an upper 95% risk level of 0.07 cases per 100,000. Exposure to PAHs via inhalation revealed a maximum excess lifetime cancer risk of less than 0.1 cases per 100,000. Conclusions Excess lifetime risk values below 1 case per 100,000 is generally considered negligible, thus our analyses did not demonstrate any significant increases in cancer risks associated with PAH exposures for First Nations people inhabiting the Cold Lake region. PMID:24520827

Investigation of Antarctic Marine Metazoan Biodiversity Through Metagenomic Analysis of Environmental DNA

NASA Astrophysics Data System (ADS)

Cowart, D. A.; Cheng, C. C.; Murphy, K.

2016-02-01

Environmental DNA (eDNA), or DNA extracted from environmental collections, is frequently used to gauge biodiversity and identify the presence of rare or invasive species within a habitat. Previous studies have demonstrated that compared to traditional surveying methods, high-throughput sequencing of eDNA can provide increased detection sensitivity of aquatic taxa, holding promise for various conservation applications. To determine the potential of eDNA for assessing biodiversity of Antarctic marine metazoan communities, we have extracted eDNA from seawater sampled from four regions near Palmer Station in West Antarctic Peninsula. Metagenomic sequencing of the eDNA was performed on Illumina HiSeq2500, and produced 325 million quality-processed reads. Preliminary read mapping for two regions, Gerlache Strait and Bismarck Strait, identified approximately 4% of reads mapping to eukaryotes for each region, with >50% of the those reads mapping to metazoan animals. Key groups investigated include the nototheniidae family of Antarctic fishes, to which 0.2 and 0.8 % of the metazoan reads were assigned for each region respectively. The presence of the recently invading lithodidae king crabs was also detected at both regions. Additionally, to estimate the persistence of eDNA in polar seawater, a rate of eDNA decay will be quantified from seawater samples collected over 20 days from Antarctic fish holding tanks and held at ambient Antarctic water temperatures. The ability to detect animal signatures from eDNA, as well as the quantification of eDNA decay over time, could provide another method for reliable monitoring of polar habitats at various spatial and temporal scales.

OLED with improved light outcoupling

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

Forrest, Stephen; Sun, Yiru

2016-11-29

An OLED may include regions of a material having a refractive index less than that of the substrate, or of the organic region, allowing for emitted light in a waveguide mode to be extracted into air. These regions can be placed adjacent to the emissive regions of an OLED in a direction parallel to the electrodes. The substrate may also be given a nonstandard shape to further improve the conversion of waveguide mode and/or glass mode light to air mode. The outcoupling efficiency of such a device may be up to two to three times the efficiency of a standardmore » OLED. Methods for fabricating such a transparent or top-emitting OLED is also provided.« less

EnsembleGraph: Interactive Visual Analysis of Spatial-Temporal Behavior for Ensemble Simulation Data

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

Shu, Qingya; Guo, Hanqi; Che, Limei

We present a novel visualization framework—EnsembleGraph— for analyzing ensemble simulation data, in order to help scientists understand behavior similarities between ensemble members over space and time. A graph-based representation is used to visualize individual spatiotemporal regions with similar behaviors, which are extracted by hierarchical clustering algorithms. A user interface with multiple-linked views is provided, which enables users to explore, locate, and compare regions that have similar behaviors between and then users can investigate and analyze the selected regions in detail. The driving application of this paper is the studies on regional emission influences over tropospheric ozone, which is based onmore » ensemble simulations conducted with different anthropogenic emission absences using the MOZART-4 (model of ozone and related tracers, version 4) model. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations. Positive feedbacks from domain experts and two case studies prove efficiency of our method.« less

Antifungal activity of Curcuma longa grown in Thailand.

PubMed

Wuthi-udomlert, M; Grisanapan, W; Luanratana, O; Caichompoo, W

2000-01-01

Curcuma longa Linn. or turmeric (Zingiberaceae) is a medicinal plant widely used and cultivated in tropical regions. According to Thai traditional texts, fresh and dried rhizomes are used as peptic ulcer treatment, carminatives, wound treatment and anti-inflammatory agent. Using hydro distillation, 1.88% and 7.02% (v/w) volatile oils were extracted from fresh and dried rhizomes, respectively, and 6.95% (w/w)crude curcuminoids were extracted from dried rhizomes. Dried powder was extracted with 95% ethanol and yielded 29.52% (w/w) crude ethanol extract composed of curcumin (11.6%), demethoxycurcumin (10.32%) and bisdemethoxycurcumin (10.77%). These extracts were tested for antifungal activity by agar disc diffusion method against 29 clinical strains of dermatophytes. It was found that crude ethanol extract exhibited an inhibition zone range of 6.1 to 26.0 mm. There was no inhibition activity from crude curcuminoids while curcumin, demethoxycurcumin and bisdemethoxycutcumin gave different inhibition zone diameters ranging from 6.1 to 16.0 mm. Although antifungal activity of undiluted freshly distilled oil and 18-month-old oil revealed some differences, the inhibition zone diameters for both extracts varied within 26.1 to 46.0 mm. With 200 mg/ml ketoconazole, the activities of the standard agent were similar to the oil, both freshly distilled and 18-month-old, but were significantly different from those of curcuminoid compounds and crude ethanol extracts (p < 0.01). Turmeric oil was also tested for its minimum inhibitory concentration (MIC) by broth dilution method. The MICs of freshly distilled and 18-month-old oils were 7.8 and 7.2 mg/ml respectively.

SU-F-J-207: Non-Small Cell Lung Cancer Patient Survival Prediction with Quantitative Tumor Textures Analysis in Baseline CT

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

Wu, Y; Zou, J; Murillo, P

Purpose: Chemo-radiation therapy (CRT) is widely used in treating patients with locally advanced non-small cell lung cancer (NSCLC). Determination of the likelihood of patient response to treatment and optimization of treatment regime is of clinical significance. Up to date, no imaging biomarker has reliably correlated to NSCLC patient survival rate. This pilot study is to extract CT texture information from tumor regions for patient survival prediction. Methods: Thirteen patients with stage II-III NSCLC were treated using CRT with a median dose of 6210 cGy. Non-contrast-enhanced CT images were acquired for treatment planning and retrospectively collected for this study. Texture analysismore » was applied in segmented tumor regions using the Local Binary Pattern method (LBP). By comparing its HU with neighboring voxels, the LBPs of a voxel were measured in multiple scales with different group radiuses and numbers of neighbors. The LBP histograms formed a multi-dimensional texture vector for each patient, which was then used to establish and test a Support Vector Machine (SVM) model to predict patients’ one year survival. The leave-one-out cross validation strategy was used recursively to enlarge the training set and derive a reliable predictor. The predictions were compared with the true clinical outcomes. Results: A 10-dimensional LBP histogram was extracted from 3D segmented tumor region for each of the 13 patients. Using the SVM model with the leave-one-out strategy, only 1 out of 13 patients was misclassified. The experiments showed an accuracy of 93%, sensitivity of 100%, and specificity of 86%. Conclusion: Within the framework of a Support Vector Machine based model, the Local Binary Pattern method is able to extract a quantitative imaging biomarker in the prediction of NSCLC patient survival. More patients are to be included in the study.« less

Informative frame detection from wireless capsule video endoscopic images

NASA Astrophysics Data System (ADS)

Bashar, Md. Khayrul; Mori, Kensaku; Suenaga, Yasuhito; Kitasaka, Takayuki; Mekada, Yoshito

2008-03-01

Wireless capsule endoscopy (WCE) is a new clinical technology permitting the visualization of the small bowel, the most difficult segment of the digestive tract. The major drawback of this technology is the high amount of time for video diagnosis. In this study, we propose a method for informative frame detection by isolating useless frames that are substantially covered by turbid fluids or their contamination with other materials, e.g., faecal, semi-processed or unabsorbed foods etc. Such materials and fluids present a wide range of colors, from brown to yellow, and/or bubble-like texture patterns. The detection scheme, therefore, consists of two stages: highly contaminated non-bubbled (HCN) frame detection and significantly bubbled (SB) frame detection. Local color moments in the Ohta color space are used to characterize HCN frames, which are isolated by the Support Vector Machine (SVM) classifier in Stage-1. The rest of the frames go to the Stage-2, where Laguerre gauss Circular Harmonic Functions (LG-CHFs) extract the characteristics of the bubble-structures in a multi-resolution framework. An automatic segmentation method is designed to extract the bubbled regions based on local absolute energies of the CHF responses, derived from the grayscale version of the original color image. Final detection of the informative frames is obtained by using threshold operation on the extracted regions. An experiment with 20,558 frames from the three videos shows the excellent average detection accuracy (96.75%) by the proposed method, when compared with the Gabor based- (74.29%) and discrete wavelet based features (62.21%).

Effects of Hydrocarbon Extraction on Landscapes of the Appalachian Basin

USGS Publications Warehouse

Slonecker, Terry E.; Milheim, Lesley E.; Roig-Silva, Coral M.; Kalaly, Siddiq S.

2015-09-30

The need for energy resources has created numerous economic opportunities for hydrocarbon extraction in the Appalachian basin. The development of alternative energy natural gas resources from deep-shale drilling techniques, along with conventional natural gas extraction methods, has created a flurry of wells, roads, pipelines, and related infrastructure across many parts of the region. An unintended and sometimes overlooked consequence of these activities is their effect on the structure and function of the landscape and ecosystems. The collective effect of over 100,000 hydrocarbon extraction permits for oil, coal bed methane, Marcellus and Utica Shale natural gas wells, and other types of hydrocarbon gases and their associated infrastructure has saturated much of the landscape and disturbed the natural environment in the Appalachian basin. The disturbance created by the sheer magnitude of the development of these collective wells and infrastructure directly affects how the landscape and ecosystems function and how they provide ecological goods and services. 

Turmeric extract inhibits apoptosis of hippocampal neurons of trimethyltin-exposed rats.

PubMed

Yuliani, S; Widyarini, S; Mustofa; Partadiredja, G

2017-01-01

The aim of the present study was to reveal the possible antiapoptotic effect of turmeric (Curcuma longa Linn.) on the hippocampal neurons of rats exposed to trimethyltin (TMT). Oxidative damage in the hippocampus can induce the apoptosis of neurons associated with the pathogenesis of dementiaMETHODS. The ethanolic turmeric extract and a citicoline (as positive control) solution were administered to the TMT-exposed rats for 28 days. The body weights of rats were recorded once a week. The hippocampal weights and imumunohistochemical expression of caspase 3 proteins in the CA1 and CA2-CA3 regions of the hippocampi were examined at the end of the experiment. Immunohistochemical analysis showed that the injection of TMT increased the expression of caspase 3 in the CA1 and CA2-CA3 regions of hippocampus. TMT also decreased the body and hippocampal weights. Furthermore, the administration of 200 mg/kg bw dose of turmeric extract decreased the caspase 3 expression in the CA2-CA3 pyramidal neurons but not in the CA1 neurons. It also prevented the decrease of the body and hippocampal weights. We suggest that the 200 mg/kg bw dose of turmeric extract may exert antiapoptotic effect on the hippocampal neurons of the TMT-exposed rats (Tab. 1, Fig. 3, Ref. 49).

[A method for the analysis of overlapped peaks in the high performance liquid chromatogram based on spectrum analysis].

PubMed

Liu, Bao; Fan, Xiaoming; Huo, Shengnan; Zhou, Lili; Wang, Jun; Zhang, Hui; Hu, Mei; Zhu, Jianhua

2011-12-01

A method was established to analyse the overlapped chromatographic peaks based on the chromatographic-spectra data detected by the diode-array ultraviolet detector. In the method, the three-dimensional data were de-noised and normalized firstly; secondly the differences and clustering analysis of the spectra at different time points were calculated; then the purity of the whole chromatographic peak were analysed and the region were sought out in which the spectra of different time points were stable. The feature spectra were extracted from the spectrum-stable region as the basic foundation. The nonnegative least-square method was chosen to separate the overlapped peaks and get the flow curve which was based on the feature spectrum. The three-dimensional divided chromatographic-spectrum peak could be gained by the matrix operations of the feature spectra with the flow curve. The results displayed that this method could separate the overlapped peaks.

An Improved Image Ringing Evaluation Method with Weighted Sum of Gray Extreme Value

NASA Astrophysics Data System (ADS)

Yang, Ling; Meng, Yanhua; Wang, Bo; Bai, Xu

2018-03-01

Blind image restoration algorithm usually produces ringing more obvious at the edges. Ringing phenomenon is mainly affected by noise, species of restoration algorithm, and the impact of the blur kernel estimation during restoration. Based on the physical mechanism of ringing, a method of evaluating the ringing on blind restoration images is proposed. The method extracts the ringing image overshooting and ripple region to make the weighted statistics for the regional gradient value. According to the weights set by multiple experiments, the edge information is used to characterize the details of the edge to determine the weight, quantify the seriousness of the ring effect, and propose the evaluation method of the ringing caused by blind restoration. The experimental results show that the method can effectively evaluate the ring effect in the restoration images under different restoration algorithms and different restoration parameters. The evaluation results are consistent with the visual evaluation results.

Automated prostate cancer localization without the need for peripheral zone extraction using multiparametric MRI.

PubMed

Liu, Xin; Yetik, Imam Samil

2011-06-01

Multiparametric magnetic resonance imaging (MRI) has been shown to have higher localization accuracy than transrectal ultrasound (TRUS) for prostate cancer. Therefore, automated cancer segmentation using multiparametric MRI is receiving a growing interest, since MRI can provide both morphological and functional images for tissue of interest. However, all automated methods to this date are applicable to a single zone of the prostate, and the peripheral zone (PZ) of the prostate needs to be extracted manually, which is a tedious and time-consuming job. In this paper, our goal is to remove the need of PZ extraction by incorporating the spatial and geometric information of prostate tumors with multiparametric MRI derived from T2-weighted MRI, diffusion-weighted imaging (DWI) and dynamic contrast enhanced MRI (DCE-MRI). In order to remove the need of PZ extraction, the authors propose a new method to incorporate the spatial information of the cancer. This is done by introducing a new feature called location map. This new feature is constructed by applying a nonlinear transformation to the spatial position coordinates of each pixel, so that the location map implicitly represents the geometric position of each pixel with respect to the prostate region. Then, this new feature is combined with multiparametric MR images to perform tumor localization. The proposed algorithm is applied to multiparametric prostate MRI data obtained from 20 patients with biopsy-confirmed prostate cancer. The proposed method which does not need the masks of PZ was found to have prostate cancer detection specificity of 0.84, sensitivity of 0.80 and dice coefficient value of 0.42. The authors have found that fusing the spatial information allows us to obtain tumor outline without the need of PZ extraction with a considerable success (better or similar performance to methods that require manual PZ extraction). Our experimental results quantitatively demonstrate the effectiveness of the proposed method, depicting that the proposed method has a slightly better or similar localization performance compared to methods which require the masks of PZ.

Optimization of plasma parameters with magnetic filter field and pressure to maximize H{sup −} ion density in a negative hydrogen ion source

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

Cho, Won-Hwi; Dang, Jeong-Jeung; Kim, June Young

2016-02-15

Transverse magnetic filter field as well as operating pressure is considered to be an important control knob to enhance negative hydrogen ion production via plasma parameter optimization in volume-produced negative hydrogen ion sources. Stronger filter field to reduce electron temperature sufficiently in the extraction region is favorable, but generally known to be limited by electron density drop near the extraction region. In this study, unexpected electron density increase instead of density drop is observed in front of the extraction region when the applied transverse filter field increases monotonically toward the extraction aperture. Measurements of plasma parameters with a movable Langmuirmore » probe indicate that the increased electron density may be caused by low energy electron accumulation in the filter region decreasing perpendicular diffusion coefficients across the increasing filter field. Negative hydrogen ion populations are estimated from the measured profiles of electron temperatures and densities and confirmed to be consistent with laser photo-detachment measurements of the H{sup −} populations for various filter field strengths and pressures. Enhanced H{sup −} population near the extraction region due to the increased low energy electrons in the filter region may be utilized to increase negative hydrogen beam currents by moving the extraction position accordingly. This new finding can be used to design efficient H{sup −} sources with an optimal filtering system by maximizing high energy electron filtering while keeping low energy electrons available in the extraction region.« less

Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

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

Danny L. Anderson

Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates amore » new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed “mDn”, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.« less

Zone-size nonuniformity of 18F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer.

PubMed

Cheng, Nai-Ming; Fang, Yu-Hua Dean; Lee, Li-yu; Chang, Joseph Tung-Chieh; Tsan, Din-Li; Ng, Shu-Hang; Wang, Hung-Ming; Liao, Chun-Ta; Yang, Lan-Yan; Hsu, Ching-Han; Yen, Tzu-Chen

2015-03-01

The question as to whether the regional textural features extracted from PET images predict prognosis in oropharyngeal squamous cell carcinoma (OPSCC) remains open. In this study, we investigated the prognostic impact of regional heterogeneity in patients with T3/T4 OPSCC. We retrospectively reviewed the records of 88 patients with T3 or T4 OPSCC who had completed primary therapy. Progression-free survival (PFS) and disease-specific survival (DSS) were the main outcome measures. In an exploratory analysis, a standardized uptake value of 2.5 (SUV 2.5) was taken as the cut-off value for the detection of tumour boundaries. A fixed threshold at 42 % of the maximum SUV (SUVmax 42 %) and an adaptive threshold method were then used for validation. Regional textural features were extracted from pretreatment (18)F-FDG PET/CT images using the grey-level run length encoding method and grey-level size zone matrix. The prognostic significance of PET textural features was examined using receiver operating characteristic (ROC) curves and Cox regression analysis. Zone-size nonuniformity (ZSNU) was identified as an independent predictor of PFS and DSS. Its prognostic impact was confirmed using both the SUVmax 42 % and the adaptive threshold segmentation methods. Based on (1) total lesion glycolysis, (2) uniformity (a local scale texture parameter), and (3) ZSNU, we devised a prognostic stratification system that allowed the identification of four distinct risk groups. The model combining the three prognostic parameters showed a higher predictive value than each variable alone. ZSNU is an independent predictor of outcome in patients with advanced T-stage OPSCC, and may improve their prognostic stratification.

Assessment of global and local region-based bilateral mammographic feature asymmetry to predict short-term breast cancer risk

NASA Astrophysics Data System (ADS)

Li, Yane; Fan, Ming; Cheng, Hu; Zhang, Peng; Zheng, Bin; Li, Lihua

2018-01-01

This study aims to develop and test a new imaging marker-based short-term breast cancer risk prediction model. An age-matched dataset of 566 screening mammography cases was used. All ‘prior’ images acquired in the two screening series were negative, while in the ‘current’ screening images, 283 cases were positive for cancer and 283 cases remained negative. For each case, two bilateral cranio-caudal view mammograms acquired from the ‘prior’ negative screenings were selected and processed by a computer-aided image processing scheme, which segmented the entire breast area into nine strip-based local regions, extracted the element regions using difference of Gaussian filters, and computed both global- and local-based bilateral asymmetrical image features. An initial feature pool included 190 features related to the spatial distribution and structural similarity of grayscale values, as well as of the magnitude and phase responses of multidirectional Gabor filters. Next, a short-term breast cancer risk prediction model based on a generalized linear model was built using an embedded stepwise regression analysis method to select features and a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) values significantly increased from 0.5863  ±  0.0237 to 0.6870  ±  0.0220 when the model trained by the image features extracted from the global regions and by the features extracted from both the global and the matched local regions (p  =  0.0001). The odds ratio values monotonically increased from 1.00-8.11 with a significantly increasing trend in slope (p  =  0.0028) as the model-generated risk score increased. In addition, the AUC values were 0.6555  ±  0.0437, 0.6958  ±  0.0290, and 0.7054  ±  0.0529 for the three age groups of 37-49, 50-65, and 66-87 years old, respectively. AUC values of 0.6529  ±  0.1100, 0.6820  ±  0.0353, 0.6836  ±  0.0302 and 0.8043  ±  0.1067 were yielded for the four mammography density sub-groups (BIRADS from 1-4), respectively. This study demonstrated that bilateral asymmetry features extracted from local regions combined with the global region in bilateral negative mammograms could be used as a new imaging marker to assist in the prediction of short-term breast cancer risk.

Plantar fascia segmentation and thickness estimation in ultrasound images.

PubMed

Boussouar, Abdelhafid; Meziane, Farid; Crofts, Gillian

2017-03-01

Ultrasound (US) imaging offers significant potential in diagnosis of plantar fascia (PF) injury and monitoring treatment. In particular US imaging has been shown to be reliable in foot and ankle assessment and offers a real-time effective imaging technique that is able to reliably confirm structural changes, such as thickening, and identify changes in the internal echo structure associated with diseased or damaged tissue. Despite the advantages of US imaging, images are difficult to interpret during medical assessment. This is partly due to the size and position of the PF in relation to the adjacent tissues. It is therefore a requirement to devise a system that allows better and easier interpretation of PF ultrasound images during diagnosis. This study proposes an automatic segmentation approach which for the first time extracts ultrasound data to estimate size across three sections of the PF (rearfoot, midfoot and forefoot). This segmentation method uses artificial neural network module (ANN) in order to classify small overlapping patches as belonging or not-belonging to the region of interest (ROI) of the PF tissue. Features ranking and selection techniques were performed as a post-processing step for features extraction to reduce the dimension and number of the extracted features. The trained ANN classifies the image overlapping patches into PF and non-PF tissue, and then it is used to segment the desired PF region. The PF thickness was calculated using two different methods: distance transformation and area-length calculation algorithms. This new approach is capable of accurately segmenting the PF region, differentiating it from surrounding tissues and estimating its thickness. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evaluation of Biologically Active Compounds from Calendula officinalis Flowers using Spectrophotometry

PubMed Central

2012-01-01

Background This study aimed to quantify the active biological compounds in C. officinalis flowers. Based on the active principles and biological properties of marigolds flowers reported in the literature, we sought to obtain and characterize the molecular composition of extracts prepared using different solvents. The antioxidant capacities of extracts were assessed by using spectrophotometry to measure both absorbance of the colorimetric free radical scavenger 2,2-diphenyl-1-picrylhydrazyl (DPPH) as well as the total antioxidant potential, using the ferric reducing power (FRAP) assay. Results Spectrophotometric assays in the ultraviolet-visible (UV-VIS) region enabled identification and characterization of the full range of phenolic and flavonoids acids, and high-performance liquid chromatography (HPLC) was used to identify and quantify phenolic compounds (depending on the method of extraction). Methanol ensured more efficient extraction of flavonoids than the other solvents tested. Antioxidant activity in methanolic extracts was correlated with the polyphenol content. Conclusions The UV-VIS spectra of assimilator pigments (e.g. chlorophylls), polyphenols and flavonoids extracted from the C. officinalis flowers consisted in quantitative evaluation of compounds which absorb to wavelengths broader than 360 nm. PMID:22540963

PCA Tomography: how to extract information from data cubes

NASA Astrophysics Data System (ADS)

Steiner, J. E.; Menezes, R. B.; Ricci, T. V.; Oliveira, A. S.

2009-05-01

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector's orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the National Science Foundation on behalf of the Gemini partnership: the National Science Foundation (United States), the Science and Technology Facilities Council (United Kingdom), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência e Tecnologia (Brazil) and SECYT (Argentina). E-mail: steiner@astro.iag.usp.br

Study of the chemical composition of particulate matter from the Rio de Janeiro metropolitan region, Brazil, by inductively coupled plasma-mass spectrometry and optical emission spectrometry

NASA Astrophysics Data System (ADS)

Mateus, Vinícius Lionel; Monteiro, Isabela Luizi Gonçalves; Rocha, Rafael Christian Chávez; Saint'Pierre, Tatiana Dillenburg; Gioda, Adriana

2013-08-01

Air quality in the metropolitan region of Rio de Janeiro was evaluated by analysis of particulate matter (PM) in industrial (Santa Cruz) and rural (Seropédica) areas. Total suspended particles (TSP) and fine particulate matter (PM2.5) collected in filters over 24 h were quantified and their chemical composition determined. TSP exceeded Brazilian guidelines (80 μg m- 3) in Santa Cruz, while PM2.5 levels exceeded the World Health Organization guidelines (10 μg m- 3) in both locations. Filters were extracted with water and/or HNO3, and the concentrations of 20 elements, mostly metals, were determined by inductively coupled plasma mass spectrometry (ICP-MS) and optical emission spectrometry (ICP OES). Water soluble inorganic anions were determined by ion chromatography (IC). To estimate the proportion of these elements extracted, a certified reference material (NIST SRM 1648a, Urban Dust) was subjected to the same extraction process. Concordant results were obtained by ICP-MS and ICP OES for most elements. Some elements could not be quantified by both techniques; the most appropriate technique was chosen in each case. The urban dust was also analyzed by the United States Environmental Protection Agency (US EPA) method, which employs a combination of hydrochloric and nitric acids for the extraction, but higher extraction efficiency was obtained when only nitric acid was employed. The US EPA method gave better results only for Sb. In the PM samples, the elements found in the highest average concentrations by ICP were Zn and Al (3-6 μg m- 3). The anions found in the highest average concentrations were SO42 - in PM2.5 (2-4 μg m- 3) and Cl- in TSP (2-6 μg m- 3). Principal component analysis (PCA) in combination with enrichment factors (EF) indicated industrial sources in PM2.5. Analysis of TSP suggested both anthropogenic and natural sources. In conclusion, this work contributes data on air quality, as well as a method for the analysis of PM samples by ICP-MS.

RRE: a tool for the extraction of non-coding regions surrounding annotated genes from genomic datasets.

PubMed

Lazzarato, F; Franceschinis, G; Botta, M; Cordero, F; Calogero, R A

2004-11-01

RRE allows the extraction of non-coding regions surrounding a coding sequence [i.e. gene upstream region, 5'-untranslated region (5'-UTR), introns, 3'-UTR, downstream region] from annotated genomic datasets available at NCBI. RRE parser and web-based interface are accessible at http://www.bioinformatica.unito.it/bioinformatics/rre/rre.html

Observing rotation and deformation of sea ice with synthetic aperture radar

NASA Technical Reports Server (NTRS)

Vesecky, J. F.; Samadani, R.; Daida, J. M.; Smith, M. P.; Bracewell, R. N.

1987-01-01

The ESA's ERS-1 satellite will carry SARs over the polar regions; an important component in the use of these data is an automated scheme for the extraction of sea ice velocity fields from a sequence of SAR images of the same geographical region. The image pyramid area-correlation hierarchical method is noted to be vulnerable to uncertainties for sea ice rotations greater than 10-15 deg between SAR observations. Rotation-invariant methods can successfully track isolated floes in the marginal ice zone. Hu's (1962) invariant moments are also worth considering as a possible basis for rotation-invariant tracking methods. Feature tracking is inherently robust for tracking rotating sea ice, but is limited when features are floe-lead boundaries. A variety of techniques appears neccessary.

An adaptive tensor voting algorithm combined with texture spectrum

NASA Astrophysics Data System (ADS)

Wang, Gang; Su, Qing-tang; Lü, Gao-huan; Zhang, Xiao-feng; Liu, Yu-huan; He, An-zhi

2015-01-01

An adaptive tensor voting algorithm combined with texture spectrum is proposed. The image texture spectrum is used to get the adaptive scale parameter of voting field. Then the texture information modifies both the attenuation coefficient and the attenuation field so that we can use this algorithm to create more significant and correct structures in the original image according to the human visual perception. At the same time, the proposed method can improve the edge extraction quality, which includes decreasing the flocculent region efficiently and making image clear. In the experiment for extracting pavement cracks, the original pavement image is processed by the proposed method which is combined with the significant curve feature threshold procedure, and the resulted image displays the faint crack signals submerged in the complicated background efficiently and clearly.

Imaging different components of a tectonic tremor sequence in southwestern Japan using an automatic statistical detection and location method

NASA Astrophysics Data System (ADS)

Poiata, Natalia; Vilotte, Jean-Pierre; Bernard, Pascal; Satriano, Claudio; Obara, Kazushige

2018-06-01

In this study, we demonstrate the capability of an automatic network-based detection and location method to extract and analyse different components of tectonic tremor activity by analysing a 9-day energetic tectonic tremor sequence occurring at the downdip extension of the subducting slab in southwestern Japan. The applied method exploits the coherency of multiscale, frequency-selective characteristics of non-stationary signals recorded across the seismic network. Use of different characteristic functions, in the signal processing step of the method, allows to extract and locate the sources of short-duration impulsive signal transients associated with low-frequency earthquakes and of longer-duration energy transients during the tectonic tremor sequence. Frequency-dependent characteristic functions, based on higher-order statistics' properties of the seismic signals, are used for the detection and location of low-frequency earthquakes. This allows extracting a more complete (˜6.5 times more events) and time-resolved catalogue of low-frequency earthquakes than the routine catalogue provided by the Japan Meteorological Agency. As such, this catalogue allows resolving the space-time evolution of the low-frequency earthquakes activity in great detail, unravelling spatial and temporal clustering, modulation in response to tide, and different scales of space-time migration patterns. In the second part of the study, the detection and source location of longer-duration signal energy transients within the tectonic tremor sequence is performed using characteristic functions built from smoothed frequency-dependent energy envelopes. This leads to a catalogue of longer-duration energy sources during the tectonic tremor sequence, characterized by their durations and 3-D spatial likelihood maps of the energy-release source regions. The summary 3-D likelihood map for the 9-day tectonic tremor sequence, built from this catalogue, exhibits an along-strike spatial segmentation of the long-duration energy-release regions, matching the large-scale clustering features evidenced from the low-frequency earthquake's activity analysis. Further examination of the two catalogues showed that the extracted short-duration low-frequency earthquakes activity coincides in space, within about 10-15 km distance, with the longer-duration energy sources during the tectonic tremor sequence. This observation provides a potential constraint on the size of the longer-duration energy-radiating source region in relation with the clustering of low-frequency earthquakes activity during the analysed tectonic tremor sequence. We show that advanced statistical network-based methods offer new capabilities for automatic high-resolution detection, location and monitoring of different scale-components of tectonic tremor activity, enriching existing slow earthquakes catalogues. Systematic application of such methods to large continuous data sets will allow imaging the slow transient seismic energy-release activity at higher resolution, and therefore, provide new insights into the underlying multiscale mechanisms of slow earthquakes generation.

Imaging different components of a tectonic tremor sequence in southwestern Japan using an automatic statistical detection and location method

NASA Astrophysics Data System (ADS)

Poiata, Natalia; Vilotte, Jean-Pierre; Bernard, Pascal; Satriano, Claudio; Obara, Kazushige

2018-02-01

In this study, we demonstrate the capability of an automatic network-based detection and location method to extract and analyse different components of tectonic tremor activity by analysing a 9-day energetic tectonic tremor sequence occurring at the down-dip extension of the subducting slab in southwestern Japan. The applied method exploits the coherency of multi-scale, frequency-selective characteristics of non-stationary signals recorded across the seismic network. Use of different characteristic functions, in the signal processing step of the method, allows to extract and locate the sources of short-duration impulsive signal transients associated with low-frequency earthquakes and of longer-duration energy transients during the tectonic tremor sequence. Frequency-dependent characteristic functions, based on higher-order statistics' properties of the seismic signals, are used for the detection and location of low-frequency earthquakes. This allows extracting a more complete (˜6.5 times more events) and time-resolved catalogue of low-frequency earthquakes than the routine catalogue provided by the Japan Meteorological Agency. As such, this catalogue allows resolving the space-time evolution of the low-frequency earthquakes activity in great detail, unravelling spatial and temporal clustering, modulation in response to tide, and different scales of space-time migration patterns. In the second part of the study, the detection and source location of longer-duration signal energy transients within the tectonic tremor sequence is performed using characteristic functions built from smoothed frequency-dependent energy envelopes. This leads to a catalogue of longer-duration energy sources during the tectonic tremor sequence, characterized by their durations and 3-D spatial likelihood maps of the energy-release source regions. The summary 3-D likelihood map for the 9-day tectonic tremor sequence, built from this catalogue, exhibits an along-strike spatial segmentation of the long-duration energy-release regions, matching the large-scale clustering features evidenced from the low-frequency earthquake's activity analysis. Further examination of the two catalogues showed that the extracted short-duration low-frequency earthquakes activity coincides in space, within about 10-15 km distance, with the longer-duration energy sources during the tectonic tremor sequence. This observation provides a potential constraint on the size of the longer-duration energy-radiating source region in relation with the clustering of low-frequency earthquakes activity during the analysed tectonic tremor sequence. We show that advanced statistical network-based methods offer new capabilities for automatic high-resolution detection, location and monitoring of different scale-components of tectonic tremor activity, enriching existing slow earthquakes catalogues. Systematic application of such methods to large continuous data sets will allow imaging the slow transient seismic energy-release activity at higher resolution, and therefore, provide new insights into the underlying multi-scale mechanisms of slow earthquakes generation.

The Photostabilizing Effect of Grape Seed Extract on Three Common Sunscreen Absorbers.

PubMed

Martincigh, Bice S; Ollengo, Moses A

2016-11-01

The photostabilizing ability of grape seed extract on three common sunscreen absorbers, 2-ethylhexyl-p-methoxycinnamate (EHMC), benzophenone-3 (BP3) and tert-butylmethoxy dibenzoylmethane (BMDBM), was investigated. Samples were exposed to simulated solar radiation and monitored by spectrophotometric and chromatographic methods. The chemical composition of the grape seed extract was determined by GC-MS and HPLC-MS, and the major secondary metabolites were found to be epicatechin and catechin. Exposure of the extract to UV radiation increased the UV absorption capacity of the extract. All sunscreens showed an improved photostability in the extract. The inherent photo-instability of BMDBM when exposed to UV radiation was almost eliminated in the presence of grape seed extract. A mixture of all three sunscreens in the extract showed very high photostability and a red shift covering the entire UVB and UVA regions, thereby improving the broad-spectrum protection. The incorporation of grape seed extract in sunscreen and other cosmetic formulations for topical application boosts photoprotection by stabilizing the UV filters and enhancing broad-spectrum coverage. This in turn helps in reducing the amounts of absorbers and other additives incorporated in a sunscreen product and consequently lowers the risk of an unprecedented buildup of photoproducts whose toxicities are currently unknown. © 2016 The American Society of Photobiology.

Sono-assisted extraction of alcohol-insoluble extract from Althaea rosea: purification and chemical analysis.

PubMed

Eskandari, Meghdad; Samavati, Vahid

2015-01-01

A Box-Behnken design (BBD) was used to evaluate the effects of ultrasonic power, extraction time, extraction temperature, and water to raw material ratio on extraction yield of alcohol-insoluble polysaccharide of Althaea rosea leaf (ARLP). Purification was carried out by dialysis method. Chemical analysis of ARLP revealed contained 12.69 ± 0.48% moisture, 79.33 ± 0.51% total sugar, 3.82 ± 0.21% protein, 11.25 ± 0.37% uronic acid and 3.77 ± 0.15% ash. The response surface methodology (RSM) showed that the significant quadratic regression equation with high R(2) (=0.9997) was successfully fitted for extraction yield of ARLP as function of independent variables. The overall optimum region was found to be at the combined level of ultrasonic power 91.85 W, extraction time 29.94 min, extraction temperature 89.78 °C, and the ratio of water to raw material 28.77 (mL/g). At this optimum point, extraction yield of ARLP was 19.47 ± 0.41%. No significant (p>0.05) difference was found between the actual and predicted (19.30 ± 0.075%) values. The results demonstrated that ARLP had strong scavenging activities on DPPH and hydroxyl radicals. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic segmentation of the liver using multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images

NASA Astrophysics Data System (ADS)

Jang, Yujin; Hong, Helen; Chung, Jin Wook; Yoon, Young Ho

2012-02-01

We propose an effective technique for the extraction of liver boundary based on multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images. Our method is composed of four main steps. First, for extracting an optimal volume circumscribing a liver, lower and side boundaries are defined by positional information of pelvis and rib. An upper boundary is defined by separating the lungs and heart from CT images. Second, for extracting an initial liver volume, optimal liver volume is smoothed by anisotropic diffusion filtering and is segmented using adaptively selected threshold value. Third, for removing neighbor organs from initial liver volume, morphological opening and connected component labeling are applied to multiple planes. Finally, for refining the liver boundaries, deformable surface model is applied to a posterior liver surface and missing left robe in previous step. Then, probability summation map is generated by calculating regional information of the segmented liver in coronal plane, which is used for restoring the inaccurate liver boundaries. Experimental results show that our segmentation method can accurately extract liver boundaries without leakage to neighbor organs in spite of various liver shape and ambiguous boundary.

Electrolytic recovery of mercury enriched in isotopic abundance

DOEpatents

Grossman, Mark W.

1991-01-01

The present invention is directed to a method of electrolytically extracting liquid mercury from HgO or Hg.sub.2 Cl.sub.2. Additionally there are disclosed two related techniques associated with the present invention, namely (1) a technique for selectively removing product from different regions of a long photochemical reactor (photoreactor) and (2) a method of accurately measuring the total quantity of mercury formed as either HgO or Hg.sub.2 Cl.sub.2.

The usefulness of DNA sequencing after extraction by Whatman FTA filter matrix technology and phenotypic tests for differentiation of Candida albicans and Candida dubliniensis.

PubMed

Kiraz, Nuri; Oz, Yasemin; Aslan, Huseyin; Muslumanoglu, Hamza

2014-02-01

Since C. dubliniensis is similar to C. albicans phenotypically, it can be misidentified as C. albicans. We aimed to investigate the prevalence of C. dubliniensis among isolates previously identified as C. albicans in our stocks and to compare the phenotypic methods and DNA sequencing of D1/D2 region on the ribosomal large subunit (rLSU) gene. A total of 850 isolates included in this study. Phenotypic identification was performed based on germ tube formation, chlamydospore production, colony colors on chromogenic agar, inability of growth at 45 °C and growth on hypertonic Sabouraud dextrose agar. Eighty isolates compatible with C. dubliniensis by at least one phenotypic test were included in the sequence analysis. Nested PCR amplification of D1/D2 region of the rLSU gene was performed after the fungal DNA extraction by Whatman FTA filter paper technology. The sequencing analysis of PCR products carried out by an automated capillary gel electrophoresis device. The rate of C. dubliniensis was 2.35 % (n = 20) among isolates previously described as C. albicans. Consequently, none of the phenotypic tests provided satisfactory performance alone in our study, and molecular methods required special equipment and high cost. Thus, at least two phenotypic methods can be used for identification of C. dubliniensis, and molecular methods can be used for confirmation.

Optical model potentials for 6He+64Zn from 63Cu(7Li,6He)64Zn reactions

NASA Astrophysics Data System (ADS)

Yang, L.; Lin, C. J.; Jia, H. M.; Wang, D. X.; Sun, L. J.; Ma, N. R.; Yang, F.; Wu, Z. D.; Xu, X. X.; Zhang, H. Q.; Liu, Z. H.; Bao, P. F.

2017-03-01

Angular distributions of the transfer reaction 63Cu(7Li,6He )64Zn were measured at Elab(7Li) =12.67 , 15.21, 16.33, 23.30, 27.30, and 30.96 MeV. With the interaction potentials of the entrance channel 7Li+63Cu obtained from elastic scattering data as input, the optical potentials of the halo nuclear system 6He+64Zn in the exit channel were extracted by fitting the experimental data with the distorted-wave Born approximation (DWBA) and coupled reaction channels (CRC) methods, respectively. The results show that the threshold anomaly presents in the weakly bound system of 7Li+63Cu and the dispersion relation can be adopted to describe the connection between the real and imaginary potentials, while both the real and imaginary potentials nearly keep constant within the researched energy region for the halo system of 6He+64Zn . Moreover, calculations by the potentials extracted from the CRC method can reproduce the experimental elastic scattering of the 6He+64Zn system rather well, but those by the potentials from the DWBA method cannot, where the couplings between 7Li and 6He are absent. This work verifies the validity of the transfer method in the medium-mass target region and lays a solid foundation for the further study of optical potentials for exotic nuclear systems.

Application of morphological bit planes in retinal blood vessel extraction.

PubMed

Fraz, M M; Basit, A; Barman, S A

2013-04-01

The appearance of the retinal blood vessels is an important diagnostic indicator of various clinical disorders of the eye and the body. Retinal blood vessels have been shown to provide evidence in terms of change in diameter, branching angles, or tortuosity, as a result of ophthalmic disease. This paper reports the development for an automated method for segmentation of blood vessels in retinal images. A unique combination of methods for retinal blood vessel skeleton detection and multidirectional morphological bit plane slicing is presented to extract the blood vessels from the color retinal images. The skeleton of main vessels is extracted by the application of directional differential operators and then evaluation of combination of derivative signs and average derivative values. Mathematical morphology has been materialized as a proficient technique for quantifying the retinal vasculature in ocular fundus images. A multidirectional top-hat operator with rotating structuring elements is used to emphasize the vessels in a particular direction, and information is extracted using bit plane slicing. An iterative region growing method is applied to integrate the main skeleton and the images resulting from bit plane slicing of vessel direction-dependent morphological filters. The approach is tested on two publicly available databases DRIVE and STARE. Average accuracy achieved by the proposed method is 0.9423 for both the databases with significant values of sensitivity and specificity also; the algorithm outperforms the second human observer in terms of precision of segmented vessel tree.

Automated segmentations of skin, soft-tissue, and skeleton, from torso CT images

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kiryu, Takuji; Hoshi, Hiroaki

2004-05-01

We have been developing a computer-aided diagnosis (CAD) scheme for automatically recognizing human tissue and organ regions from high-resolution torso CT images. We show some initial results for extracting skin, soft-tissue and skeleton regions. 139 patient cases of torso CT images (male 92, female 47; age: 12-88) were used in this study. Each case was imaged with a common protocol (120kV/320mA) and covered the whole torso with isotopic spatial resolution of about 0.63 mm and density resolution of 12 bits. A gray-level thresholding based procedure was applied to separate the human body from background. The density and distance features to body surface were used to determine the skin, and separate soft-tissue from the others. A 3-D region growing based method was used to extract the skeleton. We applied this system to the 139 cases and found that the skin, soft-tissue and skeleton regions were recognized correctly for 93% of the patient cases. The accuracy of segmentation results was acceptable by evaluating the results slice by slice. This scheme will be included in CAD systems for detecting and diagnosing the abnormal lesions in multi-slice torso CT images.

Assessment of Brine Management for Geologic Carbon Sequestration

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

Breunig, Hanna M.; Birkholzer, Jens T.; Borgia, Andrea

2013-06-13

Geologic carbon sequestration (GCS) is the injection of carbon dioxide (CO 2), typically captured from stationary emission sources, into deep geologic formations to prevent its entry into the atmosphere. Active pilot facilities run by regional United States (US) carbon sequestration partnerships inject on the order of one million metric tonnes (mt) CO 2 annually while the US electric power sector emits over 2000 million mt-CO 2 annually. GCS is likely to play an increasing role in US carbon mitigation initiatives, but scaling up GCS poses several challenges. Injecting CO 2 into sedimentary basins raises fluid pressure in the pore space,more » which is typically already occupied by naturally occurring, or native, brine. The resulting elevated pore pressures increase the likelihood of induced seismicity, of brine or CO 2 escaping into potable groundwater resources, and of CO 2 escaping into the atmosphere. Brine extraction is one method for pressure management, in which brine in the injection formation is brought to the surface through extraction wells. Removal of the brine makes room for the CO 2 and decreases pressurization. Although the technology required for brine extraction is mature, this form of pressure management will only be applicable if there are cost-­effective and sustainable methods of disposing of the extracted brine. Brine extraction, treatment, and disposal may increase the already substantial capital, energy, and water demands of Carbon dioxide Capture and Sequestration (CCS). But, regionally specific brine management strategies may be able to treat the extracted water as a source of revenue, energy, and water to subsidize CCS costs, while minimizing environmental impacts. By this approach, value from the extracted water would be recovered before disposing of any resulting byproducts. Until a price is placed on carbon, we expect that utilities and other CO 2 sources will be reluctant to invest in capital intensive, high risk GCS projects; early technical, economic, and environmental assessments of brine management are extremely valuable for determining the potential role of GCS in the US. We performed a first order feasibility and economic assessment, at three different locations in the US, of twelve GCS extracted-­water management options, including: geothermal energy extraction, desalination, salt and mineral harvesting, rare-­earth element harvesting, aquaculture, algae biodiesel production, road de-­icing, enhanced geothermal system (EGS) recharge, underground reinjection, landfill disposal, ocean disposal, and evaporation pond disposal. Three saline aquifers from different regions of the US were selected as hypothetical GCS project sites to encompass variation in parameters that are relevant to the feasibility and economics of brine disposal. The three aquifers are the southern Mt. Simon Sandstone Formation in the Illinois Basin, IL; the Vedder Formation in the southern San Joaquin Basin, CA; and the Jasper Interval in the eastern Texas Gulf Basin, TX. These aquifers are candidates for GCS due to their physical characteristics and their close proximity to large CO 2 emission sources. Feasibility and impacts were calculated using one mt-­CO 2 injected as the functional unit of brine management. Scenarios were performed for typical 1000MW coal-­fired power plants (CFPP) that incurred an assumed 24 percent carbon capture energy penalty (EP), injected 90 percent of CO 2 emissions (~9 million mt-­ CO 2 injected annually), and treated extracted water onsite. Net present value (NPV), land requirements, laws and regulations, and technological limits were determined for each stage of disposal, and used to estimate feasibility. The boundary of the assessment began once extracted water was brought to the surface, and ended once the water evaporated, was injected underground, or was discharged into surface water bodies. Results of the assessment were generated, stored, and analyzed using Microsoft Excel spreadsheets and ESRI Geographical Information System (GIS) maps. Conclusions about the relative benefits and impacts of alternative brine-­management strategies were highly sensitive to local climate and weather, and aquifer water chemistry. The NPV of certain scenarios ranged from -­$50/mt-­CO 2 (a cost) to +$10/mt-­CO 2 (revenue). The land footprint of the scenarios in this study ranged from <1 km 2 to 100 km 2. Brine extraction as a pressure management tool for GCS has potential for improving the economics and for minimizing the environmental impacts of CCS. In order to maximize this potential, careful analysis of each saline aquifer and region must be conducted to determine a regionally appropriate brine use sequence (BUS) at the time of site selection. Models that use GIS will be essential tools in determining such sequences for individual CFPP. Future studies that perform risk and life cycle assessments (LCA) of BUS scenarios, incorporate additional impact metrics into the BUS model, and enhance the temporal sensitivity of the model would improve the robustness of this regional assessment method.« less

Ethanolic extracts of Alstonia Scholaris and Bacopa Monniera possess neuroleptic activity due to anti-dopaminergic effect

PubMed Central

Jash, Rajiv; Chowdary, K. Appana

2014-01-01

Background: An increased inclination has been observed for the use of herbal drugs in chronic and incurable diseases. Treatment of psychiatric diseases like schizophrenia is largely palliative and more importantly, a prominent adverse effect prevails with the majority of anti-psychotic drugs, which are the extrapyramidal motor disorders. Existing anti-psychotic drug therapy is not so promising, and their adverse effect is a matter of concern for continuing the therapy for long duration. Objective: This experimental study was done to evaluate the neuroleptic activity of the ethanolic extracts of two plants Alstonia Scholaris and Bacopa Monnieri with different anti-psychotic animal models with a view that these plant extracts shall have no or at least reduced adverse effect so that it can be used for long duration. Materials and Methods: Two doses of both the extracts (100 and 200 mg/kg) and also standard drug haloperidol (0.2 mg/kg) were administered to their respective groups once daily with 5 different animal models. After that, the concentration of the dopamine neurotransmitter was estimated in two different regions of the brain viz. frontal cortex and striatum. Results: The result of the study indicated a significant reduction of amphetamine-induced stereotype and conditioned avoidance response for both the extracts compared with the control group, but both did not have any significant effect in phencyclidine-induced locomotor activity and social interaction activity. However, both the extracts showed minor signs of catalepsy compared to the control group. The study also revealed that the neuroleptic effect was due to the reduction of the dopamine concentration in the frontal cortex region of the rat brain. The results largely pointed out the fact that both the extract may be having the property to alleviate the positive symptoms of schizophrenia by reducing the dopamine levels of dopaminergic neurons of the brain. Conclusion: The estimation of dopamine in the two major regions of brain indicated the alteration of dopamine levels was the reason for the anti-psychotic activity as demonstrated by the different animal models. PMID:24497742

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.

Geometrically robust image watermarking by sector-shaped partitioning of geometric-invariant regions.

PubMed

Tian, Huawei; Zhao, Yao; Ni, Rongrong; Cao, Gang

2009-11-23

In a feature-based geometrically robust watermarking system, it is a challenging task to detect geometric-invariant regions (GIRs) which can survive a broad range of image processing operations. Instead of commonly used Harris detector or Mexican hat wavelet method, a more robust corner detector named multi-scale curvature product (MSCP) is adopted to extract salient features in this paper. Based on such features, disk-like GIRs are found, which consists of three steps. First, robust edge contours are extracted. Then, MSCP is utilized to detect the centers for GIRs. Third, the characteristic scale selection is performed to calculate the radius of each GIR. A novel sector-shaped partitioning method for the GIRs is designed, which can divide a GIR into several sector discs with the help of the most important corner (MIC). The watermark message is then embedded bit by bit in each sector by using Quantization Index Modulation (QIM). The GIRs and the divided sector discs are invariant to geometric transforms, so the watermarking method inherently has high robustness against geometric attacks. Experimental results show that the scheme has a better robustness against various image processing operations including common processing attacks, affine transforms, cropping, and random bending attack (RBA) than the previous approaches.

The Economics of Reduced Impact Logging in the American Tropics: A Review of Recent Initiatives

Treesearch

Frederick Boltz; Thomas P. Holmes; Douglas R. Carter

1999-01-01

Programs aimed at developing and implementing reduced-impact logging (RIL) techniques are currently underway in important forest regions of Latin America, given the importance of timber production in the American tropics to national and global markets. RIL efforts focus upon planning and extraction methods which lessen harvest impact on residual commercial timber...

[Evaluation of eco-environmental quality based on artificial neural network and remote sensing techniques].

PubMed

Li, Hongyi; Shi, Zhou; Sha, Jinming; Cheng, Jieliang

2006-08-01

In the present study, vegetation, soil brightness, and moisture indices were extracted from Landsat ETM remote sensing image, heat indices were extracted from MODIS land surface temperature product, and climate index and other auxiliary geographical information were selected as the input of neural network. The remote sensing eco-environmental background value of standard interest region evaluated in situ was selected as the output of neural network, and the back propagation (BP) neural network prediction model containing three layers was designed. The network was trained, and the remote sensing eco-environmental background value of Fuzhou in China was predicted by using software MATLAB. The class mapping of remote sensing eco-environmental background values based on evaluation standard showed that the total classification accuracy was 87. 8%. The method with a scheme of prediction first and classification then could provide acceptable results in accord with the regional eco-environment types.

Electron energy recovery system for negative ion sources

DOEpatents

Dagenhart, W.K.; Stirling, W.L.

1979-10-25

An electron energy recovery system for negative ion sources is provided. The system, employing crossed electric and magnetic fields, separates the electrons from the ions as they are extracted from the ion source plasma generator and before the ions are accelerated to their full energy. With the electric and magnetic fields oriented 90/sup 0/ to each other, the electrons remain at approximately the electrical potential at which they were generated. The electromagnetic forces cause the ions to be accelerated to the full accelerating supply voltage energy while being deflected through an angle of less than 90/sup 0/. The electrons precess out of the accelerating field region into an electron recovery region where they are collected at a small fraction of the full accelerating supply energy. It is possible, by this method, to collect > 90% of the electrons extracted along with the negative ions from a negative ion source beam at < 4% of full energy.

Collection and Extraction of Occupational Air Samples for Analysis of Fungal DNA.

PubMed

Lemons, Angela R; Lindsley, William G; Green, Brett J

2018-05-02

Traditional methods of identifying fungal exposures in occupational environments, such as culture and microscopy-based approaches, have several limitations that have resulted in the exclusion of many species. Advances in the field over the last two decades have led occupational health researchers to turn to molecular-based approaches for identifying fungal hazards. These methods have resulted in the detection of many species within indoor and occupational environments that have not been detected using traditional methods. This protocol details an approach for determining fungal diversity within air samples through genomic DNA extraction, amplification, sequencing, and taxonomic identification of fungal internal transcribed spacer (ITS) regions. ITS sequencing results in the detection of many fungal species that are either not detected or difficult to identify to species level using culture or microscopy. While these methods do not provide quantitative measures of fungal burden, they offer a new approach to hazard identification and can be used to determine overall species richness and diversity within an occupational environment.

"Antimicrobial and antiproliferative activity of essential oil, aqueous and ethanolic extracts of Ocimum micranthum Willd leaves".

PubMed

Caamal-Herrera, Isabel O; Carrillo-Cocom, Leydi M; Escalante-Réndiz, Diana Y; Aráiz-Hernández, Diana; Azamar-Barrios, José A

2018-02-08

Ocimum micranthum Willd is a plant used in traditional medicine practiced in the region of the Yucatan peninsula. In particular, it is used for the treatment of cutaneous infections and wound healing, however there are currently no existing scientific studies that support these applications. The aim of the present study was to evaluate the antimicrobial and the in vitro proliferative activity (on healthy mammalian cell lines) of the essential oil and extracts (aqueous and ethanolic) of this plant. The minimal inhibitory concentration (MIC) of essential oil and aqueous and ethanolic extracts of Ocimum micranthum leaves against Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa and Candida albicans was determined using the microdilution technique. The in vitro proliferative activity of human fibroblast (hFB) and Chinese hamster ovary (CHO-K1) cells treated with these extracts was evaluated using the MTT test. The hFB cell line was also evaluated using Trypan Blue assay. Candida albicans was more susceptible to the ethanolic extract and the aqueous extract (MIC value of 5 μL/mL and 80 μL/mL respectively). In the case of Staphylococcus aureus, Bacillus subtilis, and Pseudomonas aeruginosa, the MIC of the aqueous and ethanolic extract was 125 μL/mL. The aqueous extract showed a significant (p < 0.05) antiproliferative effect on hFB cells at a concentration of 4%, with cell proliferation percentage values of 73.56% and 20.59% by MTT method and Trypan Blue assay, respectively; the same effect was observed for the ethanolic extract at concentration from 0.06% to 0.25% using MTT method and at a concentration from 0.125% to 0.25% using Trypan Blue assay. In CHO-K1 cells an antiproliferative effect was observed at a concentration of 8% of aqueous extract and from 0.06% to 0.25% of ethanolic extract using the MTT method. These assays showed that low concentrations of essential oil and extracts of Ocimum micranthum leaves are sufficient to cause an antiproliferative effect on the hFB cell line but do not produce an antimicrobial effect against the microorganisms evaluated. More studies are necessary to improve understanding of the mechanism of action of the compounds implicated in the bioactivities shown by the crude extracts.

Review of particle-in-cell modeling for the extraction region of large negative hydrogen ion sources for fusion

NASA Astrophysics Data System (ADS)

Wünderlich, D.; Mochalskyy, S.; Montellano, I. M.; Revel, A.

2018-05-01

Particle-in-cell (PIC) codes are used since the early 1960s for calculating self-consistently the motion of charged particles in plasmas, taking into account external electric and magnetic fields as well as the fields created by the particles itself. Due to the used very small time steps (in the order of the inverse plasma frequency) and mesh size, the computational requirements can be very high and they drastically increase with increasing plasma density and size of the calculation domain. Thus, usually small computational domains and/or reduced dimensionality are used. In the last years, the available central processing unit (CPU) power strongly increased. Together with a massive parallelization of the codes, it is now possible to describe in 3D the extraction of charged particles from a plasma, using calculation domains with an edge length of several centimeters, consisting of one extraction aperture, the plasma in direct vicinity of the aperture, and a part of the extraction system. Large negative hydrogen or deuterium ion sources are essential parts of the neutral beam injection (NBI) system in future fusion devices like the international fusion experiment ITER and the demonstration reactor (DEMO). For ITER NBI RF driven sources with a source area of 0.9 × 1.9 m2 and 1280 extraction apertures will be used. The extraction of negative ions is accompanied by the co-extraction of electrons which are deflected onto an electron dump. Typically, the maximum negative extracted ion current is limited by the amount and the temporal instability of the co-extracted electrons, especially for operation in deuterium. Different PIC codes are available for the extraction region of large driven negative ion sources for fusion. Additionally, some effort is ongoing in developing codes that describe in a simplified manner (coarser mesh or reduced dimensionality) the plasma of the whole ion source. The presentation first gives a brief overview of the current status of the ion source development for ITER NBI and of the PIC method. Different PIC codes for the extraction region are introduced as well as the coupling to codes describing the whole source (PIC codes or fluid codes). Presented and discussed are different physical and numerical aspects of applying PIC codes to negative hydrogen ion sources for fusion as well as selected code results. The main focus of future calculations will be the meniscus formation and identifying measures for reducing the co-extracted electrons, in particular for deuterium operation. The recent results of the 3D PIC code ONIX (calculation domain: one extraction aperture and its vicinity) for the ITER prototype source (1/8 size of the ITER NBI source) are presented.

Nimbus 7 earth radiation budget wide field of view climate data set improvement. I - The earth albedo from deconvolution of shortwave measurements

NASA Technical Reports Server (NTRS)

Hucek, Richard R.; Ardanuy, Philip E.; Kyle, H. Lee

1987-01-01

A deconvolution method for extracting the top of the atmosphere (TOA) mean, daily albedo field from a set of wide-FOV (WFOV) shortwave radiometer measurements is proposed. The method is based on constructing a synthetic measurement for each satellite observation. The albedo field is represented as a truncated series of spherical harmonic functions, and these linear equations are presented. Simulation studies were conducted to determine the sensitivity of the method. It is observed that a maximum of about 289 pieces of data can be extracted from a set of Nimbus 7 WFOV satellite measurements. The albedos derived using the deconvolution method are compared with albedos derived using the WFOV archival method; the developed albedo field achieved a 20 percent reduction in the global rms regional reflected flux density errors. The deconvolution method is applied to estimate the mean, daily average TOA albedo field for January 1983. A strong and extensive albedo maximum (0.42), which corresponds to the El Nino/Southern Oscillation event of 1982-1983, is detected over the south central Pacific Ocean.

Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function.

PubMed

O'Sullivan, F; Kirrane, J; Muzi, M; O'Sullivan, J N; Spence, A M; Mankoff, D A; Krohn, K A

2010-03-01

Kinetic quantitation of dynamic positron emission tomography (PET) studies via compartmental modeling usually requires the time-course of the radio-tracer concentration in the arterial blood as an arterial input function (AIF). For human and animal imaging applications, significant practical difficulties are associated with direct arterial sampling and as a result there is substantial interest in alternative methods that require no blood sampling at the time of the study. A fixed population template input function derived from prior experience with directly sampled arterial curves is one possibility. Image-based extraction, including requisite adjustment for spillover and recovery, is another approach. The present work considers a hybrid statistical approach based on a penalty formulation in which the information derived from a priori studies is combined in a Bayesian manner with information contained in the sampled image data in order to obtain an input function estimate. The absolute scaling of the input is achieved by an empirical calibration equation involving the injected dose together with the subject's weight, height and gender. The technique is illustrated in the context of (18)F -Fluorodeoxyglucose (FDG) PET studies in humans. A collection of 79 arterially sampled FDG blood curves are used as a basis for a priori characterization of input function variability, including scaling characteristics. Data from a series of 12 dynamic cerebral FDG PET studies in normal subjects are used to evaluate the performance of the penalty-based AIF estimation technique. The focus of evaluations is on quantitation of FDG kinetics over a set of 10 regional brain structures. As well as the new method, a fixed population template AIF and a direct AIF estimate based on segmentation are also considered. Kinetics analyses resulting from these three AIFs are compared with those resulting from radially sampled AIFs. The proposed penalty-based AIF extraction method is found to achieve significant improvements over the fixed template and the segmentation methods. As well as achieving acceptable kinetic parameter accuracy, the quality of fit of the region of interest (ROI) time-course data based on the extracted AIF, matches results based on arterially sampled AIFs. In comparison, significant deviation in the estimation of FDG flux and degradation in ROI data fit are found with the template and segmentation methods. The proposed AIF extraction method is recommended for practical use.

Comparison of Oil Content and Fatty Acids Profile of Western Schley, Wichita, and Native Pecan Nuts Cultured in Chihuahua, Mexico.

PubMed

Rivera-Rangel, L R; Aguilera-Campos, K I; García-Triana, A; Ayala-Soto, J G; Chavez-Flores, D; Hernández-Ochoa, L

2018-01-01

Two different extraction processes, Soxhlet and ultrasound, were used to obtain the oil extracts of Western Schley, Wichita, and Native pecan nuts cultured in Chihuahua, Mexico. The aspects evaluated in this study were the extraction yield of the processes and fatty acids' profile of the resulting extracts. Gas chromatography coupled with mass spectrometry (GC-MS) was used to identify and determine the composition percentage of fatty acids present in pecan nuts oils extracted. The results obtained show that higher oil extraction yields were obtained by Soxhlet method with hexane (69.90%) in Wichita varieties. Wichita, Western Schley, and Native pecan nuts from Chihuahua are rich in PUFA (polyunsaturated fatty acids) and MUFA (monounsaturated fatty acids) and have low levels of SFA (saturated fatty acids). The predominant fatty acid present in all pecan nuts oils was linoleic acid followed by oleic acid. Myristic acid, palmitic acid, and linolenic acid were also identified in representative quantities. The results from this study suggest that there are statistically significant differences in the chemical composition of the pecan nuts oils extracted from the varieties cultured in Chihuahua, Mexico, and those cultivated in other regions of the world.

Comparison of Oil Content and Fatty Acids Profile of Western Schley, Wichita, and Native Pecan Nuts Cultured in Chihuahua, Mexico

PubMed Central

Rivera-Rangel, L. R.; Aguilera-Campos, K. I.; García-Triana, A.; Ayala-Soto, J. G.; Chavez-Flores, D.

2018-01-01

Two different extraction processes, Soxhlet and ultrasound, were used to obtain the oil extracts of Western Schley, Wichita, and Native pecan nuts cultured in Chihuahua, Mexico. The aspects evaluated in this study were the extraction yield of the processes and fatty acids' profile of the resulting extracts. Gas chromatography coupled with mass spectrometry (GC-MS) was used to identify and determine the composition percentage of fatty acids present in pecan nuts oils extracted. The results obtained show that higher oil extraction yields were obtained by Soxhlet method with hexane (69.90%) in Wichita varieties. Wichita, Western Schley, and Native pecan nuts from Chihuahua are rich in PUFA (polyunsaturated fatty acids) and MUFA (monounsaturated fatty acids) and have low levels of SFA (saturated fatty acids). The predominant fatty acid present in all pecan nuts oils was linoleic acid followed by oleic acid. Myristic acid, palmitic acid, and linolenic acid were also identified in representative quantities. The results from this study suggest that there are statistically significant differences in the chemical composition of the pecan nuts oils extracted from the varieties cultured in Chihuahua, Mexico, and those cultivated in other regions of the world. PMID:29610686

Extraction of green labeled pectins and pectic oligosaccharides from plant byproducts.

PubMed

Zykwinska, Agata; Boiffard, Marie-Hélène; Kontkanen, Hanna; Buchert, Johanna; Thibault, Jean-François; Bonnin, Estelle

2008-10-08

Green labeled pectins were extracted by an environmentally friendly way using proteases and cellulases being able to act on proteins and cellulose present in cell walls. Pectins were isolated from different plant byproducts, i.e., chicory roots, citrus peel, cauliflower florets and leaves, endive, and sugar beet pulps. Enzymatic extraction was performed at 50 degrees C for 4 h, in order to fulfill the conditions required for microbiological safety of extracted products. High methoxy (HM) pectins of high molar mass were extracted with three different enzyme mixtures. These pectins were subsequently demethylated with two pectin methyl esterases (PMEs), either the fungal PME from Aspergillus aculeatus or the orange PME. It was further demonstrated that high molar mass low methoxy (LM) pectins could also be extracted directly from cell walls by adding the fungal PME to the mixture of protease and cellulase. Moreover, health benefit pectic oligosaccharides, the so-called modified hairy regions, were obtained after enzymatic treatment of the residue recovered after pectin extraction. The enzymatic method demonstrates that it is possible to convert vegetable byproducts into high-added value compounds, such as pectins and pectic oligosaccharides, and thus considerably reduce the amount of these residues generated by food industries.

Method and source for producing a high concentration of positively charged molecular hydrogen or deuterium ions

DOEpatents

Ehlers, Kenneth W.; Leung, Ka-Ngo

1988-01-01

A high concentration of positive molecular ions of hydrogen or deuterium gas is extracted from a positive ion source having a short path length of extracted ions, relative to the mean free path of the gas molecules, to minimize the production of other ion species by collision between the positive ions and gas molecules. The ion source has arrays of permanent magnets to produce a multi-cusp magnetic field in regions remote from the plasma grid and the electron emitters, for largely confining the plasma to the space therebetween. The ion source has a chamber which is short in length, relative to its transverse dimensions, and the electron emitters are at an even shorter distance from the plasma grid, which contains one or more extraction apertures.

Composite Wavelet Filters for Enhanced Automated Target Recognition

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

A novel scene-based non-uniformity correction method for SWIR push-broom hyperspectral sensors

NASA Astrophysics Data System (ADS)

Hu, Bin-Lin; Hao, Shi-Jing; Sun, De-Xin; Liu, Yin-Nian

2017-09-01

A novel scene-based non-uniformity correction (NUC) method for short-wavelength infrared (SWIR) push-broom hyperspectral sensors is proposed and evaluated. This method relies on the assumption that for each band there will be ground objects with similar reflectance to form uniform regions when a sufficient number of scanning lines are acquired. The uniform regions are extracted automatically through a sorting algorithm, and are used to compute the corresponding NUC coefficients. SWIR hyperspectral data from airborne experiment are used to verify and evaluate the proposed method, and results show that stripes in the scenes have been well corrected without any significant information loss, and the non-uniformity is less than 0.5%. In addition, the proposed method is compared to two other regular methods, and they are evaluated based on their adaptability to the various scenes, non-uniformity, roughness and spectral fidelity. It turns out that the proposed method shows strong adaptability, high accuracy and efficiency.

Chemical constituents and toxicological studies of leaves from Mimosa caesalpiniifolia Benth., a Brazilian honey plant

PubMed Central

Monção, Nayana Bruna Nery; Costa, Luciana Muratori; Arcanjo, Daniel Dias Rufino; Araújo, Bruno Quirino; Lustosa, Maria do Carmo Gomes; Rodrigues, Klinger Antônio da França; Carvalho, Fernando Aécio de Amorim; Costa, Amilton Paulo Raposo; Lopes Citó, Antônia Maria das Graças

2014-01-01

Background: Mimosa caesalpiniifolia Benth. (Leguminosae) is widely found in the Brazilian Northeast region and markedly contributes to production of pollen and honey, being considered an important honey plant in this region. Objective: To investigate the chemical composition of the ethanol extract of leaves from M. caesalpiniifolia by GC-MS after derivatization (silylation), as well as to evaluate the in vitro and in vivo toxicological effects and androgenic activity in rats. Materials and Methods: The ethanol extract of leaves from Mimosa caesalpiniifolia was submitted to derivatization by silylation and analyzed by gas chromatography-mass spectrometry (GC-MS) to identification of chemical constituents. In vitro toxicological evaluation was performed by MTT assay in murine macrophages and by Artemia salina lethality assay, and the in vivo acute oral toxicity and androgenic evaluation in rats. Results: Totally, 32 components were detected: Phytol-TMS (11.66%), lactic acid-2TMS (9.16%), α-tocopherol-TMS (7.34%) and β-sitosterol-TMS (6.80%) were the major constituents. At the concentrations analyzed, the ethanol extract showed low cytotoxicity against brine shrimp (Artemia salina) and murine macrophages. In addition, the extract did not exhibit any toxicological effect or androgenic activity in rats. Conclusions: The derivatization by silylation allowed a rapid identification of chemical compounds from the M. caesalpiniifolia leaves extract. Besides, this species presents a good safety profile as observed in toxicological studies, and possess a great potential in the production of herbal medicines or as for food consumption. PMID:25298660

Automated Fluid Feature Extraction from Transient Simulations

NASA Technical Reports Server (NTRS)

Haimes, Robert; Lovely, David

1999-01-01

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snap-shot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: (1) Shocks, (2) Vortex cores, (3) Regions of recirculation, (4) Boundary layers, (5) Wakes. Three papers and an initial specification for the (The Fluid eXtraction tool kit) FX Programmer's guide were included. The papers, submitted to the AIAA Computational Fluid Dynamics Conference, are entitled : (1) Using Residence Time for the Extraction of Recirculation Regions, (2) Shock Detection from Computational Fluid Dynamics results and (3) On the Velocity Gradient Tensor and Fluid Feature Extraction.

Extraction of 3D Femur Neck Trabecular Bone Architecture from Clinical CT Images in Osteoporotic Evaluation: a Novel Framework.

PubMed

Sapthagirivasan, V; Anburajan, M; Janarthanam, S

2015-08-01

The early detection of osteoporosis risk enhances the lifespan and quality of life of an individual. A reasonable in-vivo assessment of trabecular bone strength at the proximal femur helps to evaluate the fracture risk and henceforth, to understand the associated structural dynamics on occurrence of osteoporosis. The main aim of our study was to develop a framework to automatically determine the trabecular bone strength from clinical femur CT images and thereby to estimate its correlation with BMD. All the 50 studied south Indian female subjects aged 30 to 80 years underwent CT and DXA measurements at right femur region. Initially, the original CT slices were intensified and active contour model was utilised for the extraction of the neck region. After processing through a novel process called trabecular enrichment approach (TEA), the three dimensional (3D) trabecular features were extracted. The extracted 3D trabecular features, such as volume fraction (VF), solidity of delta points (SDP) and boundness, demonstrated a significant correlation with femoral neck bone mineral density (r = 0.551, r = 0.432, r = 0.552 respectively) at p < 0.001. The higher area under the curve values of the extracted features (VF: 85.3 %; 95CI: 68.2-100 %, SDP: 82.1 %; 95CI: 65.1-98.9 % and boundness: 90.4 %; 95CI: 78.7-100 %) were observed. The findings suggest that the proposed framework with TEA method would be useful for spotting women vulnerable to osteoporotic risk.

Salient region detection by fusing bottom-up and top-down features extracted from a single image.

PubMed

Tian, Huawei; Fang, Yuming; Zhao, Yao; Lin, Weisi; Ni, Rongrong; Zhu, Zhenfeng

2014-10-01

Recently, some global contrast-based salient region detection models have been proposed based on only the low-level feature of color. It is necessary to consider both color and orientation features to overcome their limitations, and thus improve the performance of salient region detection for images with low-contrast in color and high-contrast in orientation. In addition, the existing fusion methods for different feature maps, like the simple averaging method and the selective method, are not effective sufficiently. To overcome these limitations of existing salient region detection models, we propose a novel salient region model based on the bottom-up and top-down mechanisms: the color contrast and orientation contrast are adopted to calculate the bottom-up feature maps, while the top-down cue of depth-from-focus from the same single image is used to guide the generation of final salient regions, since depth-from-focus reflects the photographer's preference and knowledge of the task. A more general and effective fusion method is designed to combine the bottom-up feature maps. According to the degree-of-scattering and eccentricities of feature maps, the proposed fusion method can assign adaptive weights to different feature maps to reflect the confidence level of each feature map. The depth-from-focus of the image as a significant top-down feature for visual attention in the image is used to guide the salient regions during the fusion process; with its aid, the proposed fusion method can filter out the background and highlight salient regions for the image. Experimental results show that the proposed model outperforms the state-of-the-art models on three public available data sets.

Video shot boundary detection using region-growing-based watershed method

NASA Astrophysics Data System (ADS)

Wang, Jinsong; Patel, Nilesh; Grosky, William

2004-10-01

In this paper, a novel shot boundary detection approach is presented, based on the popular region growing segmentation method - Watershed segmentation. In image processing, gray-scale pictures could be considered as topographic reliefs, in which the numerical value of each pixel of a given image represents the elevation at that point. Watershed method segments images by filling up basins with water starting at local minima, and at points where water coming from different basins meet, dams are built. In our method, each frame in the video sequences is first transformed from the feature space into the topographic space based on a density function. Low-level features are extracted from frame to frame. Each frame is then treated as a point in the feature space. The density of each point is defined as the sum of the influence functions of all neighboring data points. The height function that is originally used in Watershed segmentation is then replaced by inverting the density at the point. Thus, all the highest density values are transformed into local minima. Subsequently, Watershed segmentation is performed in the topographic space. The intuitive idea under our method is that frames within a shot are highly agglomerative in the feature space and have higher possibilities to be merged together, while those frames between shots representing the shot changes are not, hence they have less density values and are less likely to be clustered by carefully extracting the markers and choosing the stopping criterion.

Enrichment of low molecular weight serum proteins using acetonitrile precipitation for mass spectrometry based proteomic analysis.

PubMed

Kay, Richard; Barton, Chris; Ratcliffe, Lucy; Matharoo-Ball, Balwir; Brown, Pamela; Roberts, Jane; Teale, Phil; Creaser, Colin

2008-10-01

A rapid acetonitrile (ACN)-based extraction method has been developed that reproducibly depletes high abundance and high molecular weight proteins from serum prior to mass spectrometric analysis. A nanoflow liquid chromatography/tandem mass spectrometry (nano-LC/MS/MS) multiple reaction monitoring (MRM) method for 57 high to medium abundance serum proteins was used to characterise the ACN-depleted fraction after tryptic digestion. Of the 57 targeted proteins 29 were detected and albumin, the most abundant protein in serum and plasma, was identified as the 20th most abundant protein in the extract. The combination of ACN depletion and one-dimensional nano-LC/MS/MS enabled the detection of the low abundance serum protein, insulin-like growth factor-I (IGF-I), which has a serum concentration in the region of 100 ng/mL. One-dimensional sodium dodecyl sulfate/polyacrylamide gel electrophoresis (SDS-PAGE) analysis of the depleted serum showed no bands corresponding to proteins of molecular mass over 75 kDa after extraction, demonstrating the efficiency of the method for the depletion of high molecular weight proteins. Total protein analysis of the ACN extracts showed that approximately 99.6% of all protein is removed from the serum. The ACN-depletion strategy offers a viable alternative to the immunochemistry-based protein-depletion techniques commonly used for removing high abundance proteins from serum prior to MS-based proteomic analyses.

Fabric defect detection based on visual saliency using deep feature and low-rank recovery

NASA Astrophysics Data System (ADS)

Liu, Zhoufeng; Wang, Baorui; Li, Chunlei; Li, Bicao; Dong, Yan

2018-04-01

Fabric defect detection plays an important role in improving the quality of fabric product. In this paper, a novel fabric defect detection method based on visual saliency using deep feature and low-rank recovery was proposed. First, unsupervised training is carried out by the initial network parameters based on MNIST large datasets. The supervised fine-tuning of fabric image library based on Convolutional Neural Networks (CNNs) is implemented, and then more accurate deep neural network model is generated. Second, the fabric images are uniformly divided into the image block with the same size, then we extract their multi-layer deep features using the trained deep network. Thereafter, all the extracted features are concentrated into a feature matrix. Third, low-rank matrix recovery is adopted to divide the feature matrix into the low-rank matrix which indicates the background and the sparse matrix which indicates the salient defect. In the end, the iterative optimal threshold segmentation algorithm is utilized to segment the saliency maps generated by the sparse matrix to locate the fabric defect area. Experimental results demonstrate that the feature extracted by CNN is more suitable for characterizing the fabric texture than the traditional LBP, HOG and other hand-crafted features extraction method, and the proposed method can accurately detect the defect regions of various fabric defects, even for the image with complex texture.

Groundwater-dependent ecosystems: recent insights, new techniques and an ecosystem-scale threshold response

NASA Astrophysics Data System (ADS)

Eamus, D.; Zolfaghar, S.; Villalobos-Vega, R.; Cleverly, J.; Huete, A.

2015-05-01

Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs; and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on GDEs. We discuss three methods for identifying GDEs: (1) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration, (2) stable isotope analysis of water sources in the transpiration stream; and (3) remote sensing methods. We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of ET using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the "White method" to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of transpiration vs. evaporation (e.g., using stable isotopes) or from groundwater vs. rainwater sources. Groundwater extraction can have severe consequences on structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death following groundwater drawdown. We provide a brief review of two case studies of the impacts of GW extraction and discuss the use of C isotope ratios in xylem to reveal past influences of GW extraction. We conclude with a discussion of a depth-to-groundwater threshold in mesic and semi-arid GDEs. Across this threshold, significant changes occur in ecosystem structure and function.

Determination of fructooligosaccharides in burdock using HPLC and microwave-assisted extraction.

PubMed

Li, Jing; Liu, Xiaomei; Zhou, Bin; Zhao, Jing; Li, Shaoping

2013-06-19

The root of burdock ( Arctium lappa L.) is a commonly used vegetable in Asia. Fructooligosaccharides (FOS) are usually considered as its main bioactive components. Thus, quantitative analysis of these components is very important for the quality control of burdock. In this study, an HPLC-ELSD and microwave-assisted extraction method was developed for the simultaneous determination of seven FOS with degrees of polymerization (DP) between 3 and 9, as well as fructose, glucose, and sucrose in burdock from different regions. The separation was performed on a Waters XBridge Amide column (4.6 × 250 mm i.d., 3.5 μm) with gradient elution. All calibration curves for investigated analytes showed good linear regression (r > 0.9990). Their LODs and LOQs were lower than 3.63 and 24.82 μg/mL, respectively. The recoveries ranged from 99.2 to 102.6%. The developed method was successfully applied to determination of ten sugars in burdock from different locations of Asia. The results showed that the contents of FOS in different samples of burdock collected at appropriate times were similar, and the developed HPLC-ELSD with microwave-assisted extraction method is helpful to control the quality of burdock.

Evaluation of metabolites extraction strategies for identifying different brain regions and their relationship with alcohol preference and gender difference using NMR metabolomics.

PubMed

Wang, Jie; Zeng, Hao-Long; Du, Hongying; Liu, Zeyuan; Cheng, Ji; Liu, Taotao; Hu, Ting; Kamal, Ghulam Mustafa; Li, Xihai; Liu, Huili; Xu, Fuqiang

2018-03-01

Metabolomics generate a profile of small molecules from cellular/tissue metabolism, which could directly reflect the mechanisms of complex networks of biochemical reactions. Traditional metabolomics methods, such as OPLS-DA, PLS-DA are mainly used for binary class discrimination. Multiple groups are always involved in the biological system, especially for brain research. Multiple brain regions are involved in the neuronal study of brain metabolic dysfunctions such as alcoholism, Alzheimer's disease, etc. In the current study, 10 different brain regions were utilized for comparative studies between alcohol preferring and non-preferring rats, male and female rats respectively. As many classes are involved (ten different regions and four types of animals), traditional metabolomics methods are no longer efficient for showing differentiation. Here, a novel strategy based on the decision tree algorithm was employed for successfully constructing different classification models to screen out the major characteristics of ten brain regions at the same time. Subsequently, this method was also utilized to select the major effective brain regions related to alcohol preference and gender difference. Compared with the traditional multivariate statistical methods, the decision tree could construct acceptable and understandable classification models for multi-class data analysis. Therefore, the current technology could also be applied to other general metabolomics studies involving multi class data. Copyright © 2017 Elsevier B.V. All rights reserved.

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

PubMed

Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

2017-02-10

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

Mobile robots traversability awareness based on terrain visual sensory data fusion

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir

2007-04-01

In this paper, we have presented methods that significantly improve the robot awareness of its terrain traversability conditions. The terrain traversability awareness is achieved by association of terrain image appearances from different poses and fusion of extracted information from multimodality imaging and range sensor data for localization and clustering environment landmarks. Initially, we describe methods for extraction of salient features of the terrain for the purpose of landmarks registration from two or more images taken from different via points along the trajectory path of the robot. The method of image registration is applied as a means of overlaying (two or more) of the same terrain scene at different viewpoints. The registration geometrically aligns salient landmarks of two images (the reference and sensed images). A Similarity matching techniques is proposed for matching the terrain salient landmarks. Secondly, we present three terrain classifier models based on rule-based, supervised neural network, and fuzzy logic for classification of terrain condition under uncertainty and mapping the robot's terrain perception to apt traversability measures. This paper addresses the technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain spatial and textural cues.

Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

Is the extraction by Whatman FTA filter matrix technology and sequencing of large ribosomal subunit D1-D2 region sufficient for identification of clinical fungi?

PubMed

Kiraz, Nuri; Oz, Yasemin; Aslan, Huseyin; Erturan, Zayre; Ener, Beyza; Akdagli, Sevtap Arikan; Muslumanoglu, Hamza; Cetinkaya, Zafer

2015-10-01

Although conventional identification of pathogenic fungi is based on the combination of tests evaluating their morphological and biochemical characteristics, they can fail to identify the less common species or the differentiation of closely related species. In addition these tests are time consuming, labour-intensive and require experienced personnel. We evaluated the feasibility and sufficiency of DNA extraction by Whatman FTA filter matrix technology and DNA sequencing of D1-D2 region of the large ribosomal subunit gene for identification of clinical isolates of 21 yeast and 160 moulds in our clinical mycology laboratory. While the yeast isolates were identified at species level with 100% homology, 102 (63.75%) clinically important mould isolates were identified at species level, 56 (35%) isolates at genus level against fungal sequences existing in DNA databases and two (1.25%) isolates could not be identified. Consequently, Whatman FTA filter matrix technology was a useful method for extraction of fungal DNA; extremely rapid, practical and successful. Sequence analysis strategy of D1-D2 region of the large ribosomal subunit gene was found considerably sufficient in identification to genus level for the most clinical fungi. However, the identification to species level and especially discrimination of closely related species may require additional analysis. © 2015 Blackwell Verlag GmbH.

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

THERAPEUTIC POTENTIALS OF ETHANOLIC EXTRACT OF LEAVES OF HOLARRHENA FLORIBUNDA (G. DON) DUR. AND SCHINZ (APOCYNACEAE)

PubMed Central

Hoekou, Yao Patrick; Tchacondo, Tchadjobo; Karou, Simplice Damintoti; Yerbanga, Rakiswende Serge; Achoribo, Elom; Da, Ollo; Atakpama, Wouyo; Batawila, Komlan

2017-01-01

Background: Holarrhena floribunda is a plant of wide usage in the Togolese folk medicine. A previous ethnobotanical survey on the latex plants of the Maritime region of the country revealed that this plant was included in several recipes curing malaria and microbial infections. Therefore, this study aimed to seek for the effectiveness of the ethanolic extract of the plant in the treatment of these diseases. Methods: The antimicrobial test was performed using the agar well-diffusion and the NCCLS broth microdilution methods, while the in vivo antimalarial activity was evaluated following the four-day suppressive test of Peters. The acute toxic effects of the extract were monitored after a single oral dose (5,000 mg/kg body weight) administration in NMRI mice. Results: The results indicated that the ethanolic extract of leaves of H. floribunda was active on Staphylococcus aureus ATCC 29213 and clinical strains of Staphylococcus aureus, Salmonella typhi and Klebsiella pneumoniae with MICs ranging from 0.62 to 1.25 mg/mL. The extract also showed significant parasitaemia suppression in a dose-dependent manner. In the acute toxicity assay, the oral administration of the extract to the mice did not affect the relative weight of vital organs, and there were no signs of toxicity or death during the study period. The LD50 of the tested extract was found to be greater than 5,000 mg/kg, indicating its safety. Conclusion: This study demonstrates the antibacterial and antimalarial activities of leaves of H. floribunda and then, supports its medicinal use in the treatment of microbial infections. PMID:28573239

Single-molecule studies of oligomer extraction and uptake of dyes in poly(dimethylsiloxane) films.

PubMed

Lange, Jeffrey J; Collinson, Maryanne M; Culbertson, Christopher T; Higgins, Daniel A

2009-12-15

Single-molecule microscopic methods were used to probe the uptake, mobility, and entrapment of dye molecules in cured poly(dimethylsiloxane) (PDMS) films as a function of oligomer extraction. The results are relevant to the use of PDMS in microfluidic separations, pervaporation, solid-phase microextraction, and nanofiltration. PDMS films were prepared by spin-casting dilute solutions of Sylgard 184 onto glass coverslips, yielding approximately 1.4 microm thick films after curing. Residual oligomers were subsequently extracted from the films by "spin extraction". In this procedure, 200 microL aliquots of isopropyl alcohol were repeatedly dropped onto the film surface and spun off at 2000 rpm. Samples extracted 5, 10, 20, and 40 times were investigated. Dye molecules were loaded into these films by spin-casting nanomolar dye solutions onto the films. Both neutral perylene diimide (N,N'-bis(butoxypropyl)perylene-3,4,9,10-tetracarboxylic diimide) and cationic rhodamine 6G (R6G) dyes were employed. The films were imaged by confocal fluorescence microscopy. The images obtained depict nonzero populations of fixed and mobile molecules in all films. Cross-correlation methods were used to quantitatively determine the population of fixed molecules in a given region, while a Bayesian burst analysis was used to obtain the total population of molecules. The results show that the total amount of dye loaded increases with increased oligomer extraction, while the relative populations of fixed and mobile molecules decrease and increase, respectively. Bulk R6G data also show greater dye loading with increased oligomer extraction.

Extraction of high-quality DNA from ethanol-preserved tropical plant tissues.

PubMed

Bressan, Eduardo A; Rossi, Mônica L; Gerald, Lee T S; Figueira, Antonio

2014-04-24

Proper conservation of plant samples, especially during remote field collection, is essential to assure quality of extracted DNA. Tropical plant species contain considerable amounts of secondary compounds, such as polysaccharides, phenols, and latex, which affect DNA quality during extraction. The suitability of ethanol (96% v/v) as a preservative solution prior to DNA extraction was evaluated using leaves of Jatropha curcas and other tropical species. Total DNA extracted from leaf samples stored in liquid nitrogen or ethanol from J. curcas and other tropical species (Theobroma cacao, Coffea arabica, Ricinus communis, Saccharum spp., and Solanum lycopersicon) was similar in quality, with high-molecular-weight DNA visualized by gel electrophoresis. DNA quality was confirmed by digestion with EcoRI or HindIII and by amplification of the ribosomal gene internal transcribed spacer region. Leaf tissue of J. curcas was analyzed by light and transmission electron microscopy before and after exposure to ethanol. Our results indicate that leaf samples can be successfully preserved in ethanol for long periods (30 days) as a viable method for fixation and conservation of DNA from leaves. The success of this technique is likely due to reduction or inactivation of secondary metabolites that could contaminate or degrade genomic DNA. Tissue conservation in 96% ethanol represents an attractive low-cost alternative to commonly used methods for preservation of samples for DNA extraction. This technique yields DNA of equivalent quality to that obtained from fresh or frozen tissue.

Extraction of high-quality DNA from ethanol-preserved tropical plant tissues

PubMed Central

2014-01-01

Background Proper conservation of plant samples, especially during remote field collection, is essential to assure quality of extracted DNA. Tropical plant species contain considerable amounts of secondary compounds, such as polysaccharides, phenols, and latex, which affect DNA quality during extraction. The suitability of ethanol (96% v/v) as a preservative solution prior to DNA extraction was evaluated using leaves of Jatropha curcas and other tropical species. Results Total DNA extracted from leaf samples stored in liquid nitrogen or ethanol from J. curcas and other tropical species (Theobroma cacao, Coffea arabica, Ricinus communis, Saccharum spp., and Solanum lycopersicon) was similar in quality, with high-molecular-weight DNA visualized by gel electrophoresis. DNA quality was confirmed by digestion with EcoRI or HindIII and by amplification of the ribosomal gene internal transcribed spacer region. Leaf tissue of J. curcas was analyzed by light and transmission electron microscopy before and after exposure to ethanol. Our results indicate that leaf samples can be successfully preserved in ethanol for long periods (30 days) as a viable method for fixation and conservation of DNA from leaves. The success of this technique is likely due to reduction or inactivation of secondary metabolites that could contaminate or degrade genomic DNA. Conclusions Tissue conservation in 96% ethanol represents an attractive low-cost alternative to commonly used methods for preservation of samples for DNA extraction. This technique yields DNA of equivalent quality to that obtained from fresh or frozen tissue. PMID:24761774

Biological Activity of Blackcurrant Extracts (Ribes nigrum L.) in Relation to Erythrocyte Membranes

PubMed Central

Cyboran, Sylwia; Żyłka, Romuald; Oszmiański, Jan; Kleszczyńska, Halina

2014-01-01

Compounds contained in fruits and leaves of blackcurrant (Ribes nigrum L.) are known as agents acting preventively and therapeutically on the organism. The HPLC analysis showed they are rich in polyphenol anthocyanins in fruits and flavonoids in leaves, that have antioxidant activity and are beneficial for health. The aim of the research was to determine the effect of blackcurrant fruit and leaf extracts on the physical properties of the erythrocyte membranes and assess their antioxidant properties. The effect of the extracts on osmotic resistance, shape of erythrocytes and hemolytic and antioxidant activity of the extracts were examined with spectrophotometric methods. The FTIR investigation showed that extracts modify the erythrocyte membrane and protect it against free radicals induced by UV radiation. The results show that the extracts do not induce hemolysis and even protect erythrocytes against the harmful action of UVC radiation, while slightly strengthening the membrane and inducing echinocytes. The compounds contained in the extracts do not penetrate into the hydrophobic region, but bind to the membrane surface inducing small changes in the packing arrangement of the polar head groups of membrane lipids. The extracts have a high antioxidant activity. Their presence on the surface of the erythrocyte membrane entails protection against free radicals. PMID:24527456

A TaqMan-Based Multiplex qPCR Assay and DNA Extraction Method for Phylotype IIB Sequevars 1&2 (Select Agent) Strains of Ralstonia solanacearum

PubMed Central

Stulberg, Michael J.; Huang, Qi

2015-01-01

Ralstonia solanacearum race 3 biovar 2 strains belonging to phylotype IIB, sequevars 1 and 2 (IIB-1&2) cause brown rot of potato in temperate climates, and are quarantined pathogens in Canada and Europe. Since these strains are not established in the U.S. and because of their potential risk to the potato industry, the U.S. government has listed them as select agents. Cultivated geraniums are also a host and have the potential to spread the pathogen through trade, and its extracts strongly inhibits DNA-based detection methods. We designed four primer and probe sets for an improved qPCR method that targets stable regions of DNA. RsSA1 and RsSA2 recognize IIB-1&2 strains, RsII recognizes the current phylotype II (the newly proposed R. solanacearum species) strains (and a non-plant associated R. mannitolilytica), and Cox1 recognizes eight plant species including major hosts of R. solanacearum such as potato, tomato and cultivated geranium as an internal plant control. We multiplexed the RsSA2 with the RsII and Cox1 sets to provide two layers of detection of a positive IIB-1&2 sample, and to validate plant extracts and qPCR reactions. The TaqMan-based uniplex and multiplex qPCR assays correctly identified 34 IIB-1&2 and 52 phylotype II strains out of 90 R. solanacearum species complex strains. Additionally, the multiplex qPCR assay was validated successfully using 169 artificially inoculated symptomatic and asymptomatic plant samples from multiple plant hosts including geranium. Furthermore, we developed an extraction buffer that allowed for a quick and easy DNA extraction from infected plants including geranium for detection of R. solanacearum by qPCR. Our multiplex qPCR assay, especially when coupled with the quick extraction buffer method, allows for quick, easy and reliable detection and differentiation of the IIB-1&2 strains of R. solanacearum. PMID:26426354

Automatic Extraction of Road Markings from Mobile Laser Scanning Data

NASA Astrophysics Data System (ADS)

Ma, H.; Pei, Z.; Wei, Z.; Zhong, R.

2017-09-01

Road markings as critical feature in high-defination maps, which are Advanced Driver Assistance System (ADAS) and self-driving technology required, have important functions in providing guidance and information to moving cars. Mobile laser scanning (MLS) system is an effective way to obtain the 3D information of the road surface, including road markings, at highway speeds and at less than traditional survey costs. This paper presents a novel method to automatically extract road markings from MLS point clouds. Ground points are first filtered from raw input point clouds using neighborhood elevation consistency method. The basic assumption of the method is that the road surface is smooth. Points with small elevation-difference between neighborhood are considered to be ground points. Then ground points are partitioned into a set of profiles according to trajectory data. The intensity histogram of points in each profile is generated to find intensity jumps in certain threshold which inversely to laser distance. The separated points are used as seed points to region grow based on intensity so as to obtain road mark of integrity. We use the point cloud template-matching method to refine the road marking candidates via removing the noise clusters with low correlation coefficient. During experiment with a MLS point set of about 2 kilometres in a city center, our method provides a promising solution to the road markings extraction from MLS data.

Hexahedral finite element mesh coarsening using pillowing technique

DOEpatents

Staten, Matthew L [Pittsburgh, PA; Woodbury, Adam C [Provo, UT; Benzley, Steven E [Provo, UT; Shepherd, Jason F [Edgewood, NM

2012-06-05

A techniques for coarsening a hexahedral mesh is described. The technique includes identifying a coarsening region within a hexahedral mesh to be coarsened. A boundary sheet of hexahedral elements is inserted into the hexahedral mesh around the coarsening region. A column of hexahedral elements is identified within the boundary sheet. The column of hexahedral elements is collapsed to create an extraction sheet of hexahedral elements contained within the coarsening region. Then, the extraction sheet of hexahedral elements is extracted to coarsen the hexahedral mesh.

Predicting protein complexes using a supervised learning method combined with local structural information.

PubMed

Dong, Yadong; Sun, Yongqi; Qin, Chao

2018-01-01

The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

Photometry unlocks 3D information from 2D localization microscopy data.

PubMed

Franke, Christian; Sauer, Markus; van de Linde, Sebastian

2017-01-01

We developed a straightforward photometric method, temporal, radial-aperture-based intensity estimation (TRABI), that allows users to extract 3D information from existing 2D localization microscopy data. TRABI uses the accurate determination of photon numbers in different regions of the emission pattern of single emitters to generate a z-dependent photometric parameter. This method can determine fluorophore positions up to 600 nm from the focal plane and can be combined with biplane detection to further improve axial localization.

Electron-deuteron deep-inelastic scattering with spectator nucleon tagging and final-state interactions at intermediate x

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

Strikman, Mark; Weiss, Christian

We consider electron-deuteron deep-inelastic scattering (DIS) with detection of a proton in the nuclear fragmentation region ("spectator tagging") as a method for extracting the free neutron structure functions and studying their nuclear modifications. Such measurements could be performed at a future Electron-Ion Collider (EIC) with suitable forward detectors. The measured proton recoil momentum (≲ 100 MeV in the deuteron rest frame) specifies the deuteron configuration during the high-energy process and permits a controlled theoretical treatment of nuclear effects. Nuclear and nucleonic structure are separated using methods of light-front quantum mechanics. The impulse approximation (IA) to the tagged DIS cross sectionmore » contains the free neutron pole, which can be reached by on-shell extrapolation in the recoil momentum. Final-state interactions (FSI) distort the recoil momentum distribution away from the pole. In the intermediate-x region 0.1 < x < 0.5 FSI arise predominantly from interactions of the spectator proton with slow hadrons produced in the DIS process on the neutron (rest frame momenta ≲1 GeV, target fragmentation region). We construct a schematic model describing this effect, using final-state hadron distributions measured in nucleon DIS experiments and low-energy hadron scattering amplitudes. We investigate the magnitude of FSI, their dependence on the recoil momentum (angular dependence, forward/backward regions), their analytic properties, and their effect on the on-shell extrapolation. We comment on the prospects for neutron structure extraction in tagged DIS with EIC. Finally, we discuss possible extensions of the FSI model to other kinematic regions (large/small x). In tagged DIS at x << 0.1 FSI resulting from diffractive scattering on the nucleons become important and require separate treatment.« less

Electron-deuteron deep-inelastic scattering with spectator nucleon tagging and final-state interactions at intermediate x

NASA Astrophysics Data System (ADS)

Strikman, M.; Weiss, C.

2018-03-01

We consider electron-deuteron deep-inelastic scattering (DIS) with detection of a proton in the nuclear fragmentation region ("spectator tagging") as a method for extracting the free neutron structure functions and studying their nuclear modifications. Such measurements could be performed at a future electron-ion collider (EIC) with suitable forward detectors. The measured proton recoil momentum (≲100 MeV in the deuteron rest frame) specifies the deuteron configuration during the high-energy process and permits a controlled theoretical treatment of nuclear effects. Nuclear and nucleonic structure are separated using methods of light-front quantum mechanics. The impulse approximation to the tagged DIS cross section contains the free neutron pole, which can be reached by on-shell extrapolation in the recoil momentum. Final-state interactions (FSIs) distort the recoil momentum distribution away from the pole. In the intermediate-x region 0.1

Urbanization and prevalence of type 2 diabetes in Southern Asia: A systematic analysis

PubMed Central

Cheema, Arsalan; Adeloye, Davies; Sidhu, Simrita; Sridhar, Devi; Chan, Kit Yee

2014-01-01

Background Diabetes mellitus is one of the diseases considered to be the main constituents of the global non–communicable disease (NCD) pandemic. Despite the large impact that NCDs are predicted to have, particularly in developing countries, estimates of disease burden are sparse and inconsistent. This systematic review transparently estimates prevalence of type 2 diabetes mellitus in Southern Asia, its association with urbanization and provides insight into the policy challenges facing the region. Methods The databases Medline and PubMed were searched for population–based studies providing estimates of diabetes prevalence in the Southern Asia region. Studies using WHO diagnostic criteria of fasting plasma glucose (FPG) ≥7.0mmol/L and/or 2h–plasma glucose (2hPG) ≥11.1mmol/L were included. Data from eligible studies was extracted into bubble graphs, and trend lines were applied to UNPD figures to estimate age–specific prevalence in the regional population. Estimates specific to sex, area of residency, and diagnostic method were compared and trends analysed. Results A total of 151 age–specific prevalence estimates were extracted from 39 studies. Diabetes prevalence was estimated to be 7.47% for 2005 and 7.60% for 2010. Prevalence was strongly associated with increased age, male gender and urban residency (P < 0.001). Conclusion Diabetes prevalence in Southern Asia is high and predicted to increase in the future as life expectancy rises and the region continues to urbanise. Countries in this region need to improve NCD surveillance and monitoring so policies can be informed with the best evidence. Programs for prevention need to be put in place, and health system capacity and access needs to be assessed and increased to deal with the predicted rise in NCD prevalence. PMID:24976963

Electron-deuteron deep-inelastic scattering with spectator nucleon tagging and final-state interactions at intermediate x

DOE PAGES

Strikman, Mark; Weiss, Christian

2018-03-27

We consider electron-deuteron deep-inelastic scattering (DIS) with detection of a proton in the nuclear fragmentation region ("spectator tagging") as a method for extracting the free neutron structure functions and studying their nuclear modifications. Such measurements could be performed at a future Electron-Ion Collider (EIC) with suitable forward detectors. The measured proton recoil momentum (≲ 100 MeV in the deuteron rest frame) specifies the deuteron configuration during the high-energy process and permits a controlled theoretical treatment of nuclear effects. Nuclear and nucleonic structure are separated using methods of light-front quantum mechanics. The impulse approximation (IA) to the tagged DIS cross sectionmore » contains the free neutron pole, which can be reached by on-shell extrapolation in the recoil momentum. Final-state interactions (FSI) distort the recoil momentum distribution away from the pole. In the intermediate-x region 0.1 < x < 0.5 FSI arise predominantly from interactions of the spectator proton with slow hadrons produced in the DIS process on the neutron (rest frame momenta ≲1 GeV, target fragmentation region). We construct a schematic model describing this effect, using final-state hadron distributions measured in nucleon DIS experiments and low-energy hadron scattering amplitudes. We investigate the magnitude of FSI, their dependence on the recoil momentum (angular dependence, forward/backward regions), their analytic properties, and their effect on the on-shell extrapolation. We comment on the prospects for neutron structure extraction in tagged DIS with EIC. Finally, we discuss possible extensions of the FSI model to other kinematic regions (large/small x). In tagged DIS at x << 0.1 FSI resulting from diffractive scattering on the nucleons become important and require separate treatment.« less

Quantification of lung tumor rotation with automated landmark extraction using orthogonal cine MRI images

NASA Astrophysics Data System (ADS)

Paganelli, Chiara; Lee, Danny; Greer, Peter B.; Baroni, Guido; Riboldi, Marco; Keall, Paul

2015-09-01

The quantification of tumor motion in sites affected by respiratory motion is of primary importance to improve treatment accuracy. To account for motion, different studies analyzed the translational component only, without focusing on the rotational component, which was quantified in a few studies on the prostate with implanted markers. The aim of our study was to propose a tool able to quantify lung tumor rotation without the use of internal markers, thus providing accurate motion detection close to critical structures such as the heart or liver. Specifically, we propose the use of an automatic feature extraction method in combination with the acquisition of fast orthogonal cine MRI images of nine lung patients. As a preliminary test, we evaluated the performance of the feature extraction method by applying it on regions of interest around (i) the diaphragm and (ii) the tumor and comparing the estimated motion with that obtained by (i) the extraction of the diaphragm profile and (ii) the segmentation of the tumor, respectively. The results confirmed the capability of the proposed method in quantifying tumor motion. Then, a point-based rigid registration was applied to the extracted tumor features between all frames to account for rotation. The median lung rotation values were  -0.6   ±   2.3° and  -1.5   ±   2.7° in the sagittal and coronal planes respectively, confirming the need to account for tumor rotation along with translation to improve radiotherapy treatment.

A two-stage extraction procedure for insensitive munition (IM) explosive compounds in soils.

PubMed

Felt, Deborah; Gurtowski, Luke; Nestler, Catherine C; Johnson, Jared; Larson, Steven

2016-12-01

The Department of Defense (DoD) is developing a new category of insensitive munitions (IMs) that are more resistant to detonation or promulgation from external stimuli than traditional munition formulations. The new explosive constituent compounds are 2,4-dinitroanisole (DNAN), nitroguanidine (NQ), and nitrotriazolone (NTO). The production and use of IM formulations may result in interaction of IM component compounds with soil. The chemical properties of these IM compounds present unique challenges for extraction from environmental matrices such as soil. A two-stage extraction procedure was developed and tested using several soil types amended with known concentrations of IM compounds. This procedure incorporates both an acidified phase and an organic phase to account for the chemical properties of the IM compounds. The method detection limits (MDLs) for all IM compounds in all soil types were <5 mg/kg and met non-regulatory risk-based Regional Screening Level (RSL) criteria for soil proposed by the U.S. Army Public Health Center. At defined environmentally relevant concentrations, the average recovery of each IM compound in each soil type was consistent and greater than 85%. The two-stage extraction method decreased the influence of soil composition on IM compound recovery. UV analysis of NTO established an isosbestic point based on varied pH at a detection wavelength of 341 nm. The two-stage soil extraction method is equally effective for traditional munition compounds, a potentially important point when examining soils exposed to both traditional and insensitive munitions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Segmentation and classification of brain images using firefly and hybrid kernel-based support vector machine

NASA Astrophysics Data System (ADS)

Selva Bhuvaneswari, K.; Geetha, P.

2017-05-01

Magnetic resonance imaging segmentation refers to a process of assigning labels to set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by the radiologists to segment the medical images input into meaningful regions. In recent years, various brain tumour detection techniques are presented in the literature. The entire segmentation process of our proposed work comprises three phases: threshold generation with dynamic modified region growing phase, texture feature generation phase and region merging phase. by dynamically changing two thresholds in the modified region growing approach, the first phase of the given input image can be performed as dynamic modified region growing process, in which the optimisation algorithm, firefly algorithm help to optimise the two thresholds in modified region growing. After obtaining the region growth segmented image using modified region growing, the edges can be detected with edge detection algorithm. In the second phase, the texture feature can be extracted using entropy-based operation from the input image. In region merging phase, the results obtained from the texture feature-generation phase are combined with the results of dynamic modified region growing phase and similar regions are merged using a distance comparison between regions. After identifying the abnormal tissues, the classification can be done by hybrid kernel-based SVM (Support Vector Machine). The performance analysis of the proposed method will be carried by K-cross fold validation method. The proposed method will be implemented in MATLAB with various images.

Seamline Determination Based on PKGC Segmentation for Remote Sensing Image Mosaicking

PubMed Central

Dong, Qiang; Liu, Jinghong

2017-01-01

This paper presents a novel method of seamline determination for remote sensing image mosaicking. A two-level optimization strategy is applied to determine the seamline. Object-level optimization is executed firstly. Background regions (BRs) and obvious regions (ORs) are extracted based on the results of parametric kernel graph cuts (PKGC) segmentation. The global cost map which consists of color difference, a multi-scale morphological gradient (MSMG) constraint, and texture difference is weighted by BRs. Finally, the seamline is determined in the weighted cost from the start point to the end point. Dijkstra’s shortest path algorithm is adopted for pixel-level optimization to determine the positions of seamline. Meanwhile, a new seamline optimization strategy is proposed for image mosaicking with multi-image overlapping regions. The experimental results show the better performance than the conventional method based on mean-shift segmentation. Seamlines based on the proposed method bypass the obvious objects and take less time in execution. This new method is efficient and superior for seamline determination in remote sensing image mosaicking. PMID:28749446

Quantitative analysis of acylated oleanane-type triterpene saponins, chakasaponins I-III and floratheasaponins A-F, in the flower buds of Camellia sinensis from different regional origins.

PubMed

Morikawa, Toshio; Miyake, Sohachiro; Miki, Yoshinobu; Ninomiya, Kiyofumi; Yoshikawa, Masayuki; Muraoka, Osamu

2012-10-01

A quantitative analytical method was developed for the determination of acylated oleanane-type triterpene saponins, chakasaponins I-III (1-3) and floratheasaponins A-F (4-9), found in Camellia sinensis (Theaceae). The practical conditions for separation and detection of these saponins were established on an ODS column with methanol containing 5 mM trifluoroacetic acid as a mobile phase, and the detection and quantitation limits of the method were estimated to be 1.1-3.8 and 3.5-12.5 ng, respectively. The relative standard deviation values of intra- and interday precision were lower than 2.35 and 6.12%, respectively, overall mean recoveries of all saponins being 94.7-108.8%, and the correlation coefficients of all the calibration curves showed good linearity within the test ranges. To approve the validity of the protocol, extracts of 13 kinds of C. sinensis collected in China, Taiwan, Japan, and India were evaluated. The results indicated that the assay was reproducible and precise, and could be readily utilized for the quality evaluation of tea flowers. It was noteworthy that the distinct regional difference was observed with respect to the content of chakasaponins and floratheasaponins, more chakasaponins being contained in the extracts of tea flowers from Fujian and Sichuan provinces, China than those from Japan, Taiwan, and India. Optimum conditions for the extraction process were also established.

Potentially toxic elements (PTEs) in soils from the surroundings of the Trans-Amazonian Highway, Brazil.

PubMed

de Souza, Edna Santos; Fernandes, Antonio Rodrigues; de Souza Braz, Anderson Martins; Sabino, Lorena Lira Leite; Alleoni, Luís Reynaldo Ferracciú

2015-01-01

The Trans-Amazonian Highway (TAH) is located in the northern region of Brazil, comprising a border region where agricultural, mining, and logging activities are the main activities responsible for fostering economic development, in addition to large hydroelectric plants. Such activities lead to environmental contamination by potentially toxic elements (PTEs). Environmental monitoring is only possible through the determination of element contents under natural conditions. Many extraction methods have been proposed to determine PTEs' bioavailability in the soil; however, there is no consensus about which extractor is most suitable. In this study, we determined the contents of PTEs in soils in the surroundings of TAH after mineral extraction with diethylenetriaminepentaacetic acid-triethanolamine (DTPA-TEA), Mehlich I, and Mehlich III solutions. Soil samples were collected in areas of natural vegetation in the vicinity of TAH in the state of Pará, Brazil. Chemical attributes and particle size were determined, besides concentrations of Fe, Al, Mn, and Ti by sulfuric acid digestion, Si after alkaline solution attack, and poorly crystalline Fe, Al, and "free" Fe oxides. Mehlich III solution extracted greater contents from Fe, Al, and Pb as compared to Mehlich I and DTPA-TEA and similar contents from Cd, Mn, Zn, and Cu. Significant correlations were found between concentrations of PTEs and the contents of Fe and Mn oxides as well as organic carbon and soil cation exchange capacity. Contents of Cu, Mn, Fe, and Zn by the three methods were positively correlated.

Dried extracts of Encholirium spectabile (Bromeliaceae) present antioxidant and photoprotective activities in vitro

PubMed Central

de Oliveira, Raimundo Gonçalves; Souza, Grasielly Rocha; Guimarães, Amanda Leite; de Oliveira, Ana Paula; Silva Morais, Amanda Caroline; da Cruz Araújo, Edigênia Cavalcante; Nunes, Xirley Pereira; Almeida, Jackson Roberto Guedes da Silva

2013-01-01

The antioxidant and photoprotective activities of dried extracts from the leaves of Encholirium spectabile were investigated. It was also evaluated the total phenolic and flavonoid contents by the Folin–Ciocalteu and aluminum chloride methods, respectively. Antioxidant activities of the extracts were evaluated by using of 2,2-diphenyl-1-picrylhydrazil (DPPH) radical scavenging and β-carotene–linoleic acid bleaching and compared with ascorbic acid, butylated hydroxyanisole (BHA) and butylated hydroxytoluene (BHT) used as reference compounds. The photoprotective effect was evaluated by the spectrophotometric method. The most significant total phenolic and flavonoid contents was of 188.50 ± 27.50 mg of gallic acid equivalent/g and 129.70 ± 4.59 mg of catechin equivalent/g, respectively, for chloroform fraction (Es-CHCl3). The Es-CHCl3 also presented the best antioxidant activity (IC50 25.35 ± 4.35 μg/ml) for DPPH scavenging. The ethanol extract (Es-EtOH), Es-CHCl3 and the fraction ethyl acetate (Es-AcOEt) showed characteristic absorption bands in regions UVB and UVA in a concentration-dependent manner. Es-CHCl3 presented the highest sun protection factor SPF (8.89 ± 2.11). It shows the possibility to use this extract as sunscreen in pharmaceutical preparations. PMID:24396251

Depth of interaction decoding of a continuous crystal detector module.

PubMed

Ling, T; Lewellen, T K; Miyaoka, R S

2007-04-21

We present a clustering method to extract the depth of interaction (DOI) information from an 8 mm thick crystal version of our continuous miniature crystal element (cMiCE) small animal PET detector. This clustering method, based on the maximum-likelihood (ML) method, can effectively build look-up tables (LUT) for different DOI regions. Combined with our statistics-based positioning (SBP) method, which uses a LUT searching algorithm based on the ML method and two-dimensional mean-variance LUTs of light responses from each photomultiplier channel with respect to different gamma ray interaction positions, the position of interaction and DOI can be estimated simultaneously. Data simulated using DETECT2000 were used to help validate our approach. An experiment using our cMiCE detector was designed to evaluate the performance. Two and four DOI region clustering were applied to the simulated data. Two DOI regions were used for the experimental data. The misclassification rate for simulated data is about 3.5% for two DOI regions and 10.2% for four DOI regions. For the experimental data, the rate is estimated to be approximately 25%. By using multi-DOI LUTs, we also observed improvement of the detector spatial resolution, especially for the corner region of the crystal. These results show that our ML clustering method is a consistent and reliable way to characterize DOI in a continuous crystal detector without requiring any modifications to the crystal or detector front end electronics. The ability to characterize the depth-dependent light response function from measured data is a major step forward in developing practical detectors with DOI positioning capability.

Comparison of four DNA extraction methods for the detection of Mycobacterium leprae from Ziehl-Neelsen-stained microscopic slides.

PubMed

Ruiz-Fuentes, Jenny Laura; Díaz, Alexis; Entenza, Anayma Elena; Frión, Yahima; Suárez, Odelaisy; Torres, Pedro; de Armas, Yaxsier; Acosta, Lucrecia

2015-12-01

The diagnosis of leprosy has been a challenge due to the low sensibility of the conventional methods and the impossibility of culturing the causative organism. In this study, four methods for Mycobacterium leprae nucleic-acid extraction from Ziehl-Neelsen-stained slides (ZNS slides) were compared: Phenol/chloroform, Chelex 100 resin, and two commercial kits (Wizard Genomic DNA Purification Kit and QIAamp DNA Mini Kit). DNA was extracted from four groups of slides: a high-codification-slide group (bacteriological index [BI]⩾4), a low-codification-slide group (BI=1), a negative-slide group (BI=0), and a negative-control-slide group (BI=0). Quality DNA was evidenced by the amplification of specific repetitive element present in M. leprae genomic DNA (RLEP) using a nested polymerase chain reaction. This is the first report comparing four different extraction methods for obtaining M. leprae DNA from ZNS slides in Cuban patients, and applied in molecular diagnosis. Good-quality DNA and positive amplification were detected in the high-codification-slide group with the four methods, while from the low-codification-slide group only the QIAGEN and phenol-chloroform methods obtained amplification of M. leprae. In the negative-slide group, only the QIAGEN method was able to obtain DNA with sufficient quality for positive amplification of the RLEP region. No amplification was observed in the negative-control-slide group by any method. Patients with ZNS negative slides can still transmit the infection, and molecular methods can help identify and treat them, interrupting the chain of transmission and preventing the onset of disabilities. The ZNS slides can be sent easily to reference laboratories for later molecular analysis that can be useful not only to improve the diagnosis, but also for the application of other molecular techniques. Copyright © 2015 Asian-African Society for Mycobacteriology. Published by Elsevier Ltd. All rights reserved.

SU-E-J-252: Reproducibility of Radiogenomic Image Features: Comparison of Two Semi-Automated Segmentation Methods

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

Lee, M; Woo, B; Kim, J

Purpose: Objective and reliable quantification of imaging phenotype is an essential part of radiogenomic studies. We compared the reproducibility of two semi-automatic segmentation methods for quantitative image phenotyping in magnetic resonance imaging (MRI) of glioblastoma multiforme (GBM). Methods: MRI examinations with T1 post-gadolinium and FLAIR sequences of 10 GBM patients were downloaded from the Cancer Image Archive site. Two semi-automatic segmentation tools with different algorithms (deformable model and grow cut method) were used to segment contrast enhancement, necrosis and edema regions by two independent observers. A total of 21 imaging features consisting of area and edge groups were extracted automaticallymore » from the segmented tumor. The inter-observer variability and coefficient of variation (COV) were calculated to evaluate the reproducibility. Results: Inter-observer correlations and coefficient of variation of imaging features with the deformable model ranged from 0.953 to 0.999 and 2.1% to 9.2%, respectively, and the grow cut method ranged from 0.799 to 0.976 and 3.5% to 26.6%, respectively. Coefficient of variation for especially important features which were previously reported as predictive of patient survival were: 3.4% with deformable model and 7.4% with grow cut method for the proportion of contrast enhanced tumor region; 5.5% with deformable model and 25.7% with grow cut method for the proportion of necrosis; and 2.1% with deformable model and 4.4% with grow cut method for edge sharpness of tumor on CE-T1W1. Conclusion: Comparison of two semi-automated tumor segmentation techniques shows reliable image feature extraction for radiogenomic analysis of GBM patients with multiparametric Brain MRI.« less

Extraction and textural characterization of above-ground areas from aerial stereo pairs: a quality assessment

NASA Astrophysics Data System (ADS)

Baillard, C.; Dissard, O.; Jamet, O.; Maître, H.

Above-ground analysis is a key point to the reconstruction of urban scenes, but it is a difficult task because of the diversity of the involved objects. We propose a new method to above-ground extraction from an aerial stereo pair, which does not require any assumption about object shape or nature. A Digital Surface Model is first produced by a stereoscopic matching stage preserving discontinuities, and then processed by a region-based Markovian classification algorithm. The produced above-ground areas are finally characterized as man-made or natural according to the grey level information. The quality of the results is assessed and discussed.

Asymmetric dee-voltage compensation of beam off-centering in the milan superconducting cyclotron

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

Milinkovic, Lj.; Fabrici, E.; Ostojic, R.

1985-10-01

An analysis of the effects of orbit off-centering on the beam extraction in the Milan superconducting cyclotron is made, and the sensitivity of axial beam loss and radial phase space distortions to beam off-centering determined for various acceleration conditions. We conclude that the first field harmonic compensation of beam off-centering is ineffective in the region of the operating diagram where the Walkinshaw resonance precedes the ..nu.. /SUB r/ =1 resonance. Asymmetric dee-voltage compensation is considered in these cases, and the domain of validity of the method determined. A semi-empirical relation for dee-voltage distribution is deduced, and the extraction efficiency discussed.

Human region segmentation and description methods for domiciliary healthcare monitoring using chromatic methodology

NASA Astrophysics Data System (ADS)

Al-Temeemy, Ali A.

2018-03-01

A descriptor is proposed for use in domiciliary healthcare monitoring systems. The descriptor is produced from chromatic methodology to extract robust features from the monitoring system's images. It has superior discrimination capabilities, is robust to events that normally disturb monitoring systems, and requires less computational time and storage space to achieve recognition. A method of human region segmentation is also used with this descriptor. The performance of the proposed descriptor was evaluated using experimental data sets, obtained through a series of experiments performed in the Centre for Intelligent Monitoring Systems, University of Liverpool. The evaluation results show high recognition performance for the proposed descriptor in comparison to traditional descriptors, such as moments invariant. The results also show the effectiveness of the proposed segmentation method regarding distortion effects associated with domiciliary healthcare systems.

Organic Chemistry and the Native Plants of the Sonoran Desert: Conversion of Jojoba Oil to Biodiesel

ERIC Educational Resources Information Center

Daconta, Lisa V.; Minger, Timothy; Nedelkova, Valentina; Zikopoulos, John N.

2015-01-01

A new, general approach to the organic chemistry laboratory is introduced that is based on learning about organic chemistry techniques and research methods by exploring the natural products found in local native plants. As an example of this approach for the Sonoran desert region, the extraction of jojoba oil and its transesterification to…

Skeletal maturity determination from hand radiograph by model-based analysis

NASA Astrophysics Data System (ADS)

Vogelsang, Frank; Kohnen, Michael; Schneider, Hansgerd; Weiler, Frank; Kilbinger, Markus W.; Wein, Berthold B.; Guenther, Rolf W.

2000-06-01

Derived from a model based segmentation algorithm for hand radiographs proposed in our former work we now present a method to determine skeletal maturity by an automated analysis of regions of interest (ROI). These ROIs including the epiphyseal and carpal bones, which are most important for skeletal maturity determination, can be extracted out of the radiograph by knowledge based algorithms.

Segmentation of anterior cruciate ligament in knee MR images using graph cuts with patient-specific shape constraints and label refinement.

PubMed

Lee, Hansang; Hong, Helen; Kim, Junmo

2014-12-01

We propose a graph-cut-based segmentation method for the anterior cruciate ligament (ACL) in knee MRI with a novel shape prior and label refinement. As the initial seeds for graph cuts, candidates for the ACL and the background are extracted from knee MRI roughly by means of adaptive thresholding with Gaussian mixture model fitting. The extracted ACL candidate is segmented iteratively by graph cuts with patient-specific shape constraints. Two shape constraints termed fence and neighbor costs are suggested such that the graph cuts prevent any leakage into adjacent regions with similar intensity. The segmented ACL label is refined by means of superpixel classification. Superpixel classification makes the segmented label propagate into missing inhomogeneous regions inside the ACL. In the experiments, the proposed method segmented the ACL with Dice similarity coefficient of 66.47±7.97%, average surface distance of 2.247±0.869, and root mean squared error of 3.538±1.633, which increased the accuracy by 14.8%, 40.3%, and 37.6% from the Boykov model, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cough sound analysis - a new tool for diagnosing pneumonia.

PubMed

Abeyratne, U R; Swarnkar, V; Triasih, Rina; Setyati, Amalia

2013-01-01

Pneumonia kills over 1,800,000 children annually throughout the world. Prompt diagnosis and proper treatment are essential to prevent these unnecessary deaths. Reliable diagnosis of childhood pneumonia in remote regions is fraught with difficulties arising from the lack of field-deployable imaging and laboratory facilities as well as the scarcity of trained community healthcare workers. In this paper, we present a pioneering class of enabling technology addressing both of these problems. Our approach is centered on automated analysis of cough and respiratory sounds, collected via microphones that do not require physical contact with subjects. We collected cough sounds from 91 patients suspected of acute respiratory illness such as pneumonia, bronchiolitis and asthma. We extracted mathematical features from cough sounds and used them to train a Logistic Regression classifier. We used the clinical diagnosis provided by the paediatric respiratory clinician as the gold standard to train and validate our classifier against. The methods proposed in this paper could separate pneumonia from other diseases at a sensitivity and specificity of 94% and 75% respectively, based on parameters extracted from cough sounds alone. Our method has the potential to revolutionize the management of childhood pneumonia in remote regions of the world.

Infrared imaging based hyperventilation monitoring through respiration rate estimation

NASA Astrophysics Data System (ADS)

Basu, Anushree; Routray, Aurobinda; Mukherjee, Rashmi; Shit, Suprosanna

2016-07-01

A change in the skin temperature is used as an indicator of physical illness which can be detected through infrared thermography. Thermograms or thermal images can be used as an effective diagnostic tool for monitoring and diagnosis of various diseases. This paper describes an infrared thermography based approach for detecting hyperventilation caused due to stress and anxiety in human beings by computing their respiration rates. The work employs computer vision techniques for tracking the region of interest from thermal video to compute the breath rate. Experiments have been performed on 30 subjects. Corner feature extraction using Minimum Eigenvalue (Shi-Tomasi) algorithm and registration using Kanade Lucas-Tomasi algorithm has been used here. Thermal signature around the extracted region is detected and subsequently filtered through a band pass filter to compute the respiration profile of an individual. If the respiration profile shows unusual pattern and exceeds the threshold we conclude that the person is stressed and tending to hyperventilate. Results obtained are compared with standard contact based methods which have shown significant correlations. It is envisaged that the thermal image based approach not only will help in detecting hyperventilation but can assist in regular stress monitoring as it is non-invasive method.

Identification and annotation of erotic film based on content analysis

NASA Astrophysics Data System (ADS)

Wang, Donghui; Zhu, Miaoliang; Yuan, Xin; Qian, Hui

2005-02-01

The paper brings forward a new method for identifying and annotating erotic films based on content analysis. First, the film is decomposed to video and audio stream. Then, the video stream is segmented into shots and key frames are extracted from each shot. We filter the shots that include potential erotic content by finding the nude human body in key frames. A Gaussian model in YCbCr color space for detecting skin region is presented. An external polygon that covered the skin regions is used for the approximation of the human body. Last, we give the degree of the nudity by calculating the ratio of skin area to whole body area with weighted parameters. The result of the experiment shows the effectiveness of our method.

Diurnal variability of regional cloud and clear-sky radiative parameters derived from GOES data. I - Analysis method. II - November 1978 cloud distributions. III - November 1978 radiative parameters

NASA Technical Reports Server (NTRS)

Minnis, P.; Harrison, E. F.

1984-01-01

Cloud cover is one of the most important variables affecting the earth radiation budget (ERB) and, ultimately, the global climate. The present investigation is concerned with several aspects of the effects of extended cloudiness, taking into account hourly visible and infrared data from the Geostationary Operational Environmental Satelite (GOES). A methodology called the hybrid bispectral threshold method is developed to extract regional cloud amounts at three levels in the atmosphere, effective cloud-top temperatures, clear-sky temperature and cloud and clear-sky visible reflectance characteristics from GOES data. The diurnal variations are examined in low, middle, high, and total cloudiness determined with this methodology for November 1978. The bulk, broadband radiative properties of the resultant cloud and clear-sky data are estimated to determine the possible effect of the diurnal variability of regional cloudiness on the interpretation of ERB measurements.

Light emitting diode with porous SiC substrate and method for fabricating

DOEpatents

Li, Ting; Ibbetson, James; Keller, Bernd

2005-12-06

A method and apparatus for forming a porous layer on the surface of a semiconductor material wherein an electrolyte is provided and is placed in contact with one or more surfaces of a layer of semiconductor material. The electrolyte is heated and a bias is introduced across said electrolyte and the semiconductor material causing a current to flow between the electrolyte and the semiconductor material. The current forms a porous layer on the one or more surfaces of the semiconductor material in contact with the electrolyte. The semiconductor material with its porous layer can serve as a substrate for a light emitter. A semiconductor emission region can be formed on the substrate. The emission region is capable of emitting light omnidirectionally in response to a bias, with the porous layer enhancing extraction of the emitting region light passing through the substrate.

Polychlorinated biphenyls in coastal tropical ecosystems: Distribution, fate and risk assessment

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

Dodoo, D.K.; Essumang, D.K., E-mail: kofiessumang@yahoo.com; Jonathan, J.W.A.

2012-10-15

Polychlorinated biphenyls (PCBs) though banned still find use in most developing countries including Ghana. PCB congener residues in sediments in the coastal regions of Ghana were determined. Sediment samples (n=80) were collected between June 2008 and March 2009, extracted by the continuous soxhlet extraction using (1:1) hexane-acetone mixture for 24 h and analyzed with a CP 3800 gas chromatogram equipped with {sup 65}Ni electron capture detector (GC-ECD) and a mixed PCBs standard of the ICES 7 as marker, after clean-up. Validation of the efficiency and precision of the extraction and analytical methods were done by extracting samples spiked with 2more » ppm ICES PCB standard and a certified reference material 1941b for marine sediments from NIST, USA, and analyzed alongside the samples. Total PCBs detected in sediments during the dry and wet seasons were, respectively, 127 and 112 {mu}g/kg dry weight (dw), with a mean concentration of 120 {mu}g/kg (dw). The composition of PCB homologues in the sediments were dominated by tri-, penta- and tetra-PCBs. There was no correlation between organic carbon (OC) of the sediments and total PCBs content. Risk assessments conducted on the levels indicated that PCB levels in sediments along the coastal region of Ghana poses no significant health risk to humans.« less

Automated segmentation of middle hepatic vein in non-contrast x-ray CT images based on an atlas-driven approach

NASA Astrophysics Data System (ADS)

Kitagawa, Teruhiko; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki

2008-03-01

In order to support the diagnosis of hepatic diseases, understanding the anatomical structures of hepatic lobes and hepatic vessels is necessary. Although viewing and understanding the hepatic vessels in contrast media-enhanced CT images is easy, the observation of the hepatic vessels in non-contrast X-ray CT images that are widely used for the screening purpose is difficult. We are developing a computer-aided diagnosis (CAD) system to support the liver diagnosis based on non-contrast X-ray CT images. This paper proposes a new approach to segment the middle hepatic vein (MHV), a key structure (landmark) for separating the liver region into left and right lobes. Extraction and classification of hepatic vessels are difficult in non-contrast X-ray CT images because the contrast between hepatic vessels and other liver tissues is low. Our approach uses an atlas-driven method by the following three stages. (1) Construction of liver atlases of left and right hepatic lobes using a learning datasets. (2) Fully-automated enhancement and extraction of hepatic vessels in liver regions. (3) Extraction of MHV based on the results of (1) and (2). The proposed approach was applied to 22 normal liver cases of non-contrast X-ray CT images. The preliminary results show that the proposed approach achieves the success in 14 cases for MHV extraction.

Extracting intrinsic functional networks with feature-based group independent component analysis.

PubMed

Calhoun, Vince D; Allen, Elena

2013-04-01

There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro-connectome, particularly in the context of data fusion.

SA-Mot: a web server for the identification of motifs of interest extracted from protein loops

PubMed Central

Regad, Leslie; Saladin, Adrien; Maupetit, Julien; Geneix, Colette; Camproux, Anne-Claude

2011-01-01

The detection of functional motifs is an important step for the determination of protein functions. We present here a new web server SA-Mot (Structural Alphabet Motif) for the extraction and location of structural motifs of interest from protein loops. Contrary to other methods, SA-Mot does not focus only on functional motifs, but it extracts recurrent and conserved structural motifs involved in structural redundancy of loops. SA-Mot uses the structural word notion to extract all structural motifs from uni-dimensional sequences corresponding to loop structures. Then, SA-Mot provides a description of these structural motifs using statistics computed in the loop data set and in SCOP superfamily, sequence and structural parameters. SA-Mot results correspond to an interactive table listing all structural motifs extracted from a target structure and their associated descriptors. Using this information, the users can easily locate loop regions that are important for the protein folding and function. The SA-Mot web server is available at http://sa-mot.mti.univ-paris-diderot.fr. PMID:21665924

SA-Mot: a web server for the identification of motifs of interest extracted from protein loops.

PubMed

Regad, Leslie; Saladin, Adrien; Maupetit, Julien; Geneix, Colette; Camproux, Anne-Claude

2011-07-01

The detection of functional motifs is an important step for the determination of protein functions. We present here a new web server SA-Mot (Structural Alphabet Motif) for the extraction and location of structural motifs of interest from protein loops. Contrary to other methods, SA-Mot does not focus only on functional motifs, but it extracts recurrent and conserved structural motifs involved in structural redundancy of loops. SA-Mot uses the structural word notion to extract all structural motifs from uni-dimensional sequences corresponding to loop structures. Then, SA-Mot provides a description of these structural motifs using statistics computed in the loop data set and in SCOP superfamily, sequence and structural parameters. SA-Mot results correspond to an interactive table listing all structural motifs extracted from a target structure and their associated descriptors. Using this information, the users can easily locate loop regions that are important for the protein folding and function. The SA-Mot web server is available at http://sa-mot.mti.univ-paris-diderot.fr.

Characterization of Pectins Extracted from Different Varieties of Pink/Red and White Grapefruits [Citrus Paradisi (Macf.)] by Thermal Treatment and Thermosonication.

PubMed

La Cava, Enzo L; Gerbino, Esteban; Sgroppo, Sonia C; Gómez-Zavaglia, Andrea

2018-06-01

The physical and chemical properties of pectin extracts obtained from different white and pink/red varieties of grapefruit [Citrus paradisi (Macf.)], using both conventional heating (CHE) and thermosonication (TS), were investigated. The content of galacturonic acid (GalA), degree of esterification (%DM), color and antioxidant capacity were analyzed. Fourier-Transform Infrared Spectroscopy (FTIR) associated with multivariate analysis enabled a structural comparison among the pectin extracts, and differential scanning calorimetry (DSC) completed a full landscape of the investigated extracts. Pectin extracts obtained by CHE showed mostly higher GalA than those obtained by TS. All the extracts had a high antioxidant capacity, as determined by 2,2 diphenyl 1-picrylhydrazyl (DPPH * ) and 2,2'-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS * +) assays, and a high correlation with the GalA content. The main differences observed in the FTIR spectra occurred in the 1200 to 900 cm -1 region (differences in GalA). The glass transition temperatures (Tgs) of all extracts were above 85 °C, making them interesting as stabilizing agents for the food industry. A wide database for the characterization of pectin extracts from grapefruits was obtained. The relationship between the extraction method and the source of pectins, with the physicochemical and antioxidant properties provided great support for their application in the food industry. © 2018 Institute of Food Technologists®.

A simple and rapid technique for the authentication of the ginseng cultivar, Yunpoong, using an SNP marker in a large sample of ginseng leaves.

PubMed

Sun, Hua; Wang, Hong-Tao; Kwon, Woo-Saeng; Kim, Yeon-Ju; In, Jun-Gyo; Yang, Deok-Chun

2011-11-01

Yunpoong is an important Korean ginseng (Panax ginseng C. A. Meyer) cultivar, but no molecular marker has been available to identify Yunpoong from other cultivars. In this study, we developed a single nucleotide polymorphism (SNP) marker for Yunpoong based on analysis of expressed sequence tags (ESTs) in an exon region of the glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene. This SNP marker had high specificity to authenticate Yunpoong in twelve different main ginseng cultivars. For application of the molecular marker, a rapid identification method was established based on the NaOH-Tris method and real-time polymerase chain reaction (PCR) in order to ensure more efficiency in the cultivar selection. The biggest feature of the NaOH-Tris method was that it made the extraction of DNA very simple and rapid in young leaf tissues. We only spent 1 min to extract DNA and directly used it to do PCR. In this report, the conventional DNA extraction method was used to develop molecular marker process, and the NaOH-Tris method was applied in screening large numbers of cultivars. Moreover, the greatest advantage of the real-time PCR compared with traditional PCR, is time saving and high efficiency. Thus, this strategy provides a rapid and reliable method for the specific identification of Yunpoong in a large number of samples. Copyright © 2011 Elsevier B.V. All rights reserved.

Video rate color region segmentation for mobile robotic applications

NASA Astrophysics Data System (ADS)

de Cabrol, Aymeric; Bonnin, Patrick J.; Hugel, Vincent; Blazevic, Pierre; Chetto, Maryline

2005-08-01

Color Region may be an interesting image feature to extract for visual tasks in robotics, such as navigation and obstacle avoidance. But, whereas numerous methods are used for vision systems embedded on robots, only a few use this segmentation mainly because of the processing duration. In this paper, we propose a new real-time (ie. video rate) color region segmentation followed by a robust color classification and a merging of regions, dedicated to various applications such as RoboCup four-legged league or an industrial conveyor wheeled robot. Performances of this algorithm and confrontation with other methods, in terms of result quality and temporal performances are provided. For better quality results, the obtained speed up is between 2 and 4. For same quality results, the it is up to 10. We present also the outlines of the Dynamic Vision System of the CLEOPATRE Project - for which this segmentation has been developed - and the Clear Box Methodology which allowed us to create the new color region segmentation from the evaluation and the knowledge of other well known segmentations.

Numerical research of a 2D axial symmetry hybrid model for the radio-frequency ion thruster

NASA Astrophysics Data System (ADS)

Chenchen, WU; Xinfeng, SUN; Zuo, GU; Yanhui, JIA

2018-04-01

Since the high efficiency discharge is critical to the radio-frequency ion thruster (RIT), a 2D axial symmetry hybrid model has been developed to study the plasma evolution of RIT. The fluid method and the drift energy correction of the electron energy distribution function (EEDF) are applied to the analysis of the RIT discharge. In the meantime, the PIC-MCC method is used to investigate the ion beam current extraction character for the plasma plume region. The beam current simulation results, with the hybrid model, agree well with the experimental results, and the error is lower than 11%, which shows the validity of the model. The further study shows there is an optimal ratio for the radio-frequency (RF) power and the beam current extraction power under the fixed RIT configuration. And the beam extraction efficiency will decrease when the discharge efficiency beyond a certain threshold (about 87 W). As the input parameters of the hybrid model are all the design values, it can be directly used to the optimum design for other kinds of RITs and radio-frequency ion sources.

Human gait recognition by pyramid of HOG feature on silhouette images

NASA Astrophysics Data System (ADS)

Yang, Guang; Yin, Yafeng; Park, Jeanrok; Man, Hong

2013-03-01

As a uncommon biometric modality, human gait recognition has a great advantage of identify people at a distance without high resolution images. It has attracted much attention in recent years, especially in the fields of computer vision and remote sensing. In this paper, we propose a human gait recognition framework that consists of a reliable background subtraction method followed by the pyramid of Histogram of Gradient (pHOG) feature extraction on the silhouette image, and a Hidden Markov Model (HMM) based classifier. Through background subtraction, the silhouette of human gait in each frame is extracted and normalized from the raw video sequence. After removing the shadow and noise in each region of interest (ROI), pHOG feature is computed on the silhouettes images. Then the pHOG features of each gait class will be used to train a corresponding HMM. In the test stage, pHOG feature will be extracted from each test sequence and used to calculate the posterior probability toward each trained HMM model. Experimental results on the CASIA Gait Dataset B1 demonstrate that with our proposed method can achieve very competitive recognition rate.

Testing of a Composite Wavelet Filter to Enhance Automated Target Recognition in SONAR

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.

2011-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low resolution SONAR and camera videos taken from Unmanned Underwater Vehicles (UUVs). These SONAR images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both SONAR and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this report.

Shadow Areas Robust Matching Among Image Sequence in Planetary Landing

NASA Astrophysics Data System (ADS)

Ruoyan, Wei; Xiaogang, Ruan; Naigong, Yu; Xiaoqing, Zhu; Jia, Lin

2017-01-01

In this paper, an approach for robust matching shadow areas in autonomous visual navigation and planetary landing is proposed. The approach begins with detecting shadow areas, which are extracted by Maximally Stable Extremal Regions (MSER). Then, an affine normalization algorithm is applied to normalize the areas. Thirdly, a descriptor called Multiple Angles-SIFT (MA-SIFT) that coming from SIFT is proposed, the descriptor can extract more features of an area. Finally, for eliminating the influence of outliers, a method of improved RANSAC based on Skinner Operation Condition is proposed to extract inliers. At last, series of experiments are conducted to test the performance of the approach this paper proposed, the results show that the approach can maintain the matching accuracy at a high level even the differences among the images are obvious with no attitude measurements supplied.

Analysis of DDT and its metabolites in soil and water samples obtained in the vicinity of a closed-down factory in Bangladesh using various extraction methods.

PubMed

Al Mahmud, M N U; Khalil, Farzana; Rahman, Md Musfiqur; Mamun, M I R; Shoeb, Mohammad; Abd El-Aty, A M; Park, Jong-Hyouk; Shin, Ho-Chul; Nahar, Nilufar; Shim, Jae-Han

2015-12-01

This study was conducted to monitor the spread of dichlorodiphenyltrichloroethane (DDT) and its metabolites (dichlorodiphenyldichloroethylene (DDE), dichlorodiphenyldichloroethane (DDD)) in soil and water to regions surrounding a closed DDT factory in Bangladesh. This fulfillment was accomplished using inter-method and inter-laboratory validation studies. DDTs (DDT and its metabolites) from soil samples were extracted using microwave-assisted extraction (MAE), supercritical fluid extraction (SFE), and solvent extraction (SE). Inter-laboratory calibration was assessed by SE, and all methods were validated by intra- and inter-day accuracy (expressed as recovery %) and precision (expressed as relative standard deviation (RSD)) in the same laboratory, at three fortified concentrations (n = 4). DDTs extracted from water samples by liquid-liquid partitioning and all samples were analyzed by gas chromatography (GC)-electron capture detector (ECD) and confirmed by GC/mass spectrometry (GC/MS). Linearities expressed as determination coefficients (R (2)) were ≥0.995 for matrix-matched calibrations. The recovery rate was in the range of 72-120 and 83-110%, with <15% RSD in soil and water, respectively. The limit of quantification (LOQ) was 0.0165 mg kg(-1) in soil and 0.132 μg L(-1) in water. Greater quantities of DDTs were extracted from soil using the MAE and SE techniques than with the SFE method. Higher amounts of DDTs were discovered in the southern (2.2-936 × 10(2) mg kg(-1)) or southwestern (86.3-2067 × 10(2) mg kg(-1)) direction from the factory than in the eastern direction (1.0-48.6 × 10(2) mg kg(-1)). An exception was the soil sample collected 50 ft (15.24 m) east (2904 × 10(2) mg kg(-1)) of the factory. The spread of DDTs in the water bodies (0.59-3.01 μg L(-1)) was approximately equal in all directions. We concluded that DDTs might have been dumped randomly around the warehouse after the closing of the factory.

Object Extraction in Cluttered Environments via a P300-Based IFCE

PubMed Central

He, Huidong; Xian, Bin; Zeng, Ming; Zhou, Huihui; Niu, Linwei; Chen, Genshe

2017-01-01

One of the fundamental issues for robot navigation is to extract an object of interest from an image. The biggest challenges for extracting objects of interest are how to use a machine to model the objects in which a human is interested and extract them quickly and reliably under varying illumination conditions. This article develops a novel method for segmenting an object of interest in a cluttered environment by combining a P300-based brain computer interface (BCI) and an improved fuzzy color extractor (IFCE). The induced P300 potential identifies the corresponding region of interest and obtains the target of interest for the IFCE. The classification results not only represent the human mind but also deliver the associated seed pixel and fuzzy parameters to extract the specific objects in which the human is interested. Then, the IFCE is used to extract the corresponding objects. The results show that the IFCE delivers better performance than the BP network or the traditional FCE. The use of a P300-based IFCE provides a reliable solution for assisting a computer in identifying an object of interest within images taken under varying illumination intensities. PMID:28740505

Enzyme inhibitory and radical scavenging effects of some antidiabetic plants of Turkey.

PubMed

Orhan, Nilüfer; Hoçbaç, Sanem; Orhan, Didem Deliorman; Asian, Mustafa; Ergun, Fatma

2014-06-01

Ethnopharmacological field surveys demonstrated that many plants, such as Gentiana olivieri, Helichrysum graveolens, Helichrysum plicatum ssp. plicatum, Juniperus oxycedrus ssp. oxycedrus, Juniperus communis var. saxatilis, Viscum album (ssp. album, ssp. austriacum), are used as traditional medicine for diabetes in different regions of Anatolia. The present study was designed to evaluate the in vitro antidiabetic effects of some selected plants, tested in animal models recently. α-glucosidase and α-amylase enzyme inhibitory effects of the plant extracts were investigated and Acarbose was used as a reference drug. Additionally, radical scavenging capacities were determined using 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) ABTS radical cation scavenging assay and total phenolic content of the extracts were evaluated using Folin Ciocalteu method. H. graveolens ethanol extract exhibited the highest inhibitory activity (55.7 % ± 2.2) on α-amylase enzyme. Additionally, J. oxycedrus hydro-alcoholic leaf extract had potent α-amylase inhibitory effect, while the hydro-alcoholic extract of J. communis fruit showed the highest α-glucosidase inhibitory activity (IC50: 4.4 μg/ml). Results indicated that, antidiabetic effect of hydro-alcoholic extracts of H. graveolens capitulums, J. communis fruit and J. oxycedrus leaf might arise from inhibition of digestive enzymes.

Study on analgesic and anti-inflammatory properties of Cordia myxa fruit hydro-alcoholic extract.

PubMed

Ranjbar, Mohammadmehdi; Varzi, Hossein Najafzadeh; Sabbagh, Atefeh; Bolooki, Adeleh; Sazmand, Alireza

2013-12-15

Cordia myxa is a plant which is used in tropical regions of the world. Analgesic and anti-inflammatory effect of fruit of this medicinal plant was investigated in mice. Hydro-alcoholic extract of it was prepared by maceration method. Formalin test was conducted in six groups of mice (6 animals in each group) and acetic acid test in another six groups (6 mice). Groups one to six in each test were administered normal saline, oral indomethacin, intraperitoneal tramadol, 100 mg kg(-1) oral extract, 200 mg kg(-1) oral extract and 100 mg kg(-1) intraperitoneal extract, respectively. The duration of foot lickings were calculated in formalin- administered (1st) group within min 0 to 5 (acute phase) and 15 to 25 (chronic phase). Acetic acid-induced writhings were counted within 10 min in the 2nd group. The results showed that hydro-alcoholic extract of Cordia myxa fruit was considerably effective in formalin test. Also, analgesic and anti-inflammatory properties of this plant's fruit in both acute and chronic phase are somewhat similar to these properties in the study on animal model of experimental colitis.

Synthesis of streamflow recession curves in dry environments

NASA Astrophysics Data System (ADS)

Arciniega, Saul; Breña-Naranjo, Agustín; Pedrozo-Acuña, Adrían

2015-04-01

The elucidation and predictability of hydrological systems can largely benefit by extracting observed patterns in processes, data and models. Such type of research framework in hydrology, also known as synthesis has gained significant attention over the last decade. For instance, hydrological synthesis implies that the identification of patterns in catchment behavior can enhance the extrapolation of hydrological signatures over large spatial and temporal scales. Hydrological signatures during dry periods such as streamflow recession curves (SRC) are of special interest in regions coping with water scarcity. Indeed, the study of SRCs from observed hydrographs allows to extract information about the storage-discharge relationship of a specific catchment and some of their groundwater hydraulic properties. This work aims at performing a synthesis work of SRCs in semi-arid & arid environments across Northern Mexico. Our dataset consisted in observed daily SRCs in 63 catchments with minima human interferences. Three streamflow recession extraction methods (Vogel, Brutsaert and Aksoy-Wittenberg) along with four recession models (Maillet, Boussinesq, Coutagne y Wittenberg) and three parameter estimation techniques (regressions, lower envelope y data binning) were used to determine the combination among different possible methods, processes and models that better describes SRCs in our study sites. Our results show that the extraction method proposed by Aksoy-Wittenberg along with Coutagne's nonlinear recession model provides a better approximation of SRCs across Northern Mexico, whereas regression was found to be the most adequate parameter estimation method. This study suggests that hydrological synthesis turned out to be an useful framework to identify similar patterns and model parameters during dry periods across Mexico's water-limited environments.

Interference correction by extracting the information of interference dominant regions: Application to near-infrared spectra

NASA Astrophysics Data System (ADS)

Bi, Yiming; Tang, Liang; Shan, Peng; Xie, Qiong; Hu, Yong; Peng, Silong; Tan, Jie; Li, Changwen

2014-08-01

Interference such as baseline drift and light scattering can degrade the model predictability in multivariate analysis of near-infrared (NIR) spectra. Usually interference can be represented by an additive and a multiplicative factor. In order to eliminate these interferences, correction parameters are needed to be estimated from spectra. However, the spectra are often mixed of physical light scattering effects and chemical light absorbance effects, making it difficult for parameter estimation. Herein, a novel algorithm was proposed to find a spectral region automatically that the interesting chemical absorbance and noise are low, that is, finding an interference dominant region (IDR). Based on the definition of IDR, a two-step method was proposed to find the optimal IDR and the corresponding correction parameters estimated from IDR. Finally, the correction was performed to the full spectral range using previously obtained parameters for the calibration set and test set, respectively. The method can be applied to multi target systems with one IDR suitable for all targeted analytes. Tested on two benchmark data sets of near-infrared spectra, the performance of the proposed method provided considerable improvement compared with full spectral estimation methods and comparable with other state-of-art methods.

Protective effect of hexane and ethanol extract of piper longum L. On gentamicin-induced hair cell loss in neonatal cultures.

PubMed

Yadav, Mukesh Kumar; Choi, June; Song, Jae-Jun

2014-03-01

Gentamicin (GM) is a commonly used aminoglycoside antibiotic that generates free oxygen radicals within the inner ear, which can cause vestibulo-cochlear toxicity and permanent damage to the sensory hair cells and neurons. Piper longum L. (PL) is a well-known spice and traditional medicine in Asia and Pacific islands, which has been reported to exhibit a wide spectrum of activity, including antioxidant activity. In this study, we evaluated the effect of hexane:ethanol (2:8) PL extract (subfraction of PL [SPL] extract) on GM-induced hair cell loss in basal, middle and apical regions in a neonatal cochlea cultures. The protective effects of SPL extract were measured by phalloidin staining of cultures from postnatal day 2-3 mice with GM-induced hair cell loss. The anti-apoptosis activity of SPL extract was measured using double labeling by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) and myosin-7a staining. The radical-scavenging activity of SPL extract was assessed using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) assay. SPL extract at a concentration of 1 µg/mL significantly inhibited GM-induced hair cell loss at basal and middle region of cochlea, while 5 µg/mL was effective against apical region hair cell loss. The protective effect of SPL extract was concentration dependent and hair cells retained their stereocilia in explants treated with SPL extract prior to treatment with 0.3 mM GM. SPL extract decreased GM-induced apoptosis of hair cells as assessed by TUNEL staining. The outer hair and inner hair counts were not decreased in SPL extract treated groups in compare to GM treated explants. Additionally, SPL extract showed concentration dependent radical scavenging activity in a DPPH assay. An anti-apoptosis effect and potent radical scavenger activity of SPL extract protects from GM-induced hair cell loss at basal, middle and apical regions in neonatal cochlea cultures.

Microemulsion-based lycopene extraction: Effect of surfactants, co-surfactants and pretreatments.

PubMed

Amiri-Rigi, Atefeh; Abbasi, Soleiman

2016-04-15

Lycopene is a potent antioxidant that has received extensive attention recently. Due to the challenges encountered with current methods of lycopene extraction using hazardous solvents, industry calls for a greener, safer and more efficient process. The main purpose of present study was application of microemulsion technique to extract lycopene from tomato pomace. In this respect, the effect of eight different surfactants, four different co-surfactants, and ultrasound and enzyme pretreatments on lycopene extraction efficiency was examined. Experimental results revealed that application of combined ultrasound and enzyme pretreatments, saponin as a natural surfactant, and glycerol as a co-surfactant, in the bicontinuous region of microemulsion was the optimal experimental conditions resulting in a microemulsion containing 409.68±0.68 μg/glycopene. The high lycopene concentration achieved, indicates that microemulsion technique, using a low-cost natural surfactant could be promising for a simple and safe separation of lycopene from tomato pomace and possibly from tomato industrial wastes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Short Haul Civil Tiltrotor Contingency Power System Preliminary Design

NASA Technical Reports Server (NTRS)

Eames, David J. H.

2006-01-01

Single Langmuir probe measurements are presented over a two-dimensional array of locations in the near Discharge Cathode Assembly (DCA) region of a 30-cm diameter ring cusp ion thruster over a range of thruster operating conditions encompassing the high-power half of the NASA throttling table. The Langmuir probe data were analyzed with two separate methods. All data were analyzed initially assuming an electron population consisting of Maxwellian electrons only. The on-axis data were then analyzed assuming both Maxwellian and primary electrons. Discharge plasma data taken with beam extraction exhibit a broadening of the higher electron temperature plume boundary compared to similar discharge conditions without beam extraction. The opposite effect is evident with the electron/ion number density as the data without began, extraction appears to be more collimated than the corresponding data with beam extraction. Primary electron energy and number densities are presented for one operating condition giving an order of magnitude of their value and the error associated with this calculation.

Discharge Chamber Plasma Structure of a 30-cm NSTAR-Type Ion Engine

NASA Technical Reports Server (NTRS)

Herman, Daniel A.; Gallimore, Alec D.

2006-01-01

Single Langmuir probe measurements are presented over a two-dimensional array of locations in the near Discharge Cathode Assembly (DCA) region of a 30-cm diameter ring cusp ion thruster over a range of thruster operating conditions encompassing the high-power half of the NASA throttling table. The Langmuir probe data were analyzed with two separate methods. All data were analyzed initially assuming an electron population consisting of Maxwellian electrons only. The on-axis data were then analyzed assuming both Maxwellian and primary electrons. Discharge plasma data taken with beam extraction exhibit a broadening of the higher electron temperature plume boundary compared to similar discharge conditions without beam extraction. The opposite effect is evident with the electron/ion number density as the data without began, extraction appears to be more collimated than the corresponding data with beam extraction. Primary electron energy and number densities are presented for one operating condition giving an order of magnitude of their value and the error associated with this calculation.

Sensitive analytical method for simultaneous analysis of some vasoconstrictors with highly overlapped analytical signals

NASA Astrophysics Data System (ADS)

Nikolić, G. S.; Žerajić, S.; Cakić, M.

2011-10-01

Multivariate calibration method is a powerful mathematical tool that can be applied in analytical chemistry when the analytical signals are highly overlapped. The method with regression by partial least squares is proposed for the simultaneous spectrophotometric determination of adrenergic vasoconstrictors in decongestive solution containing two active components: phenyleprine hydrochloride and trimazoline hydrochloride. These sympathomimetic agents are that frequently associated in pharmaceutical formulations against the common cold. The proposed method, which is, simple and rapid, offers the advantages of sensitivity and wide range of determinations without the need for extraction of the vasoconstrictors. In order to minimize the optimal factors necessary to obtain the calibration matrix by multivariate calibration, different parameters were evaluated. The adequate selection of the spectral regions proved to be important on the number of factors. In order to simultaneously quantify both hydrochlorides among excipients, the spectral region between 250 and 290 nm was selected. A recovery for the vasoconstrictor was 98-101%. The developed method was applied to assay of two decongestive pharmaceutical preparations.

A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval

NASA Astrophysics Data System (ADS)

You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-01-01

Pointers (arrows and symbols) are frequently used in biomedical images to highlight specific image regions of interest (ROIs) that are mentioned in figure captions and/or text discussion. Detection of pointers is the first step toward extracting relevant visual features from ROIs and combining them with textual descriptions for a multimodal (text and image) biomedical article retrieval system. Recently we developed a pointer recognition algorithm based on an edge-based pointer segmentation method, and subsequently reported improvements made on our initial approach involving the use of Active Shape Models (ASM) for pointer recognition and region growing-based method for pointer segmentation. These methods contributed to improving the recall of pointer recognition but not much to the precision. The method discussed in this article is our recent effort to improve the precision rate. Evaluation performed on two datasets and compared with other pointer segmentation methods show significantly improved precision and the highest F1 score.

Effective gene prediction by high resolution frequency estimator based on least-norm solution technique

PubMed Central

2014-01-01

Linear algebraic concept of subspace plays a significant role in the recent techniques of spectrum estimation. In this article, the authors have utilized the noise subspace concept for finding hidden periodicities in DNA sequence. With the vast growth of genomic sequences, the demand to identify accurately the protein-coding regions in DNA is increasingly rising. Several techniques of DNA feature extraction which involves various cross fields have come up in the recent past, among which application of digital signal processing tools is of prime importance. It is known that coding segments have a 3-base periodicity, while non-coding regions do not have this unique feature. One of the most important spectrum analysis techniques based on the concept of subspace is the least-norm method. The least-norm estimator developed in this paper shows sharp period-3 peaks in coding regions completely eliminating background noise. Comparison of proposed method with existing sliding discrete Fourier transform (SDFT) method popularly known as modified periodogram method has been drawn on several genes from various organisms and the results show that the proposed method has better as well as an effective approach towards gene prediction. Resolution, quality factor, sensitivity, specificity, miss rate, and wrong rate are used to establish superiority of least-norm gene prediction method over existing method. PMID:24386895

Antioxidant activity and phytochemical constituent of two plants used to manage foot and mouth disease in the Far North Region of Cameroon

PubMed Central

Vougat, Ronald Romuald Bebey Ngom; Foyet, Harquin Simplice; Ziebe, Roland; Garabed, Rebecca B.

2015-01-01

Aim: Plants used in the Far North Region of Cameroon by livestock farmers to manage foot and mouth disease (FMD) in cattle and the phytochemical composition and antioxidant potentials of two of them (Boscia senegalensis [BS] and Tapinanthus dodoneifolius [TD]) were investigated in this study. Materials and Methods: Ethno veterinary data were collected from 325 livestock farmers using semi-structured interviews from September 2011 to April 2012. The 2,2-diphenyl-picrylhydrazyl radical scavenging activity and total phenolic content (TPC) were first performed with five different solvents to choose the best extract of each plant based on these two factors. To achieve our aim, the ferric iron reducing activity, hydroxyl radical scavenging activity (HRSA), free radical scavenging activity (FRSA), vitamin E and iron content were analyzed on extracts selected using current techniques. Results: The results showed that 12 plants of 8 different families are regularly used by farmers to manage FMD. It also demonstrated that acetone extract of TD and methanolic extract of BS are the extracts which showed the best total antioxidant activity (AA) and the best TPC. In general, TD show the best AA during the HRSA and FRSA analysis compared with BS. Similarly, TD content more phenolic compounds and tannins than BS. Both plants contain proteins, saponins, tannins, phenols, alkaloid, and polyphenols which are known to have many biological activities. Conclusion: These results support the AA of both plants and can justify their use by herders to treat FMD which is often followed by many secondary diseases. PMID:26401383

Validation of ethnopharmacology of ayurvedic sarasvata ghrita and comparative evaluation of its neuroprotective effect with modern alcoholic and lipid based extracts in β-amyloid induced memory impairment.

PubMed

Shelar, Madhuri; Nanaware, Sadhana; Arulmozhi, S; Lohidasan, Sathiyanarayanan; Mahadik, Kakasaheb

2018-06-12

Sarasvata ghrita (SG), a polyherbal formulation from ayurveda, an ancient medicinal system of India, has been used to improve intelligence and memory, treat speech delay, speaking difficulties and low digestion power in children. Study aimed to validate the ethno use of SG in memory enhancement through systematic scientific protocol. The effect of SG and modern extracts of ingredients of SG was compared on cognitive function and neuroprotection in amyloid-β peptide 25-35(Aβ25-35) induced memory impairment in wistar rats. Further the underlying mechanism for neuroprotective activity was investigated. SG was prepared as per traditional method, ethanolic extract (EE) was prepared by conventional method and lipid based extract was prepared by modern extraction method. All extracts were standardised by newly developed HPLC method with respect to marker compounds. SG, EE and LE were administered orally to male Wistar rats at doses of 100,200 and 400 mg/kg Body Weight by feeding needle for a period of 21 days after the intracerebroventricular administration of Aβ25-35 bilaterally. Spatial memory of rats was tested using Morris water maze (MWM) and Radial arm maze (RAM) test. The possible underlying mechanisms for the cognitive improvement exhibited by SG, EE and LE was investigated through ex-vivo brain antioxidant effect, monoamine level estimation, acetylcholine esterase (AchE) inhibitory effect and Brain-derived neurotropic factor (BDNF) levels estimation. SG, EE and LE were analyzed by HPLC method, results showed that EE extract has high percent of selected phytoconstituents as compared with SG and LE. SG and LE decrease escape latency and searching distance in a dose dependant manner during MWM test. In case of RAM significant decrease in number of errors and increase in number of correct choices indicate an elevation in retention and recall aspects of learning and memory after administration of SG an LE. SG and LE extract can efficiently prevent accumulation of β-amyloid plaque in hippocampus region. There was increase in SOD, GSH, CAT and NO level and decrease in MDA levels in SG and LE administered animals. SG and LE have found to exhibit AchE inhibitiory activity and significant dose-dependant increase in BDNF level in the plasma. SG and LE significantly increased the levels of noradrenaline, dopamine and 5-hydroxytryptamine in the brain. The study validated the neuroprotective activity of SG. The study concludes the extraction efficiency of SG for selected phytoconstituents is less than modern methods. However the neuroprotective activity of SG and LE was found to be greater than EE. Copyright © 2018. Published by Elsevier B.V.