Clinicopathologic and gene expression parameters predict liver cancer prognosis

International Nuclear Information System (INIS)

Hao, Ke; Zhong, Hua; Greenawalt, Danielle; Ferguson, Mark D; Ng, Irene O; Sham, Pak C; Poon, Ronnie T; Molony, Cliona; Schadt, Eric E; Dai, Hongyue; Luk, John M; Lamb, John; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Chudin, Eugene; Lee, Nikki P; Mao, Mao

2011-01-01

The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome

An algorithm to discover gene signatures with predictive potential

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Hallett Robin M

2010-09-01

Full Text Available Abstract Background The advent of global gene expression profiling has generated unprecedented insight into our molecular understanding of cancer, including breast cancer. For example, human breast cancer patients display significant diversity in terms of their survival, recurrence, metastasis as well as response to treatment. These patient outcomes can be predicted by the transcriptional programs of their individual breast tumors. Predictive gene signatures allow us to correctly classify human breast tumors into various risk groups as well as to more accurately target therapy to ensure more durable cancer treatment. Results Here we present a novel algorithm to generate gene signatures with predictive potential. The method first classifies the expression intensity for each gene as determined by global gene expression profiling as low, average or high. The matrix containing the classified data for each gene is then used to score the expression of each gene based its individual ability to predict the patient characteristic of interest. Finally, all examined genes are ranked based on their predictive ability and the most highly ranked genes are included in the master gene signature, which is then ready for use as a predictor. This method was used to accurately predict the survival outcomes in a cohort of human breast cancer patients. Conclusions We confirmed the capacity of our algorithm to generate gene signatures with bona fide predictive ability. The simplicity of our algorithm will enable biological researchers to quickly generate valuable gene signatures without specialized software or extensive bioinformatics training.

Predictability of Genetic Interactions from Functional Gene Modules

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Jonathan H. Young

2017-02-01

Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

Study of the Subjective Visibility of Packet Loss Artifacts in Decoded Video Sequences

DEFF Research Database (Denmark)

Korhonen, Jari

2018-01-01

Packet loss is a significant cause of visual impairments in video broadcasting over packet-switched networks. There are several subjective and objective video quality assessment methods focused on the overall perception of video quality. However, less attention has been paid on the visibility...... of packet loss artifacts appearing in spatially and temporally limited regions of a video sequence. In this paper, we present the results of a subjective study, using a methodology where a video sequence is displayed on a touchscreen and the users tap it in the positions where they observe artifacts. We...... also analyze the objective features derived from those artifacts, and propose different models for combining those features into an objective metric for assessing the noticeability of the artifacts. The practical results show that the proposed metric predicts visibility of packet loss impairments...

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

Science.gov (United States)

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

MADR: metal artifact detection and reduction

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Jaiswal, Sunil Prasad; Ha, Sungsoo; Mueller, Klaus

2016-04-01

Metal in CT-imaged objects drastically reduces the quality of these images due to the severe artifacts it can cause. Most metal artifacts reduction (MAR) algorithms consider the metal-affected sinogram portions as the corrupted data and replace them via sophisticated interpolation methods. While these schemes are successful in removing the metal artifacts, they fail to recover some of the edge information. To address these problems, the frequency shift metal artifact reduction algorithm (FSMAR) was recently proposed. It exploits the information hidden in the uncorrected image and combines the high frequency (edge) components of the uncorrected image with the low frequency components of the corrected image. Although this can effectively transfer the edge information of the uncorrected image, it also introduces some unwanted artifacts. The essential problem of these algorithms is that they lack the capability of detecting the artifacts and as a result cannot discriminate between desired and undesired edges. We propose a scheme that does better in these respects. Our Metal Artifact Detection and Reduction (MADR) scheme constructs a weight map which stores whether a pixel in the uncorrected image belongs to an artifact region or a non-artifact region. This weight matrix is optimal in the Linear Minimum Mean Square Sense (LMMSE). Our results demonstrate that MADR outperforms the existing algorithms and ensures that the anatomical structures close to metal implants are better preserved.

A comparative analysis of soft computing techniques for gene prediction.

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Goel, Neelam; Singh, Shailendra; Aseri, Trilok Chand

2013-07-01

The rapid growth of genomic sequence data for both human and nonhuman species has made analyzing these sequences, especially predicting genes in them, very important and is currently the focus of many research efforts. Beside its scientific interest in the molecular biology and genomics community, gene prediction is of considerable importance in human health and medicine. A variety of gene prediction techniques have been developed for eukaryotes over the past few years. This article reviews and analyzes the application of certain soft computing techniques in gene prediction. First, the problem of gene prediction and its challenges are described. These are followed by different soft computing techniques along with their application to gene prediction. In addition, a comparative analysis of different soft computing techniques for gene prediction is given. Finally some limitations of the current research activities and future research directions are provided. Copyright © 2013 Elsevier Inc. All rights reserved.

Artifacts in magnetic resonance imaging of the head

Energy Technology Data Exchange (ETDEWEB)

Iwama, Toru; Andoh, Takashi; Sakai, Noboru; Yamada, Hiromu [Gifu Univ. (Japan). Faculty of Medicine; Funakoshi, Takashi; Akiyama, Shigeru; Yoshida, Kakuro

1989-08-01

The results of 505 magnetic resonance (MR) imaging examinations of the head disclosed several different types of artifact. Various artifacts observed with two-dimentional Fourier transformation are described and illustrated. All images were obtained with a 0.5 Tesla superconducting MR imager. About 70% of all images contained artifacts. Phase encoding artifacts due to motion or flow were most frequently observed. Center, 'zipper,' truncation, radiofrequency, and ferromagnetic artifacts and contrast error on inversion recovery (IR) images were noted less frequently. Phase encoding artifacts and contrast errors on IR images totally degraded the images, and 'zipper' artifacts were regional. Center artifacts resembled small infarctions, and ferromagnetic artifacts sometimes mimicked hematmas. It is important to recognize these artifacts and to devise methods to avoid their influence on the region of interest. (author).

Use of cognitive artifacts in chemistry learning

Science.gov (United States)

Yengin, Ilker

In everyday life, we interact with cognitive artifacts to receive and/or manipulate information so as to alter our thinking processes. CHEM/TEAC 869Q is a distance course that includes extensive explicit instruction in the use of a cognitive artifact. This study investigates issues related to the design of that online artifact. In order to understand design implications and how cognitive artifacts contribute to students' thinking and learning, a qualitative research methodology was engaged that utilized think aloud sessions. Participants' described constrained and structured cognitive models while using the artifact. The study also was informed by interviews and researcher's field notes. A purposeful sampling method led to the selection of participants, four males and two females, who had no prior history of using a course from the 869 series but who had experienced the scientific content covered by the CHEM869Q course. Analysis of the results showed both that a cognitive artifact may lead users' minds in decision making, and that problem solving processes were affected by cognitive artifact's design. When there is no design flaw, users generally thought that the cognitive artifact was helpful by simplifying steps, overcoming other limitations, and reducing errors in a reliable, effective, and easy to use way. Moreover, results showed that successful implementation of cognitive artifacts into teaching --learning practices depended on user willingness to transfer a task to the artifact. While users may like the idea of benefiting from a cognitive artifact, nevertheless, they may tend to limit their usage. They sometimes think that delegating a task to a cognitive artifact makes them dependent, and that they may not learn how to perform the tasks by themselves. They appear more willing to use a cognitive artifact after they have done the task by themselves.

Iterative Covariance-Based Removal of Time-Synchronous Artifacts: Application to Gastrointestinal Electrical Recordings.

Science.gov (United States)

Erickson, Jonathan C; Putney, Joy; Hilbert, Douglas; Paskaranandavadivel, Niranchan; Cheng, Leo K; O'Grady, Greg; Angeli, Timothy R

2016-11-01

The aim of this study was to develop, validate, and apply a fully automated method for reducing large temporally synchronous artifacts present in electrical recordings made from the gastrointestinal (GI) serosa, which are problematic for properly assessing slow wave dynamics. Such artifacts routinely arise in experimental and clinical settings from motion, switching behavior of medical instruments, or electrode array manipulation. A novel iterative Covariance-Based Reduction of Artifacts (COBRA) algorithm sequentially reduced artifact waveforms using an updating across-channel median as a noise template, scaled and subtracted from each channel based on their covariance. Application of COBRA substantially increased the signal-to-artifact ratio (12.8 ± 2.5 dB), while minimally attenuating the energy of the underlying source signal by 7.9% on average ( -11.1 ± 3.9 dB). COBRA was shown to be highly effective for aiding recovery and accurate marking of slow wave events (sensitivity = 0.90 ± 0.04; positive-predictive value = 0.74 ± 0.08) from large segments of in vivo porcine GI electrical mapping data that would otherwise be lost due to a broad range of contaminating artifact waveforms. Strongly reducing artifacts with COBRA ultimately allowed for rapid production of accurate isochronal activation maps detailing the dynamics of slow wave propagation in the porcine intestine. Such mapping studies can help characterize differences between normal and dysrhythmic events, which have been associated with GI abnormalities, such as intestinal ischemia and gastroparesis. The COBRA method may be generally applicable for removing temporally synchronous artifacts in other biosignal processing domains.

Small Artifacts - Big Technologies

DEFF Research Database (Denmark)

Kreiner, Kristian

2005-01-01

The computer IC is the heart of the information and telecommunication technology. It is a tiny artifact, but with incredible organizing powers. We use this physical artifact as the location for studying central problems of the knowledge economy. First, the paper describes the history of chip design...

An extension to artifact-free projection overlaps

International Nuclear Information System (INIS)

Lin, Jianyu

2015-01-01

Purpose: In multipinhole single photon emission computed tomography, the overlapping of projections has been used to increase sensitivity. Avoiding artifacts in the reconstructed image associated with projection overlaps (multiplexing) is a critical issue. In our previous report, two types of artifact-free projection overlaps, i.e., projection overlaps that do not lead to artifacts in the reconstructed image, were formally defined and proved, and were validated via simulations. In this work, a new proposition is introduced to extend the previously defined type-II artifact-free projection overlaps so that a broader range of artifact-free overlaps is accommodated. One practical purpose of the new extension is to design a baffle window multipinhole system with artifact-free projection overlaps. Methods: First, the extended type-II artifact-free overlap was theoretically defined and proved. The new proposition accommodates the situation where the extended type-II artifact-free projection overlaps can be produced with incorrectly reconstructed portions in the reconstructed image. Next, to validate the theory, the extended-type-II artifact-free overlaps were employed in designing the multiplexing multipinhole spiral orbit imaging systems with a baffle window. Numerical validations were performed via simulations, where the corresponding 1-pinhole nonmultiplexing reconstruction results were used as the benchmark for artifact-free reconstructions. The mean square error (MSE) was the metric used for comparisons of noise-free reconstructed images. Noisy reconstructions were also performed as part of the validations. Results: Simulation results show that for noise-free reconstructions, the MSEs of the reconstructed images of the artifact-free multiplexing systems are very similar to those of the corresponding 1-pinhole systems. No artifacts were observed in the reconstructed images. Therefore, the testing results for artifact-free multiplexing systems designed using the

Exploring the Optimal Strategy to Predict Essential Genes in Microbes

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Yao Lu

2011-12-01

Full Text Available Accurately predicting essential genes is important in many aspects of biology, medicine and bioengineering. In previous research, we have developed a machine learning based integrative algorithm to predict essential genes in bacterial species. This algorithm lends itself to two approaches for predicting essential genes: learning the traits from known essential genes in the target organism, or transferring essential gene annotations from a closely related model organism. However, for an understudied microbe, each approach has its potential limitations. The first is constricted by the often small number of known essential genes. The second is limited by the availability of model organisms and by evolutionary distance. In this study, we aim to determine the optimal strategy for predicting essential genes by examining four microbes with well-characterized essential genes. Our results suggest that, unless the known essential genes are few, learning from the known essential genes in the target organism usually outperforms transferring essential gene annotations from a related model organism. In fact, the required number of known essential genes is surprisingly small to make accurate predictions. In prokaryotes, when the number of known essential genes is greater than 2% of total genes, this approach already comes close to its optimal performance. In eukaryotes, achieving the same best performance requires over 4% of total genes, reflecting the increased complexity of eukaryotic organisms. Combining the two approaches resulted in an increased performance when the known essential genes are few. Our investigation thus provides key information on accurately predicting essential genes and will greatly facilitate annotations of microbial genomes.

Gene-specific function prediction for non-synonymous mutations in monogenic diabetes genes.

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Quan Li

Full Text Available The rapid progress of genomic technologies has been providing new opportunities to address the need of maturity-onset diabetes of the young (MODY molecular diagnosis. However, whether a new mutation causes MODY can be questionable. A number of in silico methods have been developed to predict functional effects of rare human mutations. The purpose of this study is to compare the performance of different bioinformatics methods in the functional prediction of nonsynonymous mutations in each MODY gene, and provides reference matrices to assist the molecular diagnosis of MODY. Our study showed that the prediction scores by different methods of the diabetes mutations were highly correlated, but were more complimentary than replacement to each other. The available in silico methods for the prediction of diabetes mutations had varied performances across different genes. Applying gene-specific thresholds defined by this study may be able to increase the performance of in silico prediction of disease-causing mutations.

Conceptual Model of Artifacts for Design Science Research

DEFF Research Database (Denmark)

Bækgaard, Lars

2015-01-01

We present a conceptual model of design science research artifacts. The model views an artifact at three levels. At the artifact level a selected artifact is viewed as a combination of material and immaterial aspects and a set of representations hereof. At the design level the selected artifact...

Investigating media artifacts with children

DEFF Research Database (Denmark)

Chimirri, Niklas Alexander

The dissertation’s aim is to explore the everyday relevance media artifacts have for young children. It discusses and further develops analytical concepts that are committed to taking the children’s perspectives on possibilities and limitations of such artifacts seriously. These conceptual...... developments are rooted in the author’s participation in a daycare practice in Berlin, Germany. The daycare’s situational approach precisely attempted to draw on the children’s everyday life experiences so as to engage in problem-oriented learning projects, on media artifacts and beyond....

Combining Gene Signatures Improves Prediction of Breast Cancer Survival

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Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

2011-01-01

Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

Combining gene signatures improves prediction of breast cancer survival.

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Xi Zhao

Full Text Available BACKGROUND: Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123 and test set (n = 81, respectively. Gene sets from eleven previously published gene signatures are included in the study. PRINCIPAL FINDINGS: To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014. Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001. The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. CONCLUSION: Combining the predictive strength of multiple gene signatures improves

Racial IQ Differences among Transracial Adoptees: Fact or Artifact?

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Drew Thomas

2016-12-01

Full Text Available Some academic publications infer from studies of transracial adoptees’ IQs that East Asian adoptees raised in the West by Whites have higher IQs than Western Whites, and that White adoptees raised by Whites have higher IQs than Black adoptees raised by Whites. Those publications suggest that this is because genetic differences give East Asians a higher mean IQ than Whites, and Whites a higher mean IQ than Blacks. This paper proposes a parsimonious alternative explanation: the apparent IQ advantage of East Asian adoptees is an artifact caused by ignoring the Flynn effect and adoption’s beneficial effect on IQ, and most of the IQ disadvantage of Black adoptees disappears when one allows for attrition in the Minnesota Transracial Adoption Study, and acknowledges the results of other studies. Diagnosing these artifacts suggests a nil hypothesis: East Asian, White, and Black adoptees raised in the same environment would have similar IQs, hinting at a minimal role for genes in racial IQ differences.

Neural Inductive Matrix Completion for Predicting Disease-Gene Associations

KAUST Repository

Hou, Siqing

2018-05-21

In silico prioritization of undiscovered associations can help find causal genes of newly discovered diseases. Some existing methods are based on known associations, and side information of diseases and genes. We exploit the possibility of using a neural network model, Neural inductive matrix completion (NIMC), in disease-gene prediction. Comparing to the state-of-the-art inductive matrix completion method, using neural networks allows us to learn latent features from non-linear functions of input features. Previous methods use disease features only from mining text. Comparing to text mining, disease ontology is a more informative way of discovering correlation of dis- eases, from which we can calculate the similarities between diseases and help increase the performance of predicting disease-gene associations. We compare the proposed method with other state-of-the-art methods for pre- dicting associated genes for diseases from the Online Mendelian Inheritance in Man (OMIM) database. Results show that both new features and the proposed NIMC model can improve the chance of recovering an unknown associated gene in the top 100 predicted genes. Best results are obtained by using both the new features and the new model. Results also show the proposed method does better in predicting associated genes for newly discovered diseases.

Archaic artifacts resembling celestial spheres

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Dimitrakoudis, S.; Papaspyrou, P.; Petoussis, V.; Moussas, X.

We present several bronze artifacts from the Archaic Age in Greece (750-480 BC) that resemble celestial spheres or forms of other astronomical significance. They are studied in the context of the Dark Age transition from Mycenaean Age astronomical themes to the philosophical and practical revival of astronomy in the Classical Age with its plethora of astronomical devices. These artifacts, mostly votive in nature are spherical in shape and appear in a variety of forms their most striking characteristic being the depiction of meridians and/or an equator. Most of those artifacts come from Thessaly, and more specifically from the temple of Itonia Athena at Philia, a religious center of pan-Hellenic significance. Celestial spheres, similar in form to the small artifacts presented in this study, could be used to measure latitudes, or estimate the time at a known place, and were thus very useful in navigation.

Improving consensus structure by eliminating averaging artifacts

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KC Dukka B

2009-03-01

Full Text Available Abstract Background Common structural biology methods (i.e., NMR and molecular dynamics often produce ensembles of molecular structures. Consequently, averaging of 3D coordinates of molecular structures (proteins and RNA is a frequent approach to obtain a consensus structure that is representative of the ensemble. However, when the structures are averaged, artifacts can result in unrealistic local geometries, including unphysical bond lengths and angles. Results Herein, we describe a method to derive representative structures while limiting the number of artifacts. Our approach is based on a Monte Carlo simulation technique that drives a starting structure (an extended or a 'close-by' structure towards the 'averaged structure' using a harmonic pseudo energy function. To assess the performance of the algorithm, we applied our approach to Cα models of 1364 proteins generated by the TASSER structure prediction algorithm. The average RMSD of the refined model from the native structure for the set becomes worse by a mere 0.08 Å compared to the average RMSD of the averaged structures from the native structure (3.28 Å for refined structures and 3.36 A for the averaged structures. However, the percentage of atoms involved in clashes is greatly reduced (from 63% to 1%; in fact, the majority of the refined proteins had zero clashes. Moreover, a small number (38 of refined structures resulted in lower RMSD to the native protein versus the averaged structure. Finally, compared to PULCHRA 1, our approach produces representative structure of similar RMSD quality, but with much fewer clashes. Conclusion The benchmarking results demonstrate that our approach for removing averaging artifacts can be very beneficial for the structural biology community. Furthermore, the same approach can be applied to almost any problem where averaging of 3D coordinates is performed. Namely, structure averaging is also commonly performed in RNA secondary prediction 2, which

MRI-Based Computed Tomography Metal Artifact Correction Method for Improving Proton Range Calculation Accuracy

International Nuclear Information System (INIS)

Park, Peter C.; Schreibmann, Eduard; Roper, Justin; Elder, Eric; Crocker, Ian; Fox, Tim; Zhu, X. Ronald; Dong, Lei; Dhabaan, Anees

2015-01-01

Purpose: Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. Methods and Materials: The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR. Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. Results: The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. Conclusions: Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts

Artifacts as Authoritative Actors in Educational Reform

Science.gov (United States)

März, Virginie; Kelchtermans, Geert; Vermeir, Karen

2017-01-01

Educational reforms are often translated in and implemented through artifacts. Although research has frequently treated artifacts as merely functional, more recent work acknowledges the complex relationship between material artifacts and human/organizational behavior. This article aims at disentangling this relationship in order to deepen our…

Embryo quality predictive models based on cumulus cells gene expression

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Devjak R

2016-06-01

Full Text Available Since the introduction of in vitro fertilization (IVF in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

Reranking candidate gene models with cross-species comparison for improved gene prediction

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Pereira Fernando CN

2008-10-01

Full Text Available Abstract Background Most gene finders score candidate gene models with state-based methods, typically HMMs, by combining local properties (coding potential, splice donor and acceptor patterns, etc. Competing models with similar state-based scores may be distinguishable with additional information. In particular, functional and comparative genomics datasets may help to select among competing models of comparable probability by exploiting features likely to be associated with the correct gene models, such as conserved exon/intron structure or protein sequence features. Results We have investigated the utility of a simple post-processing step for selecting among a set of alternative gene models, using global scoring rules to rerank competing models for more accurate prediction. For each gene locus, we first generate the K best candidate gene models using the gene finder Evigan, and then rerank these models using comparisons with putative orthologous genes from closely-related species. Candidate gene models with lower scores in the original gene finder may be selected if they exhibit strong similarity to probable orthologs in coding sequence, splice site location, or signal peptide occurrence. Experiments on Drosophila melanogaster demonstrate that reranking based on cross-species comparison outperforms the best gene models identified by Evigan alone, and also outperforms the comparative gene finders GeneWise and Augustus+. Conclusion Reranking gene models with cross-species comparison improves gene prediction accuracy. This straightforward method can be readily adapted to incorporate additional lines of evidence, as it requires only a ranked source of candidate gene models.

On Lifecycle Constraints of Artifact-Centric Workflows

Science.gov (United States)

Kucukoguz, Esra; Su, Jianwen

Data plays a fundamental role in modeling and management of business processes and workflows. Among the recent "data-aware" workflow models, artifact-centric models are particularly interesting. (Business) artifacts are the key data entities that are used in workflows and can reflect both the business logic and the execution states of a running workflow. The notion of artifacts succinctly captures the fluidity aspect of data during workflow executions. However, much of the technical dimension concerning artifacts in workflows is not well understood. In this paper, we study a key concept of an artifact "lifecycle". In particular, we allow declarative specifications/constraints of artifact lifecycle in the spirit of DecSerFlow, and formulate the notion of lifecycle as the set of all possible paths an artifact can navigate through. We investigate two technical problems: (Compliance) does a given workflow (schema) contain only lifecycle allowed by a constraint? And (automated construction) from a given lifecycle specification (constraint), is it possible to construct a "compliant" workflow? The study is based on a new formal variant of artifact-centric workflow model called "ArtiNets" and two classes of lifecycle constraints named "regular" and "counting" constraints. We present a range of technical results concerning compliance and automated construction, including: (1) compliance is decidable when workflow is atomic or constraints are regular, (2) for each constraint, we can always construct a workflow that satisfies the constraint, and (3) sufficient conditions where atomic workflows can be constructed.

A genome-wide gene function prediction resource for Drosophila melanogaster.

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Han Yan

2010-08-01

Full Text Available Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations.

Metallic artifacts in magnetic resonance imaging

International Nuclear Information System (INIS)

Abe, Eiji; Okuyama, Koichiro; Ishikawa, Noriyuki; Hongo, Michio; Sato, Kozo; Sashi, Ryuji; Ishikawa, Eijiro.

1995-01-01

Seven metallic implants with different content of magnetic materials were compared in terms of the degree of MRI artifact. The degree of artifact well correlated with the total content of iron and cobalt than the total content of ferromagnets (iron, cobalt, nickel). No significant difference was observed regarding artifact among 4 titanium alloys containing very small amount of ferromagnet (0.058%-2.5%). Pedicle screws were made from different alloys in the same shape. Those screws were inserted into the swine vertebrae and artifact was evaluated by MRI. The degree of artifact was SUS316 (stainless steel)>MP-35N (cobalt alloy)>Ti-6AI-4V (titanium alloy), 1.5 Tesla>0.5 Tesla as for magnetic intensity, and T2 (gradient echo)>T2 (long SE)>proton density>T1 as for exposure condition. The condition of the site screw was inserted in the vertebral canal was detectable by T1-weighted images of titanium alloy and cobalt alloy in 0.5 Tesla and T1-weighted images of titanium alloy in 1.5 Tesla. (S.Y)

Inductive matrix completion for predicting gene-disease associations.

Science.gov (United States)

Natarajan, Nagarajan; Dhillon, Inderjit S

2014-06-15

Most existing methods for predicting causal disease genes rely on specific type of evidence, and are therefore limited in terms of applicability. More often than not, the type of evidence available for diseases varies-for example, we may know linked genes, keywords associated with the disease obtained by mining text, or co-occurrence of disease symptoms in patients. Similarly, the type of evidence available for genes varies-for example, specific microarray probes convey information only for certain sets of genes. In this article, we apply a novel matrix-completion method called Inductive Matrix Completion to the problem of predicting gene-disease associations; it combines multiple types of evidence (features) for diseases and genes to learn latent factors that explain the observed gene-disease associations. We construct features from different biological sources such as microarray expression data and disease-related textual data. A crucial advantage of the method is that it is inductive; it can be applied to diseases not seen at training time, unlike traditional matrix-completion approaches and network-based inference methods that are transductive. Comparison with state-of-the-art methods on diseases from the Online Mendelian Inheritance in Man (OMIM) database shows that the proposed approach is substantially better-it has close to one-in-four chance of recovering a true association in the top 100 predictions, compared to the recently proposed Catapult method (second best) that has bigdata.ices.utexas.edu/project/gene-disease. © The Author 2014. Published by Oxford University Press.

Coulomb artifacts and bottomonium hyperfine splitting in lattice NRQCD

Energy Technology Data Exchange (ETDEWEB)

Liu, T. [Department of Physics, University of Alberta,11455 Saskatchewan Drive, Edmonton, Alberta T6G 2J1 (Canada); Penin, A.A. [Department of Physics, University of Alberta,11455 Saskatchewan Drive, Edmonton, Alberta T6G 2J1 (Canada); Institut für Theoretische Teilchenphysik, Karlsruhe Institute of Technology,Wolfgang-Gaede-Strasse 1, 76128 Karlsruhe (Germany); Rayyan, A. [Department of Physics, University of Alberta,11455 Saskatchewan Drive, Edmonton, Alberta T6G 2J1 (Canada)

2017-02-16

We study the role of the lattice artifacts associated with the Coulomb binding effects in the analysis of the heavy quarkonium within lattice NRQCD. We find that a “naïve” perturbative matching generates spurious linear Coulomb artifacts, which result in a large systematic error in the lattice predictions for the heavy quarkonium spectrum. This effect is responsible, in particular, for the discrepancy between the recent determinations of the bottomonium hyperfine splitting in the radiatively improved lattice NRQCD (DOI: 10.1103/PhysRevD.92.054502; Arxiv:1309.5797). We show that the correct matching procedure which provides full control over discretization errors is based on the asymptotic expansion of the lattice theory about the continuum limit, which gives M{sub Υ(1S)}−M{sub η{sub b(1S)}}=52.9±5.5 MeV (DOI: 10.1103/PhysRevD.92.054502).

Prior-based artifact correction (PBAC) in computed tomography

International Nuclear Information System (INIS)

Heußer, Thorsten; Brehm, Marcus; Ritschl, Ludwig; Sawall, Stefan; Kachelrieß, Marc

2014-01-01

Purpose: Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion. Methods: The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form of a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image. Results: The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result. Conclusions: The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data

A deep auto-encoder model for gene expression prediction.

Science.gov (United States)

Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

2017-11-17

Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

Gene prediction validation and functional analysis of redundant pathways

DEFF Research Database (Denmark)

Sønderkær, Mads

2011-01-01

have employed a large mRNA-seq data set to improve and validate ab initio predicted gene models. This direct experimental evidence also provides reliable determinations of UTR regions and polyadenylation sites, which are not easily predicted in plants. Furthermore, once an annotated genome sequence...... is available, gene expression by mRNA-Seq enables acquisition of a more complete overview of gene isoform usage in complex enzymatic pathways enabling the identification of key genes. Metabolism in potatoes This information is useful e.g. for crop improvement based on manipulation of agronomically important...

Voting strategy for artifact reduction in digital breast tomosynthesis

International Nuclear Information System (INIS)

Wu Tao; Moore, Richard H.; Kopans, Daniel B.

2006-01-01

Artifacts are observed in digital breast tomosynthesis (DBT) reconstructions due to the small number of projections and the narrow angular range that are typically employed in tomosynthesis imaging. In this work, we investigate the reconstruction artifacts that are caused by high-attenuation features in breast and develop several artifact reduction methods based on a 'voting strategy'. The voting strategy identifies the projection(s) that would introduce artifacts to a voxel and rejects the projection(s) when reconstructing the voxel. Four approaches to the voting strategy were compared, including projection segmentation, maximum contribution deduction, one-step classification, and iterative classification. The projection segmentation method, based on segmentation of high-attenuation features from the projections, effectively reduces artifacts caused by metal and large calcifications that can be reliably detected and segmented from projections. The other three methods are based on the observation that contributions from artifact-inducing projections have higher value than those from normal projections. These methods attempt to identify the projection(s) that would cause artifacts by comparing contributions from different projections. Among the three methods, the iterative classification method provides the best artifact reduction; however, it can generate many false positive classifications that degrade the image quality. The maximum contribution deduction method and one-step classification method both reduce artifacts well from small calcifications, although the performance of artifact reduction is slightly better with the one-step classification. The combination of one-step classification and projection segmentation removes artifacts from both large and small calcifications

Social web artifacts for boosting recommenders theory and implementation

CERN Document Server

Ziegler, Cai-Nicolas

2013-01-01

Recommender systems, software programs that learn from human behavior and make predictions of what products we are expected to appreciate and purchase, have become an integral part of our everyday life. They proliferate across electronic commerce around the globe and exist for virtually all sorts of consumable goods, such as books, movies, music, or clothes. At the same time, a new evolution on the Web has started to take shape, commonly known as the “Web 2.0” or the “Social Web”: Consumer-generated media has become rife, social networks have emerged and are pulling significant shares of Web traffic. In line with these developments, novel information and knowledge artifacts have become readily available on the Web, created by the collective effort of millions of people. This textbook presents approaches to exploit the new Social Web fountain of knowledge, zeroing in first and foremost on two of those information artifacts, namely classification taxonomies and trust networks. These two are used to impr...

Guided interaction exploration in artifact-centric process models

NARCIS (Netherlands)

van Eck, M.L.; Sidorova, N.; van der Aalst, W.M.P.

2017-01-01

Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the discovery of such models. However, the focus is often on the representation of the individual artifacts rather than their interactions. Based

The Many Faces of Computational Artifacts

DEFF Research Database (Denmark)

Christensen, Lars Rune; Harper, Richard

2016-01-01

Building on data from fieldwork at a medical department, this paper focuses on the varied nature of computational artifacts in practice. It shows that medical practice relies on multiple heterogeneous computational artifacts that form complex constellations. In the hospital studied the computatio...

Reducing artifacts from varying projection truncations

DEFF Research Database (Denmark)

Borg, Leise; Jørgensen, Jakob Sauer; Frikel, Jürgen

We study samples with full and partial occlusion causing streak artifacts, and propose two modifications of filtered backprojection for artifact removal. Data is obtained by the SPring-8 synchrotron using a monochromatic parallel-beam scan [1]. Thresholding in the sinogram segments the metal...

Artifacts Quantification of Metal Implants in MRI

Science.gov (United States)

Vrachnis, I. N.; Vlachopoulos, G. F.; Maris, T. G.; Costaridou, L. I.

2017-11-01

The presence of materials with different magnetic properties, such as metal implants, causes distortion of the magnetic field locally, resulting in signal voids and pile ups, i.e. susceptibility artifacts in MRI. Quantitative and unbiased measurement of the artifact is prerequisite for optimization of acquisition parameters. In this study an image gradient based segmentation method is proposed for susceptibility artifact quantification. The method captures abrupt signal alterations by calculation of the image gradient. Then the artifact is quantified in terms of its extent by an automated cross entropy thresholding method as image area percentage. The proposed method for artifact quantification was tested in phantoms containing two orthopedic implants with significantly different magnetic permeabilities. The method was compared against a method proposed in the literature, considered as a reference, demonstrating moderate to good correlation (Spearman’s rho = 0.62 and 0.802 in case of titanium and stainless steel implants). The automated character of the proposed quantification method seems promising towards MRI acquisition parameter optimization.

Trails of meaning construction: Symbolic artifacts engage the social brain.

Science.gov (United States)

Tylén, Kristian; Philipsen, Johanne Stege; Roepstorff, Andreas; Fusaroli, Riccardo

2016-07-01

Symbolic artifacts present a challenge to theories of neurocognitive processing due to their hybrid nature: they are at the same time physical objects and vehicles of intangible social meanings. While their physical properties can be read of their perceptual appearance, the meaning of symbolic artifacts depends on the perceiver's interpretative attitude and embeddedness in cultural practices. In this study, participants built models of LEGO bricks to illustrate their understanding of abstract concepts. They were then scanned with fMRI while presented to photographs of their own and others' models. When participants attended to the meaning of the models in contrast to their bare physical properties, we observed activations in mPFC and TPJ, areas often associated with social cognition, and IFG, possibly related to semantics. When contrasting own and others' models, we also found activations in precuneus, an area associated with autobiographical memory and agency, while looking at one's own collective models yielded interaction effects in rostral ACC, right IFG and left Insula. Interestingly, variability in the insula was predicted by individual differences in participants' feeling of relatedness to their fellow group members during LEGO construction activity. Our findings support a view of symbolic artifacts as neuro-cognitive trails of human social interactions. Copyright © 2016 Elsevier Inc. All rights reserved.

Global discriminative learning for higher-accuracy computational gene prediction.

Directory of Open Access Journals (Sweden)

Axel Bernal

2007-03-01

Full Text Available Most ab initio gene predictors use a probabilistic sequence model, typically a hidden Markov model, to combine separately trained models of genomic signals and content. By combining separate models of relevant genomic features, such gene predictors can exploit small training sets and incomplete annotations, and can be trained fairly efficiently. However, that type of piecewise training does not optimize prediction accuracy and has difficulty in accounting for statistical dependencies among different parts of the gene model. With genomic information being created at an ever-increasing rate, it is worth investigating alternative approaches in which many different types of genomic evidence, with complex statistical dependencies, can be integrated by discriminative learning to maximize annotation accuracy. Among discriminative learning methods, large-margin classifiers have become prominent because of the success of support vector machines (SVM in many classification tasks. We describe CRAIG, a new program for ab initio gene prediction based on a conditional random field model with semi-Markov structure that is trained with an online large-margin algorithm related to multiclass SVMs. Our experiments on benchmark vertebrate datasets and on regions from the ENCODE project show significant improvements in prediction accuracy over published gene predictors that use intrinsic features only, particularly at the gene level and on genes with long introns.

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

Directory of Open Access Journals (Sweden)

Richard Danger

2018-01-01

Full Text Available Bronchiolitis obliterans syndrome (BOS, the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group, and 26 samples at or after BOS diagnosis (diagnosis group. An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group. We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1, T-cell leukemia/lymphoma protein 1A (TCL1A, and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01 and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

Science.gov (United States)

He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A; Watson, David B; Adams, Michael W W; Fields, Matthew W; Alm, Eric J; Hazen, Terry C; Adams, Paul D; Arkin, Adam P; Zhou, Jizhong

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly ( P contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as

Metallic artifact in MRI after removal of orthopedic implants

International Nuclear Information System (INIS)

Bagheri, Mohammad Hadi; Hosseini, Mehrdad Mohammad; Emami, Mohammad Jafar; Foroughi, Amin Aiboulhassani

2012-01-01

Objective: The aim of the present study was to evaluate the metallic artifacts in MRI of the orthopedic patients after removal of metallic implants. Subjects and methods: From March to August 2009, 40 orthopedic patients operated for removal of orthopedic metallic implants were studied by post-operative MRI from the site of removal of implants. A grading scale of 0–3 was assigned for artifact in MR images whereby 0 was considered no artifact; and I–III were considered mild, moderate, and severe metallic artifacts, respectively. These grading records were correlated with other variables including the type, size, number, and composition of metallic devices; and the site and duration of orthopedic devices stay in the body. Results: Metallic susceptibly artifacts were detected in MRI of 18 of 40 cases (45%). Screws and pins in removed hardware were the most important factors for causing artifacts in MRI. The artifacts were found more frequently in the patients who had more screws and pins in the removed implants. Gender, age, site of implantation of the device, length of the hardware, composition of the metallic implants (stainless steel versus titanium), and duration of implantation of the hardware exerted no effect in producing metallic artifacts after removal of implants. Short TE sequences of MRI (such as T1 weighted) showed fewer artifacts. Conclusion: Susceptibility of metallic artifacts is a frequent phenomenon in MRI of patients upon removal of metallic orthopedic implants.

Metallic artifact in MRI after removal of orthopedic implants.

Science.gov (United States)

Bagheri, Mohammad Hadi; Hosseini, Mehrdad Mohammad; Emami, Mohammad Jafar; Foroughi, Amin Aiboulhassani

2012-03-01

The aim of the present study was to evaluate the metallic artifacts in MRI of the orthopedic patients after removal of metallic implants. From March to August 2009, 40 orthopedic patients operated for removal of orthopedic metallic implants were studied by post-operative MRI from the site of removal of implants. A grading scale of 0-3 was assigned for artifact in MR images whereby 0 was considered no artifact; and I-III were considered mild, moderate, and severe metallic artifacts, respectively. These grading records were correlated with other variables including the type, size, number, and composition of metallic devices; and the site and duration of orthopedic devices stay in the body. Metallic susceptibly artifacts were detected in MRI of 18 of 40 cases (45%). Screws and pins in removed hardware were the most important factors for causing artifacts in MRI. The artifacts were found more frequently in the patients who had more screws and pins in the removed implants. Gender, age, site of implantation of the device, length of the hardware, composition of the metallic implants (stainless steel versus titanium), and duration of implantation of the hardware exerted no effect in producing metallic artifacts after removal of implants. Short TE sequences of MRI (such as T1 weighted) showed fewer artifacts. Susceptibility of metallic artifacts is a frequent phenomenon in MRI of patients upon removal of metallic orthopedic implants. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Analysis of aliasing artifacts in 16-slice helical CT

International Nuclear Information System (INIS)

Chen Wei; Liu Jingkang; Ou Xiaoguang; Li Wenzheng; Liao Weihua; Yan Ang

2006-01-01

Objective: To recognize the features of aliasing artifacts on CT images, and to investigate the effects of imaging parameters on the magnitude of this artifacts. Methods: An adult dry skull was placed in a plastic water-filled container and scanned with a PHILIPS 16-slice helical CT. All the acquired transaxial images by using several different acquisition or reconstruction parameters were examined for comparative assessment of the aliasing artifacts. Results: The aliasing artifacts could be seen in most instances and characterized as the spokewise patterns emanating from the edges of high contrast structure as its radius varies sharply in the longitudinal direction. The images that scanned with pitch of 0.3, 0.6 and 0.9, respectively, showed aliasing artifacts, and its severities increased with pitches escalated (detector combination 16 x 1.5, reconstruction thickness 2 mm); There were more significant aliasing artifacts on the images reconstructed with 0.8 mm slice width compared with 1-mm slice width, and no aliasing artifacts were observed on the images reconstructed with 2-mm slice width (detector combination 16 x 0.75, pitch 0.6); No artifacts were perceived on the images scanned with detector combination 16 x 0.75, while presented evidently with the use of detector combination 16 x 1.5 (pitch 0.6, reconstruction thickness 2 mm); The degrees of aliasing artifacts were unaltered when reconstruction interval and tube current changed. Conclusions: Aliasing artifacts are caused by undersampling. When the operator choose the thinner sampling thickness, lower pitch and a much wider reconstruction thickness judiciously, aliasing artifacts could be effectively mitigated or suppressed. (authors)

Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

Science.gov (United States)

Sivaraks, Haemwaan

2015-01-01

Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284

Incidental ferumoxytol artifacts in clinical brain MR imaging

Energy Technology Data Exchange (ETDEWEB)

Bowser, Bruce A.; Campeau, Norbert G.; Carr, Carrie M.; Diehn, Felix E.; McDonald, Jennifer S.; Miller, Gary M.; Kaufmann, Timothy J. [Mayo Clinic, Department of Radiology, Rochester, MN (United States)

2016-11-15

Ferumoxytol (Feraheme) is a parenteral therapy approved for treatment of iron deficiency anemia. The product insert for ferumoxytol states that it may affect the diagnostic ability of MRI for up to 3 months. However, the expected effects may not be commonly recognized among clinical neuroradiologists. Our purpose is to describe the artifacts we have seen at our institution during routine clinical practice. We reviewed the patients at our institution that had brain MRI performed within 90 days of receiving intravenous ferumoxytol. The imaging was reviewed for specific findings, including diffusion-weighted imaging vascular susceptibility artifact, gradient-echo echo-planar T2*-weighted vascular susceptibility artifact, SWI/SWAN vascular susceptibility artifact, hypointense vascular signal on T2-weighted images, pre-gadolinium contrast vascular enhancement on magnetization-prepared rapid acquisition gradient echo (MPRAGE) imaging, and effects on post-gadolinium contrast T1 imaging. Multiple artifacts were observed in patients having a brain MRI within 3 days of receiving intravenous ferumoxytol. These included susceptibility artifact on DWI, GRE, and SWAN/SWI imaging, pre-gadolinium contrast increased vascular signal on MPRAGE imaging, and decreased expected enhancement on post-gadolinium contrast T1-weighted imaging. Ferumoxytol can create imaging artifacts which complicate clinical interpretation when brain MRI is performed within 3 days of administration. Recognition of the constellation of artifacts produced by ferumoxytol is important in order to obviate additional unnecessary examinations and mitigate errors in interpretation. (orig.)

Probability-based collaborative filtering model for predicting gene-disease associations.

Science.gov (United States)

Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan

2017-12-28

Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene-disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our model. Firstly, on the basis of a typical latent factorization model, we propose model I with an average heterogeneous regularization. Secondly, we develop modified model II with personal heterogeneous regularization to enhance the accuracy of aforementioned models. In this model, vector space similarity or Pearson correlation coefficient metrics and data on related species are also used. We compared the results of PCFM with the results of four state-of-arts approaches. The results show that PCFM performs better than other advanced approaches. PCFM model can be leveraged for predictions of disease genes, especially for new human genes or diseases with no known relationships.

Teaching and Learning the Nature of Technical Artifacts

Science.gov (United States)

Frederik, Ineke; Sonneveld, Wim; de Vries, Marc J.

2011-01-01

Artifacts are probably our most obvious everyday encounter with technology. Therefore, a good understanding of the nature of technical artifacts is a relevant part of technological literacy. In this article we draw from the philosophy of technology to develop a conceptualization of technical artifacts that can be used for educational purposes.…

Metal and calcification artifact reduction for digital breast tomosynthesis

Science.gov (United States)

Wicklein, Julia; Jerebko, Anna; Ritschl, Ludwig; Mertelmeier, Thomas

2017-03-01

Tomosynthesis images of the breast suffer from artifacts caused by the presence of highly absorbing materials. These can be either induced by metal objects like needles or clips inserted during biopsy devices, or larger calcifications inside the examined breast. Mainly two different kinds of artifacts appear after the filtered backprojection procedure. The first type is undershooting artifacts near edges of high-contrast objects caused by the filtering step. The second type is out-of-plane (ripple) artifacts that appear even in slices where the metal object or macrocalcifications does not exist. Due to the limited angular range of tomosynthesis systems, overlapping structures have high influence on neighboring regions. To overcome these problems, a segmentation of artifact introducing objects is performed on the projection images. Both projection versions, with and without high-contrast objects are filtered independently to avoid undershootings. During backprojection a decision is made for each reconstructed voxel, if it is artifact or high-contrast object. This is based on a mask image, gained from the segmentation of high-contrast objects. This procedure avoids undershooting artifacts and additionally reduces out-of-plane ripple. Results are demonstrated for different kinds of artifact inducing objects and calcifications.

Iterative image-domain ring artifact removal in cone-beam CT

Science.gov (United States)

Liang, Xiaokun; Zhang, Zhicheng; Niu, Tianye; Yu, Shaode; Wu, Shibin; Li, Zhicheng; Zhang, Huailing; Xie, Yaoqin

2017-07-01

Ring artifacts in cone beam computed tomography (CBCT) images are caused by pixel gain variations using flat-panel detectors, and may lead to structured non-uniformities and deterioration of image quality. The purpose of this study is to propose a method of general ring artifact removal in CBCT images. This method is based on the polar coordinate system, where the ring artifacts manifest as stripe artifacts. Using relative total variation, the CBCT images are first smoothed to generate template images with fewer image details and ring artifacts. By subtracting the template images from the CBCT images, residual images with image details and ring artifacts are generated. As the ring artifact manifests as a stripe artifact in a polar coordinate system, the artifact image can be extracted by mean value from the residual image; the image details are generated by subtracting the artifact image from the residual image. Finally, the image details are compensated to the template image to generate the corrected images. The proposed framework is iterated until the differences in the extracted ring artifacts are minimized. We use a 3D Shepp-Logan phantom, Catphan©504 phantom, uniform acrylic cylinder, and images from a head patient to evaluate the proposed method. In the experiments using simulated data, the spatial uniformity is increased by 1.68 times and the structural similarity index is increased from 87.12% to 95.50% using the proposed method. In the experiment using clinical data, our method shows high efficiency in ring artifact removal while preserving the image structure and detail. The iterative approach we propose for ring artifact removal in cone-beam CT is practical and attractive for CBCT guided radiation therapy.

Physiological artifacts in scalp EEG and ear-EEG.

Science.gov (United States)

Kappel, Simon L; Looney, David; Mandic, Danilo P; Kidmose, Preben

2017-08-11

A problem inherent to recording EEG is the interference arising from noise and artifacts. While in a laboratory environment, artifacts and interference can, to a large extent, be avoided or controlled, in real-life scenarios this is a challenge. Ear-EEG is a concept where EEG is acquired from electrodes in the ear. We present a characterization of physiological artifacts generated in a controlled environment for nine subjects. The influence of the artifacts was quantified in terms of the signal-to-noise ratio (SNR) deterioration of the auditory steady-state response. Alpha band modulation was also studied in an open/closed eyes paradigm. Artifacts related to jaw muscle contractions were present all over the scalp and in the ear, with the highest SNR deteriorations in the gamma band. The SNR deterioration for jaw artifacts were in general higher in the ear compared to the scalp. Whereas eye-blinking did not influence the SNR in the ear, it was significant for all groups of scalps electrodes in the delta and theta bands. Eye movements resulted in statistical significant SNR deterioration in both frontal, temporal and ear electrodes. Recordings of alpha band modulation showed increased power and coherence of the EEG for ear and scalp electrodes in the closed-eyes periods. Ear-EEG is a method developed for unobtrusive and discreet recording over long periods of time and in real-life environments. This study investigated the influence of the most important types of physiological artifacts, and demonstrated that spontaneous activity, in terms of alpha band oscillations, could be recorded from the ear-EEG platform. In its present form ear-EEG was more prone to jaw related artifacts and less prone to eye-blinking artifacts compared to state-of-the-art scalp based systems.

Pitfalls and artifacts in magnetic resonance imaging

International Nuclear Information System (INIS)

Kulkarni, M.V.; Patton, J.A.

1986-01-01

As a new imaging technique, MRI is subject to new and unfamiliar artifacts. Because of the wide range of pulse sequences used in MRI, the technique is prone to some artifacts, such as even echo rephasing, which are not found in other imaging systems. With newer and stronger magnetic fields, artifacts such as those caused by chemical shift will be more pronounced. For the maintenance of high quality images, new techniques controlling quality are essential. These techniques include the development of new phantoms and new procedures. The American Association of Physicists in Medicine is currently developing guidelines for quality assurance programs. As with other imaging modalities, these quality assurance guidelines could be unique to MRI. The daily or weekly evaluation of signal-to-noise ratio, image uniformity, signal linearity, spatial linearity, spatial resolution, frequencies, etc. is essential. Some guidelines are described in the current literature. With further modifications and improvements in MRI techniques, new artifacts may be discovered. Identification of these artifacts will improve the interpretation of the image and patient management

The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

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Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

2014-06-01

With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

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Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Prediction of highly expressed genes in microbes based on chromatin accessibility

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Ussery David W

2007-02-01

Full Text Available Abstract Background It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed genes in microbial genomes. We compare these predictions with those based on codon adaptation index (CAI values, and also with experimental data for 6 different microbial genomes, with a particular interest in experimental data from Escherichia coli. Moreover, position preference is examined further in 328 sequenced microbial genomes. Results We find that absolute gene expression levels are correlated with the position preference in many microbial genomes. It is postulated that in these regions, the DNA may be more accessible to the transcriptional machinery. Moreover, ribosomal proteins and ribosomal RNA are encoded by DNA having significantly lower position preference values than other genes in fast-replicating microbes. Conclusion This insight into DNA structure-dependent gene expression in microbes may be exploited for predicting the expression of non-translated genes such as non-coding RNAs that may not be predicted by any of the conventional codon usage bias approaches.

Semi-supervised prediction of gene regulatory networks using ...

Indian Academy of Sciences (India)

2015-09-28

Sep 28, 2015 ... Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging ... two types of methods differ primarily based on whether ..... negligible, allowing us to draw the qualitative conclusions .... research will be conducted to develop additional biologically.

Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

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Liying Yang

2016-01-01

Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

Detection of artifacts from high energy bursts in neonatal EEG.

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Bhattacharyya, Sourya; Biswas, Arunava; Mukherjee, Jayanta; Majumdar, Arun Kumar; Majumdar, Bandana; Mukherjee, Suchandra; Singh, Arun Kumar

2013-11-01

Detection of non-cerebral activities or artifacts, intermixed within the background EEG, is essential to discard them from subsequent pattern analysis. The problem is much harder in neonatal EEG, where the background EEG contains spikes, waves, and rapid fluctuations in amplitude and frequency. Existing artifact detection methods are mostly limited to detect only a subset of artifacts such as ocular, muscle or power line artifacts. Few methods integrate different modules, each for detection of one specific category of artifact. Furthermore, most of the reference approaches are implemented and tested on adult EEG recordings. Direct application of those methods on neonatal EEG causes performance deterioration, due to greater pattern variation and inherent complexity. A method for detection of a wide range of artifact categories in neonatal EEG is thus required. At the same time, the method should be specific enough to preserve the background EEG information. The current study describes a feature based classification approach to detect both repetitive (generated from ECG, EMG, pulse, respiration, etc.) and transient (generated from eye blinking, eye movement, patient movement, etc.) artifacts. It focuses on artifact detection within high energy burst patterns, instead of detecting artifacts within the complete background EEG with wide pattern variation. The objective is to find true burst patterns, which can later be used to identify the Burst-Suppression (BS) pattern, which is commonly observed during newborn seizure. Such selective artifact detection is proven to be more sensitive to artifacts and specific to bursts, compared to the existing artifact detection approaches applied on the complete background EEG. Several time domain, frequency domain, statistical features, and features generated by wavelet decomposition are analyzed to model the proposed bi-classification between burst and artifact segments. A feature selection method is also applied to select the

Ring artifact correction for high-resolution micro CT

International Nuclear Information System (INIS)

Kyriakou, Yiannis; Prell, Daniel; Kalender, Willi A

2009-01-01

In high-resolution micro CT using flat detectors (FD), imperfect or defect detector elements may cause concentric-ring artifacts due to their continuous over- or underestimation of attenuation values, which often disturb image quality. We here present a dedicated image-based ring artifact correction method for high-resolution micro CT, based on median filtering of the reconstructed image and working on a transformed version of the reconstructed images in polar coordinates. This post-processing method reduced ring artifacts in the reconstructed images and improved image quality for phantom and in in vivo scans. Noise and artifacts were reduced both in transversal and in multi-planar reformations along the longitudinal axis. (note)

Identification of rat genes by TWINSCAN gene prediction, RT-PCR, and direct sequencing

DEFF Research Database (Denmark)

Wu, Jia Qian; Shteynberg, David; Arumugam, Manimozhiyan

2004-01-01

an alternative approach: reverse transcription-polymerase chain reaction (RT-PCR) and direct sequencing based on dual-genome de novo predictions from TWINSCAN. We tested 444 TWINSCAN-predicted rat genes that showed significant homology to known human genes implicated in disease but that were partially...... in the single-intron experiment. Spliced sequences were amplified in 46 cases (34%). We conclude that this procedure for elucidating gene structures with native cDNA sequences is cost-effective and will become even more so as it is further optimized.......The publication of a draft sequence of a third mammalian genome--that of the rat--suggests a need to rethink genome annotation. New mammalian sequences will not receive the kind of labor-intensive annotation efforts that are currently being devoted to human. In this paper, we demonstrate...

Genome-wide targeted prediction of ABA responsive genes in rice based on over-represented cis-motif in co-expressed genes.

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Lenka, Sangram K; Lohia, Bikash; Kumar, Abhay; Chinnusamy, Viswanathan; Bansal, Kailash C

2009-02-01

Abscisic acid (ABA), the popular plant stress hormone, plays a key role in regulation of sub-set of stress responsive genes. These genes respond to ABA through specific transcription factors which bind to cis-regulatory elements present in their promoters. We discovered the ABA Responsive Element (ABRE) core (ACGT) containing CGMCACGTGB motif as over-represented motif among the promoters of ABA responsive co-expressed genes in rice. Targeted gene prediction strategy using this motif led to the identification of 402 protein coding genes potentially regulated by ABA-dependent molecular genetic network. RT-PCR analysis of arbitrarily chosen 45 genes from the predicted 402 genes confirmed 80% accuracy of our prediction. Plant Gene Ontology (GO) analysis of ABA responsive genes showed enrichment of signal transduction and stress related genes among diverse functional categories.

Combining many interaction networks to predict gene function and analyze gene lists.

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Mostafavi, Sara; Morris, Quaid

2012-05-01

In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The role of gene-gene interaction in the prediction of criminal behavior.

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Boutwell, Brian B; Menard, Scott; Barnes, J C; Beaver, Kevin M; Armstrong, Todd A; Boisvert, Danielle

2014-04-01

A host of research has examined the possibility that environmental risk factors might condition the influence of genes on various outcomes. Less research, however, has been aimed at exploring the possibility that genetic factors might interact to impact the emergence of human traits. Even fewer studies exist examining the interaction of genes in the prediction of behavioral outcomes. The current study expands this body of research by testing the interaction between genes involved in neural transmission. Our findings suggest that certain dopamine genes interact to increase the odds of criminogenic outcomes in a national sample of Americans. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification of a robust gene signature that predicts breast cancer outcome in independent data sets

International Nuclear Information System (INIS)

Korkola, James E; Waldman, Frederic M; Blaveri, Ekaterina; DeVries, Sandy; Moore, Dan H II; Hwang, E Shelley; Chen, Yunn-Yi; Estep, Anne LH; Chew, Karen L; Jensen, Ronald H

2007-01-01

Breast cancer is a heterogeneous disease, presenting with a wide range of histologic, clinical, and genetic features. Microarray technology has shown promise in predicting outcome in these patients. We profiled 162 breast tumors using expression microarrays to stratify tumors based on gene expression. A subset of 55 tumors with extensive follow-up was used to identify gene sets that predicted outcome. The predictive gene set was further tested in previously published data sets. We used different statistical methods to identify three gene sets associated with disease free survival. A fourth gene set, consisting of 21 genes in common to all three sets, also had the ability to predict patient outcome. To validate the predictive utility of this derived gene set, it was tested in two published data sets from other groups. This gene set resulted in significant separation of patients on the basis of survival in these data sets, correctly predicting outcome in 62–65% of patients. By comparing outcome prediction within subgroups based on ER status, grade, and nodal status, we found that our gene set was most effective in predicting outcome in ER positive and node negative tumors. This robust gene selection with extensive validation has identified a predictive gene set that may have clinical utility for outcome prediction in breast cancer patients

Artifact in Pediatric Oculomotor Findings during Videonystagmography: A Retrospective Analysis.

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Doettl, Steven M; Plyler, Patrick N; McCaslin, Devin L

2017-04-01

Accurate measurement of oculomotor function using videonystagmography (VNG) is imperative for diagnosis and management of patients with reported dizziness. The oculomotor evaluation during VNG utilizes video-oculography providing valuable information regarding the central structures and pathways that control eye movements. Artifact may have an effect on the overall validity and reliability of VNG oculomotor tracings and can result from patient and/or recording errors. It is postulated that artifact could occur more frequently in the pediatric population due to both patient and equipment factors. The purpose of this study was to systematically evaluate the occurrence and impact of artifact on saccades, smooth pursuit, and optokinetic (OPK) testing in normal pediatric and adult subjects using commercially available clinical VNG equipment and standard clinical protocols for oculomotor testing. The present study utilized a retrospective analysis of a repeated measures design. Oculomotor results from a total of 62 participants were analyzed. Portions of these data have been presented in a previous research study. Group 1 consisted of twenty-nine 4- to 6-yr-olds with an average age of 4.86 (SD = 0.88) yr. Group 2 consisted of thirty-three 22- to 44-yr-olds with an average age of 25.2 (SD = 5.34) yr. Raw oculomotor recordings were analyzed "offline" by a single masked, trained investigator. Each tracing was evaluated for instances of artifact including eye blinks, eye closure, eyes moving in opposite direction of the target, eye tracking software problems, and overall poor morphology. The number of instances of artifact were noted and recorded for each participant in both groups. Individual eye movements not affected by artifact were included for final analysis. Artifact rejection techniques were also compared. The results indicated increased artifact for the pediatric group for saccade and smooth pursuit testing. Additionally, a significant decrease in instances of

Cultural Artifact Detection in Long Wave Infrared Imagery.

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Anderson, Dylan Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Craven, Julia M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ramon, Eric [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-01-01

Detection of cultural artifacts from airborne remotely sensed data is an important task in the context of on-site inspections. Airborne artifact detection can reduce the size of the search area the ground based inspection team must visit, thereby improving the efficiency of the inspection process. This report details two algorithms for detection of cultural artifacts in aerial long wave infrared imagery. The first algorithm creates an explicit model for cultural artifacts, and finds data that fits the model. The second algorithm creates a model of the background and finds data that does not fit the model. Both algorithms are applied to orthomosaic imagery generated as part of the MSFE13 data collection campaign under the spectral technology evaluation project.

Artifact detection in electrodermal activity using sparse recovery

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Kelsey, Malia; Palumbo, Richard Vincent; Urbaneja, Alberto; Akcakaya, Murat; Huang, Jeannie; Kleckner, Ian R.; Barrett, Lisa Feldman; Quigley, Karen S.; Sejdic, Ervin; Goodwin, Matthew S.

2017-05-01

Electrodermal Activity (EDA) - a peripheral index of sympathetic nervous system activity - is a primary measure used in psychophysiology. EDA is widely accepted as an indicator of physiological arousal, and it has been shown to reveal when psychologically novel events occur. Traditionally, EDA data is collected in controlled laboratory experiments. However, recent developments in wireless biosensing have led to an increase in out-of-lab studies. This transition to ambulatory data collection has introduced challenges. In particular, artifacts such as wearer motion, changes in temperature, and electrical interference can be misidentified as true EDA responses. The inability to distinguish artifact from signal hinders analyses of ambulatory EDA data. Though manual procedures for identifying and removing EDA artifacts exist, they are time consuming - which is problematic for the types of longitudinal data sets represented in modern ambulatory studies. This manuscript presents a novel technique to automatically identify and remove artifacts in EDA data using curve fitting and sparse recovery methods. Our method was evaluated using labeled data to determine the accuracy of artifact identification. Procedures, results, conclusions, and future directions are presented.

Ensemble Artifact Design For Context Sensitive Decision Support

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Shah J Miah

2014-06-01

Full Text Available Although an improvement of design knowledge is an essential goal of design research, current design research predominantly focuses on knowledge concerning the IT artifact (tool design process, rather than a more holistic understanding encompassing the dynamic usage contexts of a technological artifact. Conceptualising a design in context as an “ensemble artifact” (Sein et al., 2011 provides the basis for a more rigorous treatment. This paper describes an IS artifact design framework that has been generated from the development of several practitioner-oriented decision support systems (DSS in which contextual aspects relevant to practitioners’ decision making are considered as integral design themes. We describe five key dimensions of an ensemble artifact design and show their value in designing practitioner-oriented DSS. The features are user centredness, knowledge sharing, situation-specific customisation, reduced model orientation, and practice based secondary design abilities. It is argued that this understanding can contribute to design research knowledge more effectively both to develop dynamic DSS, and by its extensibility to other artifact designs.

Identifying the Gene Signatures from Gene-Pathway Bipartite Network Guarantees the Robust Model Performance on Predicting the Cancer Prognosis

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Li He

2014-01-01

Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes.

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Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-10-03

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.

Automatic removal of eye-movement and blink artifacts from EEG signals.

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Gao, Jun Feng; Yang, Yong; Lin, Pan; Wang, Pei; Zheng, Chong Xun

2010-03-01

Frequent occurrence of electrooculography (EOG) artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In this paper, a robust method is presented to automatically eliminate eye-movement and eye-blink artifacts from EEG signals. Independent Component Analysis (ICA) is used to decompose EEG signals into independent components. Moreover, the features of topographies and power spectral densities of those components are extracted to identify eye-movement artifact components, and a support vector machine (SVM) classifier is adopted because it has higher performance than several other classifiers. The classification results show that feature-extraction methods are unsuitable for identifying eye-blink artifact components, and then a novel peak detection algorithm of independent component (PDAIC) is proposed to identify eye-blink artifact components. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove EOG artifacts effectively from EEG signals with little distortion of the underlying brain signals.

Correction of Bowtie-Filter Normalization and Crescent Artifacts for a Clinical CBCT System.

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Zhang, Hong; Kong, Vic; Huang, Ke; Jin, Jian-Yue

2017-02-01

To present our experiences in understanding and minimizing bowtie-filter crescent artifacts and bowtie-filter normalization artifacts in a clinical cone beam computed tomography system. Bowtie-filter position and profile variations during gantry rotation were studied. Two previously proposed strategies (A and B) were applied to the clinical cone beam computed tomography system to correct bowtie-filter crescent artifacts. Physical calibration and analytical approaches were used to minimize the norm phantom misalignment and to correct for bowtie-filter normalization artifacts. A combined procedure to reduce bowtie-filter crescent artifacts and bowtie-filter normalization artifacts was proposed and tested on a norm phantom, CatPhan, and a patient and evaluated using standard deviation of Hounsfield unit along a sampling line. The bowtie-filter exhibited not only a translational shift but also an amplitude variation in its projection profile during gantry rotation. Strategy B was better than strategy A slightly in minimizing bowtie-filter crescent artifacts, possibly because it corrected the amplitude variation, suggesting that the amplitude variation plays a role in bowtie-filter crescent artifacts. The physical calibration largely reduced the misalignment-induced bowtie-filter normalization artifacts, and the analytical approach further reduced bowtie-filter normalization artifacts. The combined procedure minimized both bowtie-filter crescent artifacts and bowtie-filter normalization artifacts, with Hounsfield unit standard deviation being 63.2, 45.0, 35.0, and 18.8 Hounsfield unit for the best correction approaches of none, bowtie-filter crescent artifacts, bowtie-filter normalization artifacts, and bowtie-filter normalization artifacts + bowtie-filter crescent artifacts, respectively. The combined procedure also demonstrated reduction of bowtie-filter crescent artifacts and bowtie-filter normalization artifacts in a CatPhan and a patient. We have developed a step

Predicting cellular growth from gene expression signatures.

Directory of Open Access Journals (Sweden)

Edoardo M Airoldi

2009-01-01

Full Text Available Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

Predictions of Gene Family Distributions in Microbial Genomes: Evolution by Gene Duplication and Modification

International Nuclear Information System (INIS)

Yanai, Itai; Camacho, Carlos J.; DeLisi, Charles

2000-01-01

A universal property of microbial genomes is the considerable fraction of genes that are homologous to other genes within the same genome. The process by which these homologues are generated is not well understood, but sequence analysis of 20 microbial genomes unveils a recurrent distribution of gene family sizes. We show that a simple evolutionary model based on random gene duplication and point mutations fully accounts for these distributions and permits predictions for the number of gene families in genomes not yet complete. Our findings are consistent with the notion that a genome evolves from a set of precursor genes to a mature size by gene duplications and increasing modifications. (c) 2000 The American Physical Society

Predictions of Gene Family Distributions in Microbial Genomes: Evolution by Gene Duplication and Modification

Energy Technology Data Exchange (ETDEWEB)

Yanai, Itai; Camacho, Carlos J.; DeLisi, Charles

2000-09-18

A universal property of microbial genomes is the considerable fraction of genes that are homologous to other genes within the same genome. The process by which these homologues are generated is not well understood, but sequence analysis of 20 microbial genomes unveils a recurrent distribution of gene family sizes. We show that a simple evolutionary model based on random gene duplication and point mutations fully accounts for these distributions and permits predictions for the number of gene families in genomes not yet complete. Our findings are consistent with the notion that a genome evolves from a set of precursor genes to a mature size by gene duplications and increasing modifications. (c) 2000 The American Physical Society.

A network approach to predict pathogenic genes for Fusarium graminearum.

Science.gov (United States)

Liu, Xiaoping; Tang, Wei-Hua; Zhao, Xing-Ming; Chen, Luonan

2010-10-04

Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN) of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other pathogenic fungi, which

A network approach to predict pathogenic genes for Fusarium graminearum.

Directory of Open Access Journals (Sweden)

Xiaoping Liu

Full Text Available Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB, which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other

Reflection-artifact-free photoacoustic imaging using PAFUSion (photoacoustic-guided focused ultrasound)

Science.gov (United States)

Kuniyil Ajith Singh, Mithun; Jaeger, Michael; Frenz, Martin; Steenbergen, Wiendelt

2016-03-01

Reflection artifacts caused by acoustic inhomogeneities are a main challenge to deep-tissue photoacoustic imaging. Photoacoustic transients generated by the skin surface and superficial vasculature will propagate into the tissue and reflect back from echogenic structures to generate reflection artifacts. These artifacts can cause problems in image interpretation and limit imaging depth. In its basic version, PAFUSion mimics the inward travelling wave-field from blood vessel-like PA sources by applying focused ultrasound pulses, and thus provides a way to identify reflection artifacts. In this work, we demonstrate reflection artifact correction in addition to identification, towards obtaining an artifact-free photoacoustic image. In view of clinical applications, we implemented an improved version of PAFUSion in which photoacoustic data is backpropagated to imitate the inward travelling wave-field and thus the reflection artifacts of a more arbitrary distribution of PA sources that also includes the skin melanin layer. The backpropagation is performed in a synthetic way based on the pulse-echo acquisitions after transmission on each single element of the transducer array. We present a phantom experiment and initial in vivo measurements on human volunteers where we demonstrate significant reflection artifact reduction using our technique. The results provide a direct confirmation that reflection artifacts are prominent in clinical epi-photoacoustic imaging, and that PAFUSion can reduce these artifacts significantly to improve the deep-tissue photoacoustic imaging.

A study of metal artifacts on MR imaging. Evaluation of scanning parameters

International Nuclear Information System (INIS)

Yamashiro, Mitsuaki

1999-01-01

The purpose of this study was to evaluate scanning parameters on MR imaging for reducing metal artifacts using phantom study. Metal artifacts on sagittal images, perpendicular to static magnetic direction showed round shape in the relationship between shape of metal artifacts on MR images and scanning direction. Metal artifacts on both axial and coronal images, parallel to static magnetic direction showed oval shape in the direction of X-axis. In spin echo sequences, the largest dimension of metal artifacts was coronal image, followed by axial image and then sagittal image. In gradient echo sequences, the largest dimension of metal artifacts was axial image, followed by coronal image and then sagittal image. The best scanning plane for reducing metal artifacts was perpendicular to static magnetic direction. In scanning sequences, the largest dimensions of metal artifacts were gradient echo sequences, followed by T2-weighted spin echo sequence and then proton density-weighted and T1-weighted spin echo sequences. Large flip angle increased much metal artifacts on both axial and coronal images in gradient echo sequences. Small flip angle was useful for reducing metal artifacts on both axial and coronal images. The influence of flip angle on metal artifacts in sagittal images perpendicular static magnetic direction was less than for images in coronal and axial planes on gradient echo sequences. These results suggested that a study of metal artifacts on MR imaging about evaluation of scanning parameters was useful to reduce metal artifacts on MR images. (K.H.)

A Third Approach to Gene Prediction Suggests Thousands of Additional Human Transcribed Regions

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Glusman, Gustavo; Qin, Shizhen; El-Gewely, M. Raafat; Siegel, Andrew F; Roach, Jared C; Hood, Leroy; Smit, Arian F. A

2006-01-01

The identification and characterization of the complete ensemble of genes is a main goal of deciphering the digital information stored in the human genome. Many algorithms for computational gene prediction have been described, ultimately derived from two basic concepts: (1) modeling gene structure and (2) recognizing sequence similarity. Successful hybrid methods combining these two concepts have also been developed. We present a third orthogonal approach to gene prediction, based on detecting the genomic signatures of transcription, accumulated over evolutionary time. We discuss four algorithms based on this third concept: Greens and CHOWDER, which quantify mutational strand biases caused by transcription-coupled DNA repair, and ROAST and PASTA, which are based on strand-specific selection against polyadenylation signals. We combined these algorithms into an integrated method called FEAST, which we used to predict the location and orientation of thousands of putative transcription units not overlapping known genes. Many of the newly predicted transcriptional units do not appear to code for proteins. The new algorithms are particularly apt at detecting genes with long introns and lacking sequence conservation. They therefore complement existing gene prediction methods and will help identify functional transcripts within many apparent “genomic deserts.” PMID:16543943

Picking Up Artifacts: Storyboarding as a Gateway to Reuse

Science.gov (United States)

Wahid, Shahtab; Branham, Stacy M.; Cairco, Lauren; McCrickard, D. Scott; Harrison, Steve

Storyboarding offers designers the opportunity to illustrate a visual narrative of use. Because designers often refer to past ideas, we argue storyboards can be constructed by reusing shared artifacts. We present a study in which we explore how designers reuse artifacts consisting of images and rationale during storyboard construction. We find images can aid in accessing rationale and that connections among features aid in deciding what to reuse, creating new artifacts, and constructing. Based on requirements derived from our findings, we present a storyboarding tool, PIC-UP, to facilitate artifact sharing and reuse and evaluate its use in an exploratory study. We conclude with remarks on facilitating reuse and future work.

Artifact removal from EEG signals using adaptive filters in cascade

Science.gov (United States)

Garcés Correa, A.; Laciar, E.; Patiño, H. D.; Valentinuzzi, M. E.

2007-11-01

Artifacts in EEG (electroencephalogram) records are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). These noise sources increase the difficulty in analyzing the EEG and to obtaining clinical information. For this reason, it is necessary to design specific filters to decrease such artifacts in EEG records. In this paper, a cascade of three adaptive filters based on a least mean squares (LMS) algorithm is proposed. The first one eliminates line interference, the second adaptive filter removes the ECG artifacts and the last one cancels EOG spikes. Each stage uses a finite impulse response (FIR) filter, which adjusts its coefficients to produce an output similar to the artifacts present in the EEG. The proposed cascade adaptive filter was tested in five real EEG records acquired in polysomnographic studies. In all cases, line-frequency, ECG and EOG artifacts were attenuated. It is concluded that the proposed filter reduces the common artifacts present in EEG signals without removing significant information embedded in these records.

Artifact removal from EEG signals using adaptive filters in cascade

International Nuclear Information System (INIS)

Garces Correa, A; Laciar, E; Patino, H D; Valentinuzzi, M E

2007-01-01

Artifacts in EEG (electroencephalogram) records are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). These noise sources increase the difficulty in analyzing the EEG and to obtaining clinical information. For this reason, it is necessary to design specific filters to decrease such artifacts in EEG records. In this paper, a cascade of three adaptive filters based on a least mean squares (LMS) algorithm is proposed. The first one eliminates line interference, the second adaptive filter removes the ECG artifacts and the last one cancels EOG spikes. Each stage uses a finite impulse response (FIR) filter, which adjusts its coefficients to produce an output similar to the artifacts present in the EEG. The proposed cascade adaptive filter was tested in five real EEG records acquired in polysomnographic studies. In all cases, line-frequency, ECG and EOG artifacts were attenuated. It is concluded that the proposed filter reduces the common artifacts present in EEG signals without removing significant information embedded in these records

Artifact removal from EEG signals using adaptive filters in cascade

Energy Technology Data Exchange (ETDEWEB)

Garces Correa, A [Gabinete de TecnologIa Medica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Laciar, E [Gabinete de TecnologIa Medica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Patino, H D [Instituto de Automatica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Valentinuzzi, M E [Instituto Superior de Investigaciones Biologicas (INSIBIO), UNT-CONICET, Tucuman (Argentina)

2007-11-15

Artifacts in EEG (electroencephalogram) records are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). These noise sources increase the difficulty in analyzing the EEG and to obtaining clinical information. For this reason, it is necessary to design specific filters to decrease such artifacts in EEG records. In this paper, a cascade of three adaptive filters based on a least mean squares (LMS) algorithm is proposed. The first one eliminates line interference, the second adaptive filter removes the ECG artifacts and the last one cancels EOG spikes. Each stage uses a finite impulse response (FIR) filter, which adjusts its coefficients to produce an output similar to the artifacts present in the EEG. The proposed cascade adaptive filter was tested in five real EEG records acquired in polysomnographic studies. In all cases, line-frequency, ECG and EOG artifacts were attenuated. It is concluded that the proposed filter reduces the common artifacts present in EEG signals without removing significant information embedded in these records.

How Do Artifact Models Help Direct SPI Projects?

DEFF Research Database (Denmark)

Kuhrmann, Marco; Richardson, Ita

2015-01-01

To overcome shortcomings associated with software process improvement (SPI), we previously recommended that process engineers focus on the artifacts to be developed in SPI projects. These artifacts should define desired outcomes, rather than specific methods. During this prior research, we develo...

Contrast artifacts in tapping tip atomic force microscopy

DEFF Research Database (Denmark)

Kyhle, Anders; Sørensen, Alexis Hammer; Zandbergen, Julie Bjerring

1998-01-01

When recording images with an atomic force microscope using the resonant vibrating cantilever mode, surprising strange results are often achieved. Typical artifacts are strange contours, unexpected height shifts, and sudden changes of the apparent resolution in the acquired images. Such artifacts...

Distributed Cognition and Distributed Morality: Agency, Artifacts and Systems.

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Heersmink, Richard

2017-04-01

There are various philosophical approaches and theories describing the intimate relation people have to artifacts. In this paper, I explore the relation between two such theories, namely distributed cognition and distributed morality theory. I point out a number of similarities and differences in these views regarding the ontological status they attribute to artifacts and the larger systems they are part of. Having evaluated and compared these views, I continue by focussing on the way cognitive artifacts are used in moral practice. I specifically conceptualise how such artifacts (a) scaffold and extend moral reasoning and decision-making processes, (b) have a certain moral status which is contingent on their cognitive status, and (c) whether responsibility can be attributed to distributed systems. This paper is primarily written for those interested in the intersection of cognitive and moral theory as it relates to artifacts, but also for those independently interested in philosophical debates in extended and distributed cognition and ethics of (cognitive) technology.

Automatic detection and classification of artifacts in single-channel EEG

DEFF Research Database (Denmark)

Olund, Thomas; Duun-Henriksen, Jonas; Kjaer, Troels W.

2014-01-01

Ambulatory EEG monitoring can provide medical doctors important diagnostic information, without hospitalizing the patient. These recordings are however more exposed to noise and artifacts compared to clinically recorded EEG. An automatic artifact detection and classification algorithm for single......-channel EEG is proposed to help identifying these artifacts. Features are extracted from the EEG signal and wavelet subbands. Subsequently a selection algorithm is applied in order to identify the best discriminating features. A non-linear support vector machine is used to discriminate among different...... artifact classes using the selected features. Single-channel (Fp1-F7) EEG recordings are obtained from experiments with 12 healthy subjects performing artifact inducing movements. The dataset was used to construct and validate the model. Both subject-specific and generic implementation, are investigated...

Motion artifacts in computed tomography

International Nuclear Information System (INIS)

Yang, C.K.

1979-01-01

In the year 1972, the first Computed Tomography Scanner (or CT) was introduced and caused a revolution in the field of Diagnostic Radiology. A tomogram is a cross-sectional image of a three-dimensional object obtained through non-invasive measurements. The image that is presented is very similar to what would be seen if a thin cross-sectional slice of the patient was examined. In Computed Tomography, x-rays are passed through the body of a patient in many different directions and their attenuation is detected. By using some mathematical theorems, the attenuation information can be converted into the density of the patient along the x-ray path. Combined with modern sophisticated computer signal processing technology, a cross-sectional image can be generated and displayed on a TV monitor. Usually a good CT image relies on the patient not moving during the x-ray scanning. However, for some unconscious or severely ill patients, this is very difficult to achieve. Thus, the motion during the scan causes the so-called motion artifacts which distort the displayed image and sometimes these motion artifacts make diagnosis impossible. Today, to remove or avoid motion artifacts is one of the major efforts in developing new scanner systems. In this thesis, a better understanding of the motion artifacts problem in CT scaning is gained through computer simulations, real scanner experiments and theoretical analyses. The methods by which the distorted image can be improved are simulated also. In particular, it is assumed that perfect knowledge of the patient motion is known since this represents the theoretical limit on how well the distorted image can be improved

Artifacts by dental materials on magnetic resonance imaging

International Nuclear Information System (INIS)

Hong, Hyun Sook; Choi, Deuk Lin; Kim, Ki Jung; Suh, Won Hyuck

1992-01-01

Magnetic resonance imaging (MRI) has proved to be a valuable method for evaluation of the head and neck. Unfortunately, metallic devices associated with certain dental fillings and appliances often cause variable artifacts that can obscure normal or pathologic conditions on MR and computed tomography. In this work, we assessed the MR appearance of dental prosthetic materials in vitro and in vivo including precious alloys, nonprecions alloys, resin, amalgam and titanium alloy. For in vivo studies, these materials were placed in healthy volunteer's mouths and then images were assessed. Analysis of the appearance of shape and extent of artifact, and observed influence of these artifacts on the image interpretation at 0.2 Tesla permanent type MR scanner were valuated. Material used as temporary or permanent filling of crowns such as amalgam, precious alloy and, microfilled resin did not cause artifact on the image. The size of the artifact produced by the nonprecious alloys was influenced by the ferromagnetism of the object and the volume prosthesis, and was related to the scanning sequence. Nonprecious alloys produced minimal local signal distortion, where precious alloys, and dental resin had no effect on the MR images in vivo. These results were mainly from a low field strength MR scanner used in this study

Correction of CT artifacts and its influence on Monte Carlo dose calculations

International Nuclear Information System (INIS)

Bazalova, Magdalena; Beaulieu, Luc; Palefsky, Steven; Verhaegen, Frank

2007-01-01

Computed tomography (CT) images of patients having metallic implants or dental fillings exhibit severe streaking artifacts. These artifacts may disallow tumor and organ delineation and compromise dose calculation outcomes in radiotherapy. We used a sinogram interpolation metal streaking artifact correction algorithm on several phantoms of exact-known compositions and on a prostate patient with two hip prostheses. We compared original CT images and artifact-corrected images of both. To evaluate the effect of the artifact correction on dose calculations, we performed Monte Carlo dose calculation in the EGSnrc/DOSXYZnrc code. For the phantoms, we performed calculations in the exact geometry, in the original CT geometry and in the artifact-corrected geometry for photon and electron beams. The maximum errors in 6 MV photon beam dose calculation were found to exceed 25% in original CT images when the standard DOSXYZnrc/CTCREATE calibration is used but less than 2% in artifact-corrected images when an extended calibration is used. The extended calibration includes an extra calibration point for a metal. The patient dose volume histograms of a hypothetical target irradiated by five 18 MV photon beams in a hypothetical treatment differ significantly in the original CT geometry and in the artifact-corrected geometry. This was found to be mostly due to miss-assignment of tissue voxels to air due to metal artifacts. We also developed a simple Monte Carlo model for a CT scanner and we simulated the contribution of scatter and beam hardening to metal streaking artifacts. We found that whereas beam hardening has a minor effect on metal artifacts, scatter is an important cause of these artifacts

Edge artifact correction for industrial computed tomography images

International Nuclear Information System (INIS)

Cai Yufang; Li Dan; Wang Jue

2013-01-01

To eliminate the edge artifacts of industrial CT images, and improve the identification ability of the image and the precision of the dimension measurement, a coefficient adjusting method for reducing crosstalk noise is proposed. It is concluded from theoretical analysis that crosstalk generated from adjacent detectors by Compton scattering is the major reason for the edge artifacts. According to the mathematic model of the detector crosstalk, we design a special detector system configuration and stair-step phantom for estimating the quantity of crosstalk noise. The relationship between crosstalk ratio and intensity of the incident X-ray is acquired by regressing experimental data with least square method. The experimental result shows that the first-order crosstalk ratio between detectors is about 9.0%, and the second-order crosstalk ratio is about 1.2%. Thus the first-order crosstalk is the main factor causing edge artifacts. The proposed method can reduce the edge artifacts significantly, and meanwhile maintain the detail and edge of CT images. (authors)

Reduced aliasing artifacts using shaking projection k-space sampling trajectory

Science.gov (United States)

Zhu, Yan-Chun; Du, Jiang; Yang, Wen-Chao; Duan, Chai-Jie; Wang, Hao-Yu; Gao, Song; Bao, Shang-Lian

2014-03-01

Radial imaging techniques, such as projection-reconstruction (PR), are used in magnetic resonance imaging (MRI) for dynamic imaging, angiography, and short-T2 imaging. They are less sensitive to flow and motion artifacts, and support fast imaging with short echo times. However, aliasing and streaking artifacts are two main sources which degrade radial imaging quality. For a given fixed number of k-space projections, data distributions along radial and angular directions will influence the level of aliasing and streaking artifacts. Conventional radial k-space sampling trajectory introduces an aliasing artifact at the first principal ring of point spread function (PSF). In this paper, a shaking projection (SP) k-space sampling trajectory was proposed to reduce aliasing artifacts in MR images. SP sampling trajectory shifts the projection alternately along the k-space center, which separates k-space data in the azimuthal direction. Simulations based on conventional and SP sampling trajectories were compared with the same number projections. A significant reduction of aliasing artifacts was observed using the SP sampling trajectory. These two trajectories were also compared with different sampling frequencies. A SP trajectory has the same aliasing character when using half sampling frequency (or half data) for reconstruction. SNR comparisons with different white noise levels show that these two trajectories have the same SNR character. In conclusion, the SP trajectory can reduce the aliasing artifact without decreasing SNR and also provide a way for undersampling reconstruction. Furthermore, this method can be applied to three-dimensional (3D) hybrid or spherical radial k-space sampling for a more efficient reduction of aliasing artifacts.

Reduced aliasing artifacts using shaking projection k-space sampling trajectory

International Nuclear Information System (INIS)

Zhu Yan-Chun; Yang Wen-Chao; Wang Hao-Yu; Gao Song; Bao Shang-Lian; Du Jiang; Duan Chai-Jie

2014-01-01

Radial imaging techniques, such as projection-reconstruction (PR), are used in magnetic resonance imaging (MRI) for dynamic imaging, angiography, and short-T2 imaging. They are less sensitive to flow and motion artifacts, and support fast imaging with short echo times. However, aliasing and streaking artifacts are two main sources which degrade radial imaging quality. For a given fixed number of k-space projections, data distributions along radial and angular directions will influence the level of aliasing and streaking artifacts. Conventional radial k-space sampling trajectory introduces an aliasing artifact at the first principal ring of point spread function (PSF). In this paper, a shaking projection (SP) k-space sampling trajectory was proposed to reduce aliasing artifacts in MR images. SP sampling trajectory shifts the projection alternately along the k-space center, which separates k-space data in the azimuthal direction. Simulations based on conventional and SP sampling trajectories were compared with the same number projections. A significant reduction of aliasing artifacts was observed using the SP sampling trajectory. These two trajectories were also compared with different sampling frequencies. A SP trajectory has the same aliasing character when using half sampling frequency (or half data) for reconstruction. SNR comparisons with different white noise levels show that these two trajectories have the same SNR character. In conclusion, the SP trajectory can reduce the aliasing artifact without decreasing SNR and also provide a way for undersampling reconstruction. Furthermore, this method can be applied to three-dimensional (3D) hybrid or spherical radial k-space sampling for a more efficient reduction of aliasing artifacts

Reduction of metal artifacts: beam hardening and photon starvation effects

Science.gov (United States)

Yadava, Girijesh K.; Pal, Debashish; Hsieh, Jiang

2014-03-01

The presence of metal-artifacts in CT imaging can obscure relevant anatomy and interfere with disease diagnosis. The cause and occurrence of metal-artifacts are primarily due to beam hardening, scatter, partial volume and photon starvation; however, the contribution to the artifacts from each of them depends on the type of hardware. A comparison of CT images obtained with different metallic hardware in various applications, along with acquisition and reconstruction parameters, helps understand methods for reducing or overcoming such artifacts. In this work, a metal beam hardening correction (BHC) and a projection-completion based metal artifact reduction (MAR) algorithms were developed, and applied on phantom and clinical CT scans with various metallic implants. Stainless-steel and Titanium were used to model and correct for metal beam hardening effect. In the MAR algorithm, the corrupted projection samples are replaced by the combination of original projections and in-painted data obtained by forward projecting a prior image. The data included spine fixation screws, hip-implants, dental-filling, and body extremity fixations, covering range of clinically used metal implants. Comparison of BHC and MAR on different metallic implants was used to characterize dominant source of the artifacts, and conceivable methods to overcome those. Results of the study indicate that beam hardening could be a dominant source of artifact in many spine and extremity fixations, whereas dental and hip implants could be dominant source of photon starvation. The BHC algorithm could significantly improve image quality in CT scans with metallic screws, whereas MAR algorithm could alleviate artifacts in hip-implants and dentalfillings.

Effects of sample size on robustness and prediction accuracy of a prognostic gene signature

Directory of Open Access Journals (Sweden)

Kim Seon-Young

2009-05-01

Full Text Available Abstract Background Few overlap between independently developed gene signatures and poor inter-study applicability of gene signatures are two of major concerns raised in the development of microarray-based prognostic gene signatures. One recent study suggested that thousands of samples are needed to generate a robust prognostic gene signature. Results A data set of 1,372 samples was generated by combining eight breast cancer gene expression data sets produced using the same microarray platform and, using the data set, effects of varying samples sizes on a few performances of a prognostic gene signature were investigated. The overlap between independently developed gene signatures was increased linearly with more samples, attaining an average overlap of 16.56% with 600 samples. The concordance between predicted outcomes by different gene signatures also was increased with more samples up to 94.61% with 300 samples. The accuracy of outcome prediction also increased with more samples. Finally, analysis using only Estrogen Receptor-positive (ER+ patients attained higher prediction accuracy than using both patients, suggesting that sub-type specific analysis can lead to the development of better prognostic gene signatures Conclusion Increasing sample sizes generated a gene signature with better stability, better concordance in outcome prediction, and better prediction accuracy. However, the degree of performance improvement by the increased sample size was different between the degree of overlap and the degree of concordance in outcome prediction, suggesting that the sample size required for a study should be determined according to the specific aims of the study.

Motion Artifact in the MR imaging of temporomandibular disorders

International Nuclear Information System (INIS)

Tamamura, Kiyoharu; Miyajima, Hisashi; Nihei, Yoshinobu; Nemoto, Ryuichi; Ohno, Tomoya

1997-01-01

Recently, magnetic resonance imaging (MRI) is indispensable for the diagnosis of temporomandibular disorders (TMD). Motion Artifacts of MRI occur more frequently than in other conventional methods, because it takes a long time to obtain the images. This paper reported on Motion Artifacts on MRI. MRI studies of 232 temporomandibular joints were performed in 116 patients with TMD by using a 0.5-T magnetic resonance (MR) scanner, with spin echo sequence: protondensity-weighted. And we took MRI slices at opening phase and closing phase. So 232 slices were gathered and we evaluated clinically the incidence of Motion Artifacts, that is to say, double and multiple images and other factors. The 103 slices in 56 patients showed Motion Artifacts. There is no significant difference between sexes. By age group, those in their teens were most frequent, followed by those in their fifties, forties, thirties and twenties. Also the same results were obtained for double image and multiple image. Incidence of Motion Artifact was most frequent at the opening phase. There is no significant difference between double and multiple image. (author)

Adiabatic Low-Pass J Filters for Artifact Suppression in Heteronuclear NMR

DEFF Research Database (Denmark)

Meier, Sebastian; Benie, Andrew J; Duus, Jens Øllgaard

2009-01-01

NMR artifact purging: Modern NMR experiments depend on efficient coherence transfer pathways for their sensitivity and on suppression of undesired pathways leading to artifacts for their spectral clarity. A novel robust adiabatic element suppresses hard-to-get-at artifacts....

A seven-gene CpG-island methylation panel predicts breast cancer progression

International Nuclear Information System (INIS)

Li, Yan; Melnikov, Anatoliy A.; Levenson, Victor; Guerra, Emanuela; Simeone, Pasquale; Alberti, Saverio; Deng, Youping

2015-01-01

DNA methylation regulates gene expression, through the inhibition/activation of gene transcription of methylated/unmethylated genes. Hence, DNA methylation profiling can capture pivotal features of gene expression in cancer tissues from patients at the time of diagnosis. In this work, we analyzed a breast cancer case series, to identify DNA methylation determinants of metastatic versus non-metastatic tumors. CpG-island methylation was evaluated on a 56-gene cancer-specific biomarker microarray in metastatic versus non-metastatic breast cancers in a multi-institutional case series of 123 breast cancer patients. Global statistical modeling and unsupervised hierarchical clustering were applied to identify a multi-gene binary classifier with high sensitivity and specificity. Network analysis was utilized to quantify the connectivity of the identified genes. Seven genes (BRCA1, DAPK1, MSH2, CDKN2A, PGR, PRKCDBP, RANKL) were found informative for prognosis of metastatic diffusion and were used to calculate classifier accuracy versus the entire data-set. Individual-gene performances showed sensitivities of 63–79 %, 53–84 % specificities, positive predictive values of 59–83 % and negative predictive values of 63–80 %. When modelled together, these seven genes reached a sensitivity of 93 %, 100 % specificity, a positive predictive value of 100 % and a negative predictive value of 93 %, with high statistical power. Unsupervised hierarchical clustering independently confirmed these findings, in close agreement with the accuracy measurements. Network analyses indicated tight interrelationship between the identified genes, suggesting this to be a functionally-coordinated module, linked to breast cancer progression. Our findings identify CpG-island methylation profiles with deep impact on clinical outcome, paving the way for use as novel prognostic assays in clinical settings. The online version of this article (doi:10.1186/s12885-015-1412-9) contains supplementary

Gene Prediction in Metagenomic Fragments with Deep Learning

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Shao-Wu Zhang

2017-01-01

Full Text Available Next generation sequencing technologies used in metagenomics yield numerous sequencing fragments which come from thousands of different species. Accurately identifying genes from metagenomics fragments is one of the most fundamental issues in metagenomics. In this article, by fusing multifeatures (i.e., monocodon usage, monoamino acid usage, ORF length coverage, and Z-curve features and using deep stacking networks learning model, we present a novel method (called Meta-MFDL to predict the metagenomic genes. The results with 10 CV and independent tests show that Meta-MFDL is a powerful tool for identifying genes from metagenomic fragments.

Ring artifacts removal from synchrotron CT image slices

International Nuclear Information System (INIS)

Wei Zhouping; Chapman, Dean; Wiebe, Sheldon

2013-01-01

Ring artifacts can occur in reconstructed images from x-ray Computerized Tomography (CT) as full or partial concentric rings superimposed on the scanned structures. Due to the data corruption by those ring artifacts in CT images, qualitative and quantitative analysis of these images are compromised. In this paper, we propose to correct the ring artifacts on the reconstructed synchrotron radiation (SR) CT image slices. The proposed correction procedure includes the following steps: (1). transform the reconstructed CT images into polar coordinates; (2) apply discrete two-dimensional (2D) wavelet transform to the polar image to decompose it into four image components: low pass band image component, as well as the components from horizontal, vertical and diagonal details bands; (3). apply 2D Fourier transform to the vertical details band image component only, since the ring artifacts become vertical lines in the polar coordinates; (4). apply Gaussian filtering in Fourier domain along the abscissa direction to suppress the vertical lines, since the information of the vertical lines in Fourier domain is completely condensed to that direction; (5). perform inverse Fourier transform to get the corrected vertical details band image component; (6). perform inverse wavelet transform to get the corrected polar image; (7). transform the corrected polar image back to Cartesian coordinates to get the CT image slice with reduced ring artifacts. This approach has been successfully used on CT data acquired from the Biomedical Imaging and Therapy (BMIT) beamline in Canadian Light Source (CLS), and the results show that the ring artifacts in original SR CT images have been effectively suppressed with all the structure information in the image preserved.

Bioinformatics analysis of the predicted polyprenol reductase genes in higher plants

Science.gov (United States)

Basyuni, M.; Wati, R.

2018-03-01

The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.

Grain-boundary, glassy-phase identification and possible artifacts

International Nuclear Information System (INIS)

Simpson, Y.K.; Carter, C.B.; Sklad, P.; Bentley, J.

1985-01-01

Specimen artifacts such as grain boundary grooving, surface damage of the specimen, and Si contamination are shown experimentally to arise from the ion milling used in the preparation of transmission electron microscopy specimens. These artifacts in polycrystalline, ceramic specimens can cause clean grain boundaries to appear to contain a glassy phase when the dark-field diffuse scattering technique, the Fresnel fringe technique, and analytical electron microscopy (energy dispersive spectroscopy) are used to identify glassy phases at a grain boundary. The ambiguity in interpreting each of these techniques due to the ion milling artifacts will be discussed from a theoretical view point and compared to experimental results obtained for alumina

Historical Artifact Collection at the East Tennessee Technology Park

International Nuclear Information System (INIS)

Goodpasture, S.T.; Wood, S.K.

2009-01-01

The East Tennessee Technology Park (ETTP) was originally built during World War II as part of the Manhattan Project. Known as the K-25 Site, its primary mission was to enrich uranium for use in atomic weapons. During the Cold War, the site's mission was changed to include the enrichment of uranium for nuclear reactor fuel elements and to recycle spent fuel. In the 1980's, a reduction in the demand for nuclear fuel resulted in the shutdown of the enrichment process and production ceased. The emphasis of the mission for the ETTP was then changed to environmental management and restoration operation. Beginning in the 1990's, re-industrialization (conversion of under-utilized government facilities for use by the private sector) became a major mission at the ETTP. These activities involve cleaning and demolishing facilities. Decommission and demolition (D and D) of facilities at the ETTP or Manhattan Project K-25 Gaseous Diffusion Plant on the U.S. Department of Energy's (DOE) Oak Ridge Reservation (ORR) presented significant challenges complying with the requirements of the National Historic Preservation Act (NHPA) Memorandum of Agreement (MOA) that was negotiated with the stakeholders. Development of a process to identify, record and preserve the artifacts and the cooperation of several agencies and contractors were critical to completing the collection of the artifacts without impacting the D and D project schedule. Additional challenges included contaminated and classified artifacts, entry to facilities with hazardous conditions, schedule pressures and funding for collection and permanent storage. A process was developed to achieve compliance with the requirements of the NHPA. The NHPA requirements and implementing instruments at the ETTP as well as the process developed to preserve significant Manhattan Project era artifacts at the ETTP will be discussed. Implementation of the artifact collection process is also summarized. The challenge of complying with the

Gene prediction in metagenomic fragments: A large scale machine learning approach

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Morgenstern Burkhard

2008-04-01

Full Text Available Abstract Background Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions. Results We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability. Conclusion Large scale machine learning methods are well-suited for gene

Image statistics and nonlinear artifacts in composed transmission x-ray tomography

International Nuclear Information System (INIS)

Duerinckx, A.J.G.

1979-01-01

Knowledge of the image quality and image statistics in Computed Tomography (CT) images obtained with transmission x-ray CT scanners can increase the amount of clinically useful information that can be retrieved. Artifacts caused by nonlinear shadows are strongly object-dependent and are visible over larger areas of the image. No simple technique exists for their complete elimination. One source of artifacts in the first order statistics is the nonlinearities in the measured shadow or projection data used to reconstruct the image. One of the leading causes is the polychromaticity of the x-ray beam used in transmission CT scanners. Ways to improve the resulting image quality and techniques to extract additional information using dual energy scanning are discussed. A unique formalism consisting of a vector representation of the material dependence of the photon-tissue interactions is generalized to allow an in depth analysis. Poly-correction algorithms are compared using this analytic approach. Both quantum and detector electronic noise decrease the quality or information content of first order statistics. Preliminary results are presented using an heuristic adaptive nonlinear noise filter system for projection data. This filter system can be improved and/or modified to remove artifacts in both first and second order image statistics. Artifacts in the second order image statistics arise from the contribution of quantum noise. This can be described with a nonlinear detection equivalent model, similar to the model used to study artifacts in first order statistics. When analyzing these artifacts in second order statistics, one can divide them into linear artifacts, which do not present any problem of interpretation, and nonlinear artifacts, referred to as noise artifacts. A study of noise artifacts is presented together with a discussion of their relative importance in diagnostic radiology

Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

Science.gov (United States)

Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of EOperon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

A generic EEG artifact removal algorithm based on the multi-channel Wiener filter

Science.gov (United States)

Somers, Ben; Francart, Tom; Bertrand, Alexander

2018-06-01

Objective. The electroencephalogram (EEG) is an essential neuro-monitoring tool for both clinical and research purposes, but is susceptible to a wide variety of undesired artifacts. Removal of these artifacts is often done using blind source separation techniques, relying on a purely data-driven transformation, which may sometimes fail to sufficiently isolate artifacts in only one or a few components. Furthermore, some algorithms perform well for specific artifacts, but not for others. In this paper, we aim to develop a generic EEG artifact removal algorithm, which allows the user to annotate a few artifact segments in the EEG recordings to inform the algorithm. Approach. We propose an algorithm based on the multi-channel Wiener filter (MWF), in which the artifact covariance matrix is replaced by a low-rank approximation based on the generalized eigenvalue decomposition. The algorithm is validated using both hybrid and real EEG data, and is compared to other algorithms frequently used for artifact removal. Main results. The MWF-based algorithm successfully removes a wide variety of artifacts with better performance than current state-of-the-art methods. Significance. Current EEG artifact removal techniques often have limited applicability due to their specificity to one kind of artifact, their complexity, or simply because they are too ‘blind’. This paper demonstrates a fast, robust and generic algorithm for removal of EEG artifacts of various types, i.e. those that were annotated as unwanted by the user.

Artifact Elimination Technique in Tomogram of X-ray Computed Tomography

International Nuclear Information System (INIS)

Rasif Mohd Zain

2015-01-01

Artifacts of tomogram are main commonly problems occurred in x-ray computed tomography. The artifacts will be appearing in tomogram due to noise, beam hardening, and scattered radiation. The study has been carried out using CdTe time pix detector. The new technique has been developed to eliminate the artifact occurred in hardware and software. The hardware setup involved the careful alignment all of the components of the system and the introduction of a collimator beam. Meanwhile, in software development deal with the flat field correction, noise filter and data projection algorithm. The results show the technique developed produce good quality images and eliminate the artifacts. (author)

Analysis and prediction of gene splice sites in four Aspergillus genomes

DEFF Research Database (Denmark)

Wang, Kai; Ussery, David; Brunak, Søren

2009-01-01

Several Aspergillus fungal genomic sequences have been published, with many more in progress. Obviously, it is essential to have high-quality, consistently annotated sets of proteins from each of the genomes, in order to make meaningful comparisons. We have developed a dedicated, publicly available......, splice site prediction program called NetAspGene, for the genus Aspergillus. Gene sequences from Aspergillus fumigatus, the most common mould pathogen, were used to build and test our model. Compared to many animals and plants, Aspergillus contains smaller introns; thus we have applied a larger window...... better splice site prediction than other available tools. NetAspGene will be very helpful for the study in Aspergillus splice sites and especially in alternative splicing. A webpage for NetAspGene is publicly available at http://www.cbs.dtu.dk/services/NetAspGene....

A test of the embodied simulation theory of object perception: potentiation of responses to artifacts and animals.

Science.gov (United States)

Matheson, Heath E; White, Nicole C; McMullen, Patricia A

2014-07-01

Theories of embodied object representation predict a tight association between sensorimotor processes and visual processing of manipulable objects. Previous research has shown that object handles can 'potentiate' a manual response (i.e., button press) to a congruent location. This potentiation effect is taken as evidence that objects automatically evoke sensorimotor simulations in response to the visual presentation of manipulable objects. In the present series of experiments, we investigated a critical prediction of the theory of embodied object representations that potentiation effects should be observed with manipulable artifacts but not non-manipulable animals. In four experiments we show that (a) potentiation effects are observed with animals and artifacts; (b) potentiation effects depend on the absolute size of the objects and (c) task context influences the presence/absence of potentiation effects. We conclude that potentiation effects do not provide evidence for embodied object representations, but are suggestive of a more general stimulus-response compatibility effect that may depend on the distribution of attention to different object features.

Evaluation of alignment error due to a speed artifact in stereotactic ultrasound image guidance

International Nuclear Information System (INIS)

Salter, Bill J; Wang, Brian; Szegedi, Martin W; Rassiah-Szegedi, Prema; Shrieve, Dennis C; Cheng, Roger; Fuss, Martin

2008-01-01

Ultrasound (US) image guidance systems used in radiotherapy are typically calibrated for soft tissue applications, thus introducing errors in depth-from-transducer representation when used in media with a different speed of sound propagation (e.g. fat). This error is commonly referred to as the speed artifact. In this study we utilized a standard US phantom to demonstrate the existence of the speed artifact when using a commercial US image guidance system to image through layers of simulated body fat, and we compared the results with calculated/predicted values. A general purpose US phantom (speed of sound (SOS) = 1540 m s -1 ) was imaged on a multi-slice CT scanner at a 0.625 mm slice thickness and 0.5 mm x 0.5 mm axial pixel size. Target-simulating wires inside the phantom were contoured and later transferred to the US guidance system. Layers of various thickness (1-8 cm) of commercially manufactured fat-simulating material (SOS = 1435 m s -1 ) were placed on top of the phantom to study the depth-related alignment error. In order to demonstrate that the speed artifact is not caused by adding additional layers on top of the phantom, we repeated these measurements in an identical setup using commercially manufactured tissue-simulating material (SOS = 1540 m s -1 ) for the top layers. For the fat-simulating material used in this study, we observed the magnitude of the depth-related alignment errors resulting from the speed artifact to be 0.7 mm cm -1 of fat imaged through. The measured alignment errors caused by the speed artifact agreed with the calculated values within one standard deviation for all of the different thicknesses of fat-simulating material studied here. We demonstrated the depth-related alignment error due to the speed artifact when using US image guidance for radiation treatment alignment and note that the presence of fat causes the target to be aliased to a depth greater than it actually is. For typical US guidance systems in use today, this will

Evaluation of alignment error due to a speed artifact in stereotactic ultrasound image guidance.

Science.gov (United States)

Salter, Bill J; Wang, Brian; Szegedi, Martin W; Rassiah-Szegedi, Prema; Shrieve, Dennis C; Cheng, Roger; Fuss, Martin

2008-12-07

Ultrasound (US) image guidance systems used in radiotherapy are typically calibrated for soft tissue applications, thus introducing errors in depth-from-transducer representation when used in media with a different speed of sound propagation (e.g. fat). This error is commonly referred to as the speed artifact. In this study we utilized a standard US phantom to demonstrate the existence of the speed artifact when using a commercial US image guidance system to image through layers of simulated body fat, and we compared the results with calculated/predicted values. A general purpose US phantom (speed of sound (SOS) = 1540 m s(-1)) was imaged on a multi-slice CT scanner at a 0.625 mm slice thickness and 0.5 mm x 0.5 mm axial pixel size. Target-simulating wires inside the phantom were contoured and later transferred to the US guidance system. Layers of various thickness (1-8 cm) of commercially manufactured fat-simulating material (SOS = 1435 m s(-1)) were placed on top of the phantom to study the depth-related alignment error. In order to demonstrate that the speed artifact is not caused by adding additional layers on top of the phantom, we repeated these measurements in an identical setup using commercially manufactured tissue-simulating material (SOS = 1540 m s(-1)) for the top layers. For the fat-simulating material used in this study, we observed the magnitude of the depth-related alignment errors resulting from the speed artifact to be 0.7 mm cm(-1) of fat imaged through. The measured alignment errors caused by the speed artifact agreed with the calculated values within one standard deviation for all of the different thicknesses of fat-simulating material studied here. We demonstrated the depth-related alignment error due to the speed artifact when using US image guidance for radiation treatment alignment and note that the presence of fat causes the target to be aliased to a depth greater than it actually is. For typical US guidance systems in use today, this will

The Information Systems Artifact

DEFF Research Database (Denmark)

Chatterjee, Surtirtha; Xiao, Xiao; Elbanna, Amany

2017-01-01

Passionate debates regarding the defining characteristic of the “IT artifact” continue. Such debates, and also the lack of explicit consideration of the “information” element in the IT artifact, motivate us to propose a revised conception, drawing upon concepts from General Systems Theory (GST). ...

A dialectical take on artifact ecologies and the physical - digital divide

DEFF Research Database (Denmark)

Bødker, Susanne; Klokmose, Clemens Nylandsted

In this position paper, we will present and discuss our understanding of artifact ecologies as we have developed it, rooted in activity theoretical HCI and dialectical thinking . Our basis is in the Human-Artifact Model, as well as well as cases where we have worked with artifact ecologies...

Bioinformatic prediction and functional characterization of human KIAA0100 gene

Directory of Open Access Journals (Sweden)

He Cui

2017-02-01

Full Text Available Our previous study demonstrated that human KIAA0100 gene was a novel acute monocytic leukemia-associated antigen (MLAA gene. But the functional characterization of human KIAA0100 gene has remained unknown to date. Here, firstly, bioinformatic prediction of human KIAA0100 gene was carried out using online softwares; Secondly, Human KIAA0100 gene expression was downregulated by the clustered regularly interspaced short palindromic repeats (CRISPR/CRISPR-associated (Cas 9 system in U937 cells. Cell proliferation and apoptosis were next evaluated in KIAA0100-knockdown U937 cells. The bioinformatic prediction showed that human KIAA0100 gene was located on 17q11.2, and human KIAA0100 protein was located in the secretory pathway. Besides, human KIAA0100 protein contained a signalpeptide, a transmembrane region, three types of secondary structures (alpha helix, extended strand, and random coil , and four domains from mitochondrial protein 27 (FMP27. The observation on functional characterization of human KIAA0100 gene revealed that its downregulation inhibited cell proliferation, and promoted cell apoptosis in U937 cells. To summarize, these results suggest human KIAA0100 gene possibly comes within mitochondrial genome; moreover, it is a novel anti-apoptotic factor related to carcinogenesis or progression in acute monocytic leukemia, and may be a potential target for immunotherapy against acute monocytic leukemia.

Towards a concept of community artifact ecology in HCI?

DEFF Research Database (Denmark)

Saad-Sulonen, Joanna; Korsgaard, Henrik

or workplaces do. This has implications on understanding how to research and design HCI for communities but also on refining the ecological perspective in HCI. We look in particular at examples from preliminary research on a local self-organised urban community and discuss what existing concepts in the ecology......In this paper we introduce the concept of community artifact ecology. We argue that taking a community perspective on the concept of artifact ecologies is relevant in HCI because communities are also dealing with multitudes of artifacts, in ways di↵erent that individuals, organizations...

Thermoluminescent determination of prehistoric heat treatment of chert artifacts

International Nuclear Information System (INIS)

Melcher, C.L.; Zimmerman, D.W.

1977-01-01

In recent years archeologists have become interested in the extent to which prehistoric peoples heat-treated chert prior to shaping it into tools. Thermoluminescent determination of the radiation dose accumulated by an artifact since it was formed or last heated provides a simple, reliable test for such heat treatment. This test can be applied to single artifacts without the need for raw source material for comparison. Results on 25 artifacts from four sites indicate that, for many chert sources, color and luster are not useful indicators of heat treatment by prehistoric peoples

Panning artifacts in digital pathology images

Science.gov (United States)

Avanaki, Ali R. N.; Lanciault, Christian; Espig, Kathryn S.; Xthona, Albert; Kimpe, Tom R. L.

2017-03-01

In making a pathologic diagnosis, a pathologist uses cognitive processes: perception, attention, memory, and search (Pena and Andrade-Filho, 2009). Typically, this involves focus while panning from one region of a slide to another, using either a microscope in a traditional workflow or software program and display in a digital pathology workflow (DICOM Standard Committee, 2010). We theorize that during panning operation, the pathologist receives information important to diagnosis efficiency and/or correctness. As compared to an optical microscope, panning in a digital pathology image involves some visual artifacts due to the following: (i) the frame rate is finite; (ii) time varying visual signals are reconstructed using imperfect zero-order hold. Specifically, after pixel's digital drive is changed, it takes time for a pixel to emit the expected amount of light. Previous work suggests that 49% of navigation is conducted in low-power/overview with digital pathology (Molin et al., 2015), but the influence of display factors has not been measured. We conducted a reader study to establish a relationship between display frame rate, panel response time, and threshold panning speed (above which the artifacts become noticeable). Our results suggest visual tasks that involve tissue structure are more impacted by the simulated panning artifacts than those that only involve color (e.g., staining intensity estimation), and that the panning artifacts versus normalized panning speed has a peak behavior which is surprising and may change for a diagnostic task. This is work in progress and our final findings should be considered in designing future digital pathology systems.

Computational prediction and experimental validation of Ciona intestinalis microRNA genes

Directory of Open Access Journals (Sweden)

Pasquinelli Amy E

2007-11-01

Full Text Available Abstract Background This study reports the first collection of validated microRNA genes in the sea squirt, Ciona intestinalis. MicroRNAs are processed from hairpin precursors to ~22 nucleotide RNAs that base pair to target mRNAs and inhibit expression. As a member of the subphylum Urochordata (Tunicata whose larval form has a notochord, the sea squirt is situated at the emergence of vertebrates, and therefore may provide information about the evolution of molecular regulators of early development. Results In this study, computational methods were used to predict 14 microRNA gene families in Ciona intestinalis. The microRNA prediction algorithm utilizes configurable microRNA sequence conservation and stem-loop specificity parameters, grouping by miRNA family, and phylogenetic conservation to the related species, Ciona savignyi. The expression for 8, out of 9 attempted, of the putative microRNAs in the adult tissue of Ciona intestinalis was validated by Northern blot analyses. Additionally, a target prediction algorithm was implemented, which identified a high confidence list of 240 potential target genes. Over half of the predicted targets can be grouped into the gene ontology categories of metabolism, transport, regulation of transcription, and cell signaling. Conclusion The computational techniques implemented in this study can be applied to other organisms and serve to increase the understanding of the origins of non-coding RNAs, embryological and cellular developmental pathways, and the mechanisms for microRNA-controlled gene regulatory networks.

GOPET: A tool for automated predictions of Gene Ontology terms

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Glatting Karl-Heinz

2006-03-01

Full Text Available Abstract Background Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. Description We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO. Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool. It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar Conclusion Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

Spectral CT metal artifact reduction with an optimization-based reconstruction algorithm

Science.gov (United States)

Gilat Schmidt, Taly; Barber, Rina F.; Sidky, Emil Y.

2017-03-01

Metal objects cause artifacts in computed tomography (CT) images. This work investigated the feasibility of a spectral CT method to reduce metal artifacts. Spectral CT acquisition combined with optimization-based reconstruction is proposed to reduce artifacts by modeling the physical effects that cause metal artifacts and by providing the flexibility to selectively remove corrupted spectral measurements in the spectral-sinogram space. The proposed Constrained `One-Step' Spectral CT Image Reconstruction (cOSSCIR) algorithm directly estimates the basis material maps while enforcing convex constraints. The incorporation of constraints on the reconstructed basis material maps is expected to mitigate undersampling effects that occur when corrupted data is excluded from reconstruction. The feasibility of the cOSSCIR algorithm to reduce metal artifacts was investigated through simulations of a pelvis phantom. The cOSSCIR algorithm was investigated with and without the use of a third basis material representing metal. The effects of excluding data corrupted by metal were also investigated. The results demonstrated that the proposed cOSSCIR algorithm reduced metal artifacts and improved CT number accuracy. For example, CT number error in a bright shading artifact region was reduced from 403 HU in the reference filtered backprojection reconstruction to 33 HU using the proposed algorithm in simulation. In the dark shading regions, the error was reduced from 1141 HU to 25 HU. Of the investigated approaches, decomposing the data into three basis material maps and excluding the corrupted data demonstrated the greatest reduction in metal artifacts.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

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Zhili He

2018-02-01

Full Text Available Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN, representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5 increased significantly (P < 0.05 as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.

Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

International Nuclear Information System (INIS)

Karlsson, Elin; Delle, Ulla; Danielsson, Anna; Olsson, Björn; Abel, Frida; Karlsson, Per; Helou, Khalil

2008-01-01

It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. The research on these tumours was approved by the Medical Faculty Research

An ensemble method to predict target genes and pathways in uveal melanoma

Directory of Open Access Journals (Sweden)

Wei Chao

2018-04-01

Full Text Available This work proposes to predict target genes and pathways for uveal melanoma (UM based on an ensemble method and pathway analyses. Methods: The ensemble method integrated a correlation method (Pearson correlation coefficient, PCC, a causal inference method (IDA and a regression method (Lasso utilizing the Borda count election method. Subsequently, to validate the performance of PIL method, comparisons between confirmed database and predicted miRNA targets were performed. Ultimately, pathway enrichment analysis was conducted on target genes in top 1000 miRNA-mRNA interactions to identify target pathways for UM patients. Results: Thirty eight of the predicted interactions were matched with the confirmed interactions, indicating that the ensemble method was a suitable and feasible approach to predict miRNA targets. We obtained 50 seed miRNA-mRNA interactions of UM patients and extracted target genes from these interactions, such as ASPG, BSDC1 and C4BP. The 601 target genes in top 1,000 miRNA-mRNA interactions were enriched in 12 target pathways, of which Phototransduction was the most significant one. Conclusion: The target genes and pathways might provide a new way to reveal the molecular mechanism of UM and give hand for target treatments and preventions of this malignant tumor.

Phylogenomic detection and functional prediction of genes potentially important for plant meiosis.

Science.gov (United States)

Zhang, Luoyan; Kong, Hongzhi; Ma, Hong; Yang, Ji

2018-02-15

Meiosis is a specialized type of cell division necessary for sexual reproduction in eukaryotes. A better understanding of the cytological procedures of meiosis has been achieved by comprehensive cytogenetic studies in plants, while the genetic mechanisms regulating meiotic progression remain incompletely understood. The increasing accumulation of complete genome sequences and large-scale gene expression datasets has provided a powerful resource for phylogenomic inference and unsupervised identification of genes involved in plant meiosis. By integrating sequence homology and expression data, 164, 131, 124 and 162 genes potentially important for meiosis were identified in the genomes of Arabidopsis thaliana, Oryza sativa, Selaginella moellendorffii and Pogonatum aloides, respectively. The predicted genes were assigned to 45 meiotic GO terms, and their functions were related to different processes occurring during meiosis in various organisms. Most of the predicted meiotic genes underwent lineage-specific duplication events during plant evolution, with about 30% of the predicted genes retaining only a single copy in higher plant genomes. The results of this study provided clues to design experiments for better functional characterization of meiotic genes in plants, promoting the phylogenomic approach to the evolutionary dynamics of the plant meiotic machineries. Copyright © 2017 Elsevier B.V. All rights reserved.

The integration of weighted human gene association networks based on link prediction.

Science.gov (United States)

Yang, Jian; Yang, Tinghong; Wu, Duzhi; Lin, Limei; Yang, Fan; Zhao, Jing

2017-01-31

Physical and functional interplays between genes or proteins have important biological meaning for cellular functions. Some efforts have been made to construct weighted gene association meta-networks by integrating multiple biological resources, where the weight indicates the confidence of the interaction. However, it is found that these existing human gene association networks share only quite limited overlapped interactions, suggesting their incompleteness and noise. Here we proposed a workflow to construct a weighted human gene association network using information of six existing networks, including two weighted specific PPI networks and four gene association meta-networks. We applied link prediction algorithm to predict possible missing links of the networks, cross-validation approach to refine each network and finally integrated the refined networks to get the final integrated network. The common information among the refined networks increases notably, suggesting their higher reliability. Our final integrated network owns much more links than most of the original networks, meanwhile its links still keep high functional relevance. Being used as background network in a case study of disease gene prediction, the final integrated network presents good performance, implying its reliability and application significance. Our workflow could be insightful for integrating and refining existing gene association data.

An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

Science.gov (United States)

Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

Predictive value of MSH2 gene expression in colorectal cancer treated with capecitabine

DEFF Research Database (Denmark)

Jensen, Lars H; Danenberg, Kathleen D; Danenberg, Peter V

2007-01-01

was associated with a hazard ratio of 0.5 (95% confidence interval, 0.23-1.11; P = 0.083) in survival analysis. CONCLUSION: The higher gene expression of MSH2 in responders and the trend for predicting overall survival indicates a predictive value of this marker in the treatment of advanced CRC with capecitabine.......PURPOSE: The objective of the present study was to evaluate the gene expression of the DNA mismatch repair gene MSH2 as a predictive marker in advanced colorectal cancer (CRC) treated with first-line capecitabine. PATIENTS AND METHODS: Microdissection of paraffin-embedded tumor tissue, RNA...

WE-D-18C-01: Art of Imaging: Diagnostic Ultrasound Image Artifacts

Energy Technology Data Exchange (ETDEWEB)

Zagzebski, J [University of Wisconsin, Madison, WI (United States); Lu, Z [University of Chicago, Chicago, IL (United States)

2014-06-15

Assumptions followed during construction of B-mode and color flow images are that the pulse-echo transit time can be converted to reflector depth through uniform tissue models, echoes originate only from locations along the transmit-receive axes of pulse propagation, and first order correction schemes adequately account for acoustic wave attenuation and absorption. The latter allows the display brightness to encode tissue echogenicity. This course will challenge participants to identify imaging artifacts whose origins stem from the more complex and realistic propagating and scattering conditions common in clinical ultrasound. Speckle, a very common artifact but a clinically employed feature, originates from simultaneous echoes from diffuse scatterers and is a result of coherent detection of signals. One of the most bothersome artifacts are those due to reverberations especially that originating from superficial tissue interfaces. Methods to overcome these will be discussed. This presentation also will describe and illustrate speed of sound, refraction, enhancement, shadowing, mirroring, beam width, beam-forming, and slice thickness artifacts. All are useful examples of limitations introduced by acoustic waves propagating through complex tissue paths. New formats for physician board certification exams are demanding the inclusion of image-based examples of ultrasound physics. Instructors' knowledge of, and access to examples of ultrasound artifacts are important in this effort. The presentation will incorporate an audience response system to challenge participants in correct identification of some of these artifacts. Learning Objectives: Review basic mechanisms for producing ultrasound images. Identify the etiology of speckle, reverberation noise, beam width and slice thickness artifacts, and artifacts associated with pulse propagation. Discuss methods that reduce the impact of artifacts OR employ artifacts effectively to facilitate clinical diagnosis.

A level set method for cupping artifact correction in cone-beam CT

International Nuclear Information System (INIS)

Xie, Shipeng; Li, Haibo; Ge, Qi; Li, Chunming

2015-01-01

Purpose: To reduce cupping artifacts and improve the contrast-to-noise ratio in cone-beam computed tomography (CBCT). Methods: A level set method is proposed to reduce cupping artifacts in the reconstructed image of CBCT. The authors derive a local intensity clustering property of the CBCT image and define a local clustering criterion function of the image intensities in a neighborhood of each point. This criterion function defines an energy in terms of the level set functions, which represent a segmentation result and the cupping artifacts. The cupping artifacts are estimated as a result of minimizing this energy. Results: The cupping artifacts in CBCT are reduced by an average of 90%. The results indicate that the level set-based algorithm is practical and effective for reducing the cupping artifacts and preserving the quality of the reconstructed image. Conclusions: The proposed method focuses on the reconstructed image without requiring any additional physical equipment, is easily implemented, and provides cupping correction through a single-scan acquisition. The experimental results demonstrate that the proposed method successfully reduces the cupping artifacts

Making Digital Artifacts on the Web Verifiable and Reliable

NARCIS (Netherlands)

Kuhn, T.; Dumontier, M.

2015-01-01

The current Web has no general mechanisms to make digital artifacts - such as datasets, code, texts, and images - verifiable and permanent. For digital artifacts that are supposed to be immutable, there is moreover no commonly accepted method to enforce this immutability. These shortcomings have a

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

Science.gov (United States)

Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

2017-11-24

Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

Predictive modelling of gene expression from transcriptional regulatory elements.

Science.gov (United States)

Budden, David M; Hurley, Daniel G; Crampin, Edmund J

2015-07-01

Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent studies have demonstrated the utility of such models in identifying dysregulation of gene and miRNA expression associated with abnormal patterns of transcription factor (TF) binding or nucleosomal histone modifications (HMs). Despite the growing popularity of such approaches, a comparative review of the various modelling algorithms and feature extraction methods is lacking. We define and compare three methods of quantifying pairwise gene-TF/HM interactions and discuss their suitability for integrating the heterogeneous chromatin immunoprecipitation (ChIP)-seq binding patterns exhibited by TFs and HMs. We then construct log-linear and ϵ-support vector regression models from various mouse embryonic stem cell (mESC) and human lymphoblastoid (GM12878) data sets, considering both ChIP-seq- and position weight matrix- (PWM)-derived in silico TF-binding. The two algorithms are evaluated both in terms of their modelling prediction accuracy and ability to identify the established regulatory roles of individual TFs and HMs. Our results demonstrate that TF-binding and HMs are highly predictive of gene expression as measured by mRNA transcript abundance, irrespective of algorithm or cell type selection and considering both ChIP-seq and PWM-derived TF-binding. As we encourage other researchers to explore and develop these results, our framework is implemented using open-source software and made available as a preconfigured bootable virtual environment. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

An evaluation of three commercially available metal artifact reduction methods for CT imaging

International Nuclear Information System (INIS)

Huang, Jessie Y; Kerns, James R; Balter, Peter A; Followill, David S; Mirkovic, Dragan; Howell, Rebecca M; Kry, Stephen F; Nute, Jessica L; Liu, Xinming; Stingo, Francesco C

2015-01-01

Three commercial metal artifact reduction methods were evaluated for use in computed tomography (CT) imaging in the presence of clinically realistic metal implants: Philips O-MAR, GE’s monochromatic gemstone spectral imaging (GSI) using dual-energy CT, and GSI monochromatic imaging with metal artifact reduction software applied (MARs). Each method was evaluated according to CT number accuracy, metal size accuracy, and streak artifact severity reduction by using several phantoms, including three anthropomorphic phantoms containing metal implants (hip prosthesis, dental fillings and spinal fixation rods). All three methods showed varying degrees of success for the hip prosthesis and spinal fixation rod cases, while none were particularly beneficial for dental artifacts. Limitations of the methods were also observed. MARs underestimated the size of metal implants and introduced new artifacts in imaging planes beyond the metal implant when applied to dental artifacts, and both the O-MAR and MARs algorithms induced artifacts for spinal fixation rods in a thoracic phantom. Our findings suggest that all three artifact mitigation methods may benefit patients with metal implants, though they should be used with caution in certain scenarios. (paper)

Clustering gene expression data based on predicted differential effects of GV interaction.

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Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

Artifacts

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Harris, Samantha

2009-01-01

NASA Headquarters sent a list of items to KSC that were deemed potential artifacts. These items played arole in the Shuttle Program's development and maintenance. Because these items are national assets, many are of interest to museums, schools, other government entities, etc. upon the Space Shuttle's retirement. The list contains over 500 items. All of these items need to be located, photographed, and catalogued with accompanying specific data that needs to be gathered. Initial research suggests that this is a time, labor, and cost intensive project. The purpose of my project was to focus on 20-60 of these 500 items, gather the necessary data, and compile them in a way that can be added to by other users when/if the project goes into full effect.

Spectral CT with monochromatic imaging and metal artifacts reduction software for artifacts reduction of ¹²⁵I radioactive seeds in liver brachytherapy.

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Yang, Qiuxia; Peng, Sheng; Wu, Jing; Ban, Xiaohua; He, Mingyan; Xie, Chuanmiao; Zhang, Rong

2015-11-01

To investigate the optimal monochromatic energy for artifacts reduction from (125)I seeds as well as image improvement in the vicinity of seeds on monochromatic images with and without metal artifacts reduction software (MARS) and to compare this with traditional 120-kVp images, so as to evaluate the application value of gemstone spectral imaging for reducing artifacts from (125)I seeds in liver brachytherapy. A total of 45 tumors from 25 patients treated with (125)I seed brachytherapy in the liver were enrolled in this study. Multiphasic spectral computed tomography (CT) scanning was performed for each patient. After a delay time of 15 s of portal vein phase, a traditional 120-kVp scan was performed, focusing on several planes of (125)I seeds only. The artifact index (AI) in the vicinity of seeds and the standard deviation (SD) of the CT density of region of interest in the outside liver parenchyma were calculated. Artifact appearance was evaluated and classified on reconstructed monochromatic S and 120-kVp images. Image quality in the vicinity of seeds of three data sets were evaluated using a 1-5 scale scoring method. The Friedman rank-sum test was used to estimate the scoring results of image quality. The greatest noise in monochromatic images was found at 40 keV (SD = 27.38, AI = 206.40). The optimal monochromatic energy was found at 75 keV, which provided almost the least image noise (SD = 10.01) and good performance in artifact reduction (AI = 102.73). Image noise and AI reduction at 75 keV was decreased by 63.44 and 50.23%, compared with at 40 keV. Near-field thick artifacts were obvious in all 45 lesions, in 120-kVp images, and 75-keV images, but basically reduced in 75 keV MARS images and artifacts completely invisible in 7 lesions. The number of diagnosable images (score ≥3) was significantly more in the 75-keV MARS group (28/45), and the 75-keV group (22/45) than in the 120-kVp group (11/45) (p improve image quality, even to a state of being

Deep learning methods for CT image-domain metal artifact reduction

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Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Shan, Hongming; Claus, Bernhard; Jin, Yannan; De Man, Bruno; Wang, Ge

2017-09-01

Artifacts resulting from metal objects have been a persistent problem in CT images over the last four decades. A common approach to overcome their effects is to replace corrupt projection data with values synthesized from an interpolation scheme or by reprojection of a prior image. State-of-the-art correction methods, such as the interpolation- and normalization-based algorithm NMAR, often do not produce clinically satisfactory results. Residual image artifacts remain in challenging cases and even new artifacts can be introduced by the interpolation scheme. Metal artifacts continue to be a major impediment, particularly in radiation and proton therapy planning as well as orthopedic imaging. A new solution to the long-standing metal artifact reduction (MAR) problem is deep learning, which has been successfully applied to medical image processing and analysis tasks. In this study, we combine a convolutional neural network (CNN) with the state-of-the-art NMAR algorithm to reduce metal streaks in critical image regions. Training data was synthesized from CT simulation scans of a phantom derived from real patient images. The CNN is able to map metal-corrupted images to artifact-free monoenergetic images to achieve additional correction on top of NMAR for improved image quality. Our results indicate that deep learning is a novel tool to address CT reconstruction challenges, and may enable more accurate tumor volume estimation for radiation therapy planning.

MED: a new non-supervised gene prediction algorithm for bacterial and archaeal genomes

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Yang Yi-Fan

2007-03-01

Full Text Available Abstract Background Despite a remarkable success in the computational prediction of genes in Bacteria and Archaea, a lack of comprehensive understanding of prokaryotic gene structures prevents from further elucidation of differences among genomes. It continues to be interesting to develop new ab initio algorithms which not only accurately predict genes, but also facilitate comparative studies of prokaryotic genomes. Results This paper describes a new prokaryotic genefinding algorithm based on a comprehensive statistical model of protein coding Open Reading Frames (ORFs and Translation Initiation Sites (TISs. The former is based on a linguistic "Entropy Density Profile" (EDP model of coding DNA sequence and the latter comprises several relevant features related to the translation initiation. They are combined to form a so-called Multivariate Entropy Distance (MED algorithm, MED 2.0, that incorporates several strategies in the iterative program. The iterations enable us to develop a non-supervised learning process and to obtain a set of genome-specific parameters for the gene structure, before making the prediction of genes. Conclusion Results of extensive tests show that MED 2.0 achieves a competitive high performance in the gene prediction for both 5' and 3' end matches, compared to the current best prokaryotic gene finders. The advantage of the MED 2.0 is particularly evident for GC-rich genomes and archaeal genomes. Furthermore, the genome-specific parameters given by MED 2.0 match with the current understanding of prokaryotic genomes and may serve as tools for comparative genomic studies. In particular, MED 2.0 is shown to reveal divergent translation initiation mechanisms in archaeal genomes while making a more accurate prediction of TISs compared to the existing gene finders and the current GenBank annotation.

Cell-specific prediction and application of drug-induced gene expression profiles.

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Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

2018-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

Adipose gene expression prior to weight loss can differentiate and weakly predict dietary responders.

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David M Mutch

Full Text Available BACKGROUND: The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. METHODOLOGY/PRINCIPAL FINDINGS: The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8-12 kgs weight loss could always be differentiated from non-responders (<4 kgs weight loss. We also assessed whether this differentiation was sufficient for prediction. Using a bottom-up (i.e. black-box approach, standard class prediction algorithms were able to predict dietary responders with up to 61.1%+/-8.1% accuracy. Using a top-down approach (i.e. using differentially expressed genes to build a classifier improved prediction accuracy to 80.9%+/-2.2%. CONCLUSION: Adipose gene expression profiling prior to the consumption of a low-fat diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition.

SU-F-J-74: High Z Geometric Integrity and Beam Hardening Artifact Assessment Using a Retrospective Metal Artifact Reduction (MAR) Reconstruction Algorithm

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Woods, K; DiCostanzo, D; Gupta, N [Ohio State University Columbus, OH (United States)

2016-06-15

Purpose: To test the efficacy of a retrospective metal artifact reduction (MAR) reconstruction algorithm for a commercial computed tomography (CT) scanner for radiation therapy purposes. Methods: High Z geometric integrity and artifact reduction analysis was performed with three phantoms using General Electric’s (GE) Discovery CT. The three phantoms included: a Computerized Imaging Reference Systems (CIRS) electron density phantom (Model 062) with a 6.5 mm diameter titanium rod insert, a custom spine phantom using Synthes Spine hardware submerged in water, and a dental phantom with various high Z fillings submerged in water. Each phantom was reconstructed using MAR and compared against the original scan. Furthermore, each scenario was tested using standard and extended Hounsfield Unit (HU) ranges. High Z geometric integrity was performed using the CIRS phantom, while the artifact reduction was performed using all three phantoms. Results: Geometric integrity of the 6.5 mm diameter rod was slightly overestimated for non-MAR scans for both standard and extended HU. With MAR reconstruction, the rod was underestimated for both standard and extended HU. For artifact reduction, the mean and standard deviation was compared in a volume of interest (VOI) in the surrounding material (water and water equivalent material, ∼0HU). Overall, the mean value of the VOI was closer to 0 HU for the MAR reconstruction compared to the non-MAR scan for most phantoms. Additionally, the standard deviations for all phantoms were greatly reduced using MAR reconstruction. Conclusion: GE’s MAR reconstruction algorithm improves image quality with the presence of high Z material with minimal degradation of its geometric integrity. High Z delineation can be carried out with proper contouring techniques. The effects of beam hardening artifacts are greatly reduced with MAR reconstruction. Tissue corrections due to these artifacts can be eliminated for simple high Z geometries and greatly

SU-F-J-74: High Z Geometric Integrity and Beam Hardening Artifact Assessment Using a Retrospective Metal Artifact Reduction (MAR) Reconstruction Algorithm

International Nuclear Information System (INIS)

Woods, K; DiCostanzo, D; Gupta, N

2016-01-01

Purpose: To test the efficacy of a retrospective metal artifact reduction (MAR) reconstruction algorithm for a commercial computed tomography (CT) scanner for radiation therapy purposes. Methods: High Z geometric integrity and artifact reduction analysis was performed with three phantoms using General Electric’s (GE) Discovery CT. The three phantoms included: a Computerized Imaging Reference Systems (CIRS) electron density phantom (Model 062) with a 6.5 mm diameter titanium rod insert, a custom spine phantom using Synthes Spine hardware submerged in water, and a dental phantom with various high Z fillings submerged in water. Each phantom was reconstructed using MAR and compared against the original scan. Furthermore, each scenario was tested using standard and extended Hounsfield Unit (HU) ranges. High Z geometric integrity was performed using the CIRS phantom, while the artifact reduction was performed using all three phantoms. Results: Geometric integrity of the 6.5 mm diameter rod was slightly overestimated for non-MAR scans for both standard and extended HU. With MAR reconstruction, the rod was underestimated for both standard and extended HU. For artifact reduction, the mean and standard deviation was compared in a volume of interest (VOI) in the surrounding material (water and water equivalent material, ∼0HU). Overall, the mean value of the VOI was closer to 0 HU for the MAR reconstruction compared to the non-MAR scan for most phantoms. Additionally, the standard deviations for all phantoms were greatly reduced using MAR reconstruction. Conclusion: GE’s MAR reconstruction algorithm improves image quality with the presence of high Z material with minimal degradation of its geometric integrity. High Z delineation can be carried out with proper contouring techniques. The effects of beam hardening artifacts are greatly reduced with MAR reconstruction. Tissue corrections due to these artifacts can be eliminated for simple high Z geometries and greatly

Automated Classification and Removal of EEG Artifacts With SVM and Wavelet-ICA.

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Sai, Chong Yeh; Mokhtar, Norrima; Arof, Hamzah; Cumming, Paul; Iwahashi, Masahiro

2018-05-01

Brain electrical activity recordings by electroencephalography (EEG) are often contaminated with signal artifacts. Procedures for automated removal of EEG artifacts are frequently sought for clinical diagnostics and brain-computer interface applications. In recent years, a combination of independent component analysis (ICA) and discrete wavelet transform has been introduced as standard technique for EEG artifact removal. However, in performing the wavelet-ICA procedure, visual inspection or arbitrary thresholding may be required for identifying artifactual components in the EEG signal. We now propose a novel approach for identifying artifactual components separated by wavelet-ICA using a pretrained support vector machine (SVM). Our method presents a robust and extendable system that enables fully automated identification and removal of artifacts from EEG signals, without applying any arbitrary thresholding. Using test data contaminated by eye blink artifacts, we show that our method performed better in identifying artifactual components than did existing thresholding methods. Furthermore, wavelet-ICA in conjunction with SVM successfully removed target artifacts, while largely retaining the EEG source signals of interest. We propose a set of features including kurtosis, variance, Shannon's entropy, and range of amplitude as training and test data of SVM to identify eye blink artifacts in EEG signals. This combinatorial method is also extendable to accommodate multiple types of artifacts present in multichannel EEG. We envision future research to explore other descriptive features corresponding to other types of artifactual components.

Simulation-based artifact correction (SBAC) for metrological computed tomography

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Maier, Joscha; Leinweber, Carsten; Sawall, Stefan; Stoschus, Henning; Ballach, Frederic; Müller, Tobias; Hammer, Michael; Christoph, Ralf; Kachelrieß, Marc

2017-06-01

Computed tomography (CT) is a valuable tool for the metrolocical assessment of industrial components. However, the application of CT to the investigation of highly attenuating objects or multi-material components is often restricted by the presence of CT artifacts caused by beam hardening, x-ray scatter, off-focal radiation, partial volume effects or the cone-beam reconstruction itself. In order to overcome this limitation, this paper proposes an approach to calculate a correction term that compensates for the contribution of artifacts and thus enables an appropriate assessment of these components using CT. Therefore, we make use of computer simulations of the CT measurement process. Based on an appropriate model of the object, e.g. an initial reconstruction or a CAD model, two simulations are carried out. One simulation considers all physical effects that cause artifacts using dedicated analytic methods as well as Monte Carlo-based models. The other one represents an ideal CT measurement i.e. a measurement in parallel beam geometry with a monochromatic, point-like x-ray source and no x-ray scattering. Thus, the difference between these simulations is an estimate for the present artifacts and can be used to correct the acquired projection data or the corresponding CT reconstruction, respectively. The performance of the proposed approach is evaluated using simulated as well as measured data of single and multi-material components. Our approach yields CT reconstructions that are nearly free of artifacts and thereby clearly outperforms commonly used artifact reduction algorithms in terms of image quality. A comparison against tactile reference measurements demonstrates the ability of the proposed approach to increase the accuracy of the metrological assessment significantly.

Adaptive noise canceling of electrocardiogram artifacts in single channel electroencephalogram.

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Cho, Sung Pil; Song, Mi Hye; Park, Young Cheol; Choi, Ho Seon; Lee, Kyoung Joung

2007-01-01

A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.

Medical image of the week: DBS polysomnogram artifact

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Shetty S,

2015-10-01

Full Text Available A 79-year-old man with known Parkinson’s disease and status post deep brain stimulator (DBS implantation underwent an overnight polysomnogram for clinical suspicion of obstructive sleep apnea. Artifact was seen on the polysomnogram recording (Figures 1 & 2. Patient-related electrical artifacts may be seen from devices such as pacemakers, deep brain stimulators and vagal nerve simulators. Abrupt discontinuation of DBS is associated with a high likelihood of worsening of symptoms in patients with Parkinson’s disease (1. Patients with DBS are most commonly programmed in monopolar mode. Bipolar configuration, forms a short electrical dipole that affects a relatively smaller volume of tissue and generates far less artifact, suggesting that this may be an effective option in a Parkinsonian patient with indications for polysomnography (2.

Metal artifact reduction algorithm based on model images and spatial information

Energy Technology Data Exchange (ETDEWEB)

Wu, Jay [Institute of Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan (China); Shih, Cheng-Ting [Department of Biomedical Engineering and Environmental Sciences, National Tsing-Hua University, Hsinchu, Taiwan (China); Chang, Shu-Jun [Health Physics Division, Institute of Nuclear Energy Research, Taoyuan, Taiwan (China); Huang, Tzung-Chi [Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan (China); Sun, Jing-Yi [Institute of Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan (China); Wu, Tung-Hsin, E-mail: tung@ym.edu.tw [Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, No.155, Sec. 2, Linong Street, Taipei 112, Taiwan (China)

2011-10-01

Computed tomography (CT) has become one of the most favorable choices for diagnosis of trauma. However, high-density metal implants can induce metal artifacts in CT images, compromising image quality. In this study, we proposed a model-based metal artifact reduction (MAR) algorithm. First, we built a model image using the k-means clustering technique with spatial information and calculated the difference between the original image and the model image. Then, the projection data of these two images were combined using an exponential weighting function. At last, the corrected image was reconstructed using the filter back-projection algorithm. Two metal-artifact contaminated images were studied. For the cylindrical water phantom image, the metal artifact was effectively removed. The mean CT number of water was improved from -28.95{+-}97.97 to -4.76{+-}4.28. For the clinical pelvic CT image, the dark band and the metal line were removed, and the continuity and uniformity of the soft tissue were recovered as well. These results indicate that the proposed MAR algorithm is useful for reducing metal artifact and could improve the diagnostic value of metal-artifact contaminated CT images.

Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer

International Nuclear Information System (INIS)

Yu, Jack X; Sieuwerts, Anieta M; Zhang, Yi; Martens, John WM; Smid, Marcel; Klijn, Jan GM; Wang, Yixin; Foekens, John A

2007-01-01

Published prognostic gene signatures in breast cancer have few genes in common. Here we provide a rationale for this observation by studying the prognostic power and the underlying biological pathways of different gene signatures. Gene signatures to predict the development of metastases in estrogen receptor-positive and estrogen receptor-negative tumors were identified using 500 re-sampled training sets and mapping to Gene Ontology Biological Process to identify over-represented pathways. The Global Test program confirmed that gene expression profilings in the common pathways were associated with the metastasis of the patients. The apoptotic pathway and cell division, or cell growth regulation and G-protein coupled receptor signal transduction, were most significantly associated with the metastatic capability of estrogen receptor-positive or estrogen-negative tumors, respectively. A gene signature derived of the common pathways predicted metastasis in an independent cohort. Mapping of the pathways represented by different published prognostic signatures showed that they share 53% of the identified pathways. We show that divergent gene sets classifying patients for the same clinical endpoint represent similar biological processes and that pathway-derived signatures can be used to predict prognosis. Furthermore, our study reveals that the underlying biology related to aggressiveness of estrogen receptor subgroups of breast cancer is quite different

A simple system for detection of EEG artifacts in polysomnographic recordings.

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Durka, P J; Klekowicz, H; Blinowska, K J; Szelenberger, W; Niemcewicz, Sz

2003-04-01

We present an efficient parametric system for automatic detection of electroencephalogram (EEG) artifacts in polysomnographic recordings. For each of the selected types of artifacts, a relevant parameter was calculated for a given epoch. If any of these parameters exceeded a threshold, the epoch was marked as an artifact. Performance of the system, evaluated on 18 overnight polysomnographic recordings, revealed concordance with decisions of human experts close to the interexpert agreement and the repeatability of expert's decisions, assessed via a double-blind test. Complete software (Matlab source code) for the presented system is freely available from the Internet at http://brain.fuw.edu.pl/artifacts.

Artifacts Affecting Musculoskeletal Magnetic Resonance Imaging: Their Origins and Solutions.

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Roth, Eira; Hoff, Michael; Richardson, Michael L; Ha, Alice S; Porrino, Jack

2016-01-01

Among articles within the radiology literature, few present the manifestations of magnetic resonance imaging artifacts in a clinically oriented manner. Recognizing such artifacts is imperative given the increasing clinical use of magnetic resonance imaging and the emphasis by the American Board of Radiology on practical physics applications. The purpose of this article is to present magnetic resonance physics principles visually and conceptually in the context of common musculoskeletal radiology artifacts and their solutions, described using nonmathematical explanations. Copyright © 2016 Elsevier Inc. All rights reserved.

Metal artifact reduction method using metal streaks image subtraction

International Nuclear Information System (INIS)

Pua, Rizza D.; Cho, Seung Ryong

2014-01-01

Many studies have been dedicated for metal artifact reduction (MAR); however, the methods are successful to varying degrees depending on situations. Sinogram in-painting, filtering, iterative method are some of the major categories of MAR. Each has its own merits and weaknesses. A combination of these methods or hybrid methods have also been developed to make use of the different benefits of two techniques and minimize the unfavorable results. Our method focuses on the in-paitning approach and a hybrid MAR described by Xia et al. Although in-painting scheme is an effective technique in reducing the primary metal artifacts, a major drawback is the reintroduction of new artifacts that can be caused by an inaccurate interpolation process. Furthermore, combining the segmented metal image to the corrected nonmetal image in the final step of a conventional inpainting approach causes an issue of incorrect metal pixel values. Our proposed method begins with a sinogram in-painting approach and ends with an image-based metal artifact reduction scheme. This work provides a simple, yet effective solution for reducing metal artifacts and acquiring the original metal pixel information. The proposed method demonstrated its effectiveness in a simulation setting. The proposed method showed image quality that is comparable to the standard MAR; however, quantitatively more accurate than the standard MAR

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

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Assaf Gottlieb

2017-11-01

Full Text Available Abstract Background Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects. Methods Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. Results We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Conclusions Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort

Methods for artifact detection and removal from scalp EEG: A review.

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Islam, Md Kafiul; Rastegarnia, Amir; Yang, Zhi

2016-11-01

Electroencephalography (EEG) is the most popular brain activity recording technique used in wide range of applications. One of the commonly faced problems in EEG recordings is the presence of artifacts that come from sources other than brain and contaminate the acquired signals significantly. Therefore, much research over the past 15 years has focused on identifying ways for handling such artifacts in the preprocessing stage. However, this is still an active area of research as no single existing artifact detection/removal method is complete or universal. This article presents an extensive review of the existing state-of-the-art artifact detection and removal methods from scalp EEG for all potential EEG-based applications and analyses the pros and cons of each method. First, a general overview of the different artifact types that are found in scalp EEG and their effect on particular applications are presented. In addition, the methods are compared based on their ability to remove certain types of artifacts and their suitability in relevant applications (only functional comparison is provided not performance evaluation of methods). Finally, the future direction and expected challenges of current research is discussed. Therefore, this review is expected to be helpful for interested researchers who will develop and/or apply artifact handling algorithm/technique in future for their applications as well as for those willing to improve the existing algorithms or propose a new solution in this particular area of research. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Filtration of human EEG recordings from physiological artifacts with empirical mode method

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Grubov, Vadim V.; Runnova, Anastasiya E.; Khramova, Marina V.

2017-03-01

In the paper we propose the new method for dealing with noise and physiological artifacts in experimental human EEG recordings. The method is based on analysis of EEG signals with empirical mode decomposition (Hilbert-Huang transform). We consider noises and physiological artifacts on EEG as specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the method with following steps: empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing empirical modes with artifacts, reconstruction of the initial EEG signal. We test the method on filtration of experimental human EEG signals from eye-moving artifacts and show high efficiency of the method.

A 65‑gene signature for prognostic prediction in colon adenocarcinoma.

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Jiang, Hui; Du, Jun; Gu, Jiming; Jin, Liugen; Pu, Yong; Fei, Bojian

2018-04-01

The aim of the present study was to examine the molecular factors associated with the prognosis of colon cancer. Gene expression datasets were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases to screen differentially expressed genes (DEGs) between colon cancer samples and normal samples. Survival‑related genes were selected from the DEGs using the Cox regression method. A co‑expression network of survival‑related genes was then constructed, and functional clusters were extracted from this network. The significantly enriched functions and pathways of the genes in the network were identified. Using Bayesian discriminant analysis, a prognostic prediction system was established to distinguish the positive from negative prognostic samples. The discrimination efficacy of the system was validated in the GSE17538 dataset using Kaplan‑Meier survival analysis. A total of 636 and 1,892 DEGs between the colon cancer samples and normal samples were screened from the TCGA and GSE44861 dataset, respectively. There were 155 survival‑related genes selected. The co‑expression network of survival‑related genes included 138 genes, 534 lines (connections) and five functional clusters, including the signaling pathway, cellular response to cAMP, and immune system process functional clusters. The molecular function, cellular components and biological processes were the significantly enriched functions. The peroxisome proliferator‑activated receptor signaling pathway, Wnt signaling pathway, B cell receptor signaling pathway, and cytokine‑cytokine receptor interactions were the significant pathways. A prognostic prediction system based on a 65‑gene signature was established using this co‑expression network. Its discriminatory effect was validated in the TCGA dataset (P=3.56e‑12) and the GSE17538 dataset (P=1.67e‑6). The 65‑gene signature included kallikrein‑related peptidase 6 (KLK6), collagen type XI α1 (COL11A1), cartilage

Auditory steady-state responses in cochlear implant users: Effect of modulation frequency and stimulation artifacts.

Science.gov (United States)

Gransier, Robin; Deprez, Hanne; Hofmann, Michael; Moonen, Marc; van Wieringen, Astrid; Wouters, Jan

2016-05-01

Previous studies have shown that objective measures based on stimulation with low-rate pulse trains fail to predict the threshold levels of cochlear implant (CI) users for high-rate pulse trains, as used in clinical devices. Electrically evoked auditory steady-state responses (EASSRs) can be elicited by modulated high-rate pulse trains, and can potentially be used to objectively determine threshold levels of CI users. The responsiveness of the auditory pathway of profoundly hearing-impaired CI users to modulation frequencies is, however, not known. In the present study we investigated the responsiveness of the auditory pathway of CI users to a monopolar 500 pulses per second (pps) pulse train modulated between 1 and 100 Hz. EASSRs to forty-three modulation frequencies, elicited at the subject's maximum comfort level, were recorded by means of electroencephalography. Stimulation artifacts were removed by a linear interpolation between a pre- and post-stimulus sample (i.e., blanking). The phase delay across modulation frequencies was used to differentiate between the neural response and a possible residual stimulation artifact after blanking. Stimulation artifacts were longer than the inter-pulse interval of the 500pps pulse train for recording electrodes ipsilateral to the CI. As a result the stimulation artifacts could not be removed by artifact removal on the bases of linear interpolation for recording electrodes ipsilateral to the CI. However, artifact-free responses could be obtained in all subjects from recording electrodes contralateral to the CI, when subject specific reference electrodes (Cz or Fpz) were used. EASSRs to modulation frequencies within the 30-50 Hz range resulted in significant responses in all subjects. Only a small number of significant responses could be obtained, during a measurement period of 5 min, that originate from the brain stem (i.e., modulation frequencies in the 80-100 Hz range). This reduced synchronized activity of brain stem

Preliminary experimental insights into differential heat impact among lithic artifacts

Directory of Open Access Journals (Sweden)

Guillermo Bustos-Pérez

2016-09-01

Full Text Available The presence of thermally altered and broken flint artifacts is common at archaeological sites. Most studies focus their attention on the effects of heat treatment on flint to improve knapping qualities, disregarding the effects of fire over flint under uncontrolled conditions. This paper aims to show how under uncontrolled heating processes flint artifacts develop different heat alterations (such as levels of breakage, presence of scales, etc. as a result of vertical distribution, volume or raw material and to establish a gradient of rock changes and behavior. Artifacts where macroscopically analyzed and a series of uncontrolled heating experiments through the distribution of flint blanks under two hearths were carried out, allowing a comparison of the before and after of the blanks. Preliminary results show how levels of breakage, surface alteration or development of heat alteration features can be differentiated according to artifact volume, vertical distribution and level of surface alteration. Results also show how two different raw materials react differently to similar thermal impact, and how surface alteration reacts at different rhythm in the case of recycled artifacts. We conclude that levels of thermal alteration can be differentiated through macroscopic analysis of flint surface.

Identification of a unique cause of ring artifact seen in computed tomography trans-axial images

International Nuclear Information System (INIS)

Jha, Ashish Kumar; Purandare, Nilendu C; Shah, Sneha; Agrawal, Archi; Puranik, Ameya D; Rangarajan, Venkatesh

2013-01-01

Artifacts present in computed tomography (CT) image often degrade the image quality and ultimately, the diagnostic outcome. Ring artifact in trans-axial image is caused by either miscalibrated or defective detector element of detector row, which is often categorized as scanner based artifact. A ring artifact detected on trans-axial CT image of positron emission tomography/computed tomography (PET/CT), was caused by contamination of CT tube aperture by droplet of injectable contrast medium. This artifact was corrected by removal of contrast droplet from CT tube aperture. The ring artifact is a very common artifact, commonly cited in the literature. Our case puts forward an uncommon cause of this artifact and its method of correction, which also, has no mention in the existing literature

Quantification of Rain Induced Artifacts on Digital Satellite Television ...

African Journals Online (AJOL)

The presence of artifacts on the high definition television (TV) content and the eventual loss of the digital TV signals to rain is still a major concern to satellite operators, digital satellite television (DSTV) and terrestrial television content providers. In this paper, the artifacts present in a typical DSTV signal is examined on a ...

Reduction of artifacts caused by orthopedic hardware in the spine in spectral detector CT examinations using virtual monoenergetic image reconstructions and metal-artifact-reduction algorithms

Energy Technology Data Exchange (ETDEWEB)

Grosse Hokamp, Nils; Neuhaus, V.; Abdullayev, N.; Laukamp, K.; Lennartz, S.; Mpotsaris, A.; Borggrefe, J. [University Hospital Cologne, Department of Diagnostic and Interventional Radiology, Cologne (Germany)

2018-02-15

Aim of this study was to assess the artifact reduction in patients with orthopedic hardware in the spine as provided by (1) metal-artifact-reduction algorithms (O-MAR) and (2) virtual monoenergetic images (MonoE) as provided by spectral detector CT (SDCT) compared to conventional iterative reconstruction (CI). In all, 28 consecutive patients with orthopedic hardware in the spine who underwent SDCT-examinations were included. CI, O-MAR and MonoE (40-200 keV) images were reconstructed. Attenuation (HU) and noise (SD) were measured in order to calculate signal-to-noise ratio (SNR) of paravertebral muscle and spinal canal. Subjective image quality was assessed by two radiologists in terms of image quality and extent of artifact reduction. O-MAR and high-keV MonoE showed significant decrease of hypodense artifacts in terms of higher attenuation as compared to CI (CI vs O-MAR, 200 keV MonoE: -396.5HU vs. -115.2HU, -48.1HU; both p ≤ 0.001). Further, artifacts as depicted by noise were reduced in O-MAR and high-keV MonoE as compared to CI in (1) paravertebral muscle and (2) spinal canal - CI vs. O-MAR/200 keV: (1) 34.7 ± 19.0 HU vs. 26.4 ± 14.4 HU, p ≤ 0.05/27.4 ± 16.1, n.s.; (2) 103.4 ± 61.3 HU vs. 72.6 ± 62.6 HU/60.9 ± 40.1 HU, both p ≤ 0.001. Subjectively both O-MAR and high-keV images yielded an artifact reduction in up to 24/28 patients. Both, O-MAR and high-keV MonoE reconstructions as provided by SDCT lead to objective and subjective artifact reduction, thus the combination of O-MAR and MonoE seems promising for further reduction. (orig.)

MARSAME Radiological Release Report for Archaeological Artifacts Excavated from Area L

Energy Technology Data Exchange (ETDEWEB)

Ruedig, Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Whicker, Jeffrey Jay [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gillis, Jessica Mcdonnel [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-06-03

In 1991 Los Alamos National Laboratory’s (LANL’s) cultural resources team excavated archaeological site LA 4618 located at Technical Area 54, within Material Disposal Area L (MDA L). MDA L received non-radioactive chemical waste from the early 1960s until 1985. Further development of the MDA required excavation of several cultural sites under National Historic Preservation Act requirements; artifacts from these sites have been subsequently stored at LANL. The LANL cultural resources group would now like to release these artifacts to the Museum of Indian Arts and Culture in Santa Fe for curation. The history of disposal at Area L suggests that the artifact pool is unlikely to be chemically contaminated and LANL staff washed each artifact at least once following excavation. Thus, it is unlikely that the artifacts present a chemical hazard. LANL’s Environmental Stewardship group (EPC-ES) has evaluated the radiological survey results for the Area L artifact pool and found that the items described in this report meet the criteria for unrestricted radiological release under Department of Energy (DOE) Order 458.1 Radiation Protection of the Public and the Environment and are candidates for release without restriction from LANL control. This conclusion is based on the known history of MDA L and on radiation survey data.

Individuality evaluation for paper based artifact-metrics using transmitted light image

Science.gov (United States)

Yamakoshi, Manabu; Tanaka, Junichi; Furuie, Makoto; Hirabayashi, Masashi; Matsumoto, Tsutomu

2008-02-01

Artifact-metrics is an automated method of authenticating artifacts based on a measurable intrinsic characteristic. Intrinsic characters, such as microscopic random-patterns made during the manufacturing process, are very difficult to copy. A transmitted light image of the distribution can be used for artifact-metrics, since the fiber distribution of paper is random. Little is known about the individuality of the transmitted light image although it is an important requirement for intrinsic characteristic artifact-metrics. Measuring individuality requires that the intrinsic characteristic of each artifact significantly differs, so having sufficient individuality can make an artifact-metric system highly resistant to brute force attack. Here we investigate the influence of paper category, matching size of sample, and image-resolution on the individuality of a transmitted light image of paper through a matching test using those images. More concretely, we evaluate FMR/FNMR curves by calculating similarity scores with matches using correlation coefficients between pairs of scanner input images, and the individuality of paper by way of estimated EER with probabilistic measure through a matching method based on line segments, which can localize the influence of rotation gaps of a sample in the case of large matching size. As a result, we found that the transmitted light image of paper has a sufficient individuality.

Awe and Artifacts: Religious and Scientific Endeavor

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Ionut Untea

2017-05-01

Full Text Available The article takes as its point of departure the reflections of Henry Adams and Jacques Ellul on the possible gradual replacement of objects used in religious worship with objects used in technological worship, and advances the hypothesis that such a substitution is unlikely. Using information from psychology, history of religions, and history of science, the perspective proposed is that of a parallel historical analogous development of both religious and scientific attitudes of awe by the use of artifacts carrying two functions: firstly, to coagulate social participation around questions dealing with humanity’s destiny and interpersonal relationships across communities, and secondly to offer cultural coherence through a communal sense of social stability, comfort, and security. I argue that, though animated by attitudes of awe (“awefull”, both leading scientists and religious founders have encountered the difficulty in representing and introducing this awe to the large public via “awesome” artifacts. The failure to represent coherently the initial awe via artifacts may give rise to “anomalous awefullness”: intolerance, persecutions, global conflicts.

Exploring gene expression signatures for predicting disease free survival after resection of colorectal cancer liver metastases.

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Nikol Snoeren

Full Text Available BACKGROUND AND OBJECTIVES: This study was designed to identify and validate gene signatures that can predict disease free survival (DFS in patients undergoing a radical resection for their colorectal liver metastases (CRLM. METHODS: Tumor gene expression profiles were collected from 119 patients undergoing surgery for their CRLM in the Paul Brousse Hospital (France and the University Medical Center Utrecht (The Netherlands. Patients were divided into high and low risk groups. A randomly selected training set was used to find predictive gene signatures. The ability of these gene signatures to predict DFS was tested in an independent validation set comprising the remaining patients. Furthermore, 5 known clinical risk scores were tested in our complete patient cohort. RESULT: No gene signature was found that significantly predicted DFS in the validation set. In contrast, three out of five clinical risk scores were able to predict DFS in our patient cohort. CONCLUSIONS: No gene signature was found that could predict DFS in patients undergoing CRLM resection. Three out of five clinical risk scores were able to predict DFS in our patient cohort. These results emphasize the need for validating risk scores in independent patient groups and suggest improved designs for future studies.

Metal artifact reduction in CT using tissue-class modeling and adaptive prefiltering

International Nuclear Information System (INIS)

Bal, Matthieu; Spies, Lothar

2006-01-01

High-density objects such as metal prostheses, surgical clips, or dental fillings generate streak-like artifacts in computed tomography images. We present a novel method for metal artifact reduction by in-painting missing information into the corrupted sinogram. The information is provided by a tissue-class model extracted from the distorted image. To this end the image is first adaptively filtered to reduce the noise content and to smooth out streak artifacts. Consecutively, the image is segmented into different material classes using a clustering algorithm. The corrupted and missing information in the original sinogram is completed using the forward projected information from the tissue-class model. The performance of the correction method is assessed on phantom images. Clinical images featuring a broad spectrum of metal artifacts are studied. Phantom and clinical studies show that metal artifacts, such as streaks, are significantly reduced and shadows in the image are eliminated. Furthermore, the novel approach improves detectability of organ contours. This can be of great relevance, for instance, in radiation therapy planning, where images affected by metal artifacts may lead to suboptimal treatment plans

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

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Teng Shaolei

2013-01-01

Full Text Available Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs and Support Vector Machines (SVMs were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

Prediction of highly expressed genes in microbes based on chromatin accessibility

DEFF Research Database (Denmark)

Willenbrock, Hanni; Ussery, David

2007-01-01

BACKGROUND: It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed...

An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

Science.gov (United States)

Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

2018-05-14

A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

WE-G-209-00: Identifying Image Artifacts, Their Causes, and How to Fix Them

Energy Technology Data Exchange (ETDEWEB)

NONE

2016-06-15

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

WE-G-209-00: Identifying Image Artifacts, Their Causes, and How to Fix Them

International Nuclear Information System (INIS)

2016-01-01

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis.

Science.gov (United States)

Noar, Roslyn D; Daub, Margaret E

2016-01-01

Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity) for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity) to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that they may encode

Bioinformatics Prediction of Polyketide Synthase Gene Clusters from Mycosphaerella fijiensis.

Directory of Open Access Journals (Sweden)

Roslyn D Noar

Full Text Available Mycosphaerella fijiensis, causal agent of black Sigatoka disease of banana, is a Dothideomycete fungus closely related to fungi that produce polyketides important for plant pathogenicity. We utilized the M. fijiensis genome sequence to predict PKS genes and their gene clusters and make bioinformatics predictions about the types of compounds produced by these clusters. Eight PKS gene clusters were identified in the M. fijiensis genome, placing M. fijiensis into the 23rd percentile for the number of PKS genes compared to other Dothideomycetes. Analysis of the PKS domains identified three of the PKS enzymes as non-reducing and two as highly reducing. Gene clusters contained types of genes frequently found in PKS clusters including genes encoding transporters, oxidoreductases, methyltransferases, and non-ribosomal peptide synthases. Phylogenetic analysis identified a putative PKS cluster encoding melanin biosynthesis. None of the other clusters were closely aligned with genes encoding known polyketides, however three of the PKS genes fell into clades with clusters encoding alternapyrone, fumonisin, and solanapyrone produced by Alternaria and Fusarium species. A search for homologs among available genomic sequences from 103 Dothideomycetes identified close homologs (>80% similarity for six of the PKS sequences. One of the PKS sequences was not similar (< 60% similarity to sequences in any of the 103 genomes, suggesting that it encodes a unique compound. Comparison of the M. fijiensis PKS sequences with those of two other banana pathogens, M. musicola and M. eumusae, showed that these two species have close homologs to five of the M. fijiensis PKS sequences, but three others were not found in either species. RT-PCR and RNA-Seq analysis showed that the melanin PKS cluster was down-regulated in infected banana as compared to growth in culture. Three other clusters, however were strongly upregulated during disease development in banana, suggesting that

Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

Science.gov (United States)

Patel, Nihir; Wang, Jason T L

2015-10-01

Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.

Adaptive cancellation of motion artifact in wearable biosensors.

Science.gov (United States)

Yousefi, Rasoul; Nourani, Mehrdad; Panahi, Issa

2012-01-01

The performance of wearable biosensors is highly influenced by motion artifact. In this paper, a model is proposed for analysis of motion artifact in wearable photoplethysmography (PPG) sensors. Using this model, we proposed a robust real-time technique to estimate fundamental frequency and generate a noise reference signal. A Least Mean Square (LMS) adaptive noise canceler is then designed and validated using our synthetic noise generator. The analysis and results on proposed technique for noise cancellation shows promising performance.

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques.

Science.gov (United States)

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images.

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

Science.gov (United States)

Zhang, Ping; Wu, Linwei; Rocha, Andrea M.; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D.; Wu, Liyou; Watson, David B.; Adams, Michael W. W.; Alm, Eric J.; Adams, Paul D.; Arkin, Adam P.

2018-01-01

ABSTRACT Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. PMID:29463661

[E-MTAB-587] PCR_artifacts

NARCIS (Netherlands)

Muino Acuna, J.M.

2011-01-01

WARNING: This library was yield low amount of material and it was over-amplified by PCR. This libraries are used study the robustness of several statitical methods against PCR artifacts. ChIP experiments were performed on Arabidopsis wildtype inflorescences using an antibody raised against a

Checking behavioral conformance of artifacts

NARCIS (Netherlands)

Fahland, D.; Leoni, de M.; Dongen, van B.F.; Aalst, van der W.M.P.

2011-01-01

The usefulness of process models (e.g., for analysis, improvement, or execution) strongly depends on their ability to describe reality. Conformance checking is a technique to validate how good a given process model describes recorded executions of the actual process. Recently, artifacts have been

Predictive gene lists for breast cancer prognosis: A topographic visualisation study

Directory of Open Access Journals (Sweden)

Lowe David

2008-04-01

Full Text Available Abstract Background The controversy surrounding the non-uniqueness of predictive gene lists (PGL of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged 1. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists. Methods We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE and the Locally Linear Embedding(LLE techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether a-posteriori two prognosis groups are separable on the evidence of the gene lists. A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset. Results The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results. Conclusion The random correlation effect to an arbitrary outcome induced by small subset selection from very high

Paired hormone response elements predict caveolin-1 as a glucocorticoid target gene.

Directory of Open Access Journals (Sweden)

Marinus F van Batenburg

2010-01-01

Full Text Available Glucocorticoids act in part via glucocorticoid receptor binding to hormone response elements (HREs, but their direct target genes in vivo are still largely unknown. We developed the criterion that genomic occurrence of paired HREs at an inter-HRE distance less than 200 bp predicts hormone responsiveness, based on synergy of multiple HREs, and HRE information from known target genes. This criterion predicts a substantial number of novel responsive genes, when applied to genomic regions 10 kb upstream of genes. Multiple-tissue in situ hybridization showed that mRNA expression of 6 out of 10 selected genes was induced in a tissue-specific manner in mice treated with a single dose of corticosterone, with the spleen being the most responsive organ. Caveolin-1 was strongly responsive in several organs, and the HRE pair in its upstream region showed increased occupancy by glucocorticoid receptor in response to corticosterone. Our approach allowed for discovery of novel tissue specific glucocorticoid target genes, which may exemplify responses underlying the permissive actions of glucocorticoids.

Simultaneous ocular and muscle artifact removal from EEG data by exploiting diverse statistics.

Science.gov (United States)

Chen, Xun; Liu, Aiping; Chen, Qiang; Liu, Yu; Zou, Liang; McKeown, Martin J

2017-09-01

Electroencephalography (EEG) recordings are frequently contaminated by both ocular and muscle artifacts. These are normally dealt with separately, by employing blind source separation (BSS) techniques relying on either second-order or higher-order statistics (SOS & HOS respectively). When HOS-based methods are used, it is usually in the setting of assuming artifacts are statistically independent to the EEG. When SOS-based methods are used, it is assumed that artifacts have autocorrelation characteristics distinct from the EEG. In reality, ocular and muscle artifacts do not completely follow the assumptions of strict temporal independence to the EEG nor completely unique autocorrelation characteristics, suggesting that exploiting HOS or SOS alone may be insufficient to remove these artifacts. Here we employ a novel BSS technique, independent vector analysis (IVA), to jointly employ HOS and SOS simultaneously to remove ocular and muscle artifacts. Numerical simulations and application to real EEG recordings were used to explore the utility of the IVA approach. IVA was superior in isolating both ocular and muscle artifacts, especially for raw EEG data with low signal-to-noise ratio, and also integrated usually separate SOS and HOS steps into a single unified step. Copyright © 2017 Elsevier Ltd. All rights reserved.

Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

Energy Technology Data Exchange (ETDEWEB)

Wang, Jing; Ma, Zihao; Carr, Steven A.; Mertins, Philipp; Zhang, Hui; Zhang, Zhen; Chan, Daniel W.; Ellis, Matthew J. C.; Townsend, R. Reid; Smith, Richard D.; McDermott, Jason E.; Chen, Xian; Paulovich, Amanda G.; Boja, Emily S.; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Rodland, Karin D.; Liebler, Daniel C.; Zhang, Bing

2016-11-11

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies

Artifact reduction of different metallic implants in flat detector C-arm CT.

Science.gov (United States)

Hung, S-C; Wu, C-C; Lin, C-J; Guo, W-Y; Luo, C-B; Chang, F-C; Chang, C-Y

2014-07-01

Flat detector CT has been increasingly used as a follow-up examination after endovascular intervention. Metal artifact reduction has been successfully demonstrated in coil mass cases, but only in a small series. We attempted to objectively and subjectively evaluate the feasibility of metal artifact reduction with various metallic objects and coil lengths. We retrospectively reprocessed the flat detector CT data of 28 patients (15 men, 13 women; mean age, 55.6 years) after they underwent endovascular treatment (20 coiling ± stent placement, 6 liquid embolizers) or shunt drainage (n = 2) between January 2009 and November 2011 by using a metal artifact reduction correction algorithm. We measured CT value ranges and noise by using region-of-interest methods, and 2 experienced neuroradiologists rated the degrees of improved imaging quality and artifact reduction by comparing uncorrected and corrected images. After we applied the metal artifact reduction algorithm, the CT value ranges and the noise were substantially reduced (1815.3 ± 793.7 versus 231.7 ± 95.9 and 319.9 ± 136.6 versus 45.9 ± 14.0; both P metallic objects and various sizes of coil masses. The rater study achieved an overall improvement of imaging quality and artifact reduction (85.7% and 78.6% of cases by 2 raters, respectively), with the greatest improvement in the coiling group, moderate improvement in the liquid embolizers, and the smallest improvement in ventricular shunting (overall agreement, 0.857). The metal artifact reduction algorithm substantially reduced artifacts and improved the objective image quality in every studied case. It also allowed improved diagnostic confidence in most cases. © 2014 by American Journal of Neuroradiology.

Analysis of metal artifact reduction tools for dental hardware in CT scans of the oral cavity: kVp, iterative reconstruction, dual-energy CT, metal artifact reduction software: does it make a difference?

Energy Technology Data Exchange (ETDEWEB)

Crop, An de; Hoof, Tom van; Herde, Katharina d' ; Thierens, Hubert; Bacher, Klaus [Ghent University, Department of Basic Medical Sciences, Gent (Belgium); Casselman, Jan; Vereecke, Elke; Bossu, Nicolas [AZ Sint Jan Bruges Ostend AV, Department of Radiology, Bruges (Belgium); Dierens, Melissa [Ghent University, Dental School, Unit for Oral and Maxillofacial Imaging, Ghent (Belgium); Pamplona, Jaime [Hospital Lisboa Central, Department of Neuroradiology, Lisbon (Portugal)

2015-08-15

Metal artifacts may negatively affect radiologic assessment in the oral cavity. The aim of this study was to evaluate different metal artifact reduction techniques for metal artifacts induced by dental hardware in CT scans of the oral cavity. Clinical image quality was assessed using a Thiel-embalmed cadaver. A Catphan phantom and a polymethylmethacrylate (PMMA) phantom were used to evaluate physical-technical image quality parameters such as artifact area, artifact index (AI), and contrast detail (IQF{sub inv}). Metal cylinders were inserted in each phantom to create metal artifacts. CT images of both phantoms and the Thiel-embalmed cadaver were acquired on a multislice CT scanner using 80, 100, 120, and 140 kVp; model-based iterative reconstruction (Veo); and synthesized monochromatic keV images with and without metal artifact reduction software (MARs). Four radiologists assessed the clinical image quality, using an image criteria score (ICS). Significant influence of increasing kVp and the use of Veo was found on clinical image quality (p = 0.007 and p = 0.014, respectively). Application of MARs resulted in a smaller artifact area (p < 0.05). However, MARs reconstructed images resulted in lower ICS. Of all investigated techniques, Veo shows to be most promising, with a significant improvement of both the clinical and physical-technical image quality without adversely affecting contrast detail. MARs reconstruction in CT images of the oral cavity to reduce dental hardware metallic artifacts is not sufficient and may even adversely influence the image quality. (orig.)

Assessment of metal artifact reduction methods in pelvic CT

Energy Technology Data Exchange (ETDEWEB)

Abdoli, Mehrsima [Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX (Netherlands); Mehranian, Abolfazl [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211 (Switzerland); Ailianou, Angeliki; Becker, Minerva [Division of Radiology, Geneva University Hospital, Geneva CH-1211 (Switzerland); Zaidi, Habib, E-mail: habib.zaidi@hcuge.ch [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211 (Switzerland); Geneva Neuroscience Center, Geneva University, Geneva CH-1205 (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen 9700 RB (Netherlands)

2016-04-15

Purpose: Metal artifact reduction (MAR) produces images with improved quality potentially leading to confident and reliable clinical diagnosis and therapy planning. In this work, the authors evaluate the performance of five MAR techniques for the assessment of computed tomography images of patients with hip prostheses. Methods: Five MAR algorithms were evaluated using simulation and clinical studies. The algorithms included one-dimensional linear interpolation (LI) of the corrupted projection bins in the sinogram, two-dimensional interpolation (2D), a normalized metal artifact reduction (NMAR) technique, a metal deletion technique, and a maximum a posteriori completion (MAPC) approach. The algorithms were applied to ten simulated datasets as well as 30 clinical studies of patients with metallic hip implants. Qualitative evaluations were performed by two blinded experienced radiologists who ranked overall artifact severity and pelvic organ recognition for each algorithm by assigning scores from zero to five (zero indicating totally obscured organs with no structures identifiable and five indicating recognition with high confidence). Results: Simulation studies revealed that 2D, NMAR, and MAPC techniques performed almost equally well in all regions. LI falls behind the other approaches in terms of reducing dark streaking artifacts as well as preserving unaffected regions (p < 0.05). Visual assessment of clinical datasets revealed the superiority of NMAR and MAPC in the evaluated pelvic organs and in terms of overall image quality. Conclusions: Overall, all methods, except LI, performed equally well in artifact-free regions. Considering both clinical and simulation studies, 2D, NMAR, and MAPC seem to outperform the other techniques.

Cyber Event Artifact Investigation Training in a Virtual Environment

Science.gov (United States)

2017-12-01

information was desired in the logs as well as best practices provided by Microsoft: 1. Every Success or Failure for: Account Logon Events, Account ...use this artifact in conjunction with information discovered through investigation of other artifacts, such as logs and accounts . For instance, the...when coupled with logs, accounts , and process data, this information may provide enough evidence for transition into the reporting and Preliminary

Brain-in-Brain Artifact (BIBA) in a Patient with Hydranencepaly: A Case Report

Energy Technology Data Exchange (ETDEWEB)

Oh, Sang Young; Kim, You Me; Lee, Seung Ha; Lee, Young Seok [College of Medicine Dankook University Hospital, Cheonan (Korea, Republic of)

2011-03-15

Hydranencephaly is a condition that is characterized by an absent brain mantle along with the subadjacent white matter, with replacement of the cerebral hemispheres by a thin-walled membranous sac containing CSF. During brain sonograpy in a neonate with hydranencephaly, we have found a brain-in-brain appearance as an unusual sonographic artifact. We report here on this interesting sonographic artifact in a neonate with hydranencephaly, and this artifact was due to multipath reflection artifact of the ultrasound beam/wave, and we explain the underlying physics

Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

Science.gov (United States)

Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

2016-02-19

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

Predicting spatial and temporal gene expression using an integrative model of transcription factor occupancy and chromatin state.

Directory of Open Access Journals (Sweden)

Bartek Wilczynski

Full Text Available Precise patterns of spatial and temporal gene expression are central to metazoan complexity and act as a driving force for embryonic development. While there has been substantial progress in dissecting and predicting cis-regulatory activity, our understanding of how information from multiple enhancer elements converge to regulate a gene's expression remains elusive. This is in large part due to the number of different biological processes involved in mediating regulation as well as limited availability of experimental measurements for many of them. Here, we used a Bayesian approach to model diverse experimental regulatory data, leading to accurate predictions of both spatial and temporal aspects of gene expression. We integrated whole-embryo information on transcription factor recruitment to multiple cis-regulatory modules, insulator binding and histone modification status in the vicinity of individual gene loci, at a genome-wide scale during Drosophila development. The model uses Bayesian networks to represent the relation between transcription factor occupancy and enhancer activity in specific tissues and stages. All parameters are optimized in an Expectation Maximization procedure providing a model capable of predicting tissue- and stage-specific activity of new, previously unassayed genes. Performing the optimization with subsets of input data demonstrated that neither enhancer occupancy nor chromatin state alone can explain all gene expression patterns, but taken together allow for accurate predictions of spatio-temporal activity. Model predictions were validated using the expression patterns of more than 600 genes recently made available by the BDGP consortium, demonstrating an average 15-fold enrichment of genes expressed in the predicted tissue over a naïve model. We further validated the model by experimentally testing the expression of 20 predicted target genes of unknown expression, resulting in an accuracy of 95% for temporal

Predicting Hydrologic Function With Aquatic Gene Fragments

Science.gov (United States)

Good, S. P.; URycki, D. R.; Crump, B. C.

2018-03-01

Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

Science.gov (United States)

2017-02-01

affecting the function of Fanconi Anemia (FA) genes ( FANCA /B/C/D2/E/F/G/I/J/L/M, PALB2) or DNA damage response genes involved in HR 5 (ATM, ATR...Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...To) 15 July 2010 – 2 Nov.2016 4. TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP

View-Angle Tilting and Slice-Encoding Metal Artifact Correction for Artifact Reduction in MRI: Experimental Sequence Optimization for Orthopaedic Tumor Endoprostheses and Clinical Application.

Directory of Open Access Journals (Sweden)

Pia M Jungmann

Full Text Available MRI plays a major role in follow-up of patients with malignant bone tumors. However, after limb salvage surgery, orthopaedic tumor endoprostheses might cause significant metal-induced susceptibility artifacts.To evaluate the benefit of view-angle tilting (VAT and slice-encoding metal artifact correction (SEMAC for MRI of large-sized orthopaedic tumor endoprostheses in an experimental model and to demonstrate clinical benefits for assessment of periprosthetic soft tissue abnormalities.In an experimental setting, tumor endoprostheses (n=4 were scanned at 1.5T with three versions of optimized high-bandwidth turbo-spin-echo pulse sequences: (i standard, (ii VAT and (iii combined VAT and SEMAC (VAT&SEMAC. Pulse sequences included coronal short-tau-inversion-recovery (STIR, coronal T1-weighted (w, transverse T1-w and T2-w TSE sequences. For clinical evaluation, VAT&SEMAC was compared to conventional metal artifact-reducing MR sequences (conventional MR in n=25 patients with metal implants and clinical suspicion of tumor recurrence or infection. Diameters of artifacts were measured quantitatively. Qualitative parameters were assessed on a five-point scale (1=best, 5=worst: "image distortion", "artificial signal changes at the edges" and "diagnostic confidence". Imaging findings were correlated with pathology. T-tests and Wilcoxon-signed rank tests were used for statistical analyses.The true size of the prostheses was overestimated on MRI (P<0.05. A significant reduction of artifacts was achieved by VAT (P<0.001 and VAT&SEMAC (P=0.003 compared to the standard group. Quantitative scores improved in the VAT and VAT&SEMAC group (P<0.05. On clinical MR images, artifact diameters were significantly reduced in the VAT&SEMAC-group as compared with the conventional-group (P<0.001. Distortion and artificial signal changes were reduced and diagnostic confidence improved (P<0.05. In two cases, tumor-recurrence, in ten cases infection and in thirteen cases other

["Long-branch Attraction" artifact in phylogenetic reconstruction].

Science.gov (United States)

Li, Yi-Wei; Yu, Li; Zhang, Ya-Ping

2007-06-01

Phylogenetic reconstruction among various organisms not only helps understand their evolutionary history but also reveal several fundamental evolutionary questions. Understanding of the evolutionary relationships among organisms establishes the foundation for the investigations of other biological disciplines. However, almost all the widely used phylogenetic methods have limitations which fail to eliminate systematic errors effectively, preventing the reconstruction of true organismal relationships. "Long-branch Attraction" (LBA) artifact is one of the most disturbing factors in phylogenetic reconstruction. In this review, the conception and analytic method as well as the avoidance strategy of LBA were summarized. In addition, several typical examples were provided. The approach to avoid and resolve LBA artifact has been discussed.

A Language of Objects and Artifacts

DEFF Research Database (Denmark)

Svabo, Connie

This is a conceptual inquiry about materiality. It gives an introductory overview to the vocabulary of materiality in a chosen selection of theories. The paper shows a language of artifacts and objects as it is used within practice-based approaches to organizational knowing. The examined...... intellectual traditions are interpretive-cultural approaches; activity theory; and sociology of translation. Similarities and differences are presented in the way these three distinct intellectual traditions conceptualize the array of material objects and artifacts which are central in the tales of practice...... concepts do the theories attempt to grasp tools and design objects – furniture, graphics, flutes-in-making and built space? The paper shows which concepts are used and it demonstrates how the interaction between social and material realities are viewed. Furthermore it highlights some of the ontological...

Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression.

Science.gov (United States)

Guilloux, Jean-Philippe; Bassi, Sabrina; Ding, Ying; Walsh, Chris; Turecki, Gustavo; Tseng, George; Cyranowski, Jill M; Sibille, Etienne

2015-02-01

Major depressive disorder (MDD) in general, and anxious-depression in particular, are characterized by poor rates of remission with first-line treatments, contributing to the chronic illness burden suffered by many patients. Prospective research is needed to identify the biomarkers predicting nonremission prior to treatment initiation. We collected blood samples from a discovery cohort of 34 adult MDD patients with co-occurring anxiety and 33 matched, nondepressed controls at baseline and after 12 weeks (of citalopram plus psychotherapy treatment for the depressed cohort). Samples were processed on gene arrays and group differences in gene expression were investigated. Exploratory analyses suggest that at pretreatment baseline, nonremitting patients differ from controls with gene function and transcription factor analyses potentially related to elevated inflammation and immune activation. In a second phase, we applied an unbiased machine learning prediction model and corrected for model-selection bias. Results show that baseline gene expression predicted nonremission with 79.4% corrected accuracy with a 13-gene model. The same gene-only model predicted nonremission after 8 weeks of citalopram treatment with 76% corrected accuracy in an independent validation cohort of 63 MDD patients treated with citalopram at another institution. Together, these results demonstrate the potential, but also the limitations, of baseline peripheral blood-based gene expression to predict nonremission after citalopram treatment. These results not only support their use in future prediction tools but also suggest that increased accuracy may be obtained with the inclusion of additional predictors (eg, genetics and clinical scales).

Prediction of metastasis from low-malignant breast cancer by gene expression profiling

DEFF Research Database (Denmark)

Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

2007-01-01

examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... with different characteristics and risk, expression-based classification specifically developed in low-risk patients have higher predictive power in this group.......Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...

Tissue artifact removal from respiratory signals based on empirical mode decomposition.

Science.gov (United States)

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty

2013-05-01

On-line measurement of respiration plays an important role in monitoring human physical activities. Such measurement commonly employs sensing belts secured around the rib cage and abdomen of the test object. Affected by the movement of body tissues, respiratory signals typically have a low signal-to-noise ratio. Removing tissue artifacts therefore is critical to ensuring effective respiration analysis. This paper presents a signal decomposition technique for tissue artifact removal from respiratory signals, based on the empirical mode decomposition (EMD). An algorithm based on the mutual information and power criteria was devised to automatically select appropriate intrinsic mode functions for tissue artifact removal and respiratory signal reconstruction. Performance of the EMD-algorithm was evaluated through simulations and real-life experiments (N = 105). Comparison with low-pass filtering that has been conventionally applied confirmed the effectiveness of the technique in tissue artifacts removal.

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

Energy Technology Data Exchange (ETDEWEB)

Yuan, C; Qi, H; Chen, Z; Wu, S; Xu, Y; Zhou, L [Southern Medical University, Guangzhou, Guangdong (China)

2016-06-15

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

International Nuclear Information System (INIS)

Yuan, C; Qi, H; Chen, Z; Wu, S; Xu, Y; Zhou, L

2016-01-01

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.

Prediction of epigenetically regulated genes in breast cancer cell lines

Energy Technology Data Exchange (ETDEWEB)

Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria EH; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram

2010-05-04

panel of breast cancer cell lines. Subnetwork enrichment of these genes has identifed 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

Language and other artifacts: socio-cultural dynamics of niche construction.

Science.gov (United States)

Sinha, Chris

2015-01-01

Niche construction theory is a relatively new approach in evolutionary biology that seeks to integrate an ecological dimension into the Darwinian theory of evolution by natural selection. It is regarded by many evolutionary biologists as providing a significant revision of the Neo-Darwinian modern synthesis that unified Darwin's theory of natural and sexual selection with 20th century population genetics. Niche construction theory has been invoked as a processual mediator of social cognitive evolution and of the emergence and evolution of language. I argue that language itself can be considered as a biocultural niche and evolutionary artifact. I provide both a general analysis of the cognitive and semiotic status of artifacts, and a formal analysis of language as a social and semiotic institution, based upon a distinction between the fundamental semiotic relations of "counting as" and "standing for." I explore the consequences for theories of language and language learning of viewing language as a biocultural niche. I suggest that not only do niches mediate organism-organism interactions, but also that organisms mediate niche-niche interactions in ways that affect evolutionary processes, with the evolution of human infancy and childhood as a key example. I argue that language as a social and semiotic system is not only grounded in embodied engagements with the material and social-interactional world, but also grounds a sub-class of artifacts of particular significance in the cultural history of human cognition. Symbolic cognitive artifacts materially and semiotically mediate human cognition, and are not merely informational repositories, but co-agentively constitutive of culturally and historically emergent cognitive domains. I provide examples of the constitutive cognitive role of symbolic cognitive artifacts drawn from my research with my colleagues on cultural and linguistic conceptualizations of time, and their cultural variability. I conclude by reflecting on

Language and other artifacts: socio-cultural dynamics of niche construction.

Directory of Open Access Journals (Sweden)

Chris eSinha

2015-10-01

Full Text Available Niche construction theory is a relatively new approach in evolutionary biology that seeks to integrate an ecological dimension into the Darwinian theory of evolution by natural selection. It is regarded by many evolutionary biologists as providing a significant revision of the Neo-Darwinian modern synthesis that unified Darwin’s theory of natural and sexual selection with 20th century population genetics. Niche construction theory has been invoked as a processual mediator of social cognitive evolution and of the emergence and evolution of language. I argue that language itself can be considered as a biocultural niche and evolutionary artifact. I provide both a general analysis of the cognitive and semiotic status of artifacts, and a formal analysis of language as a social and semiotic institution, based upon a distinction between the fundamental semiotic relations of counting as and standing for. I explore the consequences for theories of language and language learning of viewing language as a biocultural niche. I suggest that not only do niches mediate organism-organism interactions, but also that organisms mediate niche-niche interactions in ways that affect evolutionary processes, with the evolution of human infancy and childhood as a key example. I argue that language as a social and semiotic system is not only grounded in embodied engagements with the material and social-interactional world, but also grounds a sub-class of artifacts of particular significance in the cultural history of human cognition. Symbolic cognitive artifacts materially and semiotically mediate human cognition, and are not merely informational repositories, but co-agentively constitutive of culturally and historically emergent cognitive domains. I provide examples of the constitutive cognitive role of symbolic cognitive artifacts drawn from my research with my colleagues on cultural and linguistic conceptualizations of time, and their cultural variability. I conclude

Signal processing methods for reducing artifacts in microelectrode brain recordings caused by functional electrical stimulation

Science.gov (United States)

Young, D.; Willett, F.; Memberg, W. D.; Murphy, B.; Walter, B.; Sweet, J.; Miller, J.; Hochberg, L. R.; Kirsch, R. F.; Ajiboye, A. B.

2018-04-01

Objective. Functional electrical stimulation (FES) is a promising technology for restoring movement to paralyzed limbs. Intracortical brain-computer interfaces (iBCIs) have enabled intuitive control over virtual and robotic movements, and more recently over upper extremity FES neuroprostheses. However, electrical stimulation of muscles creates artifacts in intracortical microelectrode recordings that could degrade iBCI performance. Here, we investigate methods for reducing the cortically recorded artifacts that result from peripheral electrical stimulation. Approach. One participant in the BrainGate2 pilot clinical trial had two intracortical microelectrode arrays placed in the motor cortex, and thirty-six stimulating intramuscular electrodes placed in the muscles of the contralateral limb. We characterized intracortically recorded electrical artifacts during both intramuscular and surface stimulation. We compared the performance of three artifact reduction methods: blanking, common average reference (CAR) and linear regression reference (LRR), which creates channel-specific reference signals, composed of weighted sums of other channels. Main results. Electrical artifacts resulting from surface stimulation were 175  ×  larger than baseline neural recordings (which were 110 µV peak-to-peak), while intramuscular stimulation artifacts were only 4  ×  larger. The artifact waveforms were highly consistent across electrodes within each array. Application of LRR reduced artifact magnitudes to less than 10 µV and largely preserved the original neural feature values used for decoding. Unmitigated stimulation artifacts decreased iBCI decoding performance, but performance was almost completely recovered using LRR, which outperformed CAR and blanking and extracted useful neural information during stimulation artifact periods. Significance. The LRR method was effective at reducing electrical artifacts resulting from both intramuscular and surface FES, and

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2008-01-01

We present a new abstract machine for Abadi and Cardelli's untyped calculus of objects. What is special about this semantic artifact (i.e., man-made construct) is that is mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i...... actual substitutions, we then represent object methods as closures and in the same inter-derivational spirit, we present three new semantic artifacts: a reduction semantics for a version of Abadi and Cardelli's untyped calculus of objects with explicit substitutions, an environment-based abstract machine...

EEG Artifact Removal Using a Wavelet Neural Network

Science.gov (United States)

Nguyen, Hoang-Anh T.; Musson, John; Li, Jiang; McKenzie, Frederick; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom

2011-01-01

!n this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We. compared the WNN algorithm with .the ICA technique ,and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.

Ring artifact reduction in synchrotron X-ray tomography through helical acquisition

NARCIS (Netherlands)

D.M. Pelt (Daniël); D.Y. Parkinson (Dilworth)

2017-01-01

textabstractIn synchrotron X-ray tomography, systematic defects in certain detector elements can result in arc-shaped artifacts in the final reconstructed image of the scanned sample. These ring artifacts are commonly found in many applications of synchrotron tomography, and can make

Multiple Suboptimal Solutions for Prediction Rules in Gene Expression Data

Directory of Open Access Journals (Sweden)

Osamu Komori

2013-01-01

Full Text Available This paper discusses mathematical and statistical aspects in analysis methods applied to microarray gene expressions. We focus on pattern recognition to extract informative features embedded in the data for prediction of phenotypes. It has been pointed out that there are severely difficult problems due to the unbalance in the number of observed genes compared with the number of observed subjects. We make a reanalysis of microarray gene expression published data to detect many other gene sets with almost the same performance. We conclude in the current stage that it is not possible to extract only informative genes with high performance in the all observed genes. We investigate the reason why this difficulty still exists even though there are actively proposed analysis methods and learning algorithms in statistical machine learning approaches. We focus on the mutual coherence or the absolute value of the Pearson correlations between two genes and describe the distributions of the correlation for the selected set of genes and the total set. We show that the problem of finding informative genes in high dimensional data is ill-posed and that the difficulty is closely related with the mutual coherence.

Analysis of artifact and infrequent physiological uptake in 18F-FDG PET/CT

International Nuclear Information System (INIS)

Li Tianran; Zhao Chunlei; Qian Gennian; Chen Ziqian; Wang Kaitang; You Xueyu; Zheng Chunyu

2006-01-01

Objective: To explore the artifact and infrequent physiological uptake in PET/CT with its imaging and formation features. Methods: The data of PET/CT imaging were retrospectively analyzed and classified based on their cause. Besides, the infrequent physiological uptakes were also analyzed. Results: Artifacts could be classified into natural and technological causes. In natural causes, respiratory movement and high-density matters artifacts were frequently found, whereas in technological cause, the truncation, radioactive leakage and pollution commonly appeared. Infrequent physiological uptakes included uterine endometrium, breast and fat uptakes. Conclusions: The imaging features of artifact in PET can be divided into 'hot' or 'cold' area while infrequent physiological uptakes mainly are 'hot' area. Among the cause of artifact formation, CT-based attenuation corrected physical factor is the commonest. The infrequent physiological uptake somewhat relates to technological error. (authors)

Image-based metal artifact reduction in x-ray computed tomography utilizing local anatomical similarity

Science.gov (United States)

Dong, Xue; Yang, Xiaofeng; Rosenfield, Jonathan; Elder, Eric; Dhabaan, Anees

2017-03-01

X-ray computed tomography (CT) is widely used in radiation therapy treatment planning in recent years. However, metal implants such as dental fillings and hip prostheses can cause severe bright and dark streaking artifacts in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. In this work, a metal artifact reduction method is proposed based on the intrinsic anatomical similarity between neighboring CT slices. Neighboring CT slices from the same patient exhibit similar anatomical features. Exploiting this anatomical similarity, a gamma map is calculated as a weighted summation of relative HU error and distance error for each pixel in an artifact-corrupted CT image relative to a neighboring, artifactfree image. The minimum value in the gamma map for each pixel is used to identify an appropriate pixel from the artifact-free CT slice to replace the corresponding artifact-corrupted pixel. With the proposed method, the mean CT HU error was reduced from 360 HU and 460 HU to 24 HU and 34 HU on head and pelvis CT images, respectively. Dose calculation accuracy also improved, as the dose difference was reduced from greater than 20% to less than 4%. Using 3%/3mm criteria, the gamma analysis failure rate was reduced from 23.25% to 0.02%. An image-based metal artifact reduction method is proposed that replaces corrupted image pixels with pixels from neighboring CT slices free of metal artifacts. This method is shown to be capable of suppressing streaking artifacts, thereby improving HU and dose calculation accuracy.

The relation between respiratory motion artifact correction and lung standardized uptake value

International Nuclear Information System (INIS)

Yin Lijie; Liu Xiaojian; Liu Jie; Xu Rui; Yan Jue

2014-01-01

PET/CT is playing an important role in disease diagnosis and therapeutic evaluation. But the respiratory motion artifact may bring trouble in diagnosis and therapy. There are many methods to correct the respiratory motion artifact. Respiratory gated PET/CT is applied most extensively of them. Using respiratory gated PET/CT to correct respiratory motion artifact can increase the maximum standardized uptake value of lung lesion obviously, thereby improving the quality of image and accuracy of diagnosis. (authors)

Histologic processing artifacts and inter-pathologist variation in measurement of inked margins of canine mast cell tumors.

Science.gov (United States)

Kiser, Patti K; Löhr, Christiane V; Meritet, Danielle; Spagnoli, Sean T; Milovancev, Milan; Russell, Duncan S

2018-05-01

Although quantitative assessment of margins is recommended for describing excision of cutaneous malignancies, there is poor understanding of limitations associated with this technique. We described and quantified histologic artifacts in inked margins and determined the association between artifacts and variance in histologic tumor-free margin (HTFM) measurements based on a novel grading scheme applied to 50 sections of normal canine skin and 56 radial margins taken from 15 different canine mast cell tumors (MCTs). Three broad categories of artifact were 1) tissue deformation at inked edges, 2) ink-associated artifacts, and 3) sectioning-associated artifacts. The most common artifacts in MCT margins were ink-associated artifacts, specifically ink absent from an edge (mean prevalence: 50%) and inappropriate ink coloring (mean: 45%). The prevalence of other artifacts in MCT skin was 4-50%. In MCT margins, frequency-adjusted kappa statistics found fair or better inter-rater reliability for 9 of 10 artifacts; intra-rater reliability was moderate or better in 9 of 10 artifacts. Digital HTFM measurements by 5 blinded pathologists had a median standard deviation (SD) of 1.9 mm (interquartile range: 0.8-3.6 mm; range: 0-6.2 mm). Intraclass correlation coefficients demonstrated good inter-pathologist reliability in HTFM measurement (κ = 0.81). Spearman rank correlation coefficients found negligible correlation between artifacts and HTFM SDs ( r ≤ 0.3). These data confirm that although histologic artifacts commonly occur in inked margin specimens, artifacts are not meaningfully associated with variation in HTFM measurements. Investigators can use the grading scheme presented herein to identify artifacts associated with tissue processing.

Clinical evaluation of TOF versus non-TOF on PET artifacts in simultaneous PET/MR: a dual centre experience

Energy Technology Data Exchange (ETDEWEB)

Voert, Edwin E.G.W. ter [University Hospital Zurich, Department of Nuclear Medicine, Zurich (Switzerland); University of Zurich, Zurich (Switzerland); Veit-Haibach, Patrick [University Hospital Zurich, Department of Nuclear Medicine, Zurich (Switzerland); University of Zurich, Zurich (Switzerland); University Hospital Zurich, Department of Diagnostic and Interventional Radiology, Zurich (Switzerland); Ahn, Sangtae [GE Global Research, Niskayuna, NY (United States); Wiesinger, Florian [GE Global Research, Muenchen (Germany); Khalighi, M.M.; Delso, Gaspar [GE Healthcare, Waukesha, WI (United States); Levin, Craig S. [Stanford University, Department of Radiology, Molecular Imaging Program at Stanford, Stanford, CA (United States); Iagaru, Andrei H. [Stanford University, Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Stanford, CA (United States); Zaharchuk, Greg [Stanford University, Department of Radiology, Neuroradiology, Stanford, CA (United States); Huellner, Martin [University Hospital Zurich, Department of Nuclear Medicine, Zurich (Switzerland); University of Zurich, Zurich (Switzerland); University Hospital Zurich, Department of Neuroradiology, Zurich (Switzerland)

2017-07-15

Our objective was to determine clinically the value of time-of-flight (TOF) information in reducing PET artifacts and improving PET image quality and accuracy in simultaneous TOF PET/MR scanning. A total 65 patients who underwent a comparative scan in a simultaneous TOF PET/MR scanner were included. TOF and non-TOF PET images were reconstructed, clinically examined, compared and scored. PET imaging artifacts were categorized as large or small implant-related artifacts, as dental implant-related artifacts, and as implant-unrelated artifacts. Differences in image quality, especially those related to (implant) artifacts, were assessed using a scale ranging from 0 (no artifact) to 4 (severe artifact). A total of 87 image artifacts were found and evaluated. Four patients had large and eight patients small implant-related artifacts, 27 patients had dental implants/fillings, and 48 patients had implant-unrelated artifacts. The average score was 1.14 ± 0.82 for non-TOF PET images and 0.53 ± 0.66 for TOF images (p < 0.01) indicating that artifacts were less noticeable when TOF information was included. Our study indicates that PET image artifacts are significantly mitigated with integration of TOF information in simultaneous PET/MR. The impact is predominantly seen in patients with significant artifacts due to metal implants. (orig.)

Presenting Cultural Artifacts in the Art Museum: A University-Museum Collaboration

Science.gov (United States)

Chung, Sheng Kuan

2009-01-01

With increasing emphasis on multicultural art education and integrative pedagogy, educators have incorporated community resources, such as cultural artifacts exhibited in art museums, to enrich their programs. Cultural artifacts are human-made objects which generally reveal historic information about cultural values, beliefs, and traditions.…

Ecological transition predictably associated with gene degeneration.

Science.gov (United States)

Wessinger, Carolyn A; Rausher, Mark D

2015-02-01

Gene degeneration or loss can significantly contribute to phenotypic diversification, but may generate genetic constraints on future evolutionary trajectories, potentially restricting phenotypic reversal. Such constraints may manifest as directional evolutionary trends when parallel phenotypic shifts consistently involve gene degeneration or loss. Here, we demonstrate that widespread parallel evolution in Penstemon from blue to red flowers predictably involves the functional inactivation and degeneration of the enzyme flavonoid 3',5'-hydroxylase (F3'5'H), an anthocyanin pathway enzyme required for the production of blue floral pigments. Other types of genetic mutations do not consistently accompany this phenotypic shift. This pattern may be driven by the relatively large mutational target size of degenerative mutations to this locus and the apparent lack of associated pleiotropic effects. The consistent degeneration of F3'5'H may provide a mechanistic explanation for the observed asymmetry in the direction of flower color evolution in Penstemon: Blue to red transitions are common, but reverse transitions have not been observed. Although phenotypic shifts in this system are likely driven by natural selection, internal constraints may generate predictable genetic outcomes and may restrict future evolutionary trajectories. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A preliminary study of muscular artifact cancellation in single-channel EEG.

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Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K

2014-10-01

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For practical reasons, a single EEG channel system must be used in these situations. Unfortunately, there exist few studies for muscular artifact cancellation in single-channel EEG recordings. To address this issue, in this preliminary study, we propose a simple, yet effective, method to achieve the muscular artifact cancellation for the single-channel EEG case. This method is a combination of the ensemble empirical mode decomposition (EEMD) and the joint blind source separation (JBSS) techniques. We also conduct a study that compares and investigates all possible single-channel solutions and demonstrate the performance of these methods using numerical simulations and real-life applications. The proposed method is shown to significantly outperform all other methods. It can successfully remove muscular artifacts without altering the underlying EEG activity. It is thus a promising tool for use in ambulatory healthcare systems.

A gene signature in histologically normal surgical margins is predictive of oral carcinoma recurrence

International Nuclear Information System (INIS)

Reis, Patricia P; Simpson, Colleen; Goldstein, David; Brown, Dale; Gilbert, Ralph; Gullane, Patrick; Irish, Jonathan; Jurisica, Igor; Kamel-Reid, Suzanne; Waldron, Levi; Perez-Ordonez, Bayardo; Pintilie, Melania; Galloni, Natalie Naranjo; Xuan, Yali; Cervigne, Nilva K; Warner, Giles C; Makitie, Antti A

2011-01-01

Oral Squamous Cell Carcinoma (OSCC) is a major cause of cancer death worldwide, which is mainly due to recurrence leading to treatment failure and patient death. Histological status of surgical margins is a currently available assessment for recurrence risk in OSCC; however histological status does not predict recurrence, even in patients with histologically negative margins. Therefore, molecular analysis of histologically normal resection margins and the corresponding OSCC may aid in identifying a gene signature predictive of recurrence. We used a meta-analysis of 199 samples (OSCCs and normal oral tissues) from five public microarray datasets, in addition to our microarray analysis of 96 OSCCs and histologically normal margins from 24 patients, to train a gene signature for recurrence. Validation was performed by quantitative real-time PCR using 136 samples from an independent cohort of 30 patients. We identified 138 significantly over-expressed genes (> 2-fold, false discovery rate of 0.01) in OSCC. By penalized likelihood Cox regression, we identified a 4-gene signature with prognostic value for recurrence in our training set. This signature comprised the invasion-related genes MMP1, COL4A1, P4HA2, and THBS2. Over-expression of this 4-gene signature in histologically normal margins was associated with recurrence in our training cohort (p = 0.0003, logrank test) and in our independent validation cohort (p = 0.04, HR = 6.8, logrank test). Gene expression alterations occur in histologically normal margins in OSCC. Over-expression of the 4-gene signature in histologically normal surgical margins was validated and highly predictive of recurrence in an independent patient cohort. Our findings may be applied to develop a molecular test, which would be clinically useful to help predict which patients are at a higher risk of local recurrence

Effects of using coding potential, sequence conservation and mRNA structure conservation for predicting pyrroly-sine containing genes

DEFF Research Database (Denmark)

Have, Christian Theil; Zambach, Sine; Christiansen, Henning

2013-01-01

for prediction of pyrrolysine incorporating genes in genomes of bacteria and archaea leading to insights about the factors driving pyrrolysine translation and identification of new gene candidates. The method predicts known conserved genes with high recall and predicts several other promising candidates...... for experimental verification. The method is implemented as a computational pipeline which is available on request....

Metal artifact reduction using a patch-based reconstruction for digital breast tomosynthesis

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Borges, Lucas R.; Bakic, Predrag R.; Maidment, Andrew D. A.; Vieira, Marcelo A. C.

2017-03-01

Digital breast tomosynthesis (DBT) is rapidly emerging as the main clinical tool for breast cancer screening. Although several reconstruction methods for DBT are described by the literature, one common issue is the interplane artifacts caused by out-of-focus features. For breasts containing highly attenuating features, such as surgical clips and large calcifications, the artifacts are even more apparent and can limit the detection and characterization of lesions by the radiologist. In this work, we propose a novel method of combining backprojected data into tomographic slices using a patch-based approach, commonly used in denoising. Preliminary tests were performed on a geometry phantom and on an anthropomorphic phantom containing metal inserts. The reconstructed images were compared to a commercial reconstruction solution. Qualitative assessment of the reconstructed images provides evidence that the proposed method reduces artifacts while maintaining low noise levels. Objective assessment supports the visual findings. The artifact spread function shows that the proposed method is capable of suppressing artifacts generated by highly attenuating features. The signal difference to noise ratio shows that the noise levels of the proposed and commercial methods are comparable, even though the commercial method applies post-processing filtering steps, which were not implemented on the proposed method. Thus, the proposed method can produce tomosynthesis reconstructions with reduced artifacts and low noise levels.

Mitigation of artifacts in rtm with migration kernel decomposition

KAUST Repository

Zhan, Ge

2012-01-01

The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently. In this paper, we present a generalized diffraction-stack migration approach for reducing RTM artifacts via decomposition of migration kernel. The decomposition leads to an improved understanding of migration artifacts and, therefore, presents us with opportunities for improving the quality of RTM images.

Magnetic resonance imaging metallic artifact of commonly encountered surgical implants and foreign material.

Science.gov (United States)

Sutherland-Smith, James; Tilley, Brenda

2012-01-01

Magnetic resonance imaging (MRI) artifacts secondary to metallic implants and foreign bodies are well described. Herein, we provide quantitative data from veterinary implants including total hip arthroplasty implants, cranial cruciate repair implants, surgical screws, a skin staple, ligation clips, an identification microchip, ameroid constrictor, and potential foreign bodies including air gun and BB projectiles and a sewing needle. The objects were scanned in a gelatin phantom with plastic grid using standardized T2-weighted turbo-spin echo (TSE), T1-weighted spin echo, and T2*-weighted gradient recalled echo (GRE) image acquisitions at 1.5 T. Maximum linear dimensions and areas of signal voiding and grid distortion were calculated using a DICOM workstation for each sequence and object. Artifact severity was similar between the T2-weighted TSE and T1-weighted images, while the T2*-weighted images were most susceptible to artifact. Metal type influenced artifact size with the largest artifacts arising from steel objects followed by surgical stainless steel, titanium, and lead. For animals with metallic surgical implants or foreign bodies, the quantification of the artifact size will help guide clinicians on the viability of MRI. © 2012 Veterinary Radiology & Ultrasound.

Quantitative analysis of titanium-induced artifacts and correlated factors during micro-CT scanning.

Science.gov (United States)

Li, Jun Yuan; Pow, Edmond Ho Nang; Zheng, Li Wu; Ma, Li; Kwong, Dora Lai Wan; Cheung, Lim Kwong

2014-04-01

To investigate the impact of cover screw, resin embedment, and implant angulation on artifact of microcomputed tomography (micro-CT) scanning for implant. A total of twelve implants were randomly divided into 4 groups: (i) implant only; (ii) implant with cover screw; (iii) implant with resin embedment; and (iv) implants with cover screw and resin embedment. Implants angulation at 0°, 45°, and 90° were scanned by micro-CT. Images were assessed, and the ratio of artifact volume to total volume (AV/TV) was calculated. A multiple regression analysis in stepwise model was used to determine the significance of different factors. One-way ANOVA was performed to identify which combination of factors could minimize the artifact. In the regression analysis, implant angulation was identified as the best predictor for artifact among the factors (P  0.05). Non-embedded implants with the axis parallel to X-ray source of micro-CT produced minimal artifact. Implant angulation and resin embedment affected the artifact volume of micro-CT scanning for implant, while cover screw did not. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Correction of ring artifacts in X-ray tomographic images

DEFF Research Database (Denmark)

Lyckegaard, Allan; Johnson, G.; Tafforeau, P.

2011-01-01

Ring artifacts are systematic intensity distortions located on concentric circles in reconstructed tomographic X-ray images. When using X-ray tomography to study for instance low-contrast grain boundaries in metals it is crucial to correct for the ring artifacts in the images as they may have...... the same intensity level as the grain boundaries and thus make it impossible to perform grain segmentation. This paper describes an implementation of a method for correcting the ring artifacts in tomographic X-ray images of simple objects such as metal samples where the object and the background...... are separable. The method is implemented in Matlab, it works with very little user interaction and may run in parallel on a cluster if applied to a whole stack of images. The strength and robustness of the method implemented will be demonstrated on three tomographic X-ray data sets: a mono-phase β...

Dinucleotide controlled null models for comparative RNA gene prediction.

Science.gov (United States)

Gesell, Tanja; Washietl, Stefan

2008-05-27

Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. SISSIz

Dinucleotide controlled null models for comparative RNA gene prediction

Directory of Open Access Journals (Sweden)

Gesell Tanja

2008-05-01

Full Text Available Abstract Background Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. Results We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. Conclusion SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require

Dealing with noise and physiological artifacts in human EEG recordings: empirical mode methods

Science.gov (United States)

Runnova, Anastasiya E.; Grubov, Vadim V.; Khramova, Marina V.; Hramov, Alexander E.

2017-04-01

In the paper we propose the new method for removing noise and physiological artifacts in human EEG recordings based on empirical mode decomposition (Hilbert-Huang transform). As physiological artifacts we consider specific oscillatory patterns that cause problems during EEG analysis and can be detected with additional signals recorded simultaneously with EEG (ECG, EMG, EOG, etc.) We introduce the algorithm of the proposed method with steps including empirical mode decomposition of EEG signal, choosing of empirical modes with artifacts, removing these empirical modes and reconstructing of initial EEG signal. We show the efficiency of the method on the example of filtration of human EEG signal from eye-moving artifacts.

Artifacts in MR angiography of the intracranial vessels using the 3D TOF and 3D PC techniques

International Nuclear Information System (INIS)

Park, Dong Woo; Lee, Seung Ro; Hahm, Chang Kok; Kim, Yong Soo; Park, Choong Ki

1997-01-01

To classify artifacts and to assess their frequency in magnetic resonance angiography of intracranial vessels using three- dimensional time-of-flight and phase-contrast techniques. One hundred and eleven patients with suspected cerebrovascular disease were imaged on a 1.5T superconducting magnetic resonance machine employing three- dimensional time-of-flight and phase-contrast magnetic resonance angiographic techniques. We retrospectively reviewed the artifacts in three- dimensional time-of-flight and phase-contrast magnetic resonance angiography of the intracranial circulatory system, comparing them with routine spin-echo magnetic resonance images and magnetic resonance angiography source images, and partially with conventional angiography. Artifacts in magnetic resonance angiography were classified as flow-related, and flow-unrealted, by patient, hardware, magnetic resonance angiography acquisition and postprocessing techniques. Type and frequency of flow-related artifacts included saturation artifact (100%), dephasing artifact (100%), phase-encoding ghost artifact (97%), turbulence artifact (14%) and flow displacement artifact (5%) on three- dimensional time-of-flight and phase-contrast magnetic resonance angiography, and phase aliasing artifact (2%) on three-dimensional phase-contrast magnetic resonance angiography. Type and frequency of flow-unrelated artifacts included stair-step artifact (100%) by three- dimensional reconstruction process, magnetic susceptibility artifact by carotid canal (69%) and metal (4%), maximum intensity projection artifact (30%) by maximum intensity projection algorithm, and motion artifact by respiration (20%) and voluntary movement (8%); these were seen on both time-of-flight and phase-contrast magnetic resonance angiography. Paramagnetic substance artifact by fat and paranasal sinus mucosa (100%), hematoma (14%) and gadolinium (5%) were seen on time-of-flight magnetic resonance angiography. In three- dimensional time-of-flight and

Artifacts, intentions, and contraceptives: the problem with having a plan B for plan B.

Science.gov (United States)

Reed, Philip A

2013-12-01

It is commonly proposed that artifacts cannot be understood without reference to human intentions. This fact, I contend, has relevance to the use of artifacts in intentional action. I argue that because artifacts have intentions embedded into them antecedently, when we use artifacts we are sometimes compelled to intend descriptions of our actions that we might, for various reasons, be inclined to believe that we do not intend. I focus this argument to a specific set of artifacts, namely, medical devices, before considering an extended application to emergency contraceptive devices. Although there is some debate about whether emergency contraception has an abortifacient effect, I argue that if there is an abortifacient effect, then the effect cannot normally be a side effect of one's action.

HOX Gene Promoter Prediction and Inter-genomic Comparison: An Evo-Devo Study

Directory of Open Access Journals (Sweden)

Marla A. Endriga

2010-10-01

Full Text Available Homeobox genes direct the anterior-posterior axis of the body plan in eukaryotic organisms. Promoter regions upstream of the Hox genes jumpstart the transcription process. CpG islands found within the promoter regions can cause silencing of these promoters. The locations of the promoter regions and the CpG islands of Homeo sapiens sapiens (human, Pan troglodytes (chimpanzee, Mus musculus (mouse, and Rattus norvegicus (brown rat are compared and related to the possible influence on the specification of the mammalian body plan. The sequence of each gene in Hox clusters A-D of the mammals considered were retrieved from Ensembl and locations of promoter regions and CpG islands predicted using Exon Finder. The predicted promoter sequences were confirmed via BLAST and verified against the Eukaryotic Promoter Database. The significance of the locations was determined using the Kruskal-Wallis test. Among the four clusters, only promoter locations in cluster B showed significant difference. HOX B genes have been linked with the control of genes that direct the development of axial morphology, particularly of the vertebral column bones. The magnitude of variation among the body plans of closely-related species can thus be partially attributed to the promoter kind, location and number, and gene inactivation via CpG methylation.

Toddlers View Artifact Function Normatively

Science.gov (United States)

Casler, Krista; Terziyan, Treysi; Greene, Kimberly

2009-01-01

When children use objects like adults, are they simply tracking regularities in others' object use, or are they demonstrating a normatively defined awareness that there are right and wrong ways to act? This study provides the first evidence for the latter possibility. Young 2- and 3-year-olds (n = 32) learned functions of 6 artifacts, both…

Mitigation of Selected Hanford Site Manhattan Project and Cold War Era Artifacts

International Nuclear Information System (INIS)

Prendergast-Kennedy, Ellen L.; Harvey, David W.

2006-01-01

This document is the first time that Manhattan Project and Cold War era artifacts from the Hanford Site have been assembled within a publication. The publication presents photographic and written documentation of a number of Manhattan Project and Cold War era artifacts that were identified and tagged during assessment walk throughs of historic buildings on the Hanford Site but which could not be curated within the Hanford collection because they were too large for long-term storage and/or exhibit purposes or were radiologically contaminated. The significance of the artifacts in this publication and a proposed future appendix is based not on the individual significance of any single artifact but on their collective contribution to the science and engineering of creating plutonium and advancing nuclear technology in nuclear fuel and power.

Mitigation of Selected Hanford Site Manhattan Project and Cold War Era Artifacts

Energy Technology Data Exchange (ETDEWEB)

Kennedy, Ellen P.; Harvey, David W.

2006-09-08

This document is the first time that Manhattan Project and Cold War era artifacts from the Hanford Site have been assembled within a publication. The publication presents photographic and written documentation of a number of Manhattan Project and Cold War era artifacts that were identified and tagged during assessment walk throughs of historic buildings on the Hanford Site but which could not be curated within the Hanford collection because they were too large for long-term storage and/or exhibit purposes or were radiologically contaminated. The significance of the artifacts in this publication and a proposed future appendix is based not on the individual significance of any single artifact but on their collective contribution to the science and engineering of creating plutonium and advancing nuclear technology in nuclear fuel and power.

Genomic Prediction of Gene Bank Wheat Landraces

Directory of Open Access Journals (Sweden)

José Crossa

2016-07-01

Full Text Available This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H for the highly heritable traits, days to heading (DTH, and days to maturity (DTM. Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E. Two alternative prediction strategies were studied: (1 random cross-validation of the data in 20% training (TRN and 80% testing (TST (TRN20-TST80 sets, and (2 two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm

Renal streaky artifact during contrast-enhanced abdominal and pelvic CT: Comparison of high versus low osmolality contrast media

International Nuclear Information System (INIS)

Kim, Dae Hong; Kim, Jong Chul; Lee, Chung Keun; Shin, Kyoung Suk

1994-01-01

Introduction of low osmolality contrast agent(LOCA) has allowed safer, more comfortable contrast-enhanced CT examination, but there has been significant increase in image degradation when evaluating the kidneys due to streaky artifact. The authors reviewed findings of contrast- enhanced abdominal and pelvic computed tomography(CT) to know the difference of renal streaky artifact between a high osmolality contrast agent (HOCA) and LOCA. This study included two hundred contrast-enhanced CT in 200 patients, 100 performed with HOCA(meglumine ioglicate, 150 ml) and 100 performed with LOCA (iopromide,150 ml). The severity of renal streaky artifact was compared between HOCA and LOCA groups. Of the scans performed with HOCA, 40 had no artifact, 52 had grade I artifact, 6 had grade II artifact, and 2 had grade III artifact. Of the scans preformed with LOCA, 23 had no artifact, 44 had grade I artifact, 29 had grade II artifact, and 4 had grade III artifact. There was significant difference in the degree of the streaky artifact depending upon the osmolality of the contrast media used(by χ 2 -test, P=.0001). The results of this study revealed a statistically significant increased incidence of artifacts and distortions of renal image with LOCA when compared with HOCA

A robust post-processing workflow for datasets with motion artifacts in diffusion kurtosis imaging.

Science.gov (United States)

Li, Xianjun; Yang, Jian; Gao, Jie; Luo, Xue; Zhou, Zhenyu; Hu, Yajie; Wu, Ed X; Wan, Mingxi

2014-01-01

The aim of this study was to develop a robust post-processing workflow for motion-corrupted datasets in diffusion kurtosis imaging (DKI). The proposed workflow consisted of brain extraction, rigid registration, distortion correction, artifacts rejection, spatial smoothing and tensor estimation. Rigid registration was utilized to correct misalignments. Motion artifacts were rejected by using local Pearson correlation coefficient (LPCC). The performance of LPCC in characterizing relative differences between artifacts and artifact-free images was compared with that of the conventional correlation coefficient in 10 randomly selected DKI datasets. The influence of rejected artifacts with information of gradient directions and b values for the parameter estimation was investigated by using mean square error (MSE). The variance of noise was used as the criterion for MSEs. The clinical practicality of the proposed workflow was evaluated by the image quality and measurements in regions of interest on 36 DKI datasets, including 18 artifact-free (18 pediatric subjects) and 18 motion-corrupted datasets (15 pediatric subjects and 3 essential tremor patients). The relative difference between artifacts and artifact-free images calculated by LPCC was larger than that of the conventional correlation coefficient (pworkflow improved the image quality and reduced the measurement biases significantly on motion-corrupted datasets (pworkflow was reliable to improve the image quality and the measurement precision of the derived parameters on motion-corrupted DKI datasets. The workflow provided an effective post-processing method for clinical applications of DKI in subjects with involuntary movements.

Off-resonance artifacts correction with convolution in k-space (ORACLE).

Science.gov (United States)

Lin, Wei; Huang, Feng; Simonotto, Enrico; Duensing, George R; Reykowski, Arne

2012-06-01

Off-resonance artifacts hinder the wider applicability of echo-planar imaging and non-Cartesian MRI methods such as radial and spiral. In this work, a general and rapid method is proposed for off-resonance artifacts correction based on data convolution in k-space. The acquired k-space is divided into multiple segments based on their acquisition times. Off-resonance-induced artifact within each segment is removed by applying a convolution kernel, which is the Fourier transform of an off-resonance correcting spatial phase modulation term. The field map is determined from the inverse Fourier transform of a basis kernel, which is calibrated from data fitting in k-space. The technique was demonstrated in phantom and in vivo studies for radial, spiral and echo-planar imaging datasets. For radial acquisitions, the proposed method allows the self-calibration of the field map from the imaging data, when an alternating view-angle ordering scheme is used. An additional advantage for off-resonance artifacts correction based on data convolution in k-space is the reusability of convolution kernels to images acquired with the same sequence but different contrasts. Copyright © 2011 Wiley-Liss, Inc.

TU-F-CAMPUS-J-04: Evaluation of Metal Artifact Reduction Technique for the Radiation Therapy Planning

International Nuclear Information System (INIS)

Jeong, K; Kuo, H; Ritter, J; Shen, J; Basavatia, A; Yaparpalvi, R; Kalnicki, S; Tome, W

2015-01-01

Purpose: To evaluate the feasibility of using a metal artifact reduction technique in depleting metal artifact and its application in improving dose calculation in External Radiation Therapy Planning. Methods: CIRS electron density phantom was scanned with and without steel drill bits placed in some plug holes. Meta artifact reduction software with Metal Deletion Technique (MDT) was used to remove metal artifacts for scanned image with metal. Hounsfield units of electron density plugs from artifact free reference image and MDT processed images were compared. To test the dose calculation improvement after the MDT processed images, clinically approved head and neck plan with manual dental artifact correction was tested. Patient images were exported and processed with MDT and plan was recalculated with new MDT image without manual correction. Dose profiles near the metal artifacts were compared. Results: The MDT used in this study effectively reduced the metal artifact caused by beam hardening and scatter. The windmill around the metal drill was greatly improved with smooth rounded view. Difference of the mean HU in each density plug between reference and MDT images were less than 10 HU in most of the plugs. Dose difference between original plan and MDT images were minimal. Conclusion: Most metal artifact reduction methods were developed for diagnostic improvement purpose. Hence Hounsfield unit accuracy was not rigorously tested before. In our test, MDT effectively eliminated metal artifacts with good HU reproduciblity. However, it can introduce new mild artifacts so the MDT images should be checked with original images

Automatic Removal of Physiological Artifacts in EEG: The Optimized Fingerprint Method for Sports Science Applications.

Science.gov (United States)

Stone, David B; Tamburro, Gabriella; Fiedler, Patrique; Haueisen, Jens; Comani, Silvia

2018-01-01

Data contamination due to physiological artifacts such as those generated by eyeblinks, eye movements, and muscle activity continues to be a central concern in the acquisition and analysis of electroencephalographic (EEG) data. This issue is further compounded in EEG sports science applications where the presence of artifacts is notoriously difficult to control because behaviors that generate these interferences are often the behaviors under investigation. Therefore, there is a need to develop effective and efficient methods to identify physiological artifacts in EEG recordings during sports applications so that they can be isolated from cerebral activity related to the activities of interest. We have developed an EEG artifact detection model, the Fingerprint Method, which identifies different spatial, temporal, spectral, and statistical features indicative of physiological artifacts and uses these features to automatically classify artifactual independent components in EEG based on a machine leaning approach. Here, we optimized our method using artifact-rich training data and a procedure to determine which features were best suited to identify eyeblinks, eye movements, and muscle artifacts. We then applied our model to an experimental dataset collected during endurance cycling. Results reveal that unique sets of features are suitable for the detection of distinct types of artifacts and that the Optimized Fingerprint Method was able to correctly identify over 90% of the artifactual components with physiological origin present in the experimental data. These results represent a significant advancement in the search for effective means to address artifact contamination in EEG sports science applications.

Methylation of cancer-stem-cell-associated Wnt target genes predicts poor prognosis in colorectal cancer patients

NARCIS (Netherlands)

de Sousa E Melo, Felipe; Colak, Selcuk; Buikhuisen, Joyce; Koster, Jan; Cameron, Kate; de Jong, Joan H.; Tuynman, Jurriaan B.; Prasetyanti, Pramudita R.; Fessler, Evelyn; van den Bergh, Saskia P.; Rodermond, Hans; Dekker, Evelien; van der Loos, Chris M.; Pals, Steven T.; van de Vijver, Marc J.; Versteeg, Rogier; Richel, Dick J.; Vermeulen, Louis; Medema, Jan Paul

2011-01-01

Gene signatures derived from cancer stem cells (CSCs) predict tumor recurrence for many forms of cancer. Here, we derived a gene signature for colorectal CSCs defined by high Wnt signaling activity, which in agreement with previous observations predicts poor prognosis. Surprisingly, however, we

Language and other artifacts: socio-cultural dynamics of niche construction

Science.gov (United States)

Sinha, Chris

2015-01-01

Niche construction theory is a relatively new approach in evolutionary biology that seeks to integrate an ecological dimension into the Darwinian theory of evolution by natural selection. It is regarded by many evolutionary biologists as providing a significant revision of the Neo-Darwinian modern synthesis that unified Darwin’s theory of natural and sexual selection with 20th century population genetics. Niche construction theory has been invoked as a processual mediator of social cognitive evolution and of the emergence and evolution of language. I argue that language itself can be considered as a biocultural niche and evolutionary artifact. I provide both a general analysis of the cognitive and semiotic status of artifacts, and a formal analysis of language as a social and semiotic institution, based upon a distinction between the fundamental semiotic relations of “counting as” and “standing for.” I explore the consequences for theories of language and language learning of viewing language as a biocultural niche. I suggest that not only do niches mediate organism-organism interactions, but also that organisms mediate niche-niche interactions in ways that affect evolutionary processes, with the evolution of human infancy and childhood as a key example. I argue that language as a social and semiotic system is not only grounded in embodied engagements with the material and social-interactional world, but also grounds a sub-class of artifacts of particular significance in the cultural history of human cognition. Symbolic cognitive artifacts materially and semiotically mediate human cognition, and are not merely informational repositories, but co-agentively constitutive of culturally and historically emergent cognitive domains. I provide examples of the constitutive cognitive role of symbolic cognitive artifacts drawn from my research with my colleagues on cultural and linguistic conceptualizations of time, and their cultural variability. I conclude by

Accuracy and artifact: reexamining the intensity bias in affective forecasting.

Science.gov (United States)

Levine, Linda J; Lench, Heather C; Kaplan, Robin L; Safer, Martin A

2012-10-01

Research on affective forecasting shows that people have a robust tendency to overestimate the intensity of future emotion. We hypothesized that (a) people can accurately predict the intensity of their feelings about events and (b) a procedural artifact contributes to people's tendency to overestimate the intensity of their feelings in general. People may misinterpret the forecasting question as asking how they will feel about a focal event, but they are later asked to report their feelings in general without reference to that event. In the current investigation, participants predicted and reported both their feelings in general and their feelings about an election outcome (Study 1) and an exam grade (Study 3). We also assessed how participants interpreted forecasting questions (Studies 2 and 4) and conducted a meta-analysis of affective forecasting research (Study 5). The results showed that participants accurately predicted the intensity of their feelings about events. They overestimated only when asked to predict how they would feel in general and later report their feelings without reference to the focal event. Most participants, however, misinterpreted requests to predict their feelings in general as asking how they would feel when they were thinking about the focal event. Clarifying the meaning of the forecasting question significantly reduced overestimation. These findings reveal that people have more sophisticated self-knowledge than is commonly portrayed in the affective forecasting literature. Overestimation of future emotion is partly due to a procedure in which people predict one thing but are later asked to report another.

Prediction of human protein function according to Gene Ontology categories

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Gupta, Ramneek; Stærfeldt, Hans Henrik

2003-01-01

developed a method for prediction of protein function for a subset of classes from the Gene Ontology classification scheme. This subset includes several pharmaceutically interesting categories-transcription factors, receptors, ion channels, stress and immune response proteins, hormones and growth factors...

Distinction of Fly Artifacts from Human Blood using Immunodetection.

Science.gov (United States)

Rivers, David B; Acca, Gillian; Fink, Marc; Brogan, Rebecca; Chen, Dorothy; Schoeffield, Andrew

2018-02-21

Insect stains produced by necrophagous flies are indistinguishable morphologically from human bloodstains. At present, no diagnostic tests exist to overcome this deficiency. As the first step toward developing a chemical test to recognize fly artifacts, polyclonal antisera were generated in rats against three distinct antigenic sequences of fly cathepsin D-like proteinase, an enzyme that is structurally distinct in cyclorrhaphous Diptera from other animals. The resulting rat antisera bound to artifacts produced by Protophormia terraenovae and synthetic peptides used to generate the polyclonal antisera, but not with any type of mammalian blood tested in immunoassays. Among the three antisera, anti-md3 serum displayed the highest reactivity for fly stains, demonstrated cross-reactivity for all synthetic peptides representing antigenic sequences of the mature fly enzyme, and bound artifacts originating from the fly digestive tract. Further work is needed to determine whether the antisera are suitable for non-laboratory conditions. © 2018 American Academy of Forensic Sciences.

Beam Hardening Artifacts: Comparison between Two Cone Beam Computed Tomography Scanners

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Farzad Esmaeili

2012-04-01

Full Text Available Background and aims. At present, cone beam computed tomography (CBCT has become a substitute for computed tomography (CT in dental procedures. The metallic materials used in dentistry can produce artifacts due to the beam hardening phenomenon. These artifacts decrease the quality of images. In the present study, the number of artifacts as a result of beam hardening in the images of dental implants was compared between two NewTom VG and Planmeca Promax 3D Max CBCT machines. Materials and methods. An implant drilling model was used in the present study. The implants (Dentis were placed in the canine, premolar and molar areas. Scanning procedures were carried out by two CBCT machines. The corresponding sections (coronal and axial of the implants were evaluated by two radiologists. The number of artifacts in each image was determined using the scale provided. Mann-Whitney U test was used for two-by-two comparisons at a significance level of P<0.05. Results. There were statistically significant differences in beam hardening artifacts in axial and coronal sections between the two x-ray machines (P<0.001, with a higher quality in the images produced by the NewTom VG. Conclusion. Given the higher quality of the images produced by the NewTom VG x-ray machine, it is recommended for imaging of patients with extensive restorations, multiple prostheses or previous implant treatments.

Artifact removal algorithms for stroke detection using a multistatic MIST beamforming algorithm.

Science.gov (United States)

Ricci, E; Di Domenico, S; Cianca, E; Rossi, T

2015-01-01

Microwave imaging (MWI) has been recently proved as a promising imaging modality for low-complexity, low-cost and fast brain imaging tools, which could play a fundamental role to efficiently manage emergencies related to stroke and hemorrhages. This paper focuses on the UWB radar imaging approach and in particular on the processing algorithms of the backscattered signals. Assuming the use of the multistatic version of the MIST (Microwave Imaging Space-Time) beamforming algorithm, developed by Hagness et al. for the early detection of breast cancer, the paper proposes and compares two artifact removal algorithms. Artifacts removal is an essential step of any UWB radar imaging system and currently considered artifact removal algorithms have been shown not to be effective in the specific scenario of brain imaging. First of all, the paper proposes modifications of a known artifact removal algorithm. These modifications are shown to be effective to achieve good localization accuracy and lower false positives. However, the main contribution is the proposal of an artifact removal algorithm based on statistical methods, which allows to achieve even better performance but with much lower computational complexity.

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY

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YÜCEL, MERYEM A.; SELB, JULIETTE; COOPER, ROBERT J.; BOAS, DAVID A.

2014-01-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson’s correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson’s correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data. PMID:25360181

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY.

Science.gov (United States)

Yücel, Meryem A; Selb, Juliette; Cooper, Robert J; Boas, David A

2014-03-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson's correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson's correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data.

Concerted down-regulation of immune-system related genes predicts metastasis in colorectal carcinoma

International Nuclear Information System (INIS)

Fehlker, Marion; Huska, Matthew R; Jöns, Thomas; Andrade-Navarro, Miguel A; Kemmner, Wolfgang

2014-01-01

This study aimed at the identification of prognostic gene expression markers in early primary colorectal carcinomas without metastasis at the time point of surgery by analyzing genome-wide gene expression profiles using oligonucleotide microarrays. Cryo-conserved tumor specimens from 45 patients with early colorectal cancers were examined, with the majority of them being UICC stage II or earlier and with a follow-up time of 41–115 months. Gene expression profiling was performed using Whole Human Genome 4x44K Oligonucleotide Microarrays. Validation of microarray data was performed on five of the genes in a smaller cohort. Using a novel algorithm based on the recursive application of support vector machines (SVMs), we selected a signature of 44 probes that discriminated between patients developing later metastasis and patients with a good prognosis. Interestingly, almost half of the genes was related to the patients’ immune response and showed reduced expression in the metastatic cases. Whereas up to now gene signatures containing genes with various biological functions have been described for prediction of metastasis in CRC, in this study metastasis could be well predicted by a set of gene expression markers consisting exclusively of genes related to the MHC class II complex involved in immune response. Thus, our data emphasize that the proper function of a comprehensive network of immune response genes is of vital importance for the survival of colorectal cancer patients

Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower.

Science.gov (United States)

Thorwarth, Patrick; Yousef, Eltohamy A A; Schmid, Karl J

2018-02-02

Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS) and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower ( Brassica oleracea var. botrytis ) by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS) and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding. Copyright © 2018 Thorwarth et al.

Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower

Directory of Open Access Journals (Sweden)

Patrick Thorwarth

2018-02-01

Full Text Available Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower (Brassica oleracea var. botrytis by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding.

Material-Dependent Implant Artifact Reduction Using SEMAC-VAT and MAVRIC: A Prospective MRI Phantom Study.

Science.gov (United States)

Filli, Lukas; Jud, Lukas; Luechinger, Roger; Nanz, Daniel; Andreisek, Gustav; Runge, Val M; Kozerke, Sebastian; Farshad-Amacker, Nadja A

2017-06-01

The aim of this study was to compare the degree of artifact reduction in magnetic resonance imaging achieved with slice encoding for metal artifact correction (SEMAC) in combination with view angle tilting (VAT) and multiacquisition variable resonance image combination (MAVRIC) for standard contrast weightings and different metallic materials. Four identically shaped rods made of the most commonly used prosthetic materials (stainless steel, SS; titanium, Ti; cobalt-chromium-molybdenum, CoCr; and oxidized zirconium, oxZi) were scanned at 3 T. In addition to conventional fast spin-echo sequences, metal artifact reduction sequences (SEMAC-VAT and MAVRIC) with varying degrees of artifact suppression were applied at different contrast weightings (T1w, T2w, PDw). Two independent readers measured in-plane and through-plane artifacts in a standardized manner. In addition, theoretical frequency-offset and frequency-offset-gradient maps were calculated. Interobserver agreement was assessed using intraclass correlation coefficient. Interobserver agreement was almost perfect (intraclass correlation coefficient, 0.86-0.99). Stainless steel caused the greatest artifacts, followed by CoCr, Ti, and oxZi regardless of the imaging sequence. While for Ti and oxZi rods scanning with weak SEMAC-VAT showed some advantage, for SS and CoCr, higher modes of SEMAC-VAT or MAVRIC were necessary to achieve artifact reduction. MAVRIC achieved better artifact reduction than SEMAC-VAT at the cost of longer acquisition times. Simulations matched well with the apparent geometry of the frequency-offset maps. For Ti and oxZi implants, weak SEMAC-VAT may be preferred as it is faster and produces less artifact than conventional fast spin-echo. Medium or strong SEMAC-VAT or MAVRIC modes are necessary for significant artifact reduction for SS and CoCr implants.

FlexiView: A Magnet-Based Approach for Visualizing Requirements Artifacts

OpenAIRE

Ghazi, Parisa; Seyff, Norbert; Glinz, Martin

2015-01-01

Requirements engineers create large numbers of artifacts when eliciting and documenting requirements. They need to navigate through these artifacts and display information details at points of interest for reviewing or editing information. [Question/problem] Traditional visualization mechanisms such as scrolling and opening multiple windows lose context when navigating and can be cumbersome to use, hence. On the other hand, focus+context approaches can display details in context, but they dis...

Genome sequence analysis of predicted polyprenol reductase gene from mangrove plant kandelia obovata

Science.gov (United States)

Basyuni, M.; Sagami, H.; Baba, S.; Oku, H.

2018-03-01

It has been previously reported that dolichols but not polyprenols were predominated in mangrove leaves and roots. Therefore, the occurrence of larger amounts of dolichol in leaves of mangrove plants implies that polyprenol reductase is responsible for the conversion of polyprenol to dolichol may be active in mangrove leaves. Here we report the early assessment of probably polyprenol reductase gene from genome sequence of mangrove plant Kandelia obovata. The functional assignment of the gene was based on a homology search of the sequences against the non-redundant (nr) peptide database of NCBI using Blastx. The degree of sequence identity between DNA sequence and known polyprenol reductase was confirmed using the Blastx probability E-value, total score, and identity. The genome sequence data resulted in three partial sequences, termed c23157 (700 bp), c23901 (960 bp), and c24171 (531 bp). The c23157 gene showed the highest similarity (61%) to predicted polyprenol reductase 2- like from Gossypium raimondii with E-value 2e-100. The second gene was c23901 to exhibit high similarity (78%) to the steroid 5-alpha-reductase Det2 from J. curcas with E-value 2e-140. Furthermore, the c24171 gene depicted highest similarity (79%) to the polyprenol reductase 2 isoform X1 from Jatropha curcas with E- value 7e-21.The present study suggested that the c23157, c23901, and c24171, genes may encode predicted polyprenol reductase. The c23157, c23901, c24171 are therefore the new type of predicted polyprenol reductase from K. obovata.

Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes.

Directory of Open Access Journals (Sweden)

Christof Winter

Full Text Available Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

Motion-induced dose artifacts in helical tomotherapy

Energy Technology Data Exchange (ETDEWEB)

Kim, Bryan; Chen, Jeff; Battista, Jerry [London Regional Cancer Program, London Health Sciences Centre, London, ON (Canada); Kron, Tomas [Peter MacCallum Cancer Center, Melbourne (Australia)], E-mail: bryan.kim@lhsc.on.ca

2009-10-07

Tumor motion is a particular concern for a complex treatment modality such as helical tomotherapy, where couch position, gantry rotation and MLC leaf opening all change with time. In the present study, we have investigated the impact of tumor motion for helical tomotherapy, which could result in three distinct motion-induced dose artifacts, namely (1) dose rounding, (2) dose rippling and (3) IMRT leaf opening asynchronization effect. Dose rounding and dose rippling effects have been previously described, while the IMRT leaf opening asynchronization effect is a newly discovered motion-induced dose artifact. Dose rounding is the penumbral widening of a delivered dose distribution near the edges of a target volume along the direction of tumor motion. Dose rippling is a series of periodic dose peaks and valleys observed within the target region along the direction of couch motion, due to an asynchronous interplay between the couch motion and the longitudinal component of tumor motion. The IMRT leaf opening asynchronization effect is caused by an asynchronous interplay between the temporal patterns of leaf openings and tumor motion. The characteristics of each dose artifact were investigated individually as functions of target motion amplitude and period for both non-IMRT and IMRT helical tomotherapy cases, through computer simulation modeling and experimental verification. The longitudinal dose profiles generated by the simulation program agreed with the experimental data within {+-}0.5% and {+-}1.5% inside the PTV region for the non-IMRT and IMRT cases, respectively. The dose rounding effect produced a penumbral increase up to 20.5 mm for peak-to-peak target motion amplitudes ranging from 1.0 cm to 5.0 cm. Maximum dose rippling magnitude of 25% was calculated, when the target motion period approached an unusually high value of 10 s. The IMRT leaf opening asynchronization effect produced dose differences ranging from -29% to 7% inside the PTV region. This information

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

Science.gov (United States)

Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

2013-09-22

High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

Science.gov (United States)

Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-10-13

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

Inspection about the corrosion of metallic archaeological artifacts in ground. 2

Energy Technology Data Exchange (ETDEWEB)

Honda, Takashi; Yamaguchi, Shingo [Hitachi Engineering Co., Ltd., Hitachi, Ibaraki (Japan)

2002-02-01

The corrosion of iron-base archaeological artifacts, which were dug out in Iyomai-7 (Chitose-shi, Hokkaido) and Izumo-Ooyashiro-Keidai (Taisha-machi, Shimane-ken) sites, was investigated by using X-ray CT, XRD, atomic absorption spectroscopy and EDX techniques. While the artifacts such as swords in Iyomai-7 site had been buried in the ground for 400-500 years, metallic iron remained in the swords and the corrosion amounts were estimated to be 2-5 mm. Several artifacts were investigated among a lot of iron rings and nails buried beside huge pillars of the ancient shrine. Those artifacts had been in ground for 730-750 years. The corrosion amounts were estimated to be 3-5 mm. As the both soil environments are supposed to be oxidizing, the outer oxide layers of all species are composed of goethite and soil. Further, it was clarified that perfectly corroded ones had hollow structures. In this study, the sampling method of species, the corrosion environmental factors, and the corrosion kinetic models were also evaluated. (author)

A New Approach to Eliminate High Amplitude Artifacts in EEG Signals

Directory of Open Access Journals (Sweden)

Ana Rita Teixeira

2016-09-01

Full Text Available High amplitude artifacts represent a problem during EEG recordings in neuroscience research. Taking this into account, this paper proposes a method to identify high amplitude artifacts with no requirement for visual inspection, electrooscillogram (EOG reference channel or user assigned parameters. A potential solution to the high amplitude artifacts (HAA elimination is presented based on blind source separation methods. The assumption underlying the selection of components is that HAA are independent of the EEG signal and different HAA can be generated during the EEG recordings. Therefore, the number of components related to HAA is variable and depends on the processed signal, which means that the method is adaptable to the input signal. The results show, when removing the HAA artifacts, the delta band is distorted but all the other frequency bands are preserved. A case study with EEG signals recorded while participants performed on the Halstead Category Test (HCT is presented. After HAA removal, data analysis revealed, as expected, an error-related frontal ERP wave: the feedback-related negativity (FRN in response to feedback stimuli.

lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis

Directory of Open Access Journals (Sweden)

Silu Zhang

2018-01-01

Full Text Available Background: Breast cancer is intrinsically heterogeneous and is commonly classified into four main subtypes associated with distinct biological features and clinical outcomes. However, currently available data resources and methods are limited in identifying molecular subtyping on protein-coding genes, and little is known about the roles of long non-coding RNAs (lncRNAs, which occupies 98% of the whole genome. lncRNAs may also play important roles in subgrouping cancer patients and are associated with clinical phenotypes. Methods: The purpose of this project was to identify lncRNA gene signatures that are associated with breast cancer subtypes and clinical outcomes. We identified lncRNA gene signatures from The Cancer Genome Atlas (TCGA RNAseq data that are associated with breast cancer subtypes by an optimized 1-Norm SVM feature selection algorithm. We evaluated the prognostic performance of these gene signatures with a semi-supervised principal component (superPC method. Results: Although lncRNAs can independently predict breast cancer subtypes with satisfactory accuracy, a combined gene signature including both coding and non-coding genes will give the best clinically relevant prediction performance. We highlighted eight potential biomarkers (three from coding genes and five from non-coding genes that are significantly associated with survival outcomes. Conclusion: Our proposed methods are a novel means of identifying subtype-specific coding and non-coding potential biomarkers that are both clinically relevant and biologically significant.

Twinkling artifact on color Doppler ultrasound: an advantage or a pitfall?

Science.gov (United States)

Ozan, Ebru; Atac, Gokce Kaan; Gundogdu, Sadi

2016-07-01

The twinkling artifact (TA) or color comet-tail artifact is characterized by a rapidly changing mixture of red and blue color Doppler signals. Even though many diseases and clinical conditions have been shown to produce this artifact, its source is not clearly understood yet. The TA may provide additional information to gray-scale ultrasound findings in several clinical situations. However, there may be pitfalls to keep in mind. We must first be aware of the TA to benefit from the advantages and avoid the pitfalls. In this review, we aim to give practicing radiologists an overview of the mechanisms and clinical applications of the TA by illustrating sample cases we have encountered.

In silico prediction of novel therapeutic targets using gene-disease association data.

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Ferrero, Enrico; Dunham, Ian; Sanseau, Philippe

2017-08-29

Target identification and validation is a pressing challenge in the pharmaceutical industry, with many of the programmes that fail for efficacy reasons showing poor association between the drug target and the disease. Computational prediction of successful targets could have a considerable impact on attrition rates in the drug discovery pipeline by significantly reducing the initial search space. Here, we explore whether gene-disease association data from the Open Targets platform is sufficient to predict therapeutic targets that are actively being pursued by pharmaceutical companies or are already on the market. To test our hypothesis, we train four different classifiers (a random forest, a support vector machine, a neural network and a gradient boosting machine) on partially labelled data and evaluate their performance using nested cross-validation and testing on an independent set. We then select the best performing model and use it to make predictions on more than 15,000 genes. Finally, we validate our predictions by mining the scientific literature for proposed therapeutic targets. We observe that the data types with the best predictive power are animal models showing a disease-relevant phenotype, differential expression in diseased tissue and genetic association with the disease under investigation. On a test set, the neural network classifier achieves over 71% accuracy with an AUC of 0.76 when predicting therapeutic targets in a semi-supervised learning setting. We use this model to gain insights into current and failed programmes and to predict 1431 novel targets, of which a highly significant proportion has been independently proposed in the literature. Our in silico approach shows that data linking genes and diseases is sufficient to predict novel therapeutic targets effectively and confirms that this type of evidence is essential for formulating or strengthening hypotheses in the target discovery process. Ultimately, more rapid and automated target

GPU-Based Simulation of Ultrasound Imaging Artifacts for Cryosurgery Training

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Keelan, Robert; Shimada, Kenji

2016-01-01

This study presents an efficient computational technique for the simulation of ultrasound imaging artifacts associated with cryosurgery based on nonlinear ray tracing. This study is part of an ongoing effort to develop computerized training tools for cryosurgery, with prostate cryosurgery as a development model. The capability of performing virtual cryosurgical procedures on a variety of test cases is essential for effective surgical training. Simulated ultrasound imaging artifacts include reverberation and reflection of the cryoprobes in the unfrozen tissue, reflections caused by the freezing front, shadowing caused by the frozen region, and tissue property changes in repeated freeze–thaw cycles procedures. The simulated artifacts appear to preserve the key features observed in a clinical setting. This study displays an example of how training may benefit from toggling between the undisturbed ultrasound image, the simulated temperature field, the simulated imaging artifacts, and an augmented hybrid presentation of the temperature field superimposed on the ultrasound image. The proposed method is demonstrated on a graphic processing unit at 100 frames per second, on a mid-range personal workstation, at two orders of magnitude faster than a typical cryoprocedure. This performance is based on computation with C++ accelerated massive parallelism and its interoperability with the DirectX-rendering application programming interface. PMID:26818026

Prediction of lymphatic metastasis based on gene expression profile analysis after brachytherapy for early-stage oral tongue carcinoma

International Nuclear Information System (INIS)

Watanabe, Hiroshi; Mogushi, Kaoru; Miura, Masahiko; Yoshimura, Ryo-ichi; Kurabayashi, Tohru; Shibuya, Hitoshi; Tanaka, Hiroshi; Noda, Shuhei; Iwakawa, Mayumi; Imai, Takashi

2008-01-01

Background and purpose: The management of lymphatic metastasis of early-stage oral tongue carcinoma patients is crucial for its prognosis. The purpose of this study was to evaluate the predictive ability of lymphatic metastasis after brachytherapy (BRT) for early-stage tongue carcinoma based on gene expression profiling. Patients and methods: Pre-therapeutic biopsies from 39 patients with T1 or T2 tongue cancer were analyzed for gene expression signatures using Codelink Uniset Human 20K Bioarray. All patients were treated with low dose-rate BRT for their primary lesions and underwent strict follow-up under a wait-and-see policy for cervical lymphatic metastasis. Candidate genes were selected for predicting lymph-node status in the reference group by the permutation test. Predictive accuracy was further evaluated by the prediction strength (PS) scoring system using an independent validation group. Results: We selected a set of 19 genes whose expression differed significantly between classes with or without lymphatic metastasis in the reference group. The lymph-node status in the validation group was predicted by the PS scoring system with an accuracy of 76%. Conclusions: Gene expression profiling using 19 genes in primary tumor tissues may allow prediction of lymphatic metastasis after BRT for early-stage oral tongue carcinoma

Independent component analysis for cochlear implant artifacts attenuation from electrically evoked auditory steady-state response measurements

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Deprez, Hanne; Gransier, Robin; Hofmann, Michael; van Wieringen, Astrid; Wouters, Jan; Moonen, Marc

2018-02-01

Objective. Electrically evoked auditory steady-state responses (EASSRs) are potentially useful for objective cochlear implant (CI) fitting and follow-up of the auditory maturation in infants and children with a CI. EASSRs are recorded in the electro-encephalogram (EEG) in response to electrical stimulation with continuous pulse trains, and are distorted by significant CI artifacts related to this electrical stimulation. The aim of this study is to evaluate a CI artifacts attenuation method based on independent component analysis (ICA) for three EASSR datasets. Approach. ICA has often been used to remove CI artifacts from the EEG to record transient auditory responses, such as cortical evoked auditory potentials. Independent components (ICs) corresponding to CI artifacts are then often manually identified. In this study, an ICA based CI artifacts attenuation method was developed and evaluated for EASSR measurements with varying CI artifacts and EASSR characteristics. Artifactual ICs were automatically identified based on their spectrum. Main results. For 40 Hz amplitude modulation (AM) stimulation at comfort level, in high SNR recordings, ICA succeeded in removing CI artifacts from all recording channels, without distorting the EASSR. For lower SNR recordings, with 40 Hz AM stimulation at lower levels, or 90 Hz AM stimulation, ICA either distorted the EASSR or could not remove all CI artifacts in most subjects, except for two of the seven subjects tested with low level 40 Hz AM stimulation. Noise levels were reduced after ICA was applied, and up to 29 ICs were rejected, suggesting poor ICA separation quality. Significance. We hypothesize that ICA is capable of separating CI artifacts and EASSR in case the contralateral hemisphere is EASSR dominated. For small EASSRs or large CI artifact amplitudes, ICA separation quality is insufficient to ensure complete CI artifacts attenuation without EASSR distortion.

ERAASR: an algorithm for removing electrical stimulation artifacts from multielectrode array recordings

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O'Shea, Daniel J.; Shenoy, Krishna V.

2018-04-01

Objective. Electrical stimulation is a widely used and effective tool in systems neuroscience, neural prosthetics, and clinical neurostimulation. However, electrical artifacts evoked by stimulation prevent the detection of spiking activity on nearby recording electrodes, which obscures the neural population response evoked by stimulation. We sought to develop a method to clean artifact-corrupted electrode signals recorded on multielectrode arrays in order to recover the underlying neural spiking activity. Approach. We created an algorithm, which performs estimation and removal of array artifacts via sequential principal components regression (ERAASR). This approach leverages the similar structure of artifact transients, but not spiking activity, across simultaneously recorded channels on the array, across pulses within a train, and across trials. The ERAASR algorithm requires no special hardware, imposes no requirements on the shape of the artifact or the multielectrode array geometry, and comprises sequential application of straightforward linear methods with intuitive parameters. The approach should be readily applicable to most datasets where stimulation does not saturate the recording amplifier. Main results. The effectiveness of the algorithm is demonstrated in macaque dorsal premotor cortex using acute linear multielectrode array recordings and single electrode stimulation. Large electrical artifacts appeared on all channels during stimulation. After application of ERAASR, the cleaned signals were quiescent on channels with no spontaneous spiking activity, whereas spontaneously active channels exhibited evoked spikes which closely resembled spontaneously occurring spiking waveforms. Significance. We hope that enabling simultaneous electrical stimulation and multielectrode array recording will help elucidate the causal links between neural activity and cognition and facilitate naturalistic sensory protheses.

"Diabetes and literacy: negotiating control through artifacts of medicalization".

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Martins, David S

2009-06-01

My experience with the California Department of Motor Vehicles offers a case to explore how bureaucratic institutions monitor, classify, and control individuals. By examining artifacts created for and used by the DMV through the lens of literacy studies, I discuss the variety of rhetorical strategies used in each document and the effects and implications of those strategies, for example on subjectivity or identity, and move beyond the language of the artifacts themselves to attend to how they are invested with power in the management and control of populations.

Quantitative assessment of image artifacts from root filling materials on CBCT scans made using several exposure parameters

International Nuclear Information System (INIS)

Rabelo, Katharina Alves; Cavalcanti, Yuri Wanderley; De Oliveira Pinto, Martina Gerlane; De Melo, Daniela Pita; Melo, Saulo Leonardo Sousa; Campos, Paulo Sergio Flores; De Andrade Freitas Oliveira, Luciana Soares

2017-01-01

To quantify artifacts from different root filling materials in cone-beam computed tomography (CBCT) images acquired using different exposure parameters. Fifteen single-rooted teeth were scanned using 8 different exposure protocols with 3 different filling materials and once without filling material as a control group. Artifact quantification was performed by a trained observer who made measurements in the central axial slice of all acquired images in a fixed region of interest using ImageJ. Hyperdense artifacts, hypodense artifacts, and the remaining tooth area were identified, and the percentages of hyperdense and hypodense artifacts, remaining tooth area, and tooth area affected by the artifacts were calculated. Artifacts were analyzed qualitatively by 2 observers using the following scores: absence (0), moderate presence (1), and high presence (2) for hypodense halos, hypodense lines, and hyperdense lines. Two-way ANOVA and the post-hoc Tukey test were used for quantitative and qualitative artifact analysis. The Dunnet test was also used for qualitative analysis. The significance level was set at P .05). Different exposure parameters did not affect the objective or subjective observations of artifacts in CBCT images; however, the filling materials used in endodontic restorations did affect both types of assessments

Automatic identification and removal of ocular artifacts in EEG--improved adaptive predictor filtering for portable applications.

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Zhao, Qinglin; Hu, Bin; Shi, Yujun; Li, Yang; Moore, Philip; Sun, Minghou; Peng, Hong

2014-06-01

Electroencephalogram (EEG) signals have a long history of use as a noninvasive approach to measure brain function. An essential component in EEG-based applications is the removal of Ocular Artifacts (OA) from the EEG signals. In this paper we propose a hybrid de-noising method combining Discrete Wavelet Transformation (DWT) and an Adaptive Predictor Filter (APF). A particularly novel feature of the proposed method is the use of the APF based on an adaptive autoregressive model for prediction of the waveform of signals in the ocular artifact zones. In our test, based on simulated data, the accuracy of noise removal in the proposed model was significantly increased when compared to existing methods including: Wavelet Packet Transform (WPT) and Independent Component Analysis (ICA), Discrete Wavelet Transform (DWT) and Adaptive Noise Cancellation (ANC). The results demonstrate that the proposed method achieved a lower mean square error and higher correlation between the original and corrected EEG. The proposed method has also been evaluated using data from calibration trials for the Online Predictive Tools for Intervention in Mental Illness (OPTIMI) project. The results of this evaluation indicate an improvement in performance in terms of the recovery of true EEG signals with EEG tracking and computational speed in the analysis. The proposed method is well suited to applications in portable environments where the constraints with respect to acceptable wearable sensor attachments usually dictate single channel devices.

Preliminary experimental insights into differential heat impact among lithic artifacts

OpenAIRE

Guillermo Bustos-Pérez; Javier Baena Preysler

2016-01-01

The presence of thermally altered and broken flint artifacts is common at archaeological sites. Most studies focus their attention on the effects of heat treatment on flint to improve knapping qualities, disregarding the effects of fire over flint under uncontrolled conditions. This paper aims to show how under uncontrolled heating processes flint artifacts develop different heat alterations (such as levels of breakage, presence of scales, etc.) as a result of vertical distribution, volume or...

How to bring a technical artifact into use: A micro-developmental perspective

NARCIS (Netherlands)

Overdijk, Maarten; Van Diggelen, Wouter; Andriessen, Jerry; Kirschner, Paul A.

2018-01-01

In order to understand how technical artifacts are attuned to, interacted with, and shaped in various and varied classrooms, it is necessary to construct detailed accounts of the use of particular artifacts in particular classrooms. This paper presents a descriptive account of how a shared

A formal ontological perspective on the behaviors and functions of technical artifacts

NARCIS (Netherlands)

Borgo, S.; Carrara, M.; Garbacz, P.; Vermaas, P.E.

2008-01-01

In this paper we present a formal characterization of the engineering concepts of behavior and function of technical artifacts. We capture the meanings that engineers attach to these concepts by formalizing, within the formal ontology DOLCE, the five meanings of artifact behavior and the two

Reduction of variable-truncation artifacts from beam occlusion during in situ x-ray tomography

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Borg, Leise; Jørgensen, Jakob S.; Frikel, Jürgen; Sporring, Jon

2017-12-01

Many in situ x-ray tomography studies require experimental rigs which may partially occlude the beam and cause parts of the projection data to be missing. In a study of fluid flow in porous chalk using a percolation cell with four metal bars drastic streak artifacts arise in the filtered backprojection (FBP) reconstruction at certain orientations. Projections with non-trivial variable truncation caused by the metal bars are the source of these variable-truncation artifacts. To understand the artifacts a mathematical model of variable-truncation data as a function of metal bar radius and distance to sample is derived and verified numerically and with experimental data. The model accurately describes the arising variable-truncation artifacts across simulated variations of the experimental setup. Three variable-truncation artifact-reduction methods are proposed, all aimed at addressing sinogram discontinuities that are shown to be the source of the streaks. The ‘reduction to limited angle’ (RLA) method simply keeps only non-truncated projections; the ‘detector-directed smoothing’ (DDS) method smooths the discontinuities; while the ‘reflexive boundary condition’ (RBC) method enforces a zero derivative at the discontinuities. Experimental results using both simulated and real data show that the proposed methods effectively reduce variable-truncation artifacts. The RBC method is found to provide the best artifact reduction and preservation of image features using both visual and quantitative assessment. The analysis and artifact-reduction methods are designed in context of FBP reconstruction motivated by computational efficiency practical for large, real synchrotron data. While a specific variable-truncation case is considered, the proposed methods can be applied to general data cut-offs arising in different in situ x-ray tomography experiments.

Histone modification profiles are predictive for tissue/cell-type specific expression of both protein-coding and microRNA genes

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Zhang Michael Q

2011-05-01

Full Text Available Abstract Background Gene expression is regulated at both the DNA sequence level and through modification of chromatin. However, the effect of chromatin on tissue/cell-type specific gene regulation (TCSR is largely unknown. In this paper, we present a method to elucidate the relationship between histone modification/variation (HMV and TCSR. Results A classifier for differentiating CD4+ T cell-specific genes from housekeeping genes using HMV data was built. We found HMV in both promoter and gene body regions to be predictive of genes which are targets of TCSR. For example, the histone modification types H3K4me3 and H3K27ac were identified as the most predictive for CpG-related promoters, whereas H3K4me3 and H3K79me3 were the most predictive for nonCpG-related promoters. However, genes targeted by TCSR can be predicted using other type of HMVs as well. Such redundancy implies that multiple type of underlying regulatory elements, such as enhancers or intragenic alternative promoters, which can regulate gene expression in a tissue/cell-type specific fashion, may be marked by the HMVs. Finally, we show that the predictive power of HMV for TCSR is not limited to protein-coding genes in CD4+ T cells, as we successfully predicted TCSR targeted genes in muscle cells, as well as microRNA genes with expression specific to CD4+ T cells, by the same classifier which was trained on HMV data of protein-coding genes in CD4+ T cells. Conclusion We have begun to understand the HMV patterns that guide gene expression in both tissue/cell-type specific and ubiquitous manner.

Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.

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Liu, Zhongming; de Zwart, Jacco A; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H

2012-02-01

We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphasis is directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac timing markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable with the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. Published by Elsevier Inc.

Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique

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Abbaspour, S; Fallah, A

2014-01-01

Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful. Objective: Removing electrocardiogram contamination from electromyogram signals. Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and electrocardiogram signal were recorded from leg muscles, the pectoralis major muscle of the left side and V4, respectively. After the pre-processing, contaminated electromyogram signal is simulated with a combination of clean electromyogram and electrocardiogram artifact. Then, contaminated electromyogram is cleaned using adaptive subtraction method. This method contains some steps; (1) QRS detection, (2) formation of electrocardiogram template by averaging the electrocardiogram complexes, (3) using low pass filter to remove undesirable artifacts, (4) subtraction. Results: Performance of our method is evaluated using qualitative criteria, power spectrum density and coherence and quantitative criteria signal to noise ratio, relative error and cross correlation. The result of signal to noise ratio, relative error and cross correlation is equal to 10.493, 0.04 and %97 respectively. Finally, there is a comparison between proposed method and some existing methods. Conclusion: The result indicates that adaptive subtraction method is somewhat effective to remove electrocardiogram artifact from contaminated electromyogram signal and has an acceptable result. PMID:25505766

The Smoothing Artifact of Spatially Constrained Canonical Correlation Analysis in Functional MRI

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Dietmar Cordes

2012-01-01

Full Text Available A wide range of studies show the capacity of multivariate statistical methods for fMRI to improve mapping of brain activations in a noisy environment. An advanced method uses local canonical correlation analysis (CCA to encompass a group of neighboring voxels instead of looking at the single voxel time course. The value of a suitable test statistic is used as a measure of activation. It is customary to assign the value to the center voxel; however, this is a choice of convenience and without constraints introduces artifacts, especially in regions of strong localized activation. To compensate for these deficiencies, different spatial constraints in CCA have been introduced to enforce dominance of the center voxel. However, even if the dominance condition for the center voxel is satisfied, constrained CCA can still lead to a smoothing artifact, often called the “bleeding artifact of CCA”, in fMRI activation patterns. In this paper a new method is introduced to measure and correct for the smoothing artifact for constrained CCA methods. It is shown that constrained CCA methods corrected for the smoothing artifact lead to more plausible activation patterns in fMRI as shown using data from a motor task and a memory task.

A standardized evaluation of artifacts from metallic compounds during fast MR imaging

DEFF Research Database (Denmark)

Murakami, Shumei; Verdonschot, Rinus G; Kataoka, Miyoshi

2016-01-01

according to the ASTM-F2119 standard and artifact volumes were assessed using OsiriX MD software Results: Tukey-Kramer post-hoc tests were used for statistical comparisons. For most materials, scanning sequences eliciting artifact volumes in the following (ascending) order FSE-T1/FSE-T2

Gene expression patterns in formalin-fixed, paraffin-embedded core biopsies predict docetaxel chemosensitivity in breast cancer patients.

Science.gov (United States)

Chang, Jenny C; Makris, Andreas; Gutierrez, M Carolina; Hilsenbeck, Susan G; Hackett, James R; Jeong, Jennie; Liu, Mei-Lan; Baker, Joffre; Clark-Langone, Kim; Baehner, Frederick L; Sexton, Krsytal; Mohsin, Syed; Gray, Tara; Alvarez, Laura; Chamness, Gary C; Osborne, C Kent; Shak, Steven

2008-03-01

Previously, we had identified gene expression patterns that predicted response to neoadjuvant docetaxel. Other studies have validated that a high Recurrence Score (RS) by the 21-gene RT-PCR assay is predictive of worse prognosis but better response to chemotherapy. We investigated whether tumor expression of these 21 genes and other candidate genes can predict response to docetaxel. Core biopsies from 97 patients were obtained before treatment with neoadjuvant docetaxel (4 cycles, 100 mg/m2 q3 weeks). Three 10-microm FFPE sections were submitted for quantitative RT-PCR assays of 192 genes that were selected from our previous work and the literature. Of the 97 patients, 81 (84%) had sufficient invasive cancer, 80 (82%) had sufficient RNA for QRTPCR assay, and 72 (74%) had clinical response data. Mean age was 48.5 years, and the median tumor size was 6 cm. Clinical complete responses (CR) were observed in 12 (17%), partial responses in 41 (57%), stable disease in 17 (24%), and progressive disease in 2 patients (3%). A significant relationship (P<0.05) between gene expression and CR was observed for 14 genes, including CYBA. CR was associated with lower expression of the ER gene group and higher expression of the proliferation gene group from the 21 gene assay. Of note, CR was more likely with a high RS (P=0.008). We have established molecular profiles of sensitivity to docetaxel. RT-PCR technology provides a potential platform for a predictive test of docetaxel chemosensitivity using small amounts of routinely processed material.

Björk-Shiley convexoconcave valves: susceptibility artifacts at brain MR imaging and mechanical valve fractures.

Science.gov (United States)

van Gorp, Maarten J; van der Graaf, Yolanda; de Mol, Bas A J M; Bakker, Chris J G; Witkamp, Theo D; Ramos, Lino M P; Mali, Willem P T M

2004-03-01

To assess the relationship between heart valve history and susceptibility artifacts at magnetic resonance (MR) imaging of the brain in patients with Björk-Shiley convexoconcave (BSCC) valves. MR images of the brain were obtained in 58 patients with prosthetic heart valves: 20 patients had BSCC valve replacements, and 38 had other types of heart valves. Two experienced neuroradiologists determined the presence or absence of susceptibility artifacts in a consensus reading. Artifacts were defined as characteristic black spots that were visible on T2*-weighted gradient-echo MR images. The statuses of the 20 explanted BSCC valves-specifically, whether they were intact or had an outlet strut fracture (OSF) or a single-leg fracture (SLF)-had been determined earlier. Number of artifacts seen at brain MR imaging was correlated with explanted valve status, and differences were analyzed with nonparametric statistical tests. Significantly more patients with BSCC valves (17 [85%] of 20 patients) than patients with other types of prosthetic valves (18 [47%] of 38 patients) had susceptibility artifacts at MR imaging (P =.005). BSCC valve OSFs were associated with a significantly higher number of artifacts than were intact BSCC valves (P =.01). No significant relationship between SLF and number of artifacts was observed. Susceptibility artifacts at brain MR imaging are not restricted to patients with BSCC valves. These artifacts can be seen on images obtained in patients with various other types of fractured and intact prosthetic heart valves. Copyright RSNA, 2004

Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

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Borlawsky Tara B

2010-10-01

Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgVH mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgVH status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgVH mutational status which can accurately predict the survival outcome are yet to be discovered. Results In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgVH mutation status from the ZAP70 co-expression network. Conclusions We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgVH mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.

Reducing Interpolation Artifacts for Mutual Information Based Image Registration

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Soleimani, H.; Khosravifard, M.A.

2011-01-01

Medical image registration methods which use mutual information as similarity measure have been improved in recent decades. Mutual Information is a basic concept of Information theory which indicates the dependency of two random variables (or two images). In order to evaluate the mutual information of two images their joint probability distribution is required. Several interpolation methods, such as Partial Volume (PV) and bilinear, are used to estimate joint probability distribution. Both of these two methods yield some artifacts on mutual information function. Partial Volume-Hanning window (PVH) and Generalized Partial Volume (GPV) methods are introduced to remove such artifacts. In this paper we show that the acceptable performance of these methods is not due to their kernel function. It's because of the number of pixels which incorporate in interpolation. Since using more pixels requires more complex and time consuming interpolation process, we propose a new interpolation method which uses only four pixels (the same as PV and bilinear interpolations) and removes most of the artifacts. Experimental results of the registration of Computed Tomography (CT) images show superiority of the proposed scheme. PMID:22606673

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

Science.gov (United States)

Mognon, Andrea; Jovicich, Jorge; Bruzzone, Lorenzo; Buiatti, Marco

2011-02-01

A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event-related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal. Copyright © 2010 Society for Psychophysiological Research.

Image quality analysis to reduce dental artifacts in head and neck imaging with dual-source computed tomography

Energy Technology Data Exchange (ETDEWEB)

Ketelsen, D.; Werner, M.K.; Thomas, C.; Tsiflikas, I.; Reimann, A.; Claussen, C.D.; Heuschmid, M. [Tuebingen Univ. (Germany). Abt. fuer Diagnostische und Interventionelle Radiologie; Koitschev, A. [Tuebingen Univ. (Germany). Abt. fuer Hals-Nasen-Ohrenheilkunde

2009-01-15

Purpose: Important oropharyngeal structures can be superimposed by metallic artifacts due to dental implants. The aim of this study was to compare the image quality of multiplanar reconstructions and an angulated spiral in dual-source computed tomography (DSCT) of the neck. Materials and Methods: Sixty-two patients were included for neck imaging with DSCT. MPRs from an axial dataset and an additional short spiral parallel to the mouth floor were acquired. Leading anatomical structures were then evaluated with respect to the extent to which they were affected by dental artifacts using a visual scale, ranging from 1 (least artifacts) to 4 (most artifacts). Results: In MPR, 87.1 % of anatomical structures had significant artifacts (3.12 {+-} 0.86), while in angulated slices leading anatomical structures of the oropharynx showed negligible artifacts (1.28 {+-} 0.46). The diagnostic growth due to primarily angulated slices concerning artifact severity was significant (p < 0.01). Conclusion: MPRs are not capable of reducing dental artifacts sufficiently. In patients with dental artifacts overlying the anatomical structures of the oropharynx, an additional short angulated spiral parallel to the floor of the mouth is recommended and should be applied for daily routine. As a result of the static gantry design of DSCT, the use of a flexible head holder is essential. (orig.)

Learning in Home Care: A Digital Artifact as a Designated Boundary Object-in-Use

Science.gov (United States)

Islind, Anna Sigridur; Lundh Snis, Ulrika

2017-01-01

Purpose: The aim of this paper is to understand how the role of an mHealth artifact plays out in home care settings. An mHealth artifact, in terms of a mobile app, was tested to see how the quality of home care work practice was enhanced and changed. The research question is: In what ways does an mHealth artifact re-shape a home care practice and…

Independent component analysis of gait-related movement artifact recorded using EEG electrodes during treadmill walking.

Directory of Open Access Journals (Sweden)

Kristine Lynne Snyder

2015-12-01

Full Text Available There has been a recent surge in the use of electroencephalography (EEG as a tool for mobile brain imaging due to its portability and fine time resolution. When EEG is combined with independent component analysis (ICA and source localization techniques, it can model electrocortical activity as arising from temporally independent signals located in spatially distinct cortical areas. However, for mobile tasks, it is not clear how movement artifacts influence ICA and source localization. We devised a novel method to collect pure movement artifact data (devoid of any electrophysiological signals with a 256-channel EEG system. We first blocked true electrocortical activity using a silicone swim cap. Over the silicone layer, we placed a simulated scalp with electrical properties similar to real human scalp. We collected EEG movement artifact signals from ten healthy, young subjects wearing this setup as they walked on a treadmill at speeds from 0.4-1.6 m/s. We performed ICA and dipole fitting on the EEG movement artifact data to quantify how accurately these methods would identify the artifact signals as non-neural. ICA and dipole fitting accurately localized 99% of the independent components in non-neural locations or lacked dipolar characteristics. The remaining 1% of sources had locations within the brain volume and low residual variances, but had topographical maps, power spectra, time courses, and event related spectral perturbations typical of non-neural sources. Caution should be exercised when interpreting ICA for data that includes semi-periodic artifacts including artifact arising from human walking. Alternative methods are needed for the identification and separation of movement artifact in mobile EEG signals, especially methods that can be performed in real time. Separating true brain signals from motion artifact could clear the way for EEG brain computer interfaces for assistance during mobile activities, such as walking.

An image-based approach to understanding the physics of MR artifacts.

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Morelli, John N; Runge, Val M; Ai, Fei; Attenberger, Ulrike; Vu, Lan; Schmeets, Stuart H; Nitz, Wolfgang R; Kirsch, John E

2011-01-01

As clinical magnetic resonance (MR) imaging becomes more versatile and more complex, it is increasingly difficult to develop and maintain a thorough understanding of the physical principles that govern the changing technology. This is particularly true for practicing radiologists, whose primary obligation is to interpret clinical images and not necessarily to understand complex equations describing the underlying physics. Nevertheless, the physics of MR imaging plays an important role in clinical practice because it determines image quality, and suboptimal image quality may hinder accurate diagnosis. This article provides an image-based explanation of the physics underlying common MR imaging artifacts, offering simple solutions for remedying each type of artifact. Solutions that have emerged from recent technologic advances with which radiologists may not yet be familiar are described in detail. Types of artifacts discussed include those resulting from voluntary and involuntary patient motion, magnetic susceptibility, magnetic field inhomogeneities, gradient nonlinearity, standing waves, aliasing, chemical shift, and signal truncation. With an improved awareness and understanding of these artifacts, radiologists will be better able to modify MR imaging protocols so as to optimize clinical image quality, allowing greater confidence in diagnosis. Copyright © RSNA, 2011.

Reduce manual curation by combining gene predictions from multiple annotation engines, a case study of start codon prediction.

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Thomas H A Ederveen

Full Text Available Nowadays, prokaryotic genomes are sequenced faster than the capacity to manually curate gene annotations. Automated genome annotation engines provide users a straight-forward and complete solution for predicting ORF coordinates and function. For many labs, the use of AGEs is therefore essential to decrease the time necessary for annotating a given prokaryotic genome. However, it is not uncommon for AGEs to provide different and sometimes conflicting predictions. Combining multiple AGEs might allow for more accurate predictions. Here we analyzed the ab initio open reading frame (ORF calling performance of different AGEs based on curated genome annotations of eight strains from different bacterial species with GC% ranging from 35-52%. We present a case study which demonstrates a novel way of comparative genome annotation, using combinations of AGEs in a pre-defined order (or path to predict ORF start codons. The order of AGE combinations is from high to low specificity, where the specificity is based on the eight genome annotations. For each AGE combination we are able to derive a so-called projected confidence value, which is the average specificity of ORF start codon prediction based on the eight genomes. The projected confidence enables estimating likeliness of a correct prediction for a particular ORF start codon by a particular AGE combination, pinpointing ORFs notoriously difficult to predict start codons. We correctly predict start codons for 90.5±4.8% of the genes in a genome (based on the eight genomes with an accuracy of 81.1±7.6%. Our consensus-path methodology allows a marked improvement over majority voting (9.7±4.4% and with an optimal path ORF start prediction sensitivity is gained while maintaining a high specificity.

Relation between chemical shift artifact and infiltration on MR imaging of renal cell carcinoma

International Nuclear Information System (INIS)

Yoshigoe, Fukuo; Makino, Hideki; Yanada, Syuichi; Ohishi, Yukihiko; Mashima, Yasuoki; Yamada, Hideo.

1994-01-01

Retrospective study on the relation between existence of the interruption and disturbance of chemical shift artifact and tumor infiltration at the periphery of the kidney on MR imaging was evaluated in 28 cases with renal cell carcinoma. Judgement was possible in 9 out of the 11 cases with pathological stage below pT2 and 14 cases out of 17 pT3 cases. Judgement was impracticable in 5 cases because the peripheral fat tissue of the kidney was too less to observe chemical shift artifact and the tumor was spreading at the side opposite to the chemical shift artifact. Chemical shift artifact on MRI in this study correlated well with renal tumor infiltration. (author)

Technical Note: On GAFChromic EBT-XD film and the lateral response artifact

International Nuclear Information System (INIS)

Lewis, David F.; Chan, Maria F.

2016-01-01

Purpose: The new radiochromic film, GAFChromic EBT-XD, contains the same active material, lithium-10,12-pentacosadiynoate, as GAFChromic EBT3, but the crystalline form is different. This work investigates the effect of this change on the well-known lateral response artifact when EBT-XD film is digitized on a flatbed scanner. Methods: The dose response of a single production lot of EBT-XD was characterized by scanning an unexposed film plus a set of films exposed to doses between 2.5 and 50 Gy using 6 MV photons. To characterize the lateral response artifact, the authors used the unexposed film plus a subset of samples exposed to doses between 20 and 50 Gy. Digital images of these films were acquired at seven discrete lateral locations perpendicular to the scan direction on three Epson 10000XL scanners. Using measurements at the discrete lateral positions, the scanner responses were determined as a function of the lateral position of the film. From the data for each scanner, a set of coefficients were derived whereby measured response values could be corrected to remove the effects of the lateral response artifact. The EBT-XD data were analyzed as in their previous work and compared to results reported for EBT3 in that paper. Results: For films scanned in the same orientation and having equal responses, the authors found that the lateral response artifact for EBT-XD and EBT3 films was remarkably similar. For both films, the artifact increases with increased net response. However, as EBT-XD is less sensitive than EBT3, a greater exposure dose is required to reach the same net response. On this basis, the lower sensitivity of EBT-XD relative to EBT3 results in less net response change for equal exposure and a reduction in the impact of the lateral response artifact. Conclusions: The shape of the crystalline active component in EBT-XD and EBT3 does not affect the fundamental existence of the lateral response artifact when the films are digitized on flatbed scanners

Technical Note: On GAFChromic EBT-XD film and the lateral response artifact.

Science.gov (United States)

Lewis, David F; Chan, Maria F

2016-02-01

The new radiochromic film, GAFChromic EBT-XD, contains the same active material, lithium-10,12-pentacosadiynoate, as GAFChromic EBT3, but the crystalline form is different. This work investigates the effect of this change on the well-known lateral response artifact when EBT-XD film is digitized on a flatbed scanner. The dose response of a single production lot of EBT-XD was characterized by scanning an unexposed film plus a set of films exposed to doses between 2.5 and 50 Gy using 6 MV photons. To characterize the lateral response artifact, the authors used the unexposed film plus a subset of samples exposed to doses between 20 and 50 Gy. Digital images of these films were acquired at seven discrete lateral locations perpendicular to the scan direction on three Epson 10000XL scanners. Using measurements at the discrete lateral positions, the scanner responses were determined as a function of the lateral position of the film. From the data for each scanner, a set of coefficients were derived whereby measured response values could be corrected to remove the effects of the lateral response artifact. The EBT-XD data were analyzed as in their previous work and compared to results reported for EBT3 in that paper. For films scanned in the same orientation and having equal responses, the authors found that the lateral response artifact for EBT-XD and EBT3 films was remarkably similar. For both films, the artifact increases with increased net response. However, as EBT-XD is less sensitive than EBT3, a greater exposure dose is required to reach the same net response. On this basis, the lower sensitivity of EBT-XD relative to EBT3 results in less net response change for equal exposure and a reduction in the impact of the lateral response artifact. The shape of the crystalline active component in EBT-XD and EBT3 does not affect the fundamental existence of the lateral response artifact when the films are digitized on flatbed scanners. Owing its lower sensitivity, EBT-XD film

Technical Note: On GAFChromic EBT-XD film and the lateral response artifact

Energy Technology Data Exchange (ETDEWEB)

Lewis, David F., E-mail: rcfilmconsulting@gmail.com [RC Film Consulting LLC, 54 Benedict Road, Monroe, Connecticut 06468 (United States); Chan, Maria F. [Memorial Sloan-Kettering Cancer Center, 136 Mountain View Boulevard, Basking Ridge, New Jersey 07920 (United States)

2016-02-15

Purpose: The new radiochromic film, GAFChromic EBT-XD, contains the same active material, lithium-10,12-pentacosadiynoate, as GAFChromic EBT3, but the crystalline form is different. This work investigates the effect of this change on the well-known lateral response artifact when EBT-XD film is digitized on a flatbed scanner. Methods: The dose response of a single production lot of EBT-XD was characterized by scanning an unexposed film plus a set of films exposed to doses between 2.5 and 50 Gy using 6 MV photons. To characterize the lateral response artifact, the authors used the unexposed film plus a subset of samples exposed to doses between 20 and 50 Gy. Digital images of these films were acquired at seven discrete lateral locations perpendicular to the scan direction on three Epson 10000XL scanners. Using measurements at the discrete lateral positions, the scanner responses were determined as a function of the lateral position of the film. From the data for each scanner, a set of coefficients were derived whereby measured response values could be corrected to remove the effects of the lateral response artifact. The EBT-XD data were analyzed as in their previous work and compared to results reported for EBT3 in that paper. Results: For films scanned in the same orientation and having equal responses, the authors found that the lateral response artifact for EBT-XD and EBT3 films was remarkably similar. For both films, the artifact increases with increased net response. However, as EBT-XD is less sensitive than EBT3, a greater exposure dose is required to reach the same net response. On this basis, the lower sensitivity of EBT-XD relative to EBT3 results in less net response change for equal exposure and a reduction in the impact of the lateral response artifact. Conclusions: The shape of the crystalline active component in EBT-XD and EBT3 does not affect the fundamental existence of the lateral response artifact when the films are digitized on flatbed scanners

Negligible motion artifacts in scalp electroencephalography (EEG during treadmill walking

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Kevin eNathan

2016-01-01

Full Text Available Recent Mobile Brain/Body Imaging (MoBI techniques based on active electrode scalp electroencephalogram (EEG allow the acquisition and real-time analysis of brain dynamics during active unrestrained motor behavior involving whole body movements such as treadmill walking, over-ground walking and other locomotive and non-locomotive tasks. Unfortunately, MoBI protocols are prone to physiological and non-physiological artifacts, including motion artifacts that may contaminate the EEG recordings. A few attempts have been made to quantify these artifacts during locomotion tasks but with inconclusive results due in part to methodological pitfalls. In this paper, we investigate the potential contributions of motion artifacts in scalp EEG during treadmill walking at three different speeds (1.5, 3.0, and 4.5 km/h using a wireless 64 channel active EEG system and a wireless inertial sensor attached to the subject’s head. The experimental setup was designed according to good measurement practices using state-of-the-art commercially-available instruments, and the measurements were analyzed using Fourier analysis and wavelet coherence approaches. Contrary to prior claims, the subjects’ motion did not significantly affect their EEG during treadmill walking although precaution should be taken when gait speeds approach 4.5 km/h. Overall, these findings suggest how MoBI methods may be safely deployed in neural, cognitive, and rehabilitation engineering applications.

Artifact suppression and analysis of brain activities with electroencephalography signals.

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Rashed-Al-Mahfuz, Md; Islam, Md Rabiul; Hirose, Keikichi; Molla, Md Khademul Islam

2013-06-05

Brain-computer interface is a communication system that connects the brain with computer (or other devices) but is not dependent on the normal output of the brain (i.e., peripheral nerve and muscle). Electro-oculogram is a dominant artifact which has a significant negative influence on further analysis of real electroencephalography data. This paper presented a data adaptive technique for artifact suppression and brain wave extraction from electroencephalography signals to detect regional brain activities. Empirical mode decomposition based adaptive thresholding approach was employed here to suppress the electro-oculogram artifact. Fractional Gaussian noise was used to determine the threshold level derived from the analysis data without any training. The purified electroencephalography signal was composed of the brain waves also called rhythmic components which represent the brain activities. The rhythmic components were extracted from each electroencephalography channel using adaptive wiener filter with the original scale. The regional brain activities were mapped on the basis of the spatial distribution of rhythmic components, and the results showed that different regions of the brain are activated in response to different stimuli. This research analyzed the activities of a single rhythmic component, alpha with respect to different motor imaginations. The experimental results showed that the proposed method is very efficient in artifact suppression and identifying individual motor imagery based on the activities of alpha component.

Analysis of main artifacts in scanning probe microscopy (1)

International Nuclear Information System (INIS)

Alekperov, S.D.; Alekperov, S.D.

2012-01-01

The analysis of experiment carrying methodology in the scanning probe microscopy (SPM) region is carried out, the main parameters influencing on image quality are revealed. In order to reveal the artifact reason the main components of SPM signal which are divided on 5 groups : the useful signal; noises connected with external influences and temperature drift; distortions connected with piezoceramics and piezo-scanner non-ideality; probe geometry influence; apparatus noises are considered. The main methods of removal and minimization of the given artifacts are considered. The second and third groups of main components of SPM signal are considered in the articles first part

Depolarization artifacts in dual rotating-compensator Mueller matrix ellipsometry

International Nuclear Information System (INIS)

Li, Weiqi; Zhang, Chuanwei; Jiang, Hao; Chen, Xiuguo; Liu, Shiyuan

2016-01-01

Noticeable depolarization effects are observed in the measurement of the air using an in-house developed dual rotating-compensator Mueller matrix ellipsometer. We demonstrate that these depolarization effects are essentially artifacts and mainly induced when the compensator with wavelength-dependent optical properties is integrated with the finite bandwidth detector. We define a general formula to represent the actual Mueller matrix of the compensator by taking into account the depolarization artifacts. After incorporating this formula into the system model, a correction method is further proposed, and consequently, improved accuracy can be achieved in the Mueller matrix measurement. (paper)

Survey on the artifacts of magnetic resonance imaging in the maxillo-facial regions

International Nuclear Information System (INIS)

Arita, Masahiro; Okayosi, Tetsuo; Sakamoto, Fumihiko; Furuhasi, Kaiji; Wakuta, Kazunari; Ohba, Takeshi; Morikawa, Masao; Han, Dongwei

2000-01-01

Magnetic resonance imaging (MRI) is accepted as a valuable method for evaluating and diagnosing various diseases in medical and dental area. On the other hand, dental magnetic attachments have been applied as one of the most suitable retainers of removable prostheses. The dental magnetic attachment is an advanced procedure for the restoration, whereas the dental magnetic attachment is one of the causes of MRI artifacts and/or distortions. In this study the results obtained by a survey in general hospitals on MRI artifacts caused by dental metals, especially dental magnetic attachments, are reported. The results obtained were as follows; MRI artifacts are experienced in most hospitals. Most radiologists did not regard the effect of the magnetic alloy as the cause, although they thought dental metals in oral cavity were the main cause of MRI artifact. Although about a half of radiologist were aware of the presence of the magnetic attachments, few of them had little experience in taking pictures of the patients with magnetic attachment or magnetic keepers by using MRI. Even when dental metals and magnetic keepers in oral cavity were considered to produce the MRI artifacts, none of radiologists asked dentists to remove them. They tried to solve the trouble of MRI artifacts by themselves. Prothodontists should give much more information about the dental magnetic attachment to radiologists and medical doctors in addition to improving the magnetic attachment and investigating materials to minimize the effect on MRI. (author)

Establishment of a 12-gene expression signature to predict colon cancer prognosis

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Dalong Sun

2018-06-01

Full Text Available A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA. The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS: Kaplan Meier (KM Log Rank p = 0.0034; overall survival (OS: KM Log Rank p = 0.0336 in GSE17538. For patients with proficient mismatch repair system (pMMR in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS: KM Log Rank p = 0.022. Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003. After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01 and stage II & III (Log Rank p = 0.017 in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041. Among stage II/III pMMR patients

Evaluation of the effects of an arm artifact reduction filter in computed tomography

International Nuclear Information System (INIS)

Nozaki, Fumie; Ohno, Hajime; Hirako, Tetsuya

2002-01-01

While performing CT during arterial portography (CTAP) or CT arteriography (CTA), we have instructed patients to in order to reduce streak artifacts. However the repetitive raising and lowering their arms has made it difficult to keep a clean zone and as well as to maintain the position of a target organ. An arm artifact reduction (AAR) filter developed by GE Yokokawa Medical System has been reported to be useful for reducing streak artifacts in CTAP and CTA. The purpose of this study was to estimate the effectiveness of the AAR filter in terms of artifact reduction ratio, CT value, standard deviation and spatial resolution. The use of an AAR filter reduced streak artifacts on images by 15-22% compared with those on images obtained by without the use of the filter and limited deterioration of spatial resolution to within 1%. Moreover, CT value in examination using AAR filter showed no significant change compared with that in non-filter's examination. It is concluded that the use of an AAR filter reduces the burden for the patient and increase the accuracy and flexibility of CT examination while minimizing the reduction in the image quality in CTAP and CTA. (author)

Wavelet-Based Artifact Identification and Separation Technique for EEG Signals during Galvanic Vestibular Stimulation

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Adib, Mani; Cretu, Edmond

2013-01-01

We present a new method for removing artifacts in electroencephalography (EEG) records during Galvanic Vestibular Stimulation (GVS). The main challenge in exploiting GVS is to understand how the stimulus acts as an input to brain. We used EEG to monitor the brain and elicit the GVS reflexes. However, GVS current distribution throughout the scalp generates an artifact on EEG signals. We need to eliminate this artifact to be able to analyze the EEG signals during GVS. We propose a novel method to estimate the contribution of the GVS current in the EEG signals at each electrode by combining time-series regression methods with wavelet decomposition methods. We use wavelet transform to project the recorded EEG signal into various frequency bands and then estimate the GVS current distribution in each frequency band. The proposed method was optimized using simulated signals, and its performance was compared to well-accepted artifact removal methods such as ICA-based methods and adaptive filters. The results show that the proposed method has better performance in removing GVS artifacts, compared to the others. Using the proposed method, a higher signal to artifact ratio of −1.625 dB was achieved, which outperformed other methods such as ICA-based methods, regression methods, and adaptive filters. PMID:23956786

Wavelet-Based Artifact Identification and Separation Technique for EEG Signals during Galvanic Vestibular Stimulation

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Mani Adib

2013-01-01

Full Text Available We present a new method for removing artifacts in electroencephalography (EEG records during Galvanic Vestibular Stimulation (GVS. The main challenge in exploiting GVS is to understand how the stimulus acts as an input to brain. We used EEG to monitor the brain and elicit the GVS reflexes. However, GVS current distribution throughout the scalp generates an artifact on EEG signals. We need to eliminate this artifact to be able to analyze the EEG signals during GVS. We propose a novel method to estimate the contribution of the GVS current in the EEG signals at each electrode by combining time-series regression methods with wavelet decomposition methods. We use wavelet transform to project the recorded EEG signal into various frequency bands and then estimate the GVS current distribution in each frequency band. The proposed method was optimized using simulated signals, and its performance was compared to well-accepted artifact removal methods such as ICA-based methods and adaptive filters. The results show that the proposed method has better performance in removing GVS artifacts, compared to the others. Using the proposed method, a higher signal to artifact ratio of −1.625 dB was achieved, which outperformed other methods such as ICA-based methods, regression methods, and adaptive filters.

Evaluating an artifact in design science research

CSIR Research Space (South Africa)

Herselman, M

2015-09-01

Full Text Available In this paper, we describe the iterative evaluation of an artifact developed through the application of Design Science Research (DSR) methodology in a resource constrained environment. In the DSR process the aspect of evaluation is often done...

Improved Image Quality in Head and Neck CT Using a 3D Iterative Approach to Reduce Metal Artifact.

Science.gov (United States)

Wuest, W; May, M S; Brand, M; Bayerl, N; Krauss, A; Uder, M; Lell, M

2015-10-01

Metal artifacts from dental fillings and other devices degrade image quality and may compromise the detection and evaluation of lesions in the oral cavity and oropharynx by CT. The aim of this study was to evaluate the effect of iterative metal artifact reduction on CT of the oral cavity and oropharynx. Data from 50 consecutive patients with metal artifacts from dental hardware were reconstructed with standard filtered back-projection, linear interpolation metal artifact reduction (LIMAR), and iterative metal artifact reduction. The image quality of sections that contained metal was analyzed for the severity of artifacts and diagnostic value. A total of 455 sections (mean ± standard deviation, 9.1 ± 4.1 sections per patient) contained metal and were evaluated with each reconstruction method. Sections without metal were not affected by the algorithms and demonstrated image quality identical to each other. Of these sections, 38% were considered nondiagnostic with filtered back-projection, 31% with LIMAR, and only 7% with iterative metal artifact reduction. Thirty-three percent of the sections had poor image quality with filtered back-projection, 46% with LIMAR, and 10% with iterative metal artifact reduction. Thirteen percent of the sections with filtered back-projection, 17% with LIMAR, and 22% with iterative metal artifact reduction were of moderate image quality, 16% of the sections with filtered back-projection, 5% with LIMAR, and 30% with iterative metal artifact reduction were of good image quality, and 1% of the sections with LIMAR and 31% with iterative metal artifact reduction were of excellent image quality. Iterative metal artifact reduction yields the highest image quality in comparison with filtered back-projection and linear interpolation metal artifact reduction in patients with metal hardware in the head and neck area. © 2015 by American Journal of Neuroradiology.

Home-Explorer: Ontology-Based Physical Artifact Search and Hidden Object Detection System

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Bin Guo

2008-01-01

Full Text Available A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses sensors attached to the everyday artifacts (called smart objects in the real world. This paper makes two main contributions: First, it addresses, the robustness of the embedded sensors, which is seldom discussed in previous smart artifact research. Because sensors may sometimes be broken or fail to work under certain conditions, smart objects become hidden ones. However, current systems provide no mechanism to detect and manage objects when this problem occurs. Second, there is no common context infrastructure for building smart artifact systems, which makes it difficult for separately developed applications to interact with each other and uneasy for them to share and reuse knowledge. Unlike previous systems, Home-Explorer builds on an ontology-based knowledge infrastructure named Sixth-Sense, which makes it easy for the system to interact with other applications or agents also based on this ontology. The hidden object problem is also reflected in our ontology, which enables Home-Explorer to deal with both smart objects and hidden objects. A set of rules for deducing an object's status or location information and for locating hidden objects are described and evaluated.

Metal artifact reduction in x-ray computed tomography (CT) by constrained optimization

International Nuclear Information System (INIS)

Zhang Xiaomeng; Wang Jing; Xing Lei

2011-01-01

Purpose: The streak artifacts caused by metal implants have long been recognized as a problem that limits various applications of CT imaging. In this work, the authors propose an iterative metal artifact reduction algorithm based on constrained optimization. Methods: After the shape and location of metal objects in the image domain is determined automatically by the binary metal identification algorithm and the segmentation of ''metal shadows'' in projection domain is done, constrained optimization is used for image reconstruction. It minimizes a predefined function that reflects a priori knowledge of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available metal-shadow-excluded projection data, with image non-negativity enforced. The minimization problem is solved through the alternation of projection-onto-convex-sets and the steepest gradient descent of the objective function. The constrained optimization algorithm is evaluated with a penalized smoothness objective. Results: The study shows that the proposed method is capable of significantly reducing metal artifacts, suppressing noise, and improving soft-tissue visibility. It outperforms the FBP-type methods and ART and EM methods and yields artifacts-free images. Conclusions: Constrained optimization is an effective way to deal with CT reconstruction with embedded metal objects. Although the method is presented in the context of metal artifacts, it is applicable to general ''missing data'' image reconstruction problems.

Mediating Artifact in Teacher Professional Development

Science.gov (United States)

Svendsen, Bodil

2015-01-01

This article focuses on teacher professional development (TPD) in natural science through the 5E model as mediating artifact. The study was conducted in an upper secondary school, grounded in a school-based intervention research project. My contribution to the field of research on TPD is founded on the hypothesis that teachers would be best…

Novel technique for addressing streak artifact in gated dual-source MDCT angiography utilizing ECG-editing

Energy Technology Data Exchange (ETDEWEB)

Meyer, Laura T.; Boll, Daniel T. [Duke University Medical Center, Department of Radiology, Box 3808, Durham, NC (United States)

2008-11-15

Streak artifact is an important source of image degradation in computed tomographic imaging. In coronary MDCT angiography, streak artifact from pacemaker leads in the SVC can render segments of the right coronary artery uninterpretable. With current technology in clinical practice, there is no effective way to eliminate streak artifact in coronary MDCT angiography entirely. We propose a technique to minimize the impact of streak artifact in retrospectively gated coronary MDCT angiography by utilizing small shifts in the reconstruction window. In our experience, previously degraded portions of the coronary vasculature were able to be well evaluated using this technique. (orig.)

Influence of orthodontic appliance-derived artifacts on 3-T MRI movies.

Science.gov (United States)

Ozawa, Erika; Honda, Ei-Ichi; Parakonthun, Kulthida Nunthayanon; Ohmori, Hiroko; Shimazaki, Kazuo; Kurabayashi, Tohru; Ono, Takashi

2018-02-19

Magnetic resonance imaging (MRI) has been used to study configurations of speech organs in the resting state. However, MRI is sensitive to metals, and numerous types of metallic appliances, most of which have a large magnetic susceptibility, are used in orthodontic treatment and may cause severe artifacts on MRI. We have developed techniques for obtaining MRI movies of the oral region, to evaluate articulatory changes, especially movement of the tongue, palate, and teeth, pre- and post-orthodontic/orthognathic treatment. We evaluated the influence of artifacts caused by orthodontic appliances, including fixed retainers, metal brackets, and wires, on measurements in 3-T MRI movies. Sixteen healthy young adults (nine males, seven females; average age, 27 years) with normal occlusion were recruited. Four types of customized maxillary and mandibular plates were prepared by incorporating one of the following into the plate: (a) nothing, (b) a fixed canine-to-canine retainer, (c) metal brackets for the anterior and molar teeth, or (d) clear brackets for the anterior teeth and metal brackets for molars. A 3-T MRI movie, in segmented cine mode, was generated for each plate condition while participants pronounced a vowel-consonant-vowel syllable (/asa/). The size of the artifact due to the metallic brackets was measured. The face size and orthodontically important anatomical structures, such as the velum, the hard palate, and the laryngeal ventricle, were also measured. A large artifact was observed over the entire oral region around orthodontic appliances, altering regional visibility. The velopharyngeal height was measured as significantly longer in the presence of metal brackets. The maximum artifact size due to a metallic bracket was > 8 cm. Our results show that even if it is possible to obtain the measurements of palate length, nasion to sella, and nasion to basion in individuals wearing metal brackets for molars, the measurements might be affected due to the

On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP.

Science.gov (United States)

Winkler, Irene; Debener, Stefan; Müller, Klaus-Robert; Tangermann, Michael

2015-01-01

Standard artifact removal methods for electroencephalographic (EEG) signals are either based on Independent Component Analysis (ICA) or they regress out ocular activity measured at electrooculogram (EOG) channels. Successful ICA-based artifact reduction relies on suitable pre-processing. Here we systematically evaluate the effects of high-pass filtering at different frequencies. Offline analyses were based on event-related potential data from 21 participants performing a standard auditory oddball task and an automatic artifactual component classifier method (MARA). As a pre-processing step for ICA, high-pass filtering between 1-2 Hz consistently produced good results in terms of signal-to-noise ratio (SNR), single-trial classification accuracy and the percentage of `near-dipolar' ICA components. Relative to no artifact reduction, ICA-based artifact removal significantly improved SNR and classification accuracy. This was not the case for a regression-based approach to remove EOG artifacts.

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

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Karacali Bilge

2007-10-01

Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.

Science.gov (United States)

Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun

2017-01-01

Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.

Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

Science.gov (United States)

van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

2014-03-01

For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

Streak artifacts on Kidney CT: Ionic vs nonionic contrast media

International Nuclear Information System (INIS)

Cho, Eun Ok; Kim, Won Hong; Jung, Myung Suk; Kim, Yong Hoon; Hur, Gham

1993-01-01

The authors reviewed findings of enhanced abdominal computed tomography (CT) scans to know the difference between a higher dose of conventional ionic contrast media(iothalamate meglumine) and a lower dose of a new, nonionic contrast material(ioversol). One hundred adult patients were divided into two groups. Each group consisted of 50 patients. Iothalamate meglumine and ioversol were intravenously administered in each group. The radio of the male to female in the former was 28:22, and the latter 29:21. We examine the degree of renal streak artifact and measure the Hounsfield number of urine in renal collecting system. There were significant differences of the degree of the streak artifact depending upon the osmolality of contrast media used and that was related with urine CT number(P value<0.005). We authors conclude that nonionic low osmolar contrast media is prone to cause streak artifacts and distortions of renal image than conventional ionic high osmolar contrast media

Evaluation of artifact-corrected electroencephalographic (EEG) training: a pilot study.

Science.gov (United States)

La Marca, Jeffry P; Cruz, Daniel; Fandino, Jennifer; Cacciaguerra, Fabiana R; Fresco, Joseph J; Guerra, Austin T

2018-07-01

This double-blind study examined the effect of electromyographical (EMG) artifacts, which contaminate electroencephalographical (EEG) signals, by comparing artifact-corrected (AC) and non-artifact-corrected (NAC) neurofeedback (NF) training procedures. 14 unmedicated college students were randomly assigned to two groups: AC (n = 7) or NAC (n = 7). Both groups received 12 sessions of NF and were trained using identical NF treatment protocols to reduce their theta/beta power ratios (TBPR). Outcomes on a continuous performance test revealed that the AC group had statistically significant increases across measures of auditory and visual attention. The NAC group showed smaller gains that only reached statistical significance on measures of visual attention. Only the AC group reduced their TBPR, the NAC group did not. AC NF appears to play an important role during training that leads to improvements in both auditory and visual attention. Additional research is required to confirm the results of this study.

Reduction of ring artifacts in CBCT: Detection and correction of pixel gain variations in flat panel detectors

International Nuclear Information System (INIS)

Altunbas, Cem; Lai, Chao-Jen; Zhong, Yuncheng; Shaw, Chris C.

2014-01-01

Purpose: In using flat panel detectors (FPD) for cone beam computed tomography (CBCT), pixel gain variations may lead to structured nonuniformities in projections and ring artifacts in CBCT images. Such gain variations can be caused by change in detector entrance exposure levels or beam hardening, and they are not accounted by conventional flat field correction methods. In this work, the authors presented a method to identify isolated pixel clusters that exhibit gain variations and proposed a pixel gain correction (PGC) method to suppress both beam hardening and exposure level dependent gain variations. Methods: To modulate both beam spectrum and entrance exposure, flood field FPD projections were acquired using beam filters with varying thicknesses. “Ideal” pixel values were estimated by performing polynomial fits in both raw and flat field corrected projections. Residuals were calculated by taking the difference between measured and ideal pixel values to identify clustered image and FPD artifacts in flat field corrected and raw images, respectively. To correct clustered image artifacts, the ratio of ideal to measured pixel values in filtered images were utilized as pixel-specific gain correction factors, referred as PGC method, and they were tabulated as a function of pixel value in a look-up table. Results: 0.035% of detector pixels lead to clustered image artifacts in flat field corrected projections, where 80% of these pixels were traced back and linked to artifacts in the FPD. The performance of PGC method was tested in variety of imaging conditions and phantoms. The PGC method reduced clustered image artifacts and fixed pattern noise in projections, and ring artifacts in CBCT images. Conclusions: Clustered projection image artifacts that lead to ring artifacts in CBCT can be better identified with our artifact detection approach. When compared to the conventional flat field correction method, the proposed PGC method enables characterization of nonlinear

ARTiiFACT: a tool for heart rate artifact processing and heart rate variability analysis.

Science.gov (United States)

Kaufmann, Tobias; Sütterlin, Stefan; Schulz, Stefan M; Vögele, Claus

2011-12-01

The importance of appropriate handling of artifacts in interbeat interval (IBI) data must not be underestimated. Even a single artifact may cause unreliable heart rate variability (HRV) results. Thus, a robust artifact detection algorithm and the option for manual intervention by the researcher form key components for confident HRV analysis. Here, we present ARTiiFACT, a software tool for processing electrocardiogram and IBI data. Both automated and manual artifact detection and correction are available in a graphical user interface. In addition, ARTiiFACT includes time- and frequency-based HRV analyses and descriptive statistics, thus offering the basic tools for HRV analysis. Notably, all program steps can be executed separately and allow for data export, thus offering high flexibility and interoperability with a whole range of applications.

A Preliminary Study of Muscular Artifact Cancellation in Single-Channel EEG

OpenAIRE

Chen, Xun; Liu, Aiping; Peng, Hu; Ward, Rabab K.

2014-01-01

Electroencephalogram (EEG) recordings are often contaminated with muscular artifacts that strongly obscure the EEG signals and complicates their analysis. For the conventional case, where the EEG recordings are obtained simultaneously over many EEG channels, there exists a considerable range of methods for removing muscular artifacts. In recent years, there has been an increasing trend to use EEG information in ambulatory healthcare and related physiological signal monitoring systems. For pra...

EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

International Nuclear Information System (INIS)

Vialatte, François-Benoit; Cichocki, Andrzej; Solé-Casals, Jordi

2008-01-01

EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning of EEG data is then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9)

An Approach for Multi-Artifact Testing Through an Ontological Perspective for Behavior-Driven Development

Directory of Open Access Journals (Sweden)

Thiago Rocha Silva

2016-07-01

Full Text Available In a user-centered development process, artifacts evolve in iterative cycles until they meet users’ requirements and then become the final product. Every cycle gives the opportunity to revise the design and to introduce new requirements which might affect the specification of artifacts that have been set in former development phases. Testing the consistency of multiple artifacts used to develop interactive systems every time that new requirements are introduced is a cumbersome activity, especially if it is done manually. This paper proposes an approach based on Behavior-Driven Development (BDD to support the automated assessment of artifacts along the development process of interactive systems. The paper uses an ontology for specifying tests that can run over multiple artifacts sharing similar concepts. A case study testing Task Models, Prototypes, and Final User Interfaces is presented to demonstrate the feasibility of this approach from the early phases of the design process, providing a continuous quality assurance of requirements, and helping clients and development teams to identify potential problems and inconsistencies before commitments with software implementation are made.

Correcting for motion artifact in handheld laser speckle images

Science.gov (United States)

Lertsakdadet, Ben; Yang, Bruce Y.; Dunn, Cody E.; Ponticorvo, Adrien; Crouzet, Christian; Bernal, Nicole; Durkin, Anthony J.; Choi, Bernard

2018-03-01

Laser speckle imaging (LSI) is a wide-field optical technique that enables superficial blood flow quantification. LSI is normally performed in a mounted configuration to decrease the likelihood of motion artifact. However, mounted LSI systems are cumbersome and difficult to transport quickly in a clinical setting for which portability is essential in providing bedside patient care. To address this issue, we created a handheld LSI device using scientific grade components. To account for motion artifact of the LSI device used in a handheld setup, we incorporated a fiducial marker (FM) into our imaging protocol and determined the difference between highest and lowest speckle contrast values for the FM within each data set (Kbest and Kworst). The difference between Kbest and Kworst in mounted and handheld setups was 8% and 52%, respectively, thereby reinforcing the need for motion artifact quantification. When using a threshold FM speckle contrast value (KFM) to identify a subset of images with an acceptable level of motion artifact, mounted and handheld LSI measurements of speckle contrast of a flow region (KFLOW) in in vitro flow phantom experiments differed by 8%. Without the use of the FM, mounted and handheld KFLOW values differed by 20%. To further validate our handheld LSI device, we compared mounted and handheld data from an in vivo porcine burn model of superficial and full thickness burns. The speckle contrast within the burn region (KBURN) of the mounted and handheld LSI data differed by burns. Collectively, our results suggest the potential of handheld LSI with an FM as a suitable alternative to mounted LSI, especially in challenging clinical settings with space limitations such as the intensive care unit.

Compton scattering artifacts in electron excited X-ray spectra measured with a silicon drift detector.

Science.gov (United States)

Ritchie, Nicholas W M; Newbury, Dale E; Lindstrom, Abigail P

2011-12-01

Artifacts are the nemesis of trace element analysis in electron-excited energy dispersive X-ray spectrometry. Peaks that result from nonideal behavior in the detector or sample can fool even an experienced microanalyst into believing that they have trace amounts of an element that is not present. Many artifacts, such as the Si escape peak, absorption edges, and coincidence peaks, can be traced to the detector. Others, such as secondary fluorescence peaks and scatter peaks, can be traced to the sample. We have identified a new sample-dependent artifact that we attribute to Compton scattering of energetic X-rays generated in a small feature and subsequently scattered from a low atomic number matrix. It seems likely that this artifact has not previously been reported because it only occurs under specific conditions and represents a relatively small signal. However, with the advent of silicon drift detectors and their utility for trace element analysis, we anticipate that more people will observe it and possibly misidentify it. Though small, the artifact is not inconsequential. Under some conditions, it is possible to mistakenly identify the Compton scatter artifact as approximately 1% of an element that is not present.

Reference geometry-based detection of (4D-)CT motion artifacts: a feasibility study

Science.gov (United States)

Werner, René; Gauer, Tobias

2015-03-01

Respiration-correlated computed tomography (4D or 3D+t CT) can be considered as standard of care in radiation therapy treatment planning for lung and liver lesions. The decision about an application of motion management devices and the estimation of patient-specific motion effects on the dose distribution relies on precise motion assessment in the planning 4D CT data { which is impeded in case of CT motion artifacts. The development of image-based/post-processing approaches to reduce motion artifacts would benefit from precise detection and localization of the artifacts. Simple slice-by-slice comparison of intensity values and threshold-based analysis of related metrics suffer from- depending on the threshold- high false-positive or -negative rates. In this work, we propose exploiting prior knowledge about `ideal' (= artifact free) reference geometries to stabilize metric-based artifact detection by transferring (multi-)atlas-based concepts to this specific task. Two variants are introduced and evaluated: (S1) analysis and comparison of warped atlas data obtained by repeated non-linear atlas-to-patient registration with different levels of regularization; (S2) direct analysis of vector field properties (divergence, curl magnitude) of the atlas-to-patient transformation. Feasibility of approaches (S1) and (S2) is evaluated by motion-phantom data and intra-subject experiments (four patients) as well as - adopting a multi-atlas strategy- inter-subject investigations (twelve patients involved). It is demonstrated that especially sorting/double structure artifacts can be precisely detected and localized by (S1). In contrast, (S2) suffers from high false positive rates.

Removal of the ballistocardiographic artifact from EEG-fMRI data: a canonical correlation approach

International Nuclear Information System (INIS)

Assecondi, Sara; Hallez, Hans; Staelens, Steven; Lemahieu, Ignace; Bianchi, Anna M; Huiskamp, Geertjan M

2009-01-01

The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) can give new insights into how the brain functions. However, the strong electromagnetic field of the MR scanner generates artifacts that obscure the EEG and diminish its readability. Among them, the ballistocardiographic artifact (BCGa) that appears on the EEG is believed to be related to blood flow in scalp arteries leading to electrode movements. Average artifact subtraction (AAS) techniques, used to remove the BCGa, assume a deterministic nature of the artifact. This assumption may be too strong, considering the blood flow related nature of the phenomenon. In this work we propose a new method, based on canonical correlation analysis (CCA) and blind source separation (BSS) techniques, to reduce the BCGa from simultaneously recorded EEG-fMRI. We optimized the method to reduce the user's interaction to a minimum. When tested on six subjects, recorded in 1.5 T or 3 T, the average artifact extracted with BSS-CCA and AAS did not show significant differences, proving the absence of systematic errors. On the other hand, when compared on the basis of intra-subject variability, we found significant differences and better performance of the proposed method with respect to AAS. We demonstrated that our method deals with the intrinsic subject variability specific to the artifact that may cause averaging techniques to fail.

Correction of computed tomography motion artifacts using pixel-specific back-projection

International Nuclear Information System (INIS)

Ritchie, C.J.; Crawford, C.R.; Godwin, J.D.; Kim, Y. King, K.F.

1996-01-01

Cardiac and respiratory motion can cause artifacts in computed tomography scans of the chest. The authors describe a new method for reducing these artifacts called pixel-specific back-projection (PSBP). PSBP reduces artifacts caused by in-plane motion by reconstructing each pixel in a frame of reference that moves with the in-plane motion in the volume being scanned. The motion of the frame of reference is specified by constructing maps that describe the motion of each pixel in the image at the time each projection was measured; these maps are based on measurements of the in-plane motion. PSBP has been tested in computer simulations and with volunteer data. In computer simulations, PSBP removed the structured artifacts caused by motion. In scans of two volunteers, PSBP reduced doubling and streaking in chest scans to a level that made the images clinically useful. PSBP corrections of liver scans were less satisfactory because the motion of the liver is predominantly superior-inferior (S-I). PSBP uses a unique set of motion parameters to describe the motion at each point in the chest as opposed to requiring that the motion be described by a single set of parameters. Therefore, PSBP may be more useful in correcting clinical scans than are other correction techniques previously described

[The value of 5-HTT gene polymorphism for the assessment and prediction of male adolescence violence].

Science.gov (United States)

Yu, Yue; Liu, Xiang; Yang, Zhen-xing; Qiu, Chang-jian; Ma, Xiao-hong

2012-08-01

To establish an adolescent violence crime prediction model, and to assess the value of serotonin transporter (5-HTT) gene polymorphism for the assessment and prediction of violent crime. Investigative tools were used to analyze the difference in personality dimensions, social support, coping styles, aggressiveness, impulsivity, and family condition scale between 223 adolescents with violence behavior and 148 adolescents without violence behavior. The distribution of 5-HTT gene polymorphisms (5-HTTLPR and 5-HTTVNTR) was compared between the two groups. The role of 5-HTT gene polymorphism on adolescent personality, impulsion and aggression scale also was also analyzed. Stepwise logistic regression was used to establish a predictive model for adolescent violent crime. Significant difference was found between the violence group and the control group on multiple dimensions of psychology and environment scales. However, no statistical difference was found with regard to the 5-HTT genotypes and alleles between adolescents with violent behaviors and normal controls. The rate of prediction accuracy was not significantly improved when 5-HTT gene polymorphism was taken into the model. The violent crime of adolescents was closely related with social and environmental factors. No association was found between 5-HTT polymorphisms and adolescent violence criminal behavior.

Two-dimensional analysis of motion artifacts, including flow effects

International Nuclear Information System (INIS)

Litt, A.M.; Brody, A.S.; Spangler, R.A.; Scott, P.D.

1990-01-01

The effects of motion on magnetic resonance images have been theoretically analyzed for the case of a point-like object in simple harmonic motion and for other one-dimensional trajectories. The authors of this paper extend this analysis to a generalized two-dimensional magnetization with an arbitrary motion trajectory. The authors provide specific solutions for the clinically relevant cases of the cross-sections of cylindrical objects in the body, such as the aorta, which has a roughly one-dimensional, simple harmonic motion during respiration. By extending the solution to include inhomogeneous magnetizations, the authors present a model which allows the effects of motion artifacts and flow artifacts to be analyzed simultaneously

Elimination of motion and pulsation artifacts using BLADE sequences in shoulder MR imaging

International Nuclear Information System (INIS)

Lavdas, E.; Zaloni, E.; Vlychou, M.; Vassiou, K.; Fezoulidis, I.; Tsagkalis, A.; Dailiana, Z.

2015-01-01

To evaluate the ability of proton-density with fat-suppression BLADE (proprietary name for periodically rotated overlapping parallel lines with enhanced reconstruction in MR systems from Siemens Healthcare, PDFS BLADE) and turbo inversion recovery magnitude-BLADE (TIRM BLADE) sequences to reduce motion and pulsation artifacts in shoulder magnetic resonance examinations. Forty-one consecutive patients who had been routinely scanned for shoulder examination participated in the study. The following pairs of sequences with and without BLADE were compared: (a) Oblique coronal proton-density sequence with fat saturation of 25 patients and (b) oblique sagittal T2 TIRM-weighed sequence of 20 patients. Qualitative analysis was performed by two experienced radiologists. Image motion and pulsation artifacts were also evaluated. In oblique coronal PDFS BLADE sequences, motion artifacts have been significantly eliminated, even in five cases of non-diagnostic value with conventional imaging. Similarly, in oblique sagittal T2 TIRM BLADE sequences, image quality has been improved, even in six cases of non-diagnostic value with conventional imaging. Furthermore, flow artifacts have been improved in more than 80% of all the cases. The use of BLADE sequences is recommended in shoulder imaging, especially in uncooperative patients because it effectively eliminates motion and pulsation artifacts. (orig.)

Investigating the possible effect of electrode support structure on motion artifact in wearable bioelectric signal monitoring.

Science.gov (United States)

Cömert, Alper; Hyttinen, Jari

2015-05-15

With advances in technology and increasing demand, wearable biosignal monitoring is developing and new applications are emerging. One of the main challenges facing the widespread use of wearable monitoring systems is the motion artifact. The sources of the motion artifact lie in the skin-electrode interface. Reducing the motion and deformation at this interface should have positive effects on signal quality. In this study, we aim to investigate whether the structure supporting the electrode can be designed to reduce the motion artifact with the hypothesis that this can be achieved by stabilizing the skin deformations around the electrode. We compare four textile electrodes with different support structure designs: a soft padding larger than the electrode area, a soft padding larger than the electrode area with a novel skin deformation restricting design, a soft padding the same size as the electrode area, and a rigid support the same size as the electrode. With five subjects and two electrode locations placed over different kinds of tissue at various mounting forces, we simultaneously measured the motion artifact, a motion affected ECG, and the real-time skin-electrode impedance during the application of controlled motion to the electrodes. The design of the electrode support structure has an effect on the generated motion artifact; good design with a skin stabilizing structure makes the electrodes physically more motion artifact resilient, directly affecting signal quality. Increasing the applied mounting force shows a positive effect up to 1,000 gr applied force. The properties of tissue under the electrode are an important factor in the generation of the motion artifact and the functioning of the electrodes. The relationship of motion artifact amplitude to the electrode movement magnitude is seen to be linear for smaller movements. For larger movements, the increase of motion generated a disproportionally larger artifact. The motion artifact and the induced

CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes.

Science.gov (United States)

Kong, Hualei; Tong, Pan; Zhao, Xiaodong; Sun, Jielin; Li, Hua

2018-03-01

In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and

Expression Pattern Similarities Support the Prediction of Orthologs Retaining Common Functions after Gene Duplication Events1[OPEN

Science.gov (United States)

Haberer, Georg; Panda, Arup; Das Laha, Shayani; Ghosh, Tapas Chandra; Schäffner, Anton R.

2016-01-01

The identification of functionally equivalent, orthologous genes (functional orthologs) across genomes is necessary for accurate transfer of experimental knowledge from well-characterized organisms to others. This frequently relies on automated, coding sequence-based approaches such as OrthoMCL, Inparanoid, and KOG, which usually work well for one-to-one homologous states. However, this strategy does not reliably work for plants due to the occurrence of extensive gene/genome duplication. Frequently, for one query gene, multiple orthologous genes are predicted in the other genome, and it is not clear a priori from sequence comparison and similarity which one preserves the ancestral function. We have studied 11 organ-dependent and stress-induced gene expression patterns of 286 Arabidopsis lyrata duplicated gene groups and compared them with the respective Arabidopsis (Arabidopsis thaliana) genes to predict putative expressologs and nonexpressologs based on gene expression similarity. Promoter sequence divergence as an additional tool to substantiate functional orthology only partially overlapped with expressolog classification. By cloning eight A. lyrata homologs and complementing them in the respective four Arabidopsis loss-of-function mutants, we experimentally proved that predicted expressologs are indeed functional orthologs, while nonexpressologs or nonfunctionalized orthologs are not. Our study demonstrates that even a small set of gene expression data in addition to sequence homologies are instrumental in the assignment of functional orthologs in the presence of multiple orthologs. PMID:27303025

Short branches lead to systematic artifacts when BLAST searches are used as surrogate for phylogenetic reconstruction.

Science.gov (United States)

Dick, Amanda A; Harlow, Timothy J; Gogarten, J Peter

2017-02-01

Long Branch Attraction (LBA) is a well-known artifact in phylogenetic reconstruction when dealing with branch length heterogeneity. Here we show another phenomenon, Short Branch Attraction (SBA), which occurs when BLAST searches, a phenetic analysis, are used as a surrogate method for phylogenetic analysis. This error also results from branch length heterogeneity, but this time it is the short branches that are attracting. The SBA artifact is reciprocal and can be returned 100% of the time when multiple branches differ in length by a factor of more than two. SBA is an intended feature of BLAST searches, but becomes an issue, when top scoring BLAST hit analyses are used to infer Horizontal Gene Transfers (HGTs), assign taxonomic category with environmental sequence data in phylotyping, or gather homologous sequences for building gene families. SBA can lead researchers to believe that there has been a HGT event when only vertical descent has occurred, cause slowly evolving taxa to be over-represented and quickly evolving taxa to be under-represented in phylotyping, or systematically exclude quickly evolving taxa from analyses. SBA also contributes to the changing results of top scoring BLAST hit analyses as the database grows, because more slowly evolving taxa, or short branches, are added over time, introducing more potential for SBA. SBA can be detected by examining reciprocal best BLAST hits among a larger group of taxa, including the known closest phylogenetic neighbors. Therefore, one should look for this phenomenon when conducting best BLAST hit analyses as a surrogate method to identify HGTs, in phylotyping, or when using BLAST to gather homologous sequences. Copyright © 2016 Elsevier Inc. All rights reserved.

WE-AB-207A-12: HLCC Based Quantitative Evaluation Method of Image Artifact in Dental CBCT

International Nuclear Information System (INIS)

Chen, Y; Wu, S; Qi, H; Xu, Y; Zhou, L

2016-01-01

Purpose: Image artifacts are usually evaluated qualitatively via visual observation of the reconstructed images, which is susceptible to subjective factors due to the lack of an objective evaluation criterion. In this work, we propose a Helgason-Ludwig consistency condition (HLCC) based evaluation method to quantify the severity level of different image artifacts in dental CBCT. Methods: Our evaluation method consists of four step: 1) Acquire Cone beam CT(CBCT) projection; 2) Convert 3D CBCT projection to fan-beam projection by extracting its central plane projection; 3) Convert fan-beam projection to parallel-beam projection utilizing sinogram-based rebinning algorithm or detail-based rebinning algorithm; 4) Obtain HLCC profile by integrating parallel-beam projection per view and calculate wave percentage and variance of the HLCC profile, which can be used to describe the severity level of image artifacts. Results: Several sets of dental CBCT projections containing only one type of artifact (i.e. geometry, scatter, beam hardening, lag and noise artifact), were simulated using gDRR, a GPU tool developed for efficient, accurate, and realistic simulation of CBCT Projections. These simulated CBCT projections were used to test our proposed method. HLCC profile wave percentage and variance induced by geometry distortion are about 3∼21 times and 16∼393 times as large as that of the artifact-free projection, respectively. The increase factor of wave percentage and variance are 6 and133 times for beam hardening, 19 and 1184 times for scatter, and 4 and16 times for lag artifacts, respectively. In contrast, for noisy projection the wave percentage, variance and inconsistency level are almost the same with those of the noise-free one. Conclusion: We have proposed a quantitative evaluation method of image artifact based on HLCC theory. According to our simulation results, the severity of different artifact types is found to be in a following order: Scatter

WE-AB-207A-12: HLCC Based Quantitative Evaluation Method of Image Artifact in Dental CBCT

Energy Technology Data Exchange (ETDEWEB)

Chen, Y; Wu, S; Qi, H; Xu, Y; Zhou, L [Southern Medical University, Guangzhou, Guangdong (China)

2016-06-15

Purpose: Image artifacts are usually evaluated qualitatively via visual observation of the reconstructed images, which is susceptible to subjective factors due to the lack of an objective evaluation criterion. In this work, we propose a Helgason-Ludwig consistency condition (HLCC) based evaluation method to quantify the severity level of different image artifacts in dental CBCT. Methods: Our evaluation method consists of four step: 1) Acquire Cone beam CT(CBCT) projection; 2) Convert 3D CBCT projection to fan-beam projection by extracting its central plane projection; 3) Convert fan-beam projection to parallel-beam projection utilizing sinogram-based rebinning algorithm or detail-based rebinning algorithm; 4) Obtain HLCC profile by integrating parallel-beam projection per view and calculate wave percentage and variance of the HLCC profile, which can be used to describe the severity level of image artifacts. Results: Several sets of dental CBCT projections containing only one type of artifact (i.e. geometry, scatter, beam hardening, lag and noise artifact), were simulated using gDRR, a GPU tool developed for efficient, accurate, and realistic simulation of CBCT Projections. These simulated CBCT projections were used to test our proposed method. HLCC profile wave percentage and variance induced by geometry distortion are about 3∼21 times and 16∼393 times as large as that of the artifact-free projection, respectively. The increase factor of wave percentage and variance are 6 and133 times for beam hardening, 19 and 1184 times for scatter, and 4 and16 times for lag artifacts, respectively. In contrast, for noisy projection the wave percentage, variance and inconsistency level are almost the same with those of the noise-free one. Conclusion: We have proposed a quantitative evaluation method of image artifact based on HLCC theory. According to our simulation results, the severity of different artifact types is found to be in a following order: Scatter

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2008-01-01

.e., big-step operational semantics) specified in Abadi and Cardelli's monograph. This abstract machine therefore embodies the soundness of Abadi and Cardelli's reduction semantics and natural semantics relative to each other. To move closer to actual implementations, which use environments rather than......We present a new abstract machine for Abadi and Cardelli's untyped calculus of objects. What is special about this semantic artifact (i.e., man-made construct) is that is mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i...... actual substitutions, we then represent object methods as closures and in the same inter-derivational spirit, we present three new semantic artifacts: a reduction semantics for a version of Abadi and Cardelli's untyped calculus of objects with explicit substitutions, an environment-based abstract machine...

Gene expression prediction by soft integration and the elastic net-best performance of the DREAM3 gene expression challenge.

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Mika Gustafsson

Full Text Available BACKGROUND: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance. METHODOLOGY/PRINCIPAL FINDINGS: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the "elastic net". Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance. CONCLUSIONS/SIGNIFICANCE: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.

Supporting Knowledge Transfer through Decomposable Reasoning Artifacts

Energy Technology Data Exchange (ETDEWEB)

Pike, William A.; May, Richard A.; Turner, Alan E.

2007-01-03

Technology to support knowledge transfer and cooperative inquiry must offer its users the ability to effectively interpret knowledge structures produced by collaborators. Communicating the reasoning processes that underlie a finding is one method for enhancing interpretation, and can result in more effective evaluation and application of shared knowledge. In knowledge management tools, interpretation is aided by creating knowledge artifacts that can expose their provenance to scrutiny and that can be transformed into diverse representations that suit their consumers’ perspectives and preferences. We outline the information management needs of inquiring communities characterized by hypothesis generation tasks, and propose a model for communication, based in theories of hermeneutics, semiotics, and abduction, in which knowledge structures can be decomposed into the lower-level reasoning artifacts that produced them. We then present a proof-of-concept implementation for an environment to support the capture and communication of analytic products, with emphasis on the domain of intelligence analysis.

Experimental analysis of motion artifacts in chest radiographs with the AMBER system

International Nuclear Information System (INIS)

Boetticher, H. von; Hofmann, K.; Luska, G.

1999-01-01

The prerequisites, mechanisms and principles of motion artifacts in AMBER radiographs were analysed. The experiments were performed using metronomes, a moving conventional mammography phantom, and arrangements of oscillating coil spring, spheroid and grid elements. A diagnostic dosimeter and TLDs, respectively, were used to measure exposure times and doses. The deree of distortion in AMBER radiographs depends on the direction of the object movement relative to the AMBER fan beam in a complex manner. The size of the motion artifacts depends on the local exposure time. The maximum value of this time is 75 ms and thus 1.5 times higher than specified by the manufacturer. To interpret AMBER radiographs possible system specific artifacts have to be considered to avoid misinterpretations of potentially significant details. (orig.) [de

SU-C-206-03: Metal Artifact Reduction in X-Ray Computed Tomography Based On Local Anatomical Similarity

International Nuclear Information System (INIS)

Dong, X; Yang, X; Rosenfield, J; Elder, E; Dhabaan, A

2016-01-01

Purpose: Metal implants such as orthopedic hardware and dental fillings cause severe bright and dark streaking in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. Additionally, such artifacts negatively impact patient set-up in image guided radiation therapy (IGRT). In this work, we propose a novel method for metal artifact reduction which utilizes the anatomical similarity between neighboring CT slices. Methods: Neighboring CT slices show similar anatomy. Based on this anatomical similarity, the proposed method replaces corrupted CT pixels with pixels from adjacent, artifact-free slices. A gamma map, which is the weighted summation of relative HU error and distance error, is calculated for each pixel in the artifact-corrupted CT image. The minimum value in each pixel’s gamma map is used to identify a pixel from the adjacent CT slice to replace the corresponding artifact-corrupted pixel. This replacement only occurs if the minimum value in a particular pixel’s gamma map is larger than a threshold. The proposed method was evaluated with clinical images. Results: Highly attenuating dental fillings and hip implants cause severe streaking artifacts on CT images. The proposed method eliminates the dark and bright streaking and improves the implant delineation and visibility. In particular, the image non-uniformity in the central region of interest was reduced from 1.88 and 1.01 to 0.28 and 0.35, respectively. Further, the mean CT HU error was reduced from 328 HU and 460 HU to 60 HU and 36 HU, respectively. Conclusions: The proposed metal artifact reduction method replaces corrupted image pixels with pixels from neighboring slices that are free of metal artifacts. This method proved capable of suppressing streaking artifacts, improving HU accuracy and image detectability.

SU-C-206-03: Metal Artifact Reduction in X-Ray Computed Tomography Based On Local Anatomical Similarity

Energy Technology Data Exchange (ETDEWEB)

Dong, X; Yang, X; Rosenfield, J; Elder, E; Dhabaan, A [Emory University, Winship Cancer Institute, Atlanta, GA (United States)

2016-06-15

Purpose: Metal implants such as orthopedic hardware and dental fillings cause severe bright and dark streaking in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. Additionally, such artifacts negatively impact patient set-up in image guided radiation therapy (IGRT). In this work, we propose a novel method for metal artifact reduction which utilizes the anatomical similarity between neighboring CT slices. Methods: Neighboring CT slices show similar anatomy. Based on this anatomical similarity, the proposed method replaces corrupted CT pixels with pixels from adjacent, artifact-free slices. A gamma map, which is the weighted summation of relative HU error and distance error, is calculated for each pixel in the artifact-corrupted CT image. The minimum value in each pixel’s gamma map is used to identify a pixel from the adjacent CT slice to replace the corresponding artifact-corrupted pixel. This replacement only occurs if the minimum value in a particular pixel’s gamma map is larger than a threshold. The proposed method was evaluated with clinical images. Results: Highly attenuating dental fillings and hip implants cause severe streaking artifacts on CT images. The proposed method eliminates the dark and bright streaking and improves the implant delineation and visibility. In particular, the image non-uniformity in the central region of interest was reduced from 1.88 and 1.01 to 0.28 and 0.35, respectively. Further, the mean CT HU error was reduced from 328 HU and 460 HU to 60 HU and 36 HU, respectively. Conclusions: The proposed metal artifact reduction method replaces corrupted image pixels with pixels from neighboring slices that are free of metal artifacts. This method proved capable of suppressing streaking artifacts, improving HU accuracy and image detectability.

Quantitative assessment of image artifacts from root filling materials on CBCT scans made using several exposure parameters

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Rabelo, Katharina Alves; Cavalcanti, Yuri Wanderley; De Oliveira Pinto, Martina Gerlane; De Melo, Daniela Pita [Dept. of Oral Diagnosis, State University of Paraiba, Campina Grande (Brazil); Melo, Saulo Leonardo Sousa [Dept. of Oral Pathology, Radiology and Medicine, University of Iowa, Iowa City (United States); Campos, Paulo Sergio Flores; De Andrade Freitas Oliveira, Luciana Soares [Federal University of Bahia, Salvador (Brazil)

2017-09-15

To quantify artifacts from different root filling materials in cone-beam computed tomography (CBCT) images acquired using different exposure parameters. Fifteen single-rooted teeth were scanned using 8 different exposure protocols with 3 different filling materials and once without filling material as a control group. Artifact quantification was performed by a trained observer who made measurements in the central axial slice of all acquired images in a fixed region of interest using ImageJ. Hyperdense artifacts, hypodense artifacts, and the remaining tooth area were identified, and the percentages of hyperdense and hypodense artifacts, remaining tooth area, and tooth area affected by the artifacts were calculated. Artifacts were analyzed qualitatively by 2 observers using the following scores: absence (0), moderate presence (1), and high presence (2) for hypodense halos, hypodense lines, and hyperdense lines. Two-way ANOVA and the post-hoc Tukey test were used for quantitative and qualitative artifact analysis. The Dunnet test was also used for qualitative analysis. The significance level was set at P<.05. There were no significant interactions among the exposure parameters in the quantitative or qualitative analysis. Significant differences were observed among the studied filling materials in all quantitative analyses. In the qualitative analyses, all materials differed from the control group in terms of hypodense and hyperdense lines (P<.05). Fiberglass posts did not differ statistically from the control group in terms of hypodense halos (P>.05). Different exposure parameters did not affect the objective or subjective observations of artifacts in CBCT images; however, the filling materials used in endodontic restorations did affect both types of assessments.

Standard artifact for the geometric verification of terrestrial laser scanning systems

Science.gov (United States)

González-Jorge, H.; Riveiro, B.; Armesto, J.; Arias, P.

2011-10-01

Terrestrial laser scanners are geodetic instruments with applications in areas such as architecture, civil engineering or environment. Although it is common to receive the technical specifications of the systems from their manufacturers, there are not any solutions for data verification in the market available for the users. This work proposes a standard artifact and a methodology to perform, in a simple way, the metrology verification of laser scanners. The artifact is manufactured using aluminium and delrin, materials that make the artifact robust and portable. The system consists of a set of five spheres situated at equal distances to one another, and a set of seven cubes of different sizes. A coordinate measuring machine with sub-millimetre precision is used for calibration purposes under controlled environmental conditions. After its calibration, the artifact can be used for the verification of metrology specifications given by manufacturers of laser scanners. The elements of the artifact are destinated to test different metrological characteristics, such as accuracy, precision and resolution. The distance between centres of the spheres is used to obtain the accuracy data, the standard deviation of the top face of the largest cube is used to establish the precision (repeatability) and the error in the measurement of the cubes provides the resolution value in axes X, Y and Z. Methodology for the evaluation is mainly supported by least squares fitting algorithms developed using Matlab programming. The artifact and methodology proposed were tested using a terrestrial laser scanner Riegl LMSZ-390i at three different ranges (10, 30 and 50 m) and four stepwidths (0.002°, 0.005°, 0.010° and 0.020°), both for horizontal and vertical displacements. Results obtained are in agreement with the accuracy and precision data given by the manufacturer, 6 and 4 mm, respectively. On the other hand, important influences between resolution and range and between resolution and

Entropy-based gene ranking without selection bias for the predictive classification of microarray data

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Serafini Maria

2003-11-01

Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

Effectiveness of gene expression profiling for response prediction of rectal cancer to preoperative radiotherapy

International Nuclear Information System (INIS)

Ojima, Eiki; Inoue, Yasuhiro; Miki, Chikao; Kusunoki, Masato; Mori, Masaki

2007-01-01

Our aim was to determine whether the expression levels of specific genes could predict clinical radiosensitivity in human colorectal cancer. Radioresistant colorectal cancer cell lines were established by repeated X-ray exposure (total, 100 Gy), and the gene expressions of the parent and radioresistant cell lines were compared in a microarray analysis. To verify the microarray data, we carried out a reverse transcriptase-polymerase chain reaction analysis of identified genes in clinical samples from 30 irradiated rectal cancer patients. A comparison of the intensity data for the parent and three radioresistant cell lines revealed 17 upregulated and 142 downregulated genes in all radioresistant cell lines. Next, we focused on two upregulated genes, PTMA (prothymosin α) and EIF5a2 (eukaryotic translation initiation factor 5A), in the radioresistant cell lines. In clinical samples, the expression of PTMA was significantly higher in the minor effect group than in the major effect group (P=0.004), but there were no significant differences in EIF5a2 expression between the two groups. We identified radiation-related genes in colorectal cancer and demonstrated that PTMA may play an important role in radiosensitivity. Our findings suggest that PTMA may be a novel marker for predicting the effectiveness of radiotherapy in clinical cases. (author)

Ultrasound-guided probe-generated artifacts stimulating ventricular tachycardia: A rare phenomenon

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Rafat Shamim

2017-01-01

Full Text Available Electrocardiographic (ECG artifacts may arise due to interference, faulty earthing, and current leakages in biomedical equipment which might create clinical dilemmas in the perioperative settings. Piezoelectric signals generated by ultrasonography probe are another uncommon source which might be sensed by the ECG electrodes and produce tracings similar to pathological arrhythmias triggering false alarms and avoidable therapies. Anesthesiologists should be familiar with these uncommon sources which might produce these artifacts and they should be identified swiftly.

Technical artifacts in chromatographic analysis of Tc-99m radiopharmaceuticals

International Nuclear Information System (INIS)

Kowalsky, R.J.; Creekmore, J.R.

1982-01-01

Technical artifacts produced during chromatographic analysis of technetium radiopharmaceuticals were investigated. Such artifacts are, we found, caused by improper spotting and drying techniques; these in turn produce spuriously high impurities in Tc-99m complexes of DTPA, MDP, PPi, and GH. The ITLC-SG/acetone system produces considerable streaking of Tc-complex if the applied spot is large and not dried before development. This results in activity in the solvent front portion of the chromatographic strip indicating falsely high levels of pertechnetate impurity. Proper drying of the applied spot eliminates the artifact. The ITLC-SG/saline system yields falsely high, hydrolyzed-reduced technetium impurities if the spot is allowed to enter the solvent during development. Correct spot placement and size eliminate this problem. Strips that are allowed to dry in room air for several minutes may indicate considerable pertechnetate impurity on the chromatogram; yet this may not actually be present in the radiopharmaceutical vial. Drying spots rapidly with hot air or in a nitrogen atmosphere before development eliminates this problem

A statistical method for predicting splice variants between two groups of samples using GeneChip® expression array data

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Olson James M

2006-04-01

Full Text Available Abstract Background Alternative splicing of pre-messenger RNA results in RNA variants with combinations of selected exons. It is one of the essential biological functions and regulatory components in higher eukaryotic cells. Some of these variants are detectable with the Affymetrix GeneChip® that uses multiple oligonucleotide probes (i.e. probe set, since the target sequences for the multiple probes are adjacent within each gene. Hybridization intensity from a probe correlates with abundance of the corresponding transcript. Although the multiple-probe feature in the current GeneChip® was designed to assess expression values of individual genes, it also measures transcriptional abundance for a sub-region of a gene sequence. This additional capacity motivated us to develop a method to predict alternative splicing, taking advance of extensive repositories of GeneChip® gene expression array data. Results We developed a two-step approach to predict alternative splicing from GeneChip® data. First, we clustered the probes from a probe set into pseudo-exons based on similarity of probe intensities and physical adjacency. A pseudo-exon is defined as a sequence in the gene within which multiple probes have comparable probe intensity values. Second, for each pseudo-exon, we assessed the statistical significance of the difference in probe intensity between two groups of samples. Differentially expressed pseudo-exons are predicted to be alternatively spliced. We applied our method to empirical data generated from GeneChip® Hu6800 arrays, which include 7129 probe sets and twenty probes per probe set. The dataset consists of sixty-nine medulloblastoma (27 metastatic and 42 non-metastatic samples and four cerebellum samples as normal controls. We predicted that 577 genes would be alternatively spliced when we compared normal cerebellum samples to medulloblastomas, and predicted that thirteen genes would be alternatively spliced when we compared metastatic

CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation.

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Nikulova, Anna A; Favorov, Alexander V; Sutormin, Roman A; Makeev, Vsevolod J; Mironov, Andrey A

2012-07-01

Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory 'grammar', or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila.

Reduction of variable-truncation artifacts from beam occlusion during in situ x-ray tomography

DEFF Research Database (Denmark)

Borg, Leise; Jørgensen, Jakob Sauer; Frikel, Jürgen

2017-01-01

Many in situ x-ray tomography studies require experimental rigs which may partially occlude the beam and cause parts of the projection data to be missing. In a study of fluid flow in porous chalk using a percolation cell with four metal bars drastic streak artifacts arise in the filtered...... and artifact-reduction methods are designed in context of FBP reconstruction motivated by computational efficiency practical for large, real synchrotron data. While a specific variable-truncation case is considered, the proposed methods can be applied to general data cut-offs arising in different in situ x-ray...... backprojection (FBP) reconstruction at certain orientations. Projections with non-trivial variable truncation caused by the metal bars are the source of these variable-truncation artifacts. To understand the artifacts a mathematical model of variable-truncation data as a function of metal bar radius and distance...

An illustrative review to understand and manage metal-induced artifacts in musculoskeletal MRI: a primer and updates

Energy Technology Data Exchange (ETDEWEB)

Dillenseger, J.P.; Choquet, P.; Goetz, C.; Bierry, G. [University Hospital of Strasbourg, Medical Imaging Department, Strasbourg (France); Icube, CNRS, University of Strasbourg, Strasbourg (France); University of Strasbourg, Translational Medicine Research Federation, Strasbourg Medical School, Strasbourg (France); Moliere, S. [University Hospital of Strasbourg, Medical Imaging Department, Strasbourg (France); Ehlinger, M. [Icube, CNRS, University of Strasbourg, Strasbourg (France); University of Strasbourg, Translational Medicine Research Federation, Strasbourg Medical School, Strasbourg (France); University Hospital of Strasbourg, Department of Orthopedic Surgery, Strasbourg (France)

2016-05-15

This article reviews and explains the basic physical principles of metal-induced MRI artifacts, describes simple ways to reduce them, and presents specific reduction solutions. Artifacts include signal loss, pile-up artifacts, geometric distortion, and failure of fat suppression. Their nature and origins are reviewed and explained though schematic representations that ease the understanding. Then, optimization of simple acquisition parameters is detailed. Lastly, dedicated sequences and options specifically developed to reduce metal artifacts (VAT, SEMAC, and MAVRIC) are explained. (orig.)

FACET - a "Flexible Artifact Correction and Evaluation Toolbox" for concurrently recorded EEG/fMRI data.

Science.gov (United States)

Glaser, Johann; Beisteiner, Roland; Bauer, Herbert; Fischmeister, Florian Ph S

2013-11-09

In concurrent EEG/fMRI recordings, EEG data are impaired by the fMRI gradient artifacts which exceed the EEG signal by several orders of magnitude. While several algorithms exist to correct the EEG data, these algorithms lack the flexibility to either leave out or add new steps. The here presented open-source MATLAB toolbox FACET is a modular toolbox for the fast and flexible correction and evaluation of imaging artifacts from concurrently recorded EEG datasets. It consists of an Analysis, a Correction and an Evaluation framework allowing the user to choose from different artifact correction methods with various pre- and post-processing steps to form flexible combinations. The quality of the chosen correction approach can then be evaluated and compared to different settings. FACET was evaluated on a dataset provided with the FMRIB plugin for EEGLAB using two different correction approaches: Averaged Artifact Subtraction (AAS, Allen et al., NeuroImage 12(2):230-239, 2000) and the FMRI Artifact Slice Template Removal (FASTR, Niazy et al., NeuroImage 28(3):720-737, 2005). Evaluation of the obtained results were compared to the FASTR algorithm implemented in the EEGLAB plugin FMRIB. No differences were found between the FACET implementation of FASTR and the original algorithm across all gradient artifact relevant performance indices. The FACET toolbox not only provides facilities for all three modalities: data analysis, artifact correction as well as evaluation and documentation of the results but it also offers an easily extendable framework for development and evaluation of new approaches.

Adipose Gene Expression Prior to Weight Loss Can Differentiate and Weakly Predict Dietary Responders

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Mutch, David M.; Temanni, M. Ramzi; Henegar, Corneliu; Combes, Florence; Pelloux, Véronique; Holst, Claus; Sørensen, Thorkild I. A.; Astrup, Arne; Martinez, J. Alfredo; Saris, Wim H. M.; Viguerie, Nathalie; Langin, Dominique; Zucker, Jean-Daniel; Clément, Karine

2007-01-01

Background The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. Methodology/Principal Findings The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB) trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8–12 kgs weight loss) could always be differentiated from non-responders (diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition. PMID:18094752

Attenuation of artifacts in EEG signals measured inside an MRI scanner using constrained independent component analysis

International Nuclear Information System (INIS)

Rasheed, Tahir; Lee, Young-Koo; Lee, Soo Yeol; Kim, Tae-Seong

2009-01-01

Integration of electroencephalography (EEG) and functional magnetic imaging (fMRI) resonance will allow analysis of the brain activities at superior temporal and spatial resolution. However simultaneous acquisition of EEG and fMRI is hindered by the enhancement of artifacts in EEG, the most prominent of which are ballistocardiogram (BCG) and electro-oculogram (EOG) artifacts. The situation gets even worse if the evoked potentials are measured inside MRI for their minute responses in comparison to the spontaneous brain responses. In this study, we propose a new method of attenuating these artifacts from the spontaneous and evoked EEG data acquired inside an MRI scanner using constrained independent component analysis with a priori information about the artifacts as constraints. With the proposed techniques of reference function generation for the BCG and EOG artifacts as constraints, our new approach performs significantly better than the averaged artifact subtraction (AAS) method. The proposed method could be an alternative to the conventional ICA method for artifact attenuation, with some advantages. As a performance measure we have achieved much improved normalized power spectrum ratios (INPS) for continuous EEG and correlation coefficient (cc) values with outside MRI visual evoked potentials for visual evoked EEG, as compared to those obtained with the AAS method. The results show that our new approach is more effective than the conventional methods, almost fully automatic, and no extra ECG signal measurements are involved

A systematic comparison of motion artifact correction techniques for functional near-infrared spectroscopy.

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Cooper, Robert J; Selb, Juliette; Gagnon, Louis; Phillip, Dorte; Schytz, Henrik W; Iversen, Helle K; Ashina, Messoud; Boas, David A

2012-01-01

Near-infrared spectroscopy (NIRS) is susceptible to signal artifacts caused by relative motion between NIRS optical fibers and the scalp. These artifacts can be very damaging to the utility of functional NIRS, particularly in challenging subject groups where motion can be unavoidable. A number of approaches to the removal of motion artifacts from NIRS data have been suggested. In this paper we systematically compare the utility of a variety of published NIRS motion correction techniques using a simulated functional activation signal added to 20 real NIRS datasets which contain motion artifacts. Principle component analysis, spline interpolation, wavelet analysis, and Kalman filtering approaches are compared to one another and to standard approaches using the accuracy of the recovered, simulated hemodynamic response function (HRF). Each of the four motion correction techniques we tested yields a significant reduction in the mean-squared error (MSE) and significant increase in the contrast-to-noise ratio (CNR) of the recovered HRF when compared to no correction and compared to a process of rejecting motion-contaminated trials. Spline interpolation produces the largest average reduction in MSE (55%) while wavelet analysis produces the highest average increase in CNR (39%). On the basis of this analysis, we recommend the routine application of motion correction techniques (particularly spline interpolation or wavelet analysis) to minimize the impact of motion artifacts on functional NIRS data.

sEMG during Whole-Body Vibration Contains Motion Artifacts and Reflex Activity

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Karin Lienhard

2015-01-01

Full Text Available The purpose of this study was to determine whether the excessive spikes observed in the surface electromyography (sEMG spectrum recorded during whole-body vibration (WBV exercises contain motion artifacts and/or reflex activity. The occurrence of motion artifacts was tested by electrical recordings of the patella. The involvement of reflex activity was investigated by analyzing the magnitude of the isolated spikes during changes in voluntary background muscle activity. Eighteen physically active volunteers performed static squats while the sEMG was measured of five lower limb muscles during vertical WBV using no load and an additional load of 33 kg. In order to record motion artifacts during WBV, a pair of electrodes was positioned on the patella with several layers of tape between skin and electrodes. Spectral analysis of the patella signal revealed recordings of motion artifacts as high peaks at the vibration frequency (fundamental and marginal peaks at the multiple harmonics were observed. For the sEMG recordings, the root mean square of the spikes increased with increasing additional loads (p < 0.05, and was significantly correlated to the sEMG signal without the spikes of the respective muscle (r range: 0.54 - 0.92, p < 0.05. This finding indicates that reflex activity might be contained in the isolated spikes, as identical behavior has been found for stretch reflex responses evoked during direct vibration. In conclusion, the spikes visible in the sEMG spectrum during WBV exercises contain motion artifacts and possibly reflex activity.

Using purine skews to predict genes in AT-rich poxviruses

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Upton Chris

2005-02-01

Full Text Available Abstract Background Clusters or runs of purines on the mRNA synonymous strand have been found in many different organisms including orthopoxviruses. The purine bias that is exhibited by these clusters can be observed using a purine skew and in the case of poxviruses, these skews can be used to help determine the coding strand of a particular segment of the genome. Combined with previous findings that minor ORFs have lower than average aspartate and glutamate composition and higher than average serine composition, purine content can be used to predict the likelihood of a poxvirus ORF being a "real gene". Results Using purine skews and a "quality" measure designed to incorporate previous findings about minor ORFs, we have found that in our training case (vaccinia virus strain Copenhagen, 59 of 65 minor (small and unlikely to be a real genes ORFs were correctly classified as being minor. Of the 201 major (large and likely to be real genes vaccinia ORFs, 192 were correctly classified as being major. Performing a similar analysis with the entomopoxvirus amsacta moorei (AMEV, it was found that 4 major ORFs were incorrectly classified as minor and 9 minor ORFs were incorrectly classified as major. The purine abundance observed for major ORFs in vaccinia virus was found to stem primarily from the first codon position with both the second and third codon positions containing roughly equal amounts of purines and pyrimidines. Conclusion Purine skews and a "quality" measure can be used to predict functional ORFs and purine skews in particular can be used to determine which of two overlapping ORFs is most likely to be the real gene if neither of the two ORFs has orthologs in other poxviruses.

ECG artifact cancellation in surface EMG signals by fractional order calculus application.

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Miljković, Nadica; Popović, Nenad; Djordjević, Olivera; Konstantinović, Ljubica; Šekara, Tomislav B

2017-03-01

New aspects for automatic electrocardiography artifact removal from surface electromyography signals by application of fractional order calculus in combination with linear and nonlinear moving window filters are explored. Surface electromyography recordings of skeletal trunk muscles are commonly contaminated with spike shaped artifacts. This artifact originates from electrical heart activity, recorded by electrocardiography, commonly present in the surface electromyography signals recorded in heart proximity. For appropriate assessment of neuromuscular changes by means of surface electromyography, application of a proper filtering technique of electrocardiography artifact is crucial. A novel method for automatic artifact cancellation in surface electromyography signals by applying fractional order calculus and nonlinear median filter is introduced. The proposed method is compared with the linear moving average filter, with and without prior application of fractional order calculus. 3D graphs for assessment of window lengths of the filters, crest factors, root mean square differences, and fractional calculus orders (called WFC and WRC graphs) have been introduced. For an appropriate quantitative filtering evaluation, the synthetic electrocardiography signal and analogous semi-synthetic dataset have been generated. The examples of noise removal in 10 able-bodied subjects and in one patient with muscle dystrophy are presented for qualitative analysis. The crest factors, correlation coefficients, and root mean square differences of the recorded and semi-synthetic electromyography datasets showed that the most successful method was the median filter in combination with fractional order calculus of the order 0.9. Statistically more significant (p ECG peak reduction was obtained by the median filter application compared to the moving average filter in the cases of low level amplitude of muscle contraction compared to ECG spikes. The presented results suggest that the

Reducing 4D CT artifacts using optimized sorting based on anatomic similarity.

Science.gov (United States)

Johnston, Eric; Diehn, Maximilian; Murphy, James D; Loo, Billy W; Maxim, Peter G

2011-05-01

Four-dimensional (4D) computed tomography (CT) has been widely used as a tool to characterize respiratory motion in radiotherapy. The two most commonly used 4D CT algorithms sort images by the associated respiratory phase or displacement into a predefined number of bins, and are prone to image artifacts at transitions between bed positions. The purpose of this work is to demonstrate a method of reducing motion artifacts in 4D CT by incorporating anatomic similarity into phase or displacement based sorting protocols. Ten patient datasets were retrospectively sorted using both the displacement and phase based sorting algorithms. Conventional sorting methods allow selection of only the nearest-neighbor image in time or displacement within each bin. In our method, for each bed position either the displacement or the phase defines the center of a bin range about which several candidate images are selected. The two dimensional correlation coefficients between slices bordering the interface between adjacent couch positions are then calculated for all candidate pairings. Two slices have a high correlation if they are anatomically similar. Candidates from each bin are then selected to maximize the slice correlation over the entire data set using the Dijkstra's shortest path algorithm. To assess the reduction of artifacts, two thoracic radiation oncologists independently compared the resorted 4D datasets pairwise with conventionally sorted datasets, blinded to the sorting method, to choose which had the least motion artifacts. Agreement between reviewers was evaluated using the weighted kappa score. Anatomically based image selection resulted in 4D CT datasets with significantly reduced motion artifacts with both displacement (P = 0.0063) and phase sorting (P = 0.00022). There was good agreement between the two reviewers, with complete agreement 34 times and complete disagreement 6 times. Optimized sorting using anatomic similarity significantly reduces 4D CT motion

Cooperative learning, problem solving and mediating artifacts

African Journals Online (AJOL)

PROF.MIREKU

10, 2012. 39. Cooperative learning, problem solving and mediating artifacts. F. Bahmaei6 & N. ... out cooperative learning in the end, post-test was done and by analyzing the tests it was concluded that ... Johnson et al, 1991 b, Reynolds et al. 1995, Vidakovic .... connection of mental constructs (Hiebert, Carpenter, 1992).

Computational prediction of miRNA genes from small RNA sequencing data

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Wenjing eKang

2015-01-01

Full Text Available Next-generation sequencing now for the first time allows researchers to gauge the depth and variation of entire transcriptomes. However, now as rare transcripts can be detected that are present in cells at single copies, more advanced computational tools are needed to accurately annotate and profile them. miRNAs are 22 nucleotide small RNAs (sRNAs that post-transcriptionally reduce the output of protein coding genes. They have established roles in numerous biological processes, including cancers and other diseases. During miRNA biogenesis, the sRNAs are sequentially cleaved from precursor molecules that have a characteristic hairpin RNA structure. The vast majority of new miRNA genes that are discovered are mined from small RNA sequencing (sRNA-seq, which can detect more than a billion RNAs in a single run. However, given that many of the detected RNAs are degradation products from all types of transcripts, the accurate identification of miRNAs remain a non-trivial computational problem. Here we review the tools available to predict animal miRNAs from sRNA sequencing data. We present tools for generalist and specialist use cases, including prediction from massively pooled data or in species without reference genome. We also present wet-lab methods used to validate predicted miRNAs, and approaches to computationally benchmark prediction accuracy. For each tool, we reference validation experiments and benchmarking efforts. Last, we discuss the future of the field.

Moving metal artifact reduction in cone-beam CT scans with implanted cylindrical gold markers

International Nuclear Information System (INIS)

Toftegaard, Jakob; Fledelius, Walther; Worm, Esben S.; Poulsen, Per R.; Seghers, Dieter; Huber, Michael; Brehm, Marcus; Elstrøm, Ulrik V.

2014-01-01

Purpose: Implanted gold markers for image-guided radiotherapy lead to streaking artifacts in cone-beam CT (CBCT) scans. Several methods for metal artifact reduction (MAR) have been published, but they all fail in scans with large motion. Here the authors propose and investigate a method for automatic moving metal artifact reduction (MMAR) in CBCT scans with cylindrical gold markers. Methods: The MMAR CBCT reconstruction method has six steps. (1) Automatic segmentation of the cylindrical markers in the CBCT projections. (2) Removal of each marker in the projections by replacing the pixels within a masked area with interpolated values. (3) Reconstruction of a marker-free CBCT volume from the manipulated CBCT projections. (4) Reconstruction of a standard CBCT volume with metal artifacts from the original CBCT projections. (5) Estimation of the three-dimensional (3D) trajectory during CBCT acquisition for each marker based on the segmentation in Step 1, and identification of the smallest ellipsoidal volume that encompasses 95% of the visited 3D positions. (6) Generation of the final MMAR CBCT reconstruction from the marker-free CBCT volume of Step 3 by replacing the voxels in the 95% ellipsoid with the corresponding voxels of the standard CBCT volume of Step 4. The MMAR reconstruction was performed retrospectively using a half-fan CBCT scan for 29 consecutive stereotactic body radiation therapy patients with 2–3 gold markers implanted in the liver. The metal artifacts of the MMAR reconstructions were scored and compared with a standard MAR reconstruction by counting the streaks and by calculating the standard deviation of the Hounsfield units in a region around each marker. Results: The markers were found with the same autosegmentation settings in 27 CBCT scans, while two scans needed slightly changed settings to find all markers automatically in Step 1 of the MMAR method. MMAR resulted in 15 scans with no streaking artifacts, 11 scans with 1–4 streaks, and 3 scans

Successive approximation algorithm for cancellation of artifacts in DSA images

International Nuclear Information System (INIS)

Funakami, Raiko; Hiroshima, Kyoichi; Nishino, Junji

2000-01-01

In this paper, we propose an algorithm for cancellation of artifacts in DSA images. We have already proposed an automatic registration method based on the detection of local movements. When motion of the object is large, it is difficult to estimate the exact movement, and the cancellation of artifacts may therefore fail. The algorithm we propose here is based on a simple rigid model. We present the results of applying the proposed method to a series of experimental X-ray images, as well as the results of applying the algorithm as preprocessing for a registration method based on local movement. (author)

Substance and Artifact in the Higher-Order Factors of the Big Five

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McCrae, Robert R.; Jang, Kerry L.; Ando, Juko; Ono, Yutaka; Yamagata, Shinji; Riemann, Rainer; Angleitner, Alois; Spinath, Frank M.

2018-01-01

J. M. Digman (1997) proposed that the Big Five personality traits showed a higher-order structure with 2 factors he labeled α and β. These factors have been alternatively interpreted as heritable components of personality or as artifacts of evaluative bias. Using structural equation modeling, the authors reanalyzed data from a cross-national twin study and from American cross-observer studies and analyzed new multimethod data from a German twin study. In all analyses, artifact models outperformed substance models by root-mean-square error of approximation criteria, but models combining both artifact and substance were slightly better. These findings suggest that the search for the biological basis of personality traits may be more profitably focused on the 5 factors themselves and their specific facets, especially in monomethod studies. PMID:18665712

Technical Assessment of Artifact Production from Neuro Endovascular Coil At 3 Tesla MRI: An In Vitro Study

International Nuclear Information System (INIS)

Kampaengtip, A.; Krisanachinda, A.; Singhara Na Ayudya, S.; Asavaphatiboon, S.

2012-01-01

Introduction: Magnetic resonance imaging (MRI) is an essential part of the diagnostic procedures in radiology. MRI 3 Tesla becomes more widespread due to high signal to noise ratio (SNR). The use of the neuro endovascular coil to overcome the neuro aneurysm can introduce the artifact in magnetic resonance imaging. Susceptibility artifacts and geometric distortions caused by magnetic field inhomogeneity- related signal loss is used to refer to an artifact in magnetic resonance images. It consists of a region of signal void with a surrounding area of an increased signal intensity that appears to be considerably larger than the actual size of the device causing the artifact. The objective of the study is to compare the size of the artifact on the MR image to the actual size of endovascular coils using a 3 Tesla magnetic resonance imaging system, in vitro study. Methods: The endovascular coils were made from detachable platinum and aneurysm models were constructed by using silicone tube. MRI 3 Tesla Philips Model Achieva with pulse sequence selections were: spin echo, fast spin echo, inversion recovery, fast gradient echo while additional parameters were echo time and turbo factor. Results: Improved visualization of perianeurysmal soft tissues is best accomplished by spin echo for fast spin echo sequences, even better suited to reduce metal artifact. Furthermore, shorter turbo factor and shorter effective TE in the latter sequences are beneficial for the same reason as sequences having shorter TE. Sequences with a shorter TE are preferred because of less time for dephasing and frequency shifting. Imaging at gradient echo series increases susceptibility artifacts. In this in vitro study, some of the major characteristics related to MRI imaging of coil packs have been defined. Discussion: Pulse sequence spin echo is the best sequence reducing the susceptibility artifact. Reducing the TE is the main factor in improving endovascular coil visualization on MRI images. The

A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data

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Ruzzo Walter L

2006-03-01

Full Text Available Abstract Background As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heterogeneous data sources. Methods In this paper, we address this issue by proposing a general framework for gene function prediction based on the k-nearest-neighbor (KNN algorithm. The choice of KNN is motivated by its simplicity, flexibility to incorporate different data types and adaptability to irregular feature spaces. A weakness of traditional KNN methods, especially when handling heterogeneous data, is that performance is subject to the often ad hoc choice of similarity metric. To address this weakness, we apply regression methods to infer a similarity metric as a weighted combination of a set of base similarity measures, which helps to locate the neighbors that are most likely to be in the same class as the target gene. We also suggest a novel voting scheme to generate confidence scores that estimate the accuracy of predictions. The method gracefully extends to multi-way classification problems. Results We apply this technique to gene function prediction according to three well-known Escherichia coli classification schemes suggested by biologists, using information derived from microarray and genome sequencing data. We demonstrate that our algorithm dramatically outperforms the naive KNN methods and is competitive with support vector machine (SVM algorithms for integrating heterogenous data. We also show that by combining different data sources, prediction accuracy can improve significantly. Conclusion Our extension of KNN with automatic feature weighting, multi-class prediction, and probabilistic inference, enhance prediction accuracy significantly while remaining efficient, intuitive and flexible. This general framework can also be applied to similar classification problems involving heterogeneous datasets.

Scattered image artifacts from cone beam computed tomography and its clinical potential in bone mineral density estimation.

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Ko, Hoon; Jeong, Kwanmoon; Lee, Chang-Hoon; Jun, Hong Young; Jeong, Changwon; Lee, Myeung Su; Nam, Yunyoung; Yoon, Kwon-Ha; Lee, Jinseok

2016-01-01

Image artifacts affect the quality of medical images and may obscure anatomic structure and pathology. Numerous methods for suppression and correction of scattered image artifacts have been suggested in the past three decades. In this paper, we assessed the feasibility of use of information on scattered artifacts for estimation of bone mineral density (BMD) without dual-energy X-ray absorptiometry (DXA) or quantitative computed tomographic imaging (QCT). To investigate the relationship between scattered image artifacts and BMD, we first used a forearm phantom and cone-beam computed tomography. In the phantom, we considered two regions of interest-bone-equivalent solid material containing 50 mg HA per cm(-3) and water-to represent low- and high-density trabecular bone, respectively. We compared the scattered image artifacts in the high-density material with those in the low-density material. The technique was then applied to osteoporosis patients and healthy subjects to assess its feasibility for BMD estimation. The high-density material produced a greater number of scattered image artifacts than the low-density material. Moreover, the radius and ulna of healthy subjects produced a greater number of scattered image artifacts than those from osteoporosis patients. Although other parameters, such as bone thickness and X-ray incidence, should be considered, our technique facilitated BMD estimation directly without DXA or QCT. We believe that BMD estimation based on assessment of scattered image artifacts may benefit the prevention, early treatment and management of osteoporosis.

Image artifacts in concurrent transcranial magnetic stimulation (TMS) and fMRI caused by leakage currents: modeling and compensation.

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Weiskopf, Nikolaus; Josephs, Oliver; Ruff, Christian C; Blankenburg, Felix; Featherstone, Eric; Thomas, Anthony; Bestmann, Sven; Driver, Jon; Deichmann, Ralf

2009-05-01

To characterize and eliminate a new type of image artifact in concurrent transcranial magnetic stimulation and functional MRI (TMS-fMRI) caused by small leakage currents originating from the high-voltage capacitors in the TMS stimulator system. The artifacts in echo-planar images (EPI) caused by leakage currents were characterized and quantified in numerical simulations and phantom studies with different phantom-coil geometries. A relay-diode combination was devised and inserted in the TMS circuit that shorts the leakage current. Its effectiveness for artifact reduction was assessed in a phantom scan resembling a realistic TMS-fMRI experiment. The leakage-current-induced signal changes exhibited a multipolar spatial pattern and the maxima exceeded 1% at realistic coil-cortex distances. The relay-diode combination effectively reduced the artifact to a negligible level. The leakage-current artifacts potentially obscure effects of interest or lead to false-positives. Since the artifact depends on the experimental setup and design (eg, amplitude of the leakage current, coil orientation, paradigm, EPI parameters), we recommend its assessment for each experiment. The relay-diode combination can eliminate the artifacts if necessary.

Effect of Metal Artifacts on Detection of Vertical Root Fractures Using Two Cone Beam Computed Tomography Systems.

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Safi, Yaser; Aghdasi, Mohammad Mehdi; Ezoddini-Ardakani, Fatemeh; Beiraghi, Samira; Vasegh, Zahra

2015-01-01

Vertical root fracture (VRF) is common in endodontically treated teeth. Conventional and digital radiographies have limitations for detection of VRFs. Cone-beam computed tomography (CBCT) offers greater detection accuracy of VRFs in comparison with conventional radiography. This study compared the effects of metal artifacts on detection of VRFs by using two CBCT systems. Eighty extracted premolars were selected and sectioned at the level of the cemento enamel junction (CEJ). After preparation, root canals were filled with gutta-percha. Subsequently, two thirds of the root fillings were removed for post space preparation and a custom-made post was cemented into each canal. The teeth were randomly divided into two groups (n=40). In the test group, root fracture was created with Instron universal testing machine. The control teeth remained intact. CBCT scans of all teeth were obtained with either New Tom VGI or Soredex Scanora 3D. Three observers analyzed the images for detection of VRF. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for VRF detection and percentage of probable cases were calculated for each imaging system and compared using non-parametric tests considering the non-normal distribution of data. The inter-observer reproducibility was calculated using the weighted kappa coefficient. There were no statistically significant differences in sensitivity, specificity, PPV and NPV between the two CBCT systems. The effect of metal artifacts on VRF detection was not significantly different between the two CBCT systems.

False positive reduction in protein-protein interaction predictions using gene ontology annotations

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Lin Yen-Han

2007-07-01

Full Text Available Abstract Background Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated. Results Gene Ontology (GO annotations were used to reduce false positive protein-protein interactions (PPI pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The 'strength', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the strength varies between two and ten-fold of randomly removing protein pairs from the datasets. Conclusion Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially

Radiocarbon dating study of ancient iron artifacts with accelerator mass spectrometry

International Nuclear Information System (INIS)

Igaki, Kenzo; Nakamura, Toshio; Hirasawa, Masahiro; Kato, Masako; Sano, Masamichi.

1994-01-01

In order to study the correlation between the highly resistive property against corrosion and the production method of the ancient iron artifacts, it is essentially necessary to determine the accurate ages of them. 14 C dating with accelerator mass spectrometry was applied to the two ancient artifacts, a Japanese sword of wrought iron with a production age ranged from the Kamakura to the Muromachi period, estimation based on the fabrication technique, and a planning adze of cast iron with no definite origin. The former was dated as 880±150 y.B.P., corresponding to the calendar age ranged from AD 1021 to AD 1263, and the latter as 1720±160 y.B.P. with the calendar age ranged from AD 119 to AD 457 and from AD 483 to AD 508. These calibrated 14 C ages for both iron artifacts are consistent with the relevant ages conjectured by historical considerations. (author)

Colorectal Cancer "Methylator Phenotype": Fact or Artifact?

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Charles Anacleto

2005-04-01

Full Text Available It has been proposed that human colorectal tumors can be classified into two groups: one in which methylation is rare, and another with methylation of several loci associated with a "CpG island methylated phenotype (CIMP," characterized by preferential proximal location in the colon, but otherwise poorly defined. There is considerable overlap between this putative methylator phenotype and the well-known mutator phenotype associated with microsatellite instability (MSI. We have examined hypermethylation of the promoter region of five genes (DAPK, MGMT, hMLH1, p16INK4a, and p14ARF in 106 primary colorectal cancers. A graph depicting the frequency of methylated loci in the series of tumors showed a continuous, monotonically decreasing distribution quite different from the previously claimed discontinuity. We observed a significant association between the presence of three or more methylated loci and the proximal location of the tumors. However, if we remove from analysis the tumors with hMLH1 methylation or those with MSI, the significance vanishes, suggesting that the association between multiple methylations and proximal location was indirect due to the correlation with MSI. Thus, our data do not support the independent existence of the so-called methylator phenotype and suggest that it rather may represent a statistical artifact caused by confounding of associations.

Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions.

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Ye-Lin, Yiyao; Garcia-Casado, Javier; Prats-Boluda, Gema; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

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Yiyao Ye-Lin

2014-01-01

Full Text Available Electrohysterography (EHG is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Deep Learning Approach for Automatic Classification of Ocular and Cardiac Artifacts in MEG Data

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Ahmad Hasasneh

2018-01-01

Full Text Available We propose an artifact classification scheme based on a combined deep and convolutional neural network (DCNN model, to automatically identify cardiac and ocular artifacts from neuromagnetic data, without the need for additional electrocardiogram (ECG and electrooculogram (EOG recordings. From independent components, the model uses both the spatial and temporal information of the decomposed magnetoencephalography (MEG data. In total, 7122 samples were used after data augmentation, in which task and nontask related MEG recordings from 48 subjects served as the database for this study. Artifact rejection was applied using the combined model, which achieved a sensitivity and specificity of 91.8% and 97.4%, respectively. The overall accuracy of the model was validated using a cross-validation test and revealed a median accuracy of 94.4%, indicating high reliability of the DCNN-based artifact removal in task and nontask related MEG experiments. The major advantages of the proposed method are as follows: (1 it is a fully automated and user independent workflow of artifact classification in MEG data; (2 once the model is trained there is no need for auxiliary signal recordings; (3 the flexibility in the model design and training allows for various modalities (MEG/EEG and various sensor types.

Evaluating applicability of metal artifact reduction algorithm for head and neck radiation treatment planning CT

International Nuclear Information System (INIS)

Son, Sang Jun; Park, Jang Pil; Kim, Min Jeong; Yoo, Suk Hyun

2014-01-01

The purpose of this study is evaluation for the applicability of O-MAR(Metal artifact Reduction for Orthopedic Implants)(ver. 3.6.0, Philips, Netherlands) in head and neck radiation treatment planning CT with metal artifact created by dental implant. All of the in this study's CT images were scanned by Brilliance Big Bore CT(Philips, Netherlands) at 120 kVp, 2 mm sliced and Metal artifact reduced by O-MAR. To compare the original and reconstructed CT images worked on RTPS(Eclipse ver 10.0.42, Varian, USA). In order to test the basic performance of the O-MAR, The phantom was made to create metal artifact by dental implant and other phantoms used for without artifact images. To measure a difference of HU in with artifact images and without artifact images, homogeneous phantom and inhomogeneous phantoms were used with cerrobend rods. Each of images were compared a difference of HU in ROIs. And also, 1 case of patient's original CT image applied O-MAR and density corrected CT were evaluated for dose distributions with SNC Patient(Sun Nuclear Co., USA). In cases of head and neck phantom, the difference of dose distribution is appeared 99.8% gamma passing rate(criteria 2 mm / 2%) between original and CT images applied O-MAR. And 98.5% appeared in patient case, among original CT, O-MAR and density corrected CT. The difference of total dose distribution is less than 2% that appeared both phantom and patient case study. Though the dose deviations are little, there are still matters to discuss that the dose deviations are concentrated so locally. In this study, The quality of all images applied O-MAR was improved. Unexpectedly, Increase of max. HU was founded in air cavity of the O-MAR images compare to cavity of the original images and wrong corrections were appeared, too. The result of study assuming restrained case of O-MAR adapted to near skin and low density area, it appeared image distortion and artifact correction simultaneously. In O-MAR CT, air cavity area

Synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON): A statistical model based iterative image reconstruction method to eliminate limited-view artifacts and to mitigate the temporal-average artifacts in time-resolved CT.

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Chen, Guang-Hong; Li, Yinsheng

2015-08-01

In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial-temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial-temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial-temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed

Removing Contamination-Induced Reconstruction Artifacts from Cryo-electron Tomograms

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Fernandez, Jose-Jesus; Laugks, Ulrike; Schaffer, Miroslava; Bäuerlein, Felix J.B.; Khoshouei, Maryam; Baumeister, Wolfgang; Lucic, Vladan

2016-01-01

Imaging of fully hydrated, vitrified biological samples by electron tomography yields structural information about cellular protein complexes in situ. Here we present a computational procedure that removes artifacts of three-dimensional reconstruction caused by contamination present in samples during imaging by electron microscopy. Applying the procedure to phantom data and electron tomograms of cellular samples significantly improved the resolution and the interpretability of tomograms. Artifacts caused by surface contamination associated with thinning by focused ion beam, as well as those arising from gold fiducial markers and from common, lower contrast contamination, could be removed. Our procedure is widely applicable and is especially suited for applications that strive to reach a higher resolution and involve the use of recently developed, state-of-the-art instrumentation. PMID:26743046

Evaluation of artifacts generated by zirconium implants in cone-beam computed tomography images.

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Vasconcelos, Taruska Ventorini; Bechara, Boulos B; McMahan, Clyde Alex; Freitas, Deborah Queiroz; Noujeim, Marcel

2017-02-01

To evaluate zirconium implant artifact production in cone beam computed tomography images obtained with different protocols. One zirconium implant was inserted in an edentulous mandible. Twenty scans were acquired with a ProMax 3D unit (Planmeca Oy, Helsinki, Finland), with acquisition settings ranging from 70 to 90 peak kilovoltage (kVp) and voxel sizes of 0.32 and 0.16 mm. A metal artifact reduction (MAR) tool was activated in half of the scans. An axial slice through the middle region of the implant was selected for each dataset. Gray values (mean ± standard deviation) were measured in two regions of interest, one close to and the other distant from the implant (control area). The contrast-to-noise ratio was also calculated. Standard deviation decreased with greater kVp and when the MAR tool was used. The contrast-to-noise ratio was significantly higher when the MAR tool was turned off, except for low resolution with kVp values above 80. Selection of the MAR tool and greater kVp resulted in an overall reduction of artifacts in images acquired with low resolution. Although zirconium implants do produce image artifacts in cone-bean computed tomography scans, the setting that best controlled artifact generation by zirconium implants was 90 kVp at low resolution and with the MAR tool turned on. Copyright © 2016 Elsevier Inc. All rights reserved.

Complementary contrast media for metal artifact reduction in dual-energy computed tomography.

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Lambert, Jack W; Edic, Peter M; FitzGerald, Paul F; Torres, Andrew S; Yeh, Benjamin M

2015-07-01

Metal artifacts have been a problem associated with computed tomography (CT) since its introduction. Recent techniques to mitigate this problem have included utilization of high-energy (keV) virtual monochromatic spectral (VMS) images, produced via dual-energy CT (DECT). A problem with these high-keV images is that contrast enhancement provided by all commercially available contrast media is severely reduced. Contrast agents based on higher atomic number elements can maintain contrast at the higher energy levels where artifacts are reduced. This study evaluated three such candidate elements: bismuth, tantalum, and tungsten, as well as two conventional contrast elements: iodine and barium. A water-based phantom with vials containing these five elements in solution, as well as different artifact-producing metal structures, was scanned with a DECT scanner capable of rapid operating voltage switching. In the VMS datasets, substantial reductions in the contrast were observed for iodine and barium, which suffered from contrast reductions of 97% and 91%, respectively, at 140 versus 40 keV. In comparison under the same conditions, the candidate agents demonstrated contrast enhancement reductions of only 20%, 29%, and 32% for tungsten, tantalum, and bismuth, respectively. At 140 versus 40 keV, metal artifact severity was reduced by 57% to 85% depending on the phantom configuration.

Artifact Reduction of Susceptibility-Weighted Imaging Using a Short-Echo Phase Mask

International Nuclear Information System (INIS)

Ishimori, Y.; Monma, M.; Kohno, Y.

2009-01-01

Background: Susceptibility-weighted imaging (SWI) is utilized in magnetic resonance (MR) venography and other applications, but can include artifacts caused by the phase-masking process. Purpose: To demonstrate risks of filter processes used in making phase masks for SWI, and to propose a simple method for reducing artifacts. Material and Methods: Phase linearity related to echo time (TE) was evaluated for the original phase and high-pass-filtered phase using a CuSO 4 -doped water phantom. Effect of filter size of the Hanning window and background homogeneity were also evaluated in a phantom study. Use of a phase mask generated by data with differing magnitudes of TE was attempted in a human study. Shorter TE was used for making the phase mask, and the number of multiplications was increased. As short and long TEs were necessary simultaneously for phase mask and T2* contrast, a dual-echo technique was used. Results: Linearity of TE and phase value collapsed, and an unexpected negative phase appeared in the high-pass-filtered phase. Using a short-TE phase mask, phase-aliasing artifacts were reduced and visibility of deep veins was equivalent to that under conventional methods with an increased number of multiplications. Conclusion: Use of a short-echo phase mask in SWI is useful for reducing artifacts

MSVAT-SPACE-STIR and SEMAC-STIR for Reduction of Metallic Artifacts in 3T Head and Neck MRI.

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Hilgenfeld, T; Prager, M; Schwindling, F S; Nittka, M; Rammelsberg, P; Bendszus, M; Heiland, S; Juerchott, A

2018-05-24

The incidence of metallic dental restorations and implants is increasing, and head and neck MR imaging is becoming challenging regarding artifacts. Our aim was to evaluate whether multiple-slab acquisition with view angle tilting gradient based on a sampling perfection with application-optimized contrasts by using different flip angle evolution (MSVAT-SPACE)-STIR and slice-encoding for metal artifact correction (SEMAC)-STIR are beneficial regarding artifact suppression compared with the SPACE-STIR and TSE-STIR in vitro and in vivo. At 3T, 3D artifacts of 2 dental implants, supporting different single crowns, were evaluated. Image quality was evaluated quantitatively (normalized signal-to-noise ratio) and qualitatively (2 reads by 2 blinded radiologists). Feasibility was tested in vivo in 5 volunteers and 5 patients, respectively. Maximum achievable resolution and the normalized signal-to-noise ratio of MSVAT-SPACE-STIR were higher compared with SEMAC-STIR. Performance in terms of artifact correction was dependent on the material composition. For highly paramagnetic materials, SEMAC-STIR was superior to MSVAT-SPACE-STIR (27.8% smaller artifact volume) and TSE-STIR (93.2% less slice distortion). However, MSVAT-SPACE-STIR reduced the artifact size compared with SPACE-STIR by 71.5%. For low-paramagnetic materials, MSVAT-SPACE-STIR performed as well as SEMAC-STIR. Furthermore, MSVAT-SPACE-STIR decreased artifact volume by 69.5% compared with SPACE-STIR. The image quality of all sequences did not differ systematically. In vivo results were comparable with in vitro results. Regarding susceptibility artifacts and acquisition time, MSVAT-SPACE-STIR might be advantageous over SPACE-STIR for high-resolution and isotropic head and neck imaging. Only for materials with high-susceptibility differences to soft tissue, the use of SEMAC-STIR might be beneficial. Within limited acquisition times, SEMAC-STIR cannot exploit its full advantage over TSE-STIR regarding artifact

Incidence of Artifacts and Deviating Values in Research Data Obtained from an Anesthesia Information Management System in Children.

Science.gov (United States)

Hoorweg, Anne-Lee J; Pasma, Wietze; van Wolfswinkel, Leo; de Graaff, Jurgen C

2018-02-01

Vital parameter data collected in anesthesia information management systems are often used for clinical research. The validity of this type of research is dependent on the number of artifacts. In this prospective observational cohort study, the incidence of artifacts in anesthesia information management system data was investigated in children undergoing anesthesia for noncardiac procedures. Secondary outcomes included the incidence of artifacts among deviating and nondeviating values, among the anesthesia phases, and among different anesthetic techniques. We included 136 anesthetics representing 10,236 min of anesthesia time. The incidence of artifacts was 0.5% for heart rate (95% CI: 0.4 to 0.7%), 1.3% for oxygen saturation (1.1 to 1.5%), 7.5% for end-tidal carbon dioxide (6.9 to 8.0%), 5.0% for noninvasive blood pressure (4.0 to 6.0%), and 7.3% for invasive blood pressure (5.9 to 8.8%). The incidence of artifacts among deviating values was 3.1% for heart rate (2.1 to 4.4%), 10.8% for oxygen saturation (7.6 to 14.8%), 14.1% for end-tidal carbon dioxide (13.0 to 15.2%), 14.4% for noninvasive blood pressure (10.3 to 19.4%), and 38.4% for invasive blood pressure (30.3 to 47.1%). Not all values in anesthesia information management systems are valid. The incidence of artifacts stored in the present pediatric anesthesia practice was low for heart rate and oxygen saturation, whereas noninvasive and invasive blood pressure and end-tidal carbon dioxide had higher artifact incidences. Deviating values are more often artifacts than values in a normal range, and artifacts are associated with the phase of anesthesia and anesthetic technique. Development of (automatic) data validation systems or solutions to deal with artifacts in data is warranted.

Observer Evaluation of a Metal Artifact Reduction Algorithm Applied to Head and Neck Cone Beam Computed Tomographic Images

Energy Technology Data Exchange (ETDEWEB)

Korpics, Mark; Surucu, Murat; Mescioglu, Ibrahim; Alite, Fiori; Block, Alec M.; Choi, Mehee; Emami, Bahman; Harkenrider, Matthew M.; Solanki, Abhishek A.; Roeske, John C., E-mail: jroeske@lumc.edu

2016-11-15

Purpose and Objectives: To quantify, through an observer study, the reduction in metal artifacts on cone beam computed tomographic (CBCT) images using a projection-interpolation algorithm, on images containing metal artifacts from dental fillings and implants in patients treated for head and neck (H&N) cancer. Methods and Materials: An interpolation-substitution algorithm was applied to H&N CBCT images containing metal artifacts from dental fillings and implants. Image quality with respect to metal artifacts was evaluated subjectively and objectively. First, 6 independent radiation oncologists were asked to rank randomly sorted blinded images (before and after metal artifact reduction) using a 5-point rating scale (1 = severe artifacts; 5 = no artifacts). Second, the standard deviation of different regions of interest (ROI) within each image was calculated and compared with the mean rating scores. Results: The interpolation-substitution technique successfully reduced metal artifacts in 70% of the cases. From a total of 60 images from 15 H&N cancer patients undergoing image guided radiation therapy, the mean rating score on the uncorrected images was 2.3 ± 1.1, versus 3.3 ± 1.0 for the corrected images. The mean difference in ranking score between uncorrected and corrected images was 1.0 (95% confidence interval: 0.9-1.2, P<.05). The standard deviation of each ROI significantly decreased after artifact reduction (P<.01). Moreover, a negative correlation between the mean rating score for each image and the standard deviation of the oral cavity and bilateral cheeks was observed. Conclusion: The interpolation-substitution algorithm is efficient and effective for reducing metal artifacts caused by dental fillings and implants on CBCT images, as demonstrated by the statistically significant increase in observer image quality ranking and by the decrease in ROI standard deviation between uncorrected and corrected images.