Semi-automatic Extraction Research Articles

RAPID INSPECTION OF PAVEMENT MARKINGS USING MOBILE LIDAR POINT CLOUDS

This study aims at building a robust semi-automated pavement marking extraction workflow based on the use of mobile LiDAR point clouds. The proposed workflow consists of three components: preprocessing, extraction, and classification. In preprocessing, the mobile LiDAR point clouds are converted into the radiometrically corrected intensity imagery of the road surface. Then the pavement markings are automatically extracted with the intensity using a set of algorithms, including Otsu’s thresholding, neighbor-counting filtering, and region growing. Finally, the extracted pavement markings are classified with the geometric parameters using a manually defined decision tree. Case studies are conducted using the mobile LiDAR dataset acquired in Xiamen (Fujian, China) with different road environments by the RIEGL VMX-450 system. The results demonstrated that the proposed workflow and our software tool can achieve 93% in completeness, 95% in correctness, and 94% in F-score when using Xiamen dataset.

Monocular vision-based depth map extraction method for 2D to 3D video conversion

Due to the demand of 3D visualization and lack of 3D video content, a method converting the 2D to 3D video plays an important role. In this paper, a low-cost and high efficiency post processing method is presented to enjoy the vivid 3D video. We present two semi-automatic depth map extraction methods for stereo video conversion. For the static background video sequence, we proposed a method which combined the foreground segmentation with vanishing line technology. According to the separated foreground and background results from foreground segmentation algorithm, the viewer can use their acquired visual experience to initiate this operation with some depth information of background. Moreover, we proposed another conversion method for the dynamic background video sequence. Foreground segmentation was replaced by the relative velocity estimation based on the motion estimation and motion compensation. Combining the depth map from this work and the original 2D video, a vivid 3D video is produced.

Pioneer vegetation as an indicator of the geochemical parameters in abandoned mine sites using hyperspectral airborne data

A general problem that is associated with open-pit mining is the total displacement of the former landscape’s geocomponents. Overburden conveyor bridges have an irreversible impact on the environment. The consequence of this is a completely new system—the so-called “post-mining landscapes”. These are characterized by extreme geochemical milieus, especially acidity, which is caused by weathering processes (acid mine drainage). These extreme environments are often left to natural succession because of the enormous costs and poor prospects of a successful reclamation. This study investigated the relationship between pioneer vegetation (e.g., Calamagrostis epigejos) and the geochemical properties of heap material using hyperspectral airborne HyMap data in the west Bohemian lignite district near Sokolov (Czech Republic). Thus, a fully constrained linear spectral unmixing algorithm was applied to link the geochemical parameters with fractional abundances. Due to the limitation of pure surfaces in the data set of such fragmented and mixed areas, a three-stage semiautomated endmember extraction was developed. The first stage included the selection of pure surface types using a decision tree with a self-developed narrow band and normalized difference indices. The second stage extracted the potential endmembers using the sequential maximum angle convex cone algorithm. The third stage identified the final endmembers and eliminated the spectral outliers by comparing the extractions to field/laboratory spectral libraries. The abundance fraction image of the pioneer vegetation, which was generated by the linear spectral unmixing, showed the spatial distribution and density of the vegetation. A linear regression model was used to calibrate the abundance image against the pH value. The regression model successfully predicted the pH values of the soil (R 2 = 0.67, RPD = 1.42). This method demonstrated that hyperspectral remote sensing data could be used for ecological medium- and long-term monitoring, as well as for spatial assessments in post-mining areas. In addition, this approach works with a small amount of geochemical measurements and the sparse availability of endmembers.

Improvement and automation of a real-time PCR assay for vaginal fluids

The identification of vaginal fluids is crucial in forensic science. Several molecular protocols based on PCR amplification of mfDNA (microflora DNA) specific for vaginal bacteria are now available. Unfortunately mfDNA extraction and PCR reactions require manual optimization of several steps. The aim of present study was the verification of a partial automatization of vaginal fluids identification through two instruments widely diffused in forensic laboratories: EZ1 Advanced robot and Rotor Gene Q 5Plex HRM. Moreover, taking advantage of 5-plex thermocycler technology, the ForFluid kit performances were improved by expanding the mfDNA characterization panel with a new bacterial target for vaginal fluids and with an internal positive control (IPC) to monitor PCR inhibition. Results underlined the feasibility of a semi-automated extraction of mfDNA using a BioRobot and demonstrated the analytical improvements of the kit.

Land Cover Extraction from High Resolution ZY-3 Satellite Imagery Using Ontology-Based Method

The rapid development and increasing availability of high-resolution satellite (HRS) images provides increased opportunities to monitor large scale land cover. However, inefficiency and excessive independence on expert knowledge limits the usage of HRS images on a large scale. As a knowledge organization and representation method, ontology can assist in improving the efficiency of automatic or semi-automatic land cover information extraction, especially for HRS images. This paper presents an ontology-based framework that was used to model the land cover extraction knowledge and interpret HRS remote sensing images at the regional level. The land cover ontology structure is explicitly defined, accounting for the spectral, textural, and shape features, and allowing for the automatic interpretation of the extracted results. With the help of regional prototypes for land cover class stored in Web Ontology Language (OWL) file, automated land cover extraction of the study area is then attempted. Experiments are conducted using ZY-3 (Ziyuan-3) imagery, which were acquired for the Jiangxia District, Wuhan, China, in the summers of 2012 and 2013.The experimental method provided good land cover extraction results as the overall accuracy reached 65.07%. Especially for bare surfaces, highways, ponds, and lakes, whose producer and user accuracies were both higher than 75%. The results highlight the capability of the ontology-based method to automatically extract land cover using ZY-3 HRS images.

Visualizing Computational, Transversal Narratives from the World Trade Towers

Semi-automated extraction of details corresponding to narratological fabula from a corpus of narrative interviews on a single event provides decontextualized building blocks for transversal, or cross-document, narratives. With information extracted from 503 World Trade Center Task Force Interviews comprising 12,000 pages of testimony and novel visualization techniques, this article proposes a computational method for the emergence of narratives that cross beyond the boundaries of one interview. These assembled narratives, in cases like that of Chief Ganci, can document those who did not survive to tell their own story.

Coastal Observation through Cosmo-SkyMed High-Resolution SAR Images

ABSTRACT Bruno, M.F.; Molfetta M.G.; Mossa, M., Nutricato, R., Morea, A., and Chiaradia, M.T., 2016. Coastal observation through Cosmo-SkyMed high-resolution SAR images. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 795–799. Coconut Creek (Florida), ISSN 0749-0208. The study deals with the application and further improvement of an advanced Earth Observation system, named COSMO-Beach, developed for semi-automatic shoreline extraction and coastal morphology identification. The system exploits SAR Single-Look-Complex data acquired by the COSMO-SkyMed constellation, which is able to provide X-band images with a short revisiting time. The implemented procedures have been tested over a very popular beach in Apulia Region (Italy), affected by erosion problems induced by human activities. The outcomes of the COSMO-Beach system are presented and discussed.

Ontological Lexicon Enrichment: The Badea System For Semi-Automated Extraction Of Antonymy Relations From Arabic Language Corpora

language processing tools and applications; however, they are expensive to build, maintain, and extend. In this paper, we present the Badea system for the semi-automated extraction of lexical relations, specifically antonyms using a pattern-based approach to support the task of ontological lexicon enrichment. The approach is based on an ontology of “seed” pairs of antonyms in the Arabic language; we identify patterns in which the pairs occur and then use the patterns identified to find new antonym pairs in an Arabic textual corpora. Experiments are conducted on Badea using texts from three Arabic textual corpuses: KSUCCA, KACSTAC, and CAC. The system is evaluated and the patterns’ reliability and system performance is measured. The results from our experiments on the three Arabic corpora show that the pattern-based approach can be useful in the ontological enrichment task, as the evaluation of the system resulted in the ontology being updated with over 300 new antonym pairs, thereby enriching the lexicon and increasing its size by over 400%. Moreover, the results show important findings on the reliability of patterns in extracting antonyms for Arabic. The Badea system will facilitate the enrichment of ontological lexicons that can be very useful in any Arabic natural language processing system that requires semantic relation extraction.

国内外海岸线变化研究综述

PDF HTML阅读 XML下载 导出引用 引用提醒 海岸线变化研究综述 DOI: 10.5846/stxb201406181270 作者: 作者单位: 中国科学院烟台海岸带研究所,中国科学院烟台海岸带研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 中国科学院战略性先导科技专项(XDA05130703);中国科学院重点部署项目(KZZD-EW-14);中国科学院烟台海岸带研究所"一三五"项目(Y254021031) Review of research on coastline changes Author: Affiliation: Chinese Academy of Sciences,Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:受全球及海岸带区域环境过程与人类活动的综合影响,海岸线发生剧烈的变化,对生态、环境及经济社会的影响不容忽视,海岸线变化相关研究因此得到普遍的关注。在讨论海岸线的定义和分类的基础上,介绍岸线信息提取的方法与技术,总结国内外海岸线变化的特征、机制与影响方面研究的进展,并指出未来研究的趋势,包括:对海岸线变化过程进行动态监测仍将是普遍关注的研究重点之一;对海岸线变化特征、规律与机理的认识已经日益深化,基于大量高精度数据和机理模型的研究已成为热点和前沿问题;针对不同的海岸带区域,聚焦海岸线变化的原因和机制及其对环境和生态的影响,以及不同区域之间的相互联系与影响特征,这将是未来研究的重点之一;中国海岸线变化的独特性、复杂性突出,促进和支撑中国的海岸带综合管理实践,提高决策者与管理者对岸线变化所带来的灾害风险的重视,为中国海岸带的科学规划与发展提供依据,这应该是我国海岸线变化研究的重要目标。 Abstract:Because of the combined effects of global and coastal environmental processes and human activities, dramatic changes to coastlines have had significant effects on the environment, ecosystems, and human society in the coastal zone, and the issue has increasingly become a major socio-economic concern to countries along the coast. Consequently, coastline changes have drawn great attention in the academic community, and numerous studies on this issue have been conducted and results subsequently published. Following the definition of proxy-based coastlines and rules of coastline classification, in this paper, we review the methodologies and technologies of coastline interpretation, quality calculation, and estimation of coastlines extracted from remote sensing imageries and topographic maps, as well as analytical methodologies and technologies related to coastline change. Driving factors and the effects of coastline changes are also summarized and analyzed in this paper. Progress and directions of expected research are presented in the last part of this paper. A coastline is a wet-dry boundary or ocean-land boundary. In this paper, individual shoreline indicators generally fall into two categories: visually discernible coastlines (e.g., wet-dry line, debris line, vegetation line), or intersection lines of the coastal profile with a specific vertical elevation defined by the tidal constituents of a particular area (e.g., mean high-low water line, mean sea level line). Methodologies and data sources of coastline data extraction are reviewed in the second part, and the methodologies are classified into three categories based on whether they involve human assistance (automatic extraction, semi-automatic extraction, and visual interpretation). Calculation of quality and estimation of coastlines are discussed in the second part of this paper, and include line-based evaluation, point-based evaluation, and deduction evaluation. In the third part, methods for analysis of coastline change are reviewed and explained, from simple methods to more complicated ones, and from qualitative methods to more quantitative ones. The driving factors are reduced to three categories: global environmental processes (e.g., global warming, sea level rise), coastal environmental processes (e.g., ocean dynamic, sediment movement), and human activities (e.g., coastline hardening, sea reclamation). In the last part of this paper, we discuss research progress and expected research on coastline change around the world. We put forward the following views. Dynamic monitoring of coastline changes remains one of the highest research priorities, as our understanding of features, laws, and mechanisms of coastline change deepens, and as research based on high-accuracy data and advanced mechanistic models develops. Studies focus on causes and mechanisms of coastline changes, impacts on coastal environments and ecosystems of various coastal zones, as well as on the characteristics of interrelations and mutual influences of different coastal regions, are another major area of focus of studies on global coastline change. Furthermore, coastline changes in China have distinct characteristics and complexity; therefore, studies of the Chinese coastline should be used to set the primary goals for improving and supporting the practices of ICZM (Integrated Coastal Zone Management). These studies will increase the awareness of decision-makers and stakeholders of the risks of hazards caused by coastline change, and will provide key information for coastal scientific planning and development. 参考文献 相似文献 引证文献

Can we replace curation with information extraction software?

Can we use programs for automated or semi-automated information extraction from scientific texts as practical alternatives to professional curation? I show that error rates of current information extraction programs are too high to replace professional curation today. Furthermore, current IEP programs extract single narrow slivers of information, such as individual protein interactions; they cannot extract the large breadth of information extracted by professional curators for databases such as EcoCyc. They also cannot arbitrate among conflicting statements in the literature as curators can. Therefore, funding agencies should not hobble the curation efforts of existing databases on the assumption that a problem that has stymied Artificial Intelligence researchers for more than 60 years will be solved tomorrow. Semi-automated extraction techniques appear to have significantly more potential based on a review of recent tools that enhance curator productivity. But a full cost-benefit analysis for these tools is lacking. Without such analysis it is possible to expend significant effort developing information-extraction tools that automate small parts of the overall curation workflow without achieving a significant decrease in curation costs.Database URL:

Combining Weights of Evidence Analysis with Feature Extraction – A Case Study from the Hauraki Goldfield, New Zealand

In this contribution we combine different image processing and pattern recognition methodologies to map the probability of discovering epithermal mineral deposits in the northern part of the Coromandel peninsula, in New Zealand. The objective of this work is to propose a case-study where the substitution of structural geology GIS themes (commonly developed by humans) with products derived by image processing, computer-based, semi-automatic edge detection analyses, is carried out to reduce subjective input in the prospectivity analysis. Semi-automated lineament extraction results introduced in the mineral favourability statistical modelling can more easily reveal unexpected potentially mineralised target domains, being less subjective. We present initial results of this analysis and explain some of the methodologies adopted. Preliminary results suggest that this approach increases significantly the number of geological discontinuities mapped in the region, with the following implications: (1) prospectivity models are more risk-tolerant and result in an increased number of targets; (2) increments in posterior probability affect the statistical validity of the model due to conditional independence violation, requiring careful assessment of probability overestimation; (3) the feature extraction process identifies numerous lineaments that in some instances represent false positives (lineaments determined by a variety of causes, without geological significance); however, we find that Contrast calculations in the Bayesian analysis tend to penalize these evidential themes, because of the higher number of pixels (cells) containing a positive pattern (lineament existence = 1, being positive). This aspect reduces the overall impact of these predictors on the analysis, mitigating the effect of false positives (lower positive weights of evidence). Despite the limitations, results obtained are encouraging with a clearly superior and more detailed mapping of potential structural sites and their relative probabilities of hosting epithermal deposits.

Semi-automation of Doppler Spectrum Image Analysis for Grading Aortic Valve Stenosis Severity.

Doppler echocardiography analysis has become a golden standard in the modern diagnosis of heart diseases. In this paper, we propose a set of techniques for semi-automated parameter extraction for aortic valve stenosis severity grading. The main objectives of the study is to create echocardiography image processing techniques, which minimize manual image processing work of clinicians and leads to reduced human error rates. Aortic valve and left ventricle output tract spectrogram images have been processed and analyzed. A novel method was developed to trace systoles and to extract diagnostic relevant features. The results of the introduced method have been compared to the findings of the participating cardiologists. The experimental results showed the accuracy of the proposed method is comparable to the manual measurement performed by medical professionals. Linear regression analysis of the calculated parameters and the measurements manually obtained by the cardiologists resulted in the strongly correlated values: peak systolic velocity's and mean pressure gradient's R2 both equal to 0.99, their means' differences equal to 0.02 m/s and 4.09 mmHg, respectively, and aortic valve area's R2 of 0.89 with the two methods means' difference of 0.19 mm. The introduced Doppler echocardiography images processing method can be used as a computer-aided assistance in the aortic valve stenosis diagnostics. In our future work, we intend to improve precision of left ventricular outflow tract spectrogram measurements and apply data mining methods to propose a clinical decision support system for diagnosing aortic valve stenosis.

Detection of Echinococcus multilocularis by MC-PCR: evaluation of diagnostic sensitivity and specificity without gold standard

IntroductionA semi-automated magnetic capture probe-based DNA extraction and real-time PCR method (MC-PCR), allowing for a more efficient large-scale surveillance of Echinococcus multilocularis occurrence, has been developed. The test sensitivity has previously been evaluated using the sedimentation and counting technique (SCT) as a gold standard. However, as the sensitivity of the SCT is not 1, test characteristics of the MC-PCR was also evaluated using latent class analysis, a methodology not requiring a gold standard.Materials and methodsTest results, MC-PCR and SCT, from a previous evaluation of the MC-PCR using 177 foxes shot in the spring (n=108) and autumn 2012 (n=69) in high prevalence areas in Switzerland were used. Latent class analysis was used to estimate the test characteristics of the MC-PCR. Although it is not the primary aim of this study, estimates of the test characteristics of the SCT were also obtained.Results and discussionThis study showed that the sensitivity of the MC-PCR was 0.88 [95% posterior credible interval (PCI) 0.80–0.93], which was not significantly different than the SCT, 0.83 (95% PCI 0.76–0.88), which is currently considered as the gold standard. The specificity of both tests was high, 0.98 (95% PCI 0.94–0.99) for the MC-PCR and 0.99 (95% PCI 0.99–1) for the SCT. In a previous study, using fox scats from a low prevalence area, the specificity of the MC-PCR was higher, 0.999% (95% PCI 0.997–1). One reason for the lower estimate of the specificity in this study could be that the MC-PCR detects DNA from infected but non-infectious rodents eaten by foxes. When using MC-PCR in low prevalence areas or areas free from the parasite, a positive result in the MC-PCR should be regarded as a true positive.ConclusionThe sensitivity of the MC-PCR (0.88) was comparable to the sensitivity of SCT (0.83).

Evaluation of the Full Lambda and SVM Methods Capability to Extract Roads from Digital Images

Automatic extraction of information on ground using photogrammetry and remote sensing requires the formulation of human data and image data, so that, it must include all the content of the image. Complex structure of the various objects in the image leads to the challenges for doing this. So, choose the type of digital data and a good way to extract the desired effect is important in mapping accuracy. This study has investigated the semi-automated method of extraction of various types, including straight, spiral, intersection, urban and non-urban roads from satellite and aerial images. Data used included UltraCam aerial image, Worldview satellite image of non-urban area with a resolution of 0.5 m, and Quick-Bird images of Tehran province with a resolution of 0.61 m. In the proposed method, upon performing image segmentation by using Full lambda method, image classification has been done using SVM algorithm, and morphological operations are used to improve the quality of discover ways and remove noise and cover gaps. For images in which Full lambda method has high accuracy in image segmentation, therefore, the accuracy of the image classification is increased and extraction of the road from it has been done better. The average overall accuracy of over 81 percent and the average accuracy Kappa coefficient more than 78 percent in the image classification into two classes of road and non-road indicates very good capability of the system introduced for semi-automatic extraction of different roads.

Rapid and Semi-automated Extraction of Neuronal Cell Bodies and Nuclei from Electron Microscopy Image Stacks.

Connectomics-the study of how neurons wire together in the brain-is at the forefront of modern neuroscience research. However, many connectomics studies are limited by the time and precision needed to correctly segment large volumes of electron microscopy (EM) image data. We present here a semi-automated segmentation pipeline using freely available software that can significantly decrease segmentation time for extracting both nuclei and cell bodies from EM image volumes.

APPLICABILITY OF MULTI-SEASONAL X-BAND SAR IMAGERY FOR MULTIRESOLUTION SEGMENTATION: A CASE STUDY IN A RIPARIAN MIXED FOREST

Abstract. The increasing availability of synthetic aperture radar (SAR) data from a range of different sensors necessitates efficient methods for semi-automated information extraction at multiple spatial scales for different fields of application. The focus of the presented study is two-fold: 1) to evaluate the applicability of multi-temporal TerraSAR-X imagery for multiresolution segmentation, and 2) to identify suitable Scale Parameters through different weighing of different homogeneity criteria, mainly colour variance. Multiresolution segmentation was used for segmentation of multi-temporal TerraSAR-X imagery, and the ESP (Estimation of Scale Parameter) tool was used to identify suitable Scale Parameters for image segmentation. The validation of the segmentation results was performed using very high resolution WorldView-2 imagery and a reference map, which was created by an ecological expert. The results of multiresolution segmentation revealed that in the context of object-based image analysis the TerraSAR-X images are applicable for generating optimal image objects. Furthermore, ESP tool can be used as an indicator for estimation of Scale Parameter for multiresolution segmentation of TerraSAR-X imagery. Additionally, for more reliable results, this study suggests that the homogeneity criterion of colour, in a variance based segmentation algorithm, needs to be set to high values. Setting the shape/colour criteria to 0.005/0.995 or 0.00/1 led to the best results and to the creation of adequate image objects.

Workflow Optimization of the ViroSeqTM Human Immunodeficiency Virus-1 (HIV-1) Genotyping System

Background Current therapy guidelines recommend resistance testing to guide therapy in antiretroviral ARV treatment naive patients as well as patients with suboptimal virologic responses or virologic failure Objective This study evaluated workflow optimization and automation improvements to the ViroSeq HIV Genotyping System through the use of the semi automated extraction platforms Abbott Molecular Inc m sp and bioM eacute rieux Inc NucliSens easyMAG for sample extraction NanoDrop Spectrophotometer Thermo Scientific CA and Agilent Bioanalyzer Agilent Technologies Germany for amplicon quantitation and Applied Biosystems Instruments ABI Life Technologies Ca for increased sequencing throughput Table Methods Clinical plasma samples were processed in parallel with Viroseq HIV Genotyping System per manufacturer instructions along with above described automated options Resistance associated mutations from the different approaches were evaluated and assessed for clinical impact Results All samples tested in this study gave valid results regardless of the procedure used Samples extracted with m sp demonstrated resistance associated mutations in samples while complete drug resistance concordance was observed in samples Ninety one percent of the samples extracted with easyMAG had concordance at the nucleotide level and concordance for drug resistance mutations No apparent difference was observed in sequence quality between manual and semi automated extractions and comparable drug resistance profiles were obtained regardless of the extraction method Conclusion The ViroSeq HIV Genotyping System is compatible with the semi automated extraction systems alternative amplicon quantitation devices as well as with high throughput sequencing platform such as the ABI sequencer This study also indicated that the assay can accurately sequence HIV virus below copies mL Significant workflow and turnaround time advantages were observed in this study with the automation of the Viroseq HIV Genotyping System

Collocations and Grammatical Patterns in a Multilingual Online Term Bank

This article considers the importance of including various types of collocations in a terminological database, with the aim of making this information available to the user via the user interface. We refer specifically to the inclusion of empirical and phraseological collocations, and information on grammatical patterning. Attention is also given to provision of information on semantic prosody and semantic preferences — aspects which have been rather neglected in South African terminological databanks and language for special purposes (LSP) dictionaries. Various strategies for the effective semi-automatic extraction of collocational data from specialized corpora are explored. Possibilities regarding access to and presentation of collocational information to the user are briefly considered. It is argued that users should have direct access to collocational information, and that collocations should not only be accessible via the lemmatic address of the term appearing as part of the collocation. The research is done within the context of the establishment of an Open Access Resource Term Bank, which is developed as a pedagogical tool to support students whose language of learning and teaching is not the L1.

Pharmacogenetic comparison of CYP2D6 predictive and measured phenotypes in a South African cohort.

The relationship between genetic variation in CYP2D6 and variable drug response represents a potentially powerful pharmacogenetic tool. However, little is known regarding this relationship in the genetically diverse South African population. The aim was therefore to evaluate the relationship between predicted and measured CYP2D6 phenotype. An XL-PCR+Sequencing approach was used to determine CYP2D6 genotype in 100 healthy volunteers and phenotype was predicted using activity scores. With dextromethorphan as the probe drug, metabolic ratios served as a surrogate measure of in vivo CYP2D6 activity. Three-hour plasma metabolic ratios of dextrorphan/dextromethorphan were measured simultaneously using semi-automated online solid phase extraction coupled with tandem mass spectrometry. Partial adaptation of the activity score system demonstrated a strong association between genotype and phenotype, as illustrated by a kappa value of 0.792, inter-rater discrepancy of 0.051 and sensitivity of 72.7%. Predicted phenotype frequencies using the modified activity score were 1.3% for poor metabolisers (PM), 7.6% for intermediate metabolisers (IM) and 87.3% for extensive metabolisers (EM). Measured phenotype frequencies were 1.3% for PM, 13.9% for IM and 84.8% for EM. Comprehensive CYP2D6 genotyping reliably predicts CYP2D6 activity in this South African cohort and can be utilised as a valuable pharmacogenetic tool.

A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head

BackgroundMagnetic resonance imaging (MRI) is a well-developed technique in neuroscience. Limitations in applying MRI to rodent models of neuropsychiatric disorders include the large number of animals required to achieve statistical significance, and the paucity of automation tools for the critical early step in processing, brain extraction, which prepares brain images for alignment and voxel-wise statistics. New methodThis novel timesaving automation of template-based brain extraction (“skull-stripping”) is capable of quickly and reliably extracting the brain from large numbers of whole head images in a single step. The method is simple to install and requires minimal user interaction. ResultsThis method is equally applicable to different types of MR images. Results were evaluated with Dice and Jacquard similarity indices and compared in 3D surface projections with other stripping approaches. Statistical comparisons demonstrate that individual variation of brain volumes are preserved. Comparison with existing methodsA downloadable software package not otherwise available for extraction of brains from whole head images is included here. This software tool increases speed, can be used with an atlas or a template from within the dataset, and produces masks that need little further refinement. ConclusionsOur new automation can be applied to any MR dataset, since the starting point is a template mask generated specifically for that dataset. The method reliably and rapidly extracts brain images from whole head images, rendering them useable for subsequent analytical processing. This software tool will accelerate the exploitation of mouse models for the investigation of human brain disorders by MRI.