Automated real-time detection of tonic-clonic seizures using a wearable EMG device

DEFF Research Database (Denmark)

Beniczky, Sándor; Conradsen, Isa; Henning, Oliver

2018-01-01

OBJECTIVE: To determine the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) using a wearable surface EMG device. METHODS: We prospectively tested the technical performance and diagnostic accuracy of real-time seizure detection using a wearable surface EMG device....... The seizure detection algorithm and the cutoff values were prespecified. A total of 71 patients, referred to long-term video-EEG monitoring, on suspicion of GTCS, were recruited in 3 centers. Seizure detection was real-time and fully automated. The reference standard was the evaluation of video-EEG recordings...

A fully automated algorithm of baseline correction based on wavelet feature points and segment interpolation

Science.gov (United States)

Qian, Fang; Wu, Yihui; Hao, Peng

2017-11-01

Baseline correction is a very important part of pre-processing. Baseline in the spectrum signal can induce uneven amplitude shifts across different wavenumbers and lead to bad results. Therefore, these amplitude shifts should be compensated before further analysis. Many algorithms are used to remove baseline, however fully automated baseline correction is convenient in practical application. A fully automated algorithm based on wavelet feature points and segment interpolation (AWFPSI) is proposed. This algorithm finds feature points through continuous wavelet transformation and estimates baseline through segment interpolation. AWFPSI is compared with three commonly introduced fully automated and semi-automated algorithms, using simulated spectrum signal, visible spectrum signal and Raman spectrum signal. The results show that AWFPSI gives better accuracy and has the advantage of easy use.

Automated DNA electrophoresis, hybridization and detection

International Nuclear Information System (INIS)

Zapolski, E.J.; Gersten, D.M.; Golab, T.J.; Ledley, R.S.

1986-01-01

A fully automated, computer controlled system for nucleic acid hybridization analysis has been devised and constructed. In practice, DNA is digested with restriction endonuclease enzyme(s) and loaded into the system by pipette; 32 P-labelled nucleic acid probe(s) is loaded into the nine hybridization chambers. Instructions for all the steps in the automated process are specified by answering questions that appear on the computer screen at the start of the experiment. Subsequent steps are performed automatically. The system performs horizontal electrophoresis in agarose gel, fixed the fragments to a solid phase matrix, denatures, neutralizes, prehybridizes, hybridizes, washes, dries and detects the radioactivity according to the specifications given by the operator. The results, printed out at the end, give the positions on the matrix to which radioactivity remains hybridized following stringent washing

Fully automated gamma spectrometry gauge observing possible radioactive contamination of melting-shop samples

International Nuclear Information System (INIS)

Kroos, J.; Westkaemper, G.; Stein, J.

1999-01-01

At Salzgitter AG, several monitoring systems have been installed to check the scrap transport by rail and by car. At the moment, the scrap transport by ship is reloaded onto wagons for monitoring afterwards. In the future, a detection system will be mounted onto a crane for a direct check on scrap upon the departure of ship. Furthermore, at Salzgitter AG Central Chemical Laboratory, a fully automated gamma spectrometry gauge is installed in order to observe a possible radioactive contamination of the products. The gamma spectrometer is integrated into the automated OE spectrometry line for testing melting shop samples after performing the OE spectrometry. With this technique the specific activity of selected nuclides and dose rate will be determined. The activity observation is part of the release procedure. The corresponding measurement data are stored in a database for quality management reasons. (author)

Automated visual fruit detection for harvest estimation and robotic harvesting

OpenAIRE

Puttemans, Steven; Vanbrabant, Yasmin; Tits, Laurent; Goedemé, Toon

2016-01-01

Fully automated detection and localisation of fruit in orchards is a key component in creating automated robotic harvesting systems, a dream of many farmers around the world to cope with large production and personnel costs. In recent years a lot of research on this topic has been performed, using basic computer vision techniques, like colour based segmentation, as a suggested solution. When not using standard RGB cameras, research tends to resort to other sensors, like hyper spectral or 3D. ...

Fully Automated Volumetric Modulated Arc Therapy Plan Generation for Prostate Cancer Patients

International Nuclear Information System (INIS)

Voet, Peter W.J.; Dirkx, Maarten L.P.; Breedveld, Sebastiaan; Al-Mamgani, Abrahim; Incrocci, Luca; Heijmen, Ben J.M.

2014-01-01

Purpose: To develop and evaluate fully automated volumetric modulated arc therapy (VMAT) treatment planning for prostate cancer patients, avoiding manual trial-and-error tweaking of plan parameters by dosimetrists. Methods and Materials: A system was developed for fully automated generation of VMAT plans with our commercial clinical treatment planning system (TPS), linked to the in-house developed Erasmus-iCycle multicriterial optimizer for preoptimization. For 30 randomly selected patients, automatically generated VMAT plans (VMAT auto ) were compared with VMAT plans generated manually by 1 expert dosimetrist in the absence of time pressure (VMAT man ). For all treatment plans, planning target volume (PTV) coverage and sparing of organs-at-risk were quantified. Results: All generated plans were clinically acceptable and had similar PTV coverage (V 95%  > 99%). For VMAT auto and VMAT man plans, the organ-at-risk sparing was similar as well, although only the former plans were generated without any planning workload. Conclusions: Fully automated generation of high-quality VMAT plans for prostate cancer patients is feasible and has recently been implemented in our clinic

Rapid detection of enterovirus in cerebrospinal fluid by a fully-automated PCR assay is associated with improved management of aseptic meningitis in adult patients.

Science.gov (United States)

Giulieri, Stefano G; Chapuis-Taillard, Caroline; Manuel, Oriol; Hugli, Olivier; Pinget, Christophe; Wasserfallen, Jean-Blaise; Sahli, Roland; Jaton, Katia; Marchetti, Oscar; Meylan, Pascal

2015-01-01

Enterovirus (EV) is the most frequent cause of aseptic meningitis (AM). Lack of microbiological documentation results in unnecessary antimicrobial therapy and hospitalization. To assess the impact of rapid EV detection in cerebrospinal fluid (CSF) by a fully-automated PCR (GeneXpert EV assay, GXEA) on the management of AM. Observational study in adult patients with AM. Three groups were analyzed according to EV documentation in CSF: group A = no PCR or negative PCR (n=17), group B = positive real-time PCR (n = 20), and group C = positive GXEA (n = 22). Clinical, laboratory and health-care costs data were compared. Clinical characteristics were similar in the 3 groups. Median turn-around time of EV PCR decreased from 60 h (IQR (interquartile range) 44-87) in group B to 5h (IQR 4-11) in group C (p<0.0001). Median duration of antibiotics was 1 (IQR 0-6), 1 (0-1.9), and 0.5 days (single dose) in groups A, B, and C, respectively (p < 0.001). Median length of hospitalization was 4 days (2.5-7.5), 2 (1-3.7), and 0.5 (0.3-0.7), respectively (p < 0.001). Median hospitalization costs were $5458 (2676-6274) in group A, $2796 (2062-5726) in group B, and $921 (765-1230) in group C (p < 0.0001). Rapid EV detection in CSF by a fully-automated PCR improves management of AM by significantly reducing antibiotic use, hospitalization length and costs. Copyright © 2014 Elsevier B.V. All rights reserved.

Fully automated processing of fMRI data in SPM: from MRI scanner to PACS.

Science.gov (United States)

Maldjian, Joseph A; Baer, Aaron H; Kraft, Robert A; Laurienti, Paul J; Burdette, Jonathan H

2009-01-01

Here we describe the Wake Forest University Pipeline, a fully automated method for the processing of fMRI data using SPM. The method includes fully automated data transfer and archiving from the point of acquisition, real-time batch script generation, distributed grid processing, interface to SPM in MATLAB, error recovery and data provenance, DICOM conversion and PACS insertion. It has been used for automated processing of fMRI experiments, as well as for the clinical implementation of fMRI and spin-tag perfusion imaging. The pipeline requires no manual intervention, and can be extended to any studies requiring offline processing.

Fully automated gynecomastia quantification from low-dose chest CT

Science.gov (United States)

Liu, Shuang; Sonnenblick, Emily B.; Azour, Lea; Yankelevitz, David F.; Henschke, Claudia I.; Reeves, Anthony P.

2018-02-01

Gynecomastia is characterized by the enlargement of male breasts, which is a common and sometimes distressing condition found in over half of adult men over the age of 44. Although the majority of gynecomastia is physiologic or idiopathic, its occurrence may also associate with an extensive variety of underlying systemic disease or drug toxicity. With the recent large-scale implementation of annual lung cancer screening using low-dose chest CT (LDCT), gynecomastia is believed to be a frequent incidental finding on LDCT. A fully automated system for gynecomastia quantification from LDCT is presented in this paper. The whole breast region is first segmented using an anatomyorientated approach based on the propagation of pectoral muscle fronts in the vertical direction. The subareolar region is then localized, and the fibroglandular tissue within it is measured for the assessment of gynecomastia. The presented system was validated using 454 breast regions from non-contrast LDCT scans of 227 adult men. The ground truth was established by an experienced radiologist by classifying each breast into one of the five categorical scores. The automated measurements have been demonstrated to achieve promising performance for the gynecomastia diagnosis with the AUC of 0.86 for the ROC curve and have statistically significant Spearman correlation r=0.70 (p early detection as well as the treatment of both gynecomastia and the underlying medical problems, if any, that cause gynecomastia.

DEWS (DEep White matter hyperintensity Segmentation framework): A fully automated pipeline for detecting small deep white matter hyperintensities in migraineurs.

Science.gov (United States)

Park, Bo-Yong; Lee, Mi Ji; Lee, Seung-Hak; Cha, Jihoon; Chung, Chin-Sang; Kim, Sung Tae; Park, Hyunjin

2018-01-01

Migraineurs show an increased load of white matter hyperintensities (WMHs) and more rapid deep WMH progression. Previous methods for WMH segmentation have limited efficacy to detect small deep WMHs. We developed a new fully automated detection pipeline, DEWS (DEep White matter hyperintensity Segmentation framework), for small and superficially-located deep WMHs. A total of 148 non-elderly subjects with migraine were included in this study. The pipeline consists of three components: 1) white matter (WM) extraction, 2) WMH detection, and 3) false positive reduction. In WM extraction, we adjusted the WM mask to re-assign misclassified WMHs back to WM using many sequential low-level image processing steps. In WMH detection, the potential WMH clusters were detected using an intensity based threshold and region growing approach. For false positive reduction, the detected WMH clusters were classified into final WMHs and non-WMHs using the random forest (RF) classifier. Size, texture, and multi-scale deep features were used to train the RF classifier. DEWS successfully detected small deep WMHs with a high positive predictive value (PPV) of 0.98 and true positive rate (TPR) of 0.70 in the training and test sets. Similar performance of PPV (0.96) and TPR (0.68) was attained in the validation set. DEWS showed a superior performance in comparison with other methods. Our proposed pipeline is freely available online to help the research community in quantifying deep WMHs in non-elderly adults.

Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS.

Science.gov (United States)

Zarate, Erica; Boyle, Veronica; Rupprecht, Udo; Green, Saras; Villas-Boas, Silas G; Baker, Philip; Pinu, Farhana R

2016-12-29

Gas Chromatography-Mass Spectrometry (GC-MS) has long been used for metabolite profiling of a wide range of biological samples. Many derivatisation protocols are already available and among these, trimethylsilyl (TMS) derivatisation is one of the most widely used in metabolomics. However, most TMS methods rely on off-line derivatisation prior to GC-MS analysis. In the case of manual off-line TMS derivatisation, the derivative created is unstable, so reduction in recoveries occurs over time. Thus, derivatisation is carried out in small batches. Here, we present a fully automated TMS derivatisation protocol using robotic autosamplers and we also evaluate a commercial software, Maestro available from Gerstel GmbH. Because of automation, there was no waiting time of derivatised samples on the autosamplers, thus reducing degradation of unstable metabolites. Moreover, this method allowed us to overlap samples and improved throughputs. We compared data obtained from both manual and automated TMS methods performed on three different matrices, including standard mix, wine, and plasma samples. The automated TMS method showed better reproducibility and higher peak intensity for most of the identified metabolites than the manual derivatisation method. We also validated the automated method using 114 quality control plasma samples. Additionally, we showed that this online method was highly reproducible for most of the metabolites detected and identified (RSD TMS method has been applied to analyse a large number of complex plasma samples. Furthermore, we found that this method was highly applicable for routine metabolite profiling (both targeted and untargeted) in any metabolomics laboratory.

Participation through Automation: Fully Automated Critical PeakPricing in Commercial Buildings

Energy Technology Data Exchange (ETDEWEB)

Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Kiliccote,Sila; Linkugel, Eric

2006-06-20

California electric utilities have been exploring the use of dynamic critical peak prices (CPP) and other demand response programs to help reduce peaks in customer electric loads. CPP is a tariff design to promote demand response. Levels of automation in DR can be defined as follows: Manual Demand Response involves a potentially labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. Fully Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. The receipt of the external signal initiates pre-programmed demand response strategies. They refer to this as Auto-DR. This paper describes the development, testing, and results from automated CPP (Auto-CPP) as part of a utility project in California. The paper presents the project description and test methodology. This is followed by a discussion of Auto-DR strategies used in the field test buildings. They present a sample Auto-CPP load shape case study, and a selection of the Auto-CPP response data from September 29, 2005. If all twelve sites reached their maximum saving simultaneously, a total of approximately 2 MW of DR is available from these twelve sites that represent about two million ft{sup 2}. The average DR was about half that value, at about 1 MW. These savings translate to about 0.5 to 1.0 W/ft{sup 2} of demand reduction. They are continuing field demonstrations and economic evaluations to pursue increasing penetrations of automated DR that has demonstrated ability to provide a valuable DR resource for California.

Review: Behavioral signs of estrus and the potential of fully automated systems for detection of estrus in dairy cattle.

Science.gov (United States)

Reith, S; Hoy, S

2018-02-01

Efficient detection of estrus is a permanent challenge for successful reproductive performance in dairy cattle. In this context, comprehensive knowledge of estrus-related behaviors is fundamental to achieve optimal estrus detection rates. This review was designed to identify the characteristics of behavioral estrus as a necessary basis for developing strategies and technologies to improve the reproductive management on dairy farms. The focus is on secondary symptoms of estrus (mounting, activity, aggressive and agonistic behaviors) which seem more indicative than standing behavior. The consequences of management, housing conditions and cow- and environmental-related factors impacting expression and detection of estrus as well as their relative importance are described in order to increase efficiency and accuracy of estrus detection. As traditional estrus detection via visual observation is time-consuming and ineffective, there has been a considerable advancement of detection aids during the last 10 years. By now, a number of fully automated technologies including pressure sensing systems, activity meters, video cameras, recordings of vocalization as well as measurements of body temperature and milk progesterone concentration are available. These systems differ in many aspects regarding sustainability and efficiency as keys to their adoption for farm use. As being most practical for estrus detection a high priority - according to the current research - is given to the detection based on sensor-supported activity monitoring, especially accelerometer systems. Due to differences in individual intensity and duration of estrus multivariate analysis can support herd managers in determining the onset of estrus. Actually, there is increasing interest in investigating the potential of combining data of activity monitoring and information of several other methods, which may lead to the best results concerning sensitivity and specificity of detection. Future improvements will

Fully Automated Trimethylsilyl (TMS Derivatisation Protocol for Metabolite Profiling by GC-MS

Directory of Open Access Journals (Sweden)

Erica Zarate

2016-12-01

Full Text Available Gas Chromatography-Mass Spectrometry (GC-MS has long been used for metabolite profiling of a wide range of biological samples. Many derivatisation protocols are already available and among these, trimethylsilyl (TMS derivatisation is one of the most widely used in metabolomics. However, most TMS methods rely on off-line derivatisation prior to GC-MS analysis. In the case of manual off-line TMS derivatisation, the derivative created is unstable, so reduction in recoveries occurs over time. Thus, derivatisation is carried out in small batches. Here, we present a fully automated TMS derivatisation protocol using robotic autosamplers and we also evaluate a commercial software, Maestro available from Gerstel GmbH. Because of automation, there was no waiting time of derivatised samples on the autosamplers, thus reducing degradation of unstable metabolites. Moreover, this method allowed us to overlap samples and improved throughputs. We compared data obtained from both manual and automated TMS methods performed on three different matrices, including standard mix, wine, and plasma samples. The automated TMS method showed better reproducibility and higher peak intensity for most of the identified metabolites than the manual derivatisation method. We also validated the automated method using 114 quality control plasma samples. Additionally, we showed that this online method was highly reproducible for most of the metabolites detected and identified (RSD < 20 and specifically achieved excellent results for sugars, sugar alcohols, and some organic acids. To the very best of our knowledge, this is the first time that the automated TMS method has been applied to analyse a large number of complex plasma samples. Furthermore, we found that this method was highly applicable for routine metabolite profiling (both targeted and untargeted in any metabolomics laboratory.

A novel method to determine simultaneously methane production during in vitro gas production using fully automated equipment

NARCIS (Netherlands)

Pellikaan, W.F.; Hendriks, W.H.; Uwimanaa, G.; Bongers, L.J.G.M.; Becker, P.M.; Cone, J.W.

2011-01-01

An adaptation of fully automated gas production equipment was tested for its ability to simultaneously measure methane and total gas. The simultaneous measurement of gas production and gas composition was not possible using fully automated equipment, as the bottles should be kept closed during the

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

Science.gov (United States)

Wang, Xinggang; Yang, Wei; Weinreb, Jeffrey; Han, Juan; Li, Qiubai; Kong, Xiangchuang; Yan, Yongluan; Ke, Zan; Luo, Bo; Liu, Tao; Wang, Liang

2017-11-13

Prostate cancer (PCa) is a major cause of death since ancient time documented in Egyptian Ptolemaic mummy imaging. PCa detection is critical to personalized medicine and varies considerably under an MRI scan. 172 patients with 2,602 morphologic images (axial 2D T2-weighted imaging) of the prostate were obtained. A deep learning with deep convolutional neural network (DCNN) and a non-deep learning with SIFT image feature and bag-of-word (BoW), a representative method for image recognition and analysis, were used to distinguish pathologically confirmed PCa patients from prostate benign conditions (BCs) patients with prostatitis or prostate benign hyperplasia (BPH). In fully automated detection of PCa patients, deep learning had a statistically higher area under the receiver operating characteristics curve (AUC) than non-deep learning (P = 0.0007 deep learning method and 0.70 (95% CI 0.63-0.77) for non-deep learning method, respectively. Our results suggest that deep learning with DCNN is superior to non-deep learning with SIFT image feature and BoW model for fully automated PCa patients differentiation from prostate BCs patients. Our deep learning method is extensible to image modalities such as MR imaging, CT and PET of other organs.

A new fully automated TLD badge reader

International Nuclear Information System (INIS)

Kannan, S.; Ratna, P.; Kulkarni, M.S.

2003-01-01

At present personnel monitoring in India is being carried out using a number of manual and semiautomatic TLD badge Readers and the BARC TL dosimeter badge designed during 1970. Of late the manual TLD badge readers are almost completely replaced by semiautomatic readers with a number of performance improvements like use of hot gas heating to reduce the readout time considerably. PC based design with storage of glow curve for every dosimeter, on-line dose computation and printout of dose reports, etc. However the semiautomatic system suffers from the lack of a machine readable ID code on the badge and the physical design of the dosimeter card not readily compatible for automation. This paper describes a fully automated TLD badge Reader developed in the RSS Division, using a new TLD badge with machine readable ID code. The new PC based reader has a built-in reader for reading the ID code, in the form of an array of holes, on the dosimeter card. The reader has a number of self-diagnostic features to ensure a high degree of reliability. (author)

[18F]FMeNER-D2: Reliable fully-automated synthesis for visualization of the norepinephrine transporter

International Nuclear Information System (INIS)

Rami-Mark, Christina; Zhang, Ming-Rong; Mitterhauser, Markus; Lanzenberger, Rupert; Hacker, Marcus; Wadsak, Wolfgang

2013-01-01

Purpose: In neurodegenerative diseases and neuropsychiatric disorders dysregulation of the norepinephrine transporter (NET) has been reported. For visualization of NET availability and occupancy in the human brain PET imaging can be used. Therefore, selective NET-PET tracers with high affinity are required. Amongst these, [ 18 F]FMeNER-D2 is showing the best results so far. Furthermore, a reliable fully automated radiosynthesis is a prerequisite for successful application of PET-tracers. The aim of this work was the automation of [ 18 F]FMeNER-D2 radiolabelling for subsequent clinical use. The presented study comprises 25 automated large-scale syntheses, which were directly applied to healthy volunteers and adult patients suffering from attention deficit hyperactivity disorder (ADHD). Procedures: Synthesis of [ 18 F]FMeNER-D2 was automated within a Nuclear Interface Module. Starting from 20–30 GBq [ 18 F]fluoride, azeotropic drying, reaction with Br 2 CD 2 , distillation of 1-bromo-2-[ 18 F]fluoromethane-D2 ([ 18 F]BFM) and reaction of the pure [ 18 F]BFM with unprotected precursor NER were optimized and completely automated. HPLC purification and SPE procedure were completed, formulation and sterile filtration were achieved on-line and full quality control was performed. Results: Purified product was obtained in a fully automated synthesis in clinical scale allowing maximum radiation safety and routine production under GMP-like manner. So far, more than 25 fully automated syntheses were successfully performed, yielding 1.0–2.5 GBq of formulated [ 18 F]FMeNER-D2 with specific activities between 430 and 1707 GBq/μmol within 95 min total preparation time. Conclusions: A first fully automated [ 18 F]FMeNER-D2 synthesis was established, allowing routine production of this NET-PET tracer under maximum radiation safety and standardization

[18F]FMeNER-D2: reliable fully-automated synthesis for visualization of the norepinephrine transporter.

Science.gov (United States)

Rami-Mark, Christina; Zhang, Ming-Rong; Mitterhauser, Markus; Lanzenberger, Rupert; Hacker, Marcus; Wadsak, Wolfgang

2013-11-01

In neurodegenerative diseases and neuropsychiatric disorders dysregulation of the norepinephrine transporter (NET) has been reported. For visualization of NET availability and occupancy in the human brain PET imaging can be used. Therefore, selective NET-PET tracers with high affinity are required. Amongst these, [(18)F]FMeNER-D2 is showing the best results so far. Furthermore, a reliable fully automated radiosynthesis is a prerequisite for successful application of PET-tracers. The aim of this work was the automation of [(18)F]FMeNER-D2 radiolabelling for subsequent clinical use. The presented study comprises 25 automated large-scale syntheses, which were directly applied to healthy volunteers and adult patients suffering from attention deficit hyperactivity disorder (ADHD). Synthesis of [(18)F]FMeNER-D2 was automated within a Nuclear Interface Module. Starting from 20-30 GBq [(18)F]fluoride, azeotropic drying, reaction with Br2CD2, distillation of 1-bromo-2-[(18)F]fluoromethane-D2 ([(18)F]BFM) and reaction of the pure [(18)F]BFM with unprotected precursor NER were optimized and completely automated. HPLC purification and SPE procedure were completed, formulation and sterile filtration were achieved on-line and full quality control was performed. Purified product was obtained in a fully automated synthesis in clinical scale allowing maximum radiation safety and routine production under GMP-like manner. So far, more than 25 fully automated syntheses were successfully performed, yielding 1.0-2.5 GBq of formulated [(18)F]FMeNER-D2 with specific activities between 430 and 1707 GBq/μmol within 95 min total preparation time. A first fully automated [(18)F]FMeNER-D2 synthesis was established, allowing routine production of this NET-PET tracer under maximum radiation safety and standardization. © 2013.

A fully automated microfluidic femtosecond laser axotomy platform for nerve regeneration studies in C. elegans.

Science.gov (United States)

Gokce, Sertan Kutal; Guo, Samuel X; Ghorashian, Navid; Everett, W Neil; Jarrell, Travis; Kottek, Aubri; Bovik, Alan C; Ben-Yakar, Adela

2014-01-01

Femtosecond laser nanosurgery has been widely accepted as an axonal injury model, enabling nerve regeneration studies in the small model organism, Caenorhabditis elegans. To overcome the time limitations of manual worm handling techniques, automation and new immobilization technologies must be adopted to improve throughput in these studies. While new microfluidic immobilization techniques have been developed that promise to reduce the time required for axotomies, there is a need for automated procedures to minimize the required amount of human intervention and accelerate the axotomy processes crucial for high-throughput. Here, we report a fully automated microfluidic platform for performing laser axotomies of fluorescently tagged neurons in living Caenorhabditis elegans. The presented automation process reduces the time required to perform axotomies within individual worms to ∼17 s/worm, at least one order of magnitude faster than manual approaches. The full automation is achieved with a unique chip design and an operation sequence that is fully computer controlled and synchronized with efficient and accurate image processing algorithms. The microfluidic device includes a T-shaped architecture and three-dimensional microfluidic interconnects to serially transport, position, and immobilize worms. The image processing algorithms can identify and precisely position axons targeted for ablation. There were no statistically significant differences observed in reconnection probabilities between axotomies carried out with the automated system and those performed manually with anesthetics. The overall success rate of automated axotomies was 67.4±3.2% of the cases (236/350) at an average processing rate of 17.0±2.4 s. This fully automated platform establishes a promising methodology for prospective genome-wide screening of nerve regeneration in C. elegans in a truly high-throughput manner.

Breast Density Estimation with Fully Automated Volumetric Method: Comparison to Radiologists' Assessment by BI-RADS Categories.

Science.gov (United States)

Singh, Tulika; Sharma, Madhurima; Singla, Veenu; Khandelwal, Niranjan

2016-01-01

The objective of our study was to calculate mammographic breast density with a fully automated volumetric breast density measurement method and to compare it to breast imaging reporting and data system (BI-RADS) breast density categories assigned by two radiologists. A total of 476 full-field digital mammography examinations with standard mediolateral oblique and craniocaudal views were evaluated by two blinded radiologists and BI-RADS density categories were assigned. Using a fully automated software, mean fibroglandular tissue volume, mean breast volume, and mean volumetric breast density were calculated. Based on percentage volumetric breast density, a volumetric density grade was assigned from 1 to 4. The weighted overall kappa was 0.895 (almost perfect agreement) for the two radiologists' BI-RADS density estimates. A statistically significant difference was seen in mean volumetric breast density among the BI-RADS density categories. With increased BI-RADS density category, increase in mean volumetric breast density was also seen (P BI-RADS categories and volumetric density grading by fully automated software (ρ = 0.728, P BI-RADS density category by two observers showed fair agreement (κ = 0.398 and 0.388, respectively). In our study, a good correlation was seen between density grading using fully automated volumetric method and density grading using BI-RADS density categories assigned by the two radiologists. Thus, the fully automated volumetric method may be used to quantify breast density on routine mammography. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Improved protein hydrogen/deuterium exchange mass spectrometry platform with fully automated data processing.

Science.gov (United States)

Zhang, Zhongqi; Zhang, Aming; Xiao, Gang

2012-06-05

Protein hydrogen/deuterium exchange (HDX) followed by protease digestion and mass spectrometric (MS) analysis is accepted as a standard method for studying protein conformation and conformational dynamics. In this article, an improved HDX MS platform with fully automated data processing is described. The platform significantly reduces systematic and random errors in the measurement by introducing two types of corrections in HDX data analysis. First, a mixture of short peptides with fast HDX rates is introduced as internal standards to adjust the variations in the extent of back exchange from run to run. Second, a designed unique peptide (PPPI) with slow intrinsic HDX rate is employed as another internal standard to reflect the possible differences in protein intrinsic HDX rates when protein conformations at different solution conditions are compared. HDX data processing is achieved with a comprehensive HDX model to simulate the deuterium labeling and back exchange process. The HDX model is implemented into the in-house developed software MassAnalyzer and enables fully unattended analysis of the entire protein HDX MS data set starting from ion detection and peptide identification to final processed HDX output, typically within 1 day. The final output of the automated data processing is a set (or the average) of the most possible protection factors for each backbone amide hydrogen. The utility of the HDX MS platform is demonstrated by exploring the conformational transition of a monoclonal antibody by increasing concentrations of guanidine.

Development of a fully automated online mixing system for SAXS protein structure analysis

DEFF Research Database (Denmark)

Nielsen, Søren Skou; Arleth, Lise

2010-01-01

This thesis presents the development of an automated high-throughput mixing and exposure system for Small-Angle Scattering analysis on a synchrotron using polymer microfluidics. Software and hardware for both automated mixing, exposure control on a beamline and automated data reduction...... and preliminary analysis is presented. Three mixing systems that have been the corner stones of the development process are presented including a fully functioning high-throughput microfluidic system that is able to produce and expose 36 mixed samples per hour using 30 μL of sample volume. The system is tested...

Comparison of semi-automated center-dot and fully automated endothelial cell analyses from specular microscopy images.

Science.gov (United States)

Maruoka, Sachiko; Nakakura, Shunsuke; Matsuo, Naoko; Yoshitomi, Kayo; Katakami, Chikako; Tabuchi, Hitoshi; Chikama, Taiichiro; Kiuchi, Yoshiaki

2017-10-30

To evaluate two specular microscopy analysis methods across different endothelial cell densities (ECDs). Endothelial images of one eye from each of 45 patients were taken by using three different specular microscopes (three replicates each). To determine the consistency of the center-dot method, we compared SP-6000 and SP-2000P images. CME-530 and SP-6000 images were compared to assess the consistency of the fully automated method. The SP-6000 images from the two methods were compared. Intraclass correlation coefficients (ICCs) for the three measurements were calculated, and parametric multiple comparisons tests and Bland-Altman analysis were performed. The ECD mean value was 2425 ± 883 (range 516-3707) cells/mm 2 . ICC values were > 0.9 for all three microscopes for ECD, but the coefficients of variation (CVs) were 0.3-0.6. For ECD measurements, Bland-Altman analysis revealed that the mean difference was 42 cells/mm 2 between the SP-2000P and SP-6000 for the center-dot method; 57 cells/mm 2 between the SP-6000 measurements from both methods; and -5 cells/mm 2 between the SP-6000 and CME-530 for the fully automated method (95% limits of agreement: - 201 to 284 cell/mm 2 , - 410 to 522 cells/mm 2 , and - 327 to 318 cells/mm 2 , respectively). For CV measurements, the mean differences were - 3, - 12, and 13% (95% limits of agreement - 18 to 11, - 26 to 2, and - 5 to 32%, respectively). Despite using three replicate measurements, the precision of the center-dot method with the SP-2000P and SP-6000 software was only ± 10% for ECD data and was even worse for the fully automated method. Japan Clinical Trials Register ( http://www.umin.ac.jp/ctr/index/htm9 ) number UMIN 000015236.

A Fully Automated Penumbra Segmentation Tool

DEFF Research Database (Denmark)

Nagenthiraja, Kartheeban; Ribe, Lars Riisgaard; Hougaard, Kristina Dupont

2012-01-01

Introduction: Perfusion- and diffusion weighted MRI (PWI/DWI) is widely used to select patients who are likely to benefit from recanalization therapy. The visual identification of PWI-DWI-mismatch tissue depends strongly on the observer, prompting a need for software, which estimates potentially...... salavageable tissue, quickly and accurately. We present a fully Automated Penumbra Segmentation (APS) algorithm using PWI and DWI images. We compare automatically generated PWI-DWI mismatch mask to mask outlined manually by experts, in 168 patients. Method: The algorithm initially identifies PWI lesions......) at 600∙10-6 mm2/sec. Due to the nature of thresholding, the ADC mask overestimates the DWI lesion volume and consequently we initialized level-set algorithm on DWI image with ADC mask as prior knowledge. Combining the PWI and inverted DWI mask then yield the PWI-DWI mismatch mask. Four expert raters...

[{sup 18}F]FMeNER-D2: Reliable fully-automated synthesis for visualization of the norepinephrine transporter

Energy Technology Data Exchange (ETDEWEB)

Rami-Mark, Christina [Radiochemistry and Biomarker Development Unit, Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna (Austria); Department of Inorganic Chemistry, University of Vienna (Austria); Zhang, Ming-Rong [Molecular Imaging Center, National Institute of Radiological Sciences, Chiba (Japan); Mitterhauser, Markus [Radiochemistry and Biomarker Development Unit, Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna (Austria); Hospital Pharmacy of the General Hospital of Vienna (Austria); Lanzenberger, Rupert [Department of Psychiatry and Psychotherapy, Medical University of Vienna (Austria); Hacker, Marcus [Radiochemistry and Biomarker Development Unit, Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna (Austria); Wadsak, Wolfgang [Radiochemistry and Biomarker Development Unit, Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna (Austria); Department of Inorganic Chemistry, University of Vienna (Austria)

2013-11-15

Purpose: In neurodegenerative diseases and neuropsychiatric disorders dysregulation of the norepinephrine transporter (NET) has been reported. For visualization of NET availability and occupancy in the human brain PET imaging can be used. Therefore, selective NET-PET tracers with high affinity are required. Amongst these, [{sup 18}F]FMeNER-D2 is showing the best results so far. Furthermore, a reliable fully automated radiosynthesis is a prerequisite for successful application of PET-tracers. The aim of this work was the automation of [{sup 18}F]FMeNER-D2 radiolabelling for subsequent clinical use. The presented study comprises 25 automated large-scale syntheses, which were directly applied to healthy volunteers and adult patients suffering from attention deficit hyperactivity disorder (ADHD). Procedures: Synthesis of [{sup 18}F]FMeNER-D2 was automated within a Nuclear Interface Module. Starting from 20–30 GBq [{sup 18}F]fluoride, azeotropic drying, reaction with Br{sub 2}CD{sub 2}, distillation of 1-bromo-2-[{sup 18}F]fluoromethane-D2 ([{sup 18}F]BFM) and reaction of the pure [{sup 18}F]BFM with unprotected precursor NER were optimized and completely automated. HPLC purification and SPE procedure were completed, formulation and sterile filtration were achieved on-line and full quality control was performed. Results: Purified product was obtained in a fully automated synthesis in clinical scale allowing maximum radiation safety and routine production under GMP-like manner. So far, more than 25 fully automated syntheses were successfully performed, yielding 1.0–2.5 GBq of formulated [{sup 18}F]FMeNER-D2 with specific activities between 430 and 1707 GBq/μmol within 95 min total preparation time. Conclusions: A first fully automated [{sup 18}F]FMeNER-D2 synthesis was established, allowing routine production of this NET-PET tracer under maximum radiation safety and standardization.

How a Fully Automated eHealth Program Simulates Three Therapeutic Processes: A Case Study.

Science.gov (United States)

Holter, Marianne T S; Johansen, Ayna; Brendryen, Håvar

2016-06-28

eHealth programs may be better understood by breaking down the components of one particular program and discussing its potential for interactivity and tailoring in regard to concepts from face-to-face counseling. In the search for the efficacious elements within eHealth programs, it is important to understand how a program using lapse management may simultaneously support working alliance, internalization of motivation, and behavior maintenance. These processes have been applied to fully automated eHealth programs individually. However, given their significance in face-to-face counseling, it may be important to simulate the processes simultaneously in interactive, tailored programs. We propose a theoretical model for how fully automated behavior change eHealth programs may be more effective by simulating a therapist's support of a working alliance, internalization of motivation, and managing lapses. We show how the model is derived from theory and its application to Endre, a fully automated smoking cessation program that engages the user in several "counseling sessions" about quitting. A descriptive case study based on tools from the intervention mapping protocol shows how each therapeutic process is simulated. The program supports the user's working alliance through alliance factors, the nonembodied relational agent Endre and computerized motivational interviewing. Computerized motivational interviewing also supports internalized motivation to quit, whereas a lapse management component responds to lapses. The description operationalizes working alliance, internalization of motivation, and managing lapses, in terms of eHealth support of smoking cessation. A program may simulate working alliance, internalization of motivation, and lapse management through interactivity and individual tailoring, potentially making fully automated eHealth behavior change programs more effective.

Fully Automated Deep Learning System for Bone Age Assessment.

Science.gov (United States)

Lee, Hyunkwang; Tajmir, Shahein; Lee, Jenny; Zissen, Maurice; Yeshiwas, Bethel Ayele; Alkasab, Tarik K; Choy, Garry; Do, Synho

2017-08-01

Skeletal maturity progresses through discrete phases, a fact that is used routinely in pediatrics where bone age assessments (BAAs) are compared to chronological age in the evaluation of endocrine and metabolic disorders. While central to many disease evaluations, little has changed to improve the tedious process since its introduction in 1950. In this study, we propose a fully automated deep learning pipeline to segment a region of interest, standardize and preprocess input radiographs, and perform BAA. Our models use an ImageNet pretrained, fine-tuned convolutional neural network (CNN) to achieve 57.32 and 61.40% accuracies for the female and male cohorts on our held-out test images. Female test radiographs were assigned a BAA within 1 year 90.39% and within 2 years 98.11% of the time. Male test radiographs were assigned 94.18% within 1 year and 99.00% within 2 years. Using the input occlusion method, attention maps were created which reveal what features the trained model uses to perform BAA. These correspond to what human experts look at when manually performing BAA. Finally, the fully automated BAA system was deployed in the clinical environment as a decision supporting system for more accurate and efficient BAAs at much faster interpretation time (<2 s) than the conventional method.

AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery

International Nuclear Information System (INIS)

Tsai, Yingssu; McPhillips, Scott E.; González, Ana; McPhillips, Timothy M.; Zinn, Daniel; Cohen, Aina E.; Feese, Michael D.; Bushnell, David; Tiefenbrunn, Theresa; Stout, C. David; Ludaescher, Bertram; Hedman, Britt; Hodgson, Keith O.; Soltis, S. Michael

2013-01-01

New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully

Fully Automated Detection of Corticospinal Tract Damage in Chronic Stroke Patients

Directory of Open Access Journals (Sweden)

Ming Yang

2014-01-01

Full Text Available Structural integrity of the corticospinal tract (CST after stroke is closely linked to the degree of motor impairment. However, current methods for measurement of fractional atrophy (FA of CST based on region of interest (ROI are time-consuming and open to bias. Here, we used tract-based spatial statistics (TBSS together with a CST template with healthy volunteers to quantify structural integrity of CST automatically. Two groups of patients after ischemic stroke were enrolled, group 1 (10 patients, 7 men, and Fugl-Meyer assessment (FMA scores ⩽ 50 and group 2 (12 patients, 12 men, and FMA scores = 100. CST of FAipsi, FAcontra, and FAratio was compared between the two groups. Relative to group 2, FA was decreased in group 1 in the ipsilesional CST (P<0.01, as well as the FAratio (P<0.01. There was no significant difference between the two subgroups in the contralesional CST (P=0.23. Compared with contralesional CST, FA of ipsilesional CST decreased in group 1 (P<0.01. These results suggest that the automated method used in our study could detect a surrogate biomarker to quantify the CST after stroke, which would facilitate implementation of clinical practice.

FULLY AUTOMATED IMAGE ORIENTATION IN THE ABSENCE OF TARGETS

Directory of Open Access Journals (Sweden)

C. Stamatopoulos

2012-07-01

Full Text Available Automated close-range photogrammetric network orientation has traditionally been associated with the use of coded targets in the object space to allow for an initial relative orientation (RO and subsequent spatial resection of the images. Over the past decade, automated orientation via feature-based matching (FBM techniques has attracted renewed research attention in both the photogrammetry and computer vision (CV communities. This is largely due to advances made towards the goal of automated relative orientation of multi-image networks covering untargetted (markerless objects. There are now a number of CV-based algorithms, with accompanying open-source software, that can achieve multi-image orientation within narrow-baseline networks. From a photogrammetric standpoint, the results are typically disappointing as the metric integrity of the resulting models is generally poor, or even unknown, while the number of outliers within the image matching and triangulation is large, and generally too large to allow relative orientation (RO via the commonly used coplanarity equations. On the other hand, there are few examples within the photogrammetric research field of automated markerless camera calibration to metric tolerances, and these too are restricted to narrow-baseline, low-convergence imaging geometry. The objective addressed in this paper is markerless automatic multi-image orientation, maintaining metric integrity, within networks that incorporate wide-baseline imagery. By wide-baseline we imply convergent multi-image configurations with convergence angles of up to around 90°. An associated aim is provision of a fast, fully automated process, which can be performed without user intervention. For this purpose, various algorithms require optimisation to allow parallel processing utilising multiple PC cores and graphics processing units (GPUs.

Validation of Fully Automated VMAT Plan Generation for Library-Based Plan-of-the-Day Cervical Cancer Radiotherapy

OpenAIRE

Sharfo, Abdul Wahab M.; Breedveld, Sebastiaan; Voet, Peter W. J.; Heijkoop, Sabrina T.; Mens, Jan-Willem M.; Hoogeman, Mischa S.; Heijmen, Ben J. M.

2016-01-01

textabstractPurpose: To develop and validate fully automated generation of VMAT plan-libraries for plan-of-the-day adaptive radiotherapy in locally-advanced cervical cancer. Material and Methods: Our framework for fully automated treatment plan generation (Erasmus-iCycle) was adapted to create dual-arc VMAT treatment plan libraries for cervical cancer patients. For each of 34 patients, automatically generated VMAT plans (autoVMAT) were compared to manually generated, clinically delivered 9-be...

Association between fully automated MRI-based volumetry of different brain regions and neuropsychological test performance in patients with amnestic mild cognitive impairment and Alzheimer's disease.

Science.gov (United States)

Arlt, Sönke; Buchert, Ralph; Spies, Lothar; Eichenlaub, Martin; Lehmbeck, Jan T; Jahn, Holger

2013-06-01

Fully automated magnetic resonance imaging (MRI)-based volumetry may serve as biomarker for the diagnosis in patients with mild cognitive impairment (MCI) or dementia. We aimed at investigating the relation between fully automated MRI-based volumetric measures and neuropsychological test performance in amnestic MCI and patients with mild dementia due to Alzheimer's disease (AD) in a cross-sectional and longitudinal study. In order to assess a possible prognostic value of fully automated MRI-based volumetry for future cognitive performance, the rate of change of neuropsychological test performance over time was also tested for its correlation with fully automated MRI-based volumetry at baseline. In 50 subjects, 18 with amnestic MCI, 21 with mild AD, and 11 controls, neuropsychological testing and T1-weighted MRI were performed at baseline and at a mean follow-up interval of 2.1 ± 0.5 years (n = 19). Fully automated MRI volumetry of the grey matter volume (GMV) was performed using a combined stereotactic normalisation and segmentation approach as provided by SPM8 and a set of pre-defined binary lobe masks. Left and right hippocampus masks were derived from probabilistic cytoarchitectonic maps. Volumes of the inner and outer liquor space were also determined automatically from the MRI. Pearson's test was used for the correlation analyses. Left hippocampal GMV was significantly correlated with performance in memory tasks, and left temporal GMV was related to performance in language tasks. Bilateral frontal, parietal and occipital GMVs were correlated to performance in neuropsychological tests comprising multiple domains. Rate of GMV change in the left hippocampus was correlated with decline of performance in the Boston Naming Test (BNT), Mini-Mental Status Examination, and trail making test B (TMT-B). The decrease of BNT and TMT-A performance over time correlated with the loss of grey matter in multiple brain regions. We conclude that fully automated MRI

Fully automated MR liver volumetry using watershed segmentation coupled with active contouring.

Science.gov (United States)

Huynh, Hieu Trung; Le-Trong, Ngoc; Bao, Pham The; Oto, Aytek; Suzuki, Kenji

2017-02-01

Our purpose is to develop a fully automated scheme for liver volume measurement in abdominal MR images, without requiring any user input or interaction. The proposed scheme is fully automatic for liver volumetry from 3D abdominal MR images, and it consists of three main stages: preprocessing, rough liver shape generation, and liver extraction. The preprocessing stage reduced noise and enhanced the liver boundaries in 3D abdominal MR images. The rough liver shape was revealed fully automatically by using the watershed segmentation, thresholding transform, morphological operations, and statistical properties of the liver. An active contour model was applied to refine the rough liver shape to precisely obtain the liver boundaries. The liver volumes calculated by the proposed scheme were compared to the "gold standard" references which were estimated by an expert abdominal radiologist. The liver volumes computed by using our developed scheme excellently agreed (Intra-class correlation coefficient was 0.94) with the "gold standard" manual volumes by the radiologist in the evaluation with 27 cases from multiple medical centers. The running time was 8.4 min per case on average. We developed a fully automated liver volumetry scheme in MR, which does not require any interaction by users. It was evaluated with cases from multiple medical centers. The liver volumetry performance of our developed system was comparable to that of the gold standard manual volumetry, and it saved radiologists' time for manual liver volumetry of 24.7 min per case.

Current advances and strategies towards fully automated sample preparation for regulated LC-MS/MS bioanalysis.

Science.gov (United States)

Zheng, Naiyu; Jiang, Hao; Zeng, Jianing

2014-09-01

Robotic liquid handlers (RLHs) have been widely used in automated sample preparation for liquid chromatography-tandem mass spectrometry (LC-MS/MS) bioanalysis. Automated sample preparation for regulated bioanalysis offers significantly higher assay efficiency, better data quality and potential bioanalytical cost-savings. For RLHs that are used for regulated bioanalysis, there are additional requirements, including 21 CFR Part 11 compliance, software validation, system qualification, calibration verification and proper maintenance. This article reviews recent advances in automated sample preparation for regulated bioanalysis in the last 5 years. Specifically, it covers the following aspects: regulated bioanalysis requirements, recent advances in automation hardware and software development, sample extraction workflow simplification, strategies towards fully automated sample extraction, and best practices in automated sample preparation for regulated bioanalysis.

Feasibility of Commercially Available, Fully Automated Hepatic CT Volumetry for Assessing Both Total and Territorial Liver Volumes in Liver Transplantation

Energy Technology Data Exchange (ETDEWEB)

Shin, Cheong Il; Kim, Se Hyung; Rhim, Jung Hyo; Yi, Nam Joon; Suh, Kyung Suk; Lee, Jeong Min; Han, Joon Koo; Choi, Byung Ihn [Seoul National University Hospital, Seoul (Korea, Republic of)

2013-02-15

To assess the feasibility of commercially-available, fully automated hepatic CT volumetry for measuring both total and territorial liver volumes by comparing with interactive manual volumetry and measured ex-vivo liver volume. For the assessment of total and territorial liver volume, portal phase CT images of 77 recipients and 107 donors who donated right hemiliver were used. Liver volume was measured using both the fully automated and interactive manual methods with Advanced Liver Analysis software. The quality of the automated segmentation was graded on a 4-point scale. Grading was performed by two radiologists in consensus. For the cases with excellent-to-good quality, the accuracy of automated volumetry was compared with interactive manual volumetry and measured ex-vivo liver volume which was converted from weight using analysis of variance test and Pearson's or Spearman correlation test. Processing time for both automated and interactive manual methods was also compared. Excellent-to-good quality of automated segmentation for total liver and right hemiliver was achieved in 57.1% (44/77) and 17.8% (19/107), respectively. For both total and right hemiliver volumes, there were no significant differences among automated, manual, and ex-vivo volumes except between automate volume and manual volume of the total liver (p = 0.011). There were good correlations between automate volume and ex-vivo liver volume ({gamma}= 0.637 for total liver and {gamma}= 0.767 for right hemiliver). Both correlation coefficients were higher than those with manual method. Fully automated volumetry required significantly less time than interactive manual method (total liver: 48.6 sec vs. 53.2 sec, right hemiliver: 182 sec vs. 244.5 sec). Fully automated hepatic CT volumetry is feasible and time-efficient for total liver volume measurement. However, its usefulness for territorial liver volumetry needs to be improved.

Feasibility of Commercially Available, Fully Automated Hepatic CT Volumetry for Assessing Both Total and Territorial Liver Volumes in Liver Transplantation

International Nuclear Information System (INIS)

Shin, Cheong Il; Kim, Se Hyung; Rhim, Jung Hyo; Yi, Nam Joon; Suh, Kyung Suk; Lee, Jeong Min; Han, Joon Koo; Choi, Byung Ihn

2013-01-01

To assess the feasibility of commercially-available, fully automated hepatic CT volumetry for measuring both total and territorial liver volumes by comparing with interactive manual volumetry and measured ex-vivo liver volume. For the assessment of total and territorial liver volume, portal phase CT images of 77 recipients and 107 donors who donated right hemiliver were used. Liver volume was measured using both the fully automated and interactive manual methods with Advanced Liver Analysis software. The quality of the automated segmentation was graded on a 4-point scale. Grading was performed by two radiologists in consensus. For the cases with excellent-to-good quality, the accuracy of automated volumetry was compared with interactive manual volumetry and measured ex-vivo liver volume which was converted from weight using analysis of variance test and Pearson's or Spearman correlation test. Processing time for both automated and interactive manual methods was also compared. Excellent-to-good quality of automated segmentation for total liver and right hemiliver was achieved in 57.1% (44/77) and 17.8% (19/107), respectively. For both total and right hemiliver volumes, there were no significant differences among automated, manual, and ex-vivo volumes except between automate volume and manual volume of the total liver (p = 0.011). There were good correlations between automate volume and ex-vivo liver volume (γ= 0.637 for total liver and γ= 0.767 for right hemiliver). Both correlation coefficients were higher than those with manual method. Fully automated volumetry required significantly less time than interactive manual method (total liver: 48.6 sec vs. 53.2 sec, right hemiliver: 182 sec vs. 244.5 sec). Fully automated hepatic CT volumetry is feasible and time-efficient for total liver volume measurement. However, its usefulness for territorial liver volumetry needs to be improved.

Development of a Fully-Automated Monte Carlo Burnup Code Monteburns

International Nuclear Information System (INIS)

Poston, D.I.; Trellue, H.R.

1999-01-01

Several computer codes have been developed to perform nuclear burnup calculations over the past few decades. In addition, because of advances in computer technology, it recently has become more desirable to use Monte Carlo techniques for such problems. Monte Carlo techniques generally offer two distinct advantages over discrete ordinate methods: (1) the use of continuous energy cross sections and (2) the ability to model detailed, complex, three-dimensional (3-D) geometries. These advantages allow more accurate burnup results to be obtained, provided that the user possesses the required computing power (which is required for discrete ordinate methods as well). Several linkage codes have been written that combine a Monte Carlo N-particle transport code (such as MCNP TM ) with a radioactive decay and burnup code. This paper describes one such code that was written at Los Alamos National Laboratory: monteburns. Monteburns links MCNP with the isotope generation and depletion code ORIGEN2. The basis for the development of monteburns was the need for a fully automated code that could perform accurate burnup (and other) calculations for any 3-D system (accelerator-driven or a full reactor core). Before the initial development of monteburns, a list of desired attributes was made and is given below. o The code should be fully automated (that is, after the input is set up, no further user interaction is required). . The code should allow for the irradiation of several materials concurrently (each material is evaluated collectively in MCNP and burned separately in 0RIGEN2). o The code should allow the transfer of materials (shuffling) between regions in MCNP. . The code should allow any materials to be added or removed before, during, or after each step in an automated fashion. . The code should not require the user to provide input for 0RIGEN2 and should have minimal MCNP input file requirements (other than a working MCNP deck). . The code should be relatively easy to use

Development of Fully Automated Low-Cost Immunoassay System for Research Applications.

Science.gov (United States)

Wang, Guochun; Das, Champak; Ledden, Bradley; Sun, Qian; Nguyen, Chien

2017-10-01

Enzyme-linked immunosorbent assay (ELISA) automation for routine operation in a small research environment would be very attractive. A portable fully automated low-cost immunoassay system was designed, developed, and evaluated with several protein analytes. It features disposable capillary columns as the reaction sites and uses real-time calibration for improved accuracy. It reduces the overall assay time to less than 75 min with the ability of easy adaptation of new testing targets. The running cost is extremely low due to the nature of automation, as well as reduced material requirements. Details about system configuration, components selection, disposable fabrication, system assembly, and operation are reported. The performance of the system was initially established with a rabbit immunoglobulin G (IgG) assay, and an example of assay adaptation with an interleukin 6 (IL6) assay is shown. This system is ideal for research use, but could work for broader testing applications with further optimization.

A fully automated contour detection algorithm the preliminary step for scatter and attenuation compensation in SPECT

International Nuclear Information System (INIS)

Younes, R.B.; Mas, J.; Bidet, R.

1988-01-01

Contour detection is an important step in information extraction from nuclear medicine images. In order to perform accurate quantitative studies in single photon emission computed tomography (SPECT) a new procedure is described which can rapidly derive the best fit contour of an attenuated medium. Some authors evaluate the influence of the detected contour on the reconstructed images with various attenuation correction techniques. Most of the methods are strongly affected by inaccurately detected contours. This approach uses the Compton window to redetermine the convex contour: It seems to be simpler and more practical in clinical SPECT studies. The main advantages of this procedure are the high speed of computation, the accuracy of the contour found and the programme's automation. Results obtained using computer simulated and real phantoms or clinical studies demonstrate the reliability of the present algorithm. (orig.)

Photochemical-chemiluminometric determination of aldicarb in a fully automated multicommutation based flow-assembly

International Nuclear Information System (INIS)

Palomeque, M.; Garcia Bautista, J.A.; Catala Icardo, M.; Garcia Mateo, J.V.; Martinez Calatayud, J.

2004-01-01

A sensitive and fully automated method for determination of aldicarb in technical formulations (Temik) and mineral waters is proposed. The automation of the flow-assembly is based on the multicommutation approach, which uses a set of solenoid valves acting as independent switchers. The operating cycle for obtaining a typical analytical transient signal can be easily programmed by means of a home-made software running in the Windows environment. The manifold is provided with a photoreactor consisting of a 150 cm long x 0.8 mm i.d. piece of PTFE tubing coiled around a 20 W low-pressure mercury lamp. The determination of aldicarb is performed on the basis of the iron(III) catalytic mineralization of the pesticide by UV irradiation (150 s), and the chemiluminescent (CL) behavior of the photodegradated pesticide in presence of potassium permanganate and quinine sulphate as sensitizer. UV irradiation of aldicarb turns the very week chemiluminescent pesticide into a strongly chemiluminescent photoproduct. The method is linear over the range 2.2-100.0 μg l -1 of aldicarb; the limit of detection is 0.069 μg l -1 ; the reproducibility (as the R.S.D. of 20 peaks of a 24 μg l -1 solution) is 3.7% and the sample throughput is 17 h -1

The future of fully automated vehicles : opportunities for vehicle- and ride-sharing, with cost and emissions savings.

Science.gov (United States)

2014-08-01

Fully automated or autonomous vehicles (AVs) hold great promise for the future of transportation. By 2020 : Google, auto manufacturers and other technology providers intend to introduce self-driving cars to the public with : either limited or fully a...

Improved automated lumen contour detection by novel multifrequency processing algorithm with current intravascular ultrasound system.

Science.gov (United States)

Kume, Teruyoshi; Kim, Byeong-Keuk; Waseda, Katsuhisa; Sathyanarayana, Shashidhar; Li, Wenguang; Teo, Tat-Jin; Yock, Paul G; Fitzgerald, Peter J; Honda, Yasuhiro

2013-02-01

The aim of this study was to evaluate a new fully automated lumen border tracing system based on a novel multifrequency processing algorithm. We developed the multifrequency processing method to enhance arterial lumen detection by exploiting the differential scattering characteristics of blood and arterial tissue. The implementation of the method can be integrated into current intravascular ultrasound (IVUS) hardware. This study was performed in vivo with conventional 40-MHz IVUS catheters (Atlantis SR Pro™, Boston Scientific Corp, Natick, MA) in 43 clinical patients with coronary artery disease. A total of 522 frames were randomly selected, and lumen areas were measured after automatically tracing lumen borders with the new tracing system and a commercially available tracing system (TraceAssist™) referred to as the "conventional tracing system." The data assessed by the two automated systems were compared with the results of manual tracings by experienced IVUS analysts. New automated lumen measurements showed better agreement with manual lumen area tracings compared with those of the conventional tracing system (correlation coefficient: 0.819 vs. 0.509). When compared against manual tracings, the new algorithm also demonstrated improved systematic error (mean difference: 0.13 vs. -1.02 mm(2) ) and random variability (standard deviation of difference: 2.21 vs. 4.02 mm(2) ) compared with the conventional tracing system. This preliminary study showed that the novel fully automated tracing system based on the multifrequency processing algorithm can provide more accurate lumen border detection than current automated tracing systems and thus, offer a more reliable quantitative evaluation of lumen geometry. Copyright © 2011 Wiley Periodicals, Inc.

Automated detection of retinal disease.

Science.gov (United States)

Helmchen, Lorens A; Lehmann, Harold P; Abràmoff, Michael D

2014-11-01

Nearly 4 in 10 Americans with diabetes currently fail to undergo recommended annual retinal exams, resulting in tens of thousands of cases of blindness that could have been prevented. Advances in automated retinal disease detection could greatly reduce the burden of labor-intensive dilated retinal examinations by ophthalmologists and optometrists and deliver diagnostic services at lower cost. As the current availability of ophthalmologists and optometrists is inadequate to screen all patients at risk every year, automated screening systems deployed in primary care settings and even in patients' homes could fill the current gap in supply. Expanding screens to all patients at risk by switching to automated detection systems would in turn yield significantly higher rates of detecting and treating diabetic retinopathy per dilated retinal examination. Fewer diabetic patients would develop complications such as blindness, while ophthalmologists could focus on more complex cases.

Computer-aided liver volumetry: performance of a fully-automated, prototype post-processing solution for whole-organ and lobar segmentation based on MDCT imaging.

Science.gov (United States)

Fananapazir, Ghaneh; Bashir, Mustafa R; Marin, Daniele; Boll, Daniel T

2015-06-01

To evaluate the performance of a prototype, fully-automated post-processing solution for whole-liver and lobar segmentation based on MDCT datasets. A polymer liver phantom was used to assess accuracy of post-processing applications comparing phantom volumes determined via Archimedes' principle with MDCT segmented datasets. For the IRB-approved, HIPAA-compliant study, 25 patients were enrolled. Volumetry performance compared the manual approach with the automated prototype, assessing intraobserver variability, and interclass correlation for whole-organ and lobar segmentation using ANOVA comparison. Fidelity of segmentation was evaluated qualitatively. Phantom volume was 1581.0 ± 44.7 mL, manually segmented datasets estimated 1628.0 ± 47.8 mL, representing a mean overestimation of 3.0%, automatically segmented datasets estimated 1601.9 ± 0 mL, representing a mean overestimation of 1.3%. Whole-liver and segmental volumetry demonstrated no significant intraobserver variability for neither manual nor automated measurements. For whole-liver volumetry, automated measurement repetitions resulted in identical values; reproducible whole-organ volumetry was also achieved with manual segmentation, p(ANOVA) 0.98. For lobar volumetry, automated segmentation improved reproducibility over manual approach, without significant measurement differences for either methodology, p(ANOVA) 0.95-0.99. Whole-organ and lobar segmentation results from manual and automated segmentation showed no significant differences, p(ANOVA) 0.96-1.00. Assessment of segmentation fidelity found that segments I-IV/VI showed greater segmentation inaccuracies compared to the remaining right hepatic lobe segments. Automated whole-liver segmentation showed non-inferiority of fully-automated whole-liver segmentation compared to manual approaches with improved reproducibility and post-processing duration; automated dual-seed lobar segmentation showed slight tendencies for underestimating the right hepatic lobe

Fully automated data collection and processing system on macromolecular crystallography beamlines at the PF

International Nuclear Information System (INIS)

Yamada, Yusuke; Hiraki, Masahiko; Matsugaki, Naohiro; Chavas, Leonard M.G.; Igarashi, Noriyuki; Wakatsuki, Soichi

2012-01-01

Fully automated data collection and processing system has been developed on macromolecular crystallography beamlines at the Photon Factory. In this system, the sample exchange, centering and data collection are sequentially performed for all samples stored in the sample exchange system at a beamline without any manual operations. Data processing of collected data sets is also performed automatically. These results are stored into the database system, and users can monitor the progress and results of automated experiment via a Web browser. (author)

Development of a Real-Time PCR Protocol Requiring Minimal Handling for Detection of Vancomycin-Resistant Enterococci with the Fully Automated BD Max System.

Science.gov (United States)

Dalpke, Alexander H; Hofko, Marjeta; Zimmermann, Stefan

2016-09-01

Vancomycin-resistant enterococci (VRE) are an important cause of health care-associated infections, resulting in significant mortality and a significant economic burden in hospitals. Active surveillance for at-risk populations contributes to the prevention of infections with VRE. The availability of a combination of automation and molecular detection procedures for rapid screening would be beneficial. Here, we report on the development of a laboratory-developed PCR for detection of VRE which runs on the fully automated Becton Dickinson (BD) Max platform, which combines DNA extraction, PCR setup, and real-time PCR amplification. We evaluated two protocols: one using a liquid master mix and the other employing commercially ordered dry-down reagents. The BD Max VRE PCR was evaluated in two rounds with 86 and 61 rectal elution swab (eSwab) samples, and the results were compared to the culture results. The sensitivities of the different PCR formats were 84 to 100% for vanA and 83.7 to 100% for vanB; specificities were 96.8 to 100% for vanA and 81.8 to 97% for vanB The use of dry-down reagents and the ExK DNA-2 kit for extraction showed that the samples were less inhibited (3.3%) than they were by the use of the liquid master mix (14.8%). Adoption of a cutoff threshold cycle of 35 for discrimination of vanB-positive samples allowed an increase of specificity to 87.9%. The performance of the BD Max VRE assay equaled that of the BD GeneOhm VanR assay, which was run in parallel. The use of dry-down reagents simplifies the assay and omits any need to handle liquid PCR reagents. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

Science.gov (United States)

Joslin, John; Gilligan, James; Anderson, Paul; Garcia, Catherine; Sharif, Orzala; Hampton, Janice; Cohen, Steven; King, Miranda; Zhou, Bin; Jiang, Shumei; Trussell, Christopher; Dunn, Robert; Fathman, John W; Snead, Jennifer L; Boitano, Anthony E; Nguyen, Tommy; Conner, Michael; Cooke, Mike; Harris, Jennifer; Ainscow, Ed; Zhou, Yingyao; Shaw, Chris; Sipes, Dan; Mainquist, James; Lesley, Scott

2018-05-01

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Automated lung nodule classification following automated nodule detection on CT: A serial approach

International Nuclear Information System (INIS)

Armato, Samuel G. III; Altman, Michael B.; Wilkie, Joel; Sone, Shusuke; Li, Feng; Doi, Kunio; Roy, Arunabha S.

2003-01-01

We have evaluated the performance of an automated classifier applied to the task of differentiating malignant and benign lung nodules in low-dose helical computed tomography (CT) scans acquired as part of a lung cancer screening program. The nodules classified in this manner were initially identified by our automated lung nodule detection method, so that the output of automated lung nodule detection was used as input to automated lung nodule classification. This study begins to narrow the distinction between the 'detection task' and the 'classification task'. Automated lung nodule detection is based on two- and three-dimensional analyses of the CT image data. Gray-level-thresholding techniques are used to identify initial lung nodule candidates, for which morphological and gray-level features are computed. A rule-based approach is applied to reduce the number of nodule candidates that correspond to non-nodules, and the features of remaining candidates are merged through linear discriminant analysis to obtain final detection results. Automated lung nodule classification merges the features of the lung nodule candidates identified by the detection algorithm that correspond to actual nodules through another linear discriminant classifier to distinguish between malignant and benign nodules. The automated classification method was applied to the computerized detection results obtained from a database of 393 low-dose thoracic CT scans containing 470 confirmed lung nodules (69 malignant and 401 benign nodules). Receiver operating characteristic (ROC) analysis was used to evaluate the ability of the classifier to differentiate between nodule candidates that correspond to malignant nodules and nodule candidates that correspond to benign lesions. The area under the ROC curve for this classification task attained a value of 0.79 during a leave-one-out evaluation

Automated Detection of HONcode Website Conformity Compared to Manual Detection: An Evaluation.

Science.gov (United States)

Boyer, Célia; Dolamic, Ljiljana

2015-06-02

To earn HONcode certification, a website must conform to the 8 principles of the HONcode of Conduct In the current manual process of certification, a HONcode expert assesses the candidate website using precise guidelines for each principle. In the scope of the European project KHRESMOI, the Health on the Net (HON) Foundation has developed an automated system to assist in detecting a website's HONcode conformity. Automated assistance in conducting HONcode reviews can expedite the current time-consuming tasks of HONcode certification and ongoing surveillance. Additionally, an automated tool used as a plugin to a general search engine might help to detect health websites that respect HONcode principles but have not yet been certified. The goal of this study was to determine whether the automated system is capable of performing as good as human experts for the task of identifying HONcode principles on health websites. Using manual evaluation by HONcode senior experts as a baseline, this study compared the capability of the automated HONcode detection system to that of the HONcode senior experts. A set of 27 health-related websites were manually assessed for compliance to each of the 8 HONcode principles by senior HONcode experts. The same set of websites were processed by the automated system for HONcode compliance detection based on supervised machine learning. The results obtained by these two methods were then compared. For the privacy criterion, the automated system obtained the same results as the human expert for 17 of 27 sites (14 true positives and 3 true negatives) without noise (0 false positives). The remaining 10 false negative instances for the privacy criterion represented tolerable behavior because it is important that all automatically detected principle conformities are accurate (ie, specificity [100%] is preferred over sensitivity [58%] for the privacy criterion). In addition, the automated system had precision of at least 75%, with a recall of more

Fully automated joint space width measurement and digital X-ray radiogrammetry in early RA

NARCIS (Netherlands)

Platten, Michael; Kisten, Yogan; Kälvesten, Johan; Arnaud, Laurent; Forslind, Kristina; van Vollenhoven, Ronald

2017-01-01

To study fully automated digital joint space width (JSW) and bone mineral density (BMD) in relation to a conventional radiographic scoring method in early rheumatoid arthritis (eRA). Radiographs scored by the modified Sharp van der Heijde score (SHS) in patients with eRA were acquired from the

Fully Automated Driving: Impact of Trust and Practice on Manual Control Recovery.

Science.gov (United States)

Payre, William; Cestac, Julien; Delhomme, Patricia

2016-03-01

An experiment was performed in a driving simulator to investigate the impacts of practice, trust, and interaction on manual control recovery (MCR) when employing fully automated driving (FAD). To increase the use of partially or highly automated driving efficiency and to improve safety, some studies have addressed trust in driving automation and training, but few studies have focused on FAD. FAD is an autonomous system that has full control of a vehicle without any need for intervention by the driver. A total of 69 drivers with a valid license practiced with FAD. They were distributed evenly across two conditions: simple practice and elaborate practice. When examining emergency MCR, a correlation was found between trust and reaction time in the simple practice group (i.e., higher trust meant a longer reaction time), but not in the elaborate practice group. This result indicated that to mitigate the negative impact of overtrust on reaction time, more appropriate practice may be needed. Drivers should be trained in how the automated device works so as to improve MCR performance in case of an emergency. The practice format used in this study could be used for the first interaction with an FAD car when acquiring such a vehicle. © 2015, Human Factors and Ergonomics Society.

Towards a fully automated lab-on-a-disc system integrating sample enrichment and detection of analytes from complex matrices

DEFF Research Database (Denmark)

Andreasen, Sune Zoëga

the technology on a large scale from fulfilling its potential for maturing into applied technologies and products. In this work, we have taken the first steps towards realizing a capable and truly automated “sample-to-answer” analysis system, aimed at small molecule detection and quantification from a complex...... sample matrix. The main result is a working prototype of a microfluidic system, integrating both centrifugal microfluidics for sample handling, supported liquid membrane extraction (SLM) for selective and effective sample treatment, as well as in-situ electrochemical detection. As a case study...

Quantification of common carotid artery and descending aorta vessel wall thickness from MR vessel wall imaging using a fully automated processing pipeline.

Science.gov (United States)

Gao, Shan; van 't Klooster, Ronald; Brandts, Anne; Roes, Stijntje D; Alizadeh Dehnavi, Reza; de Roos, Albert; Westenberg, Jos J M; van der Geest, Rob J

2017-01-01

To develop and evaluate a method that can fully automatically identify the vessel wall boundaries and quantify the wall thickness for both common carotid artery (CCA) and descending aorta (DAO) from axial magnetic resonance (MR) images. 3T MRI data acquired with T 1 -weighted gradient-echo black-blood imaging sequence from carotid (39 subjects) and aorta (39 subjects) were used to develop and test the algorithm. The vessel wall segmentation was achieved by respectively fitting a 3D cylindrical B-spline surface to the boundaries of lumen and outer wall. The tube-fitting was based on the edge detection performed on the signal intensity (SI) profile along the surface normal. To achieve a fully automated process, Hough Transform (HT) was developed to estimate the lumen centerline and radii for the target vessel. Using the outputs of HT, a tube model for lumen segmentation was initialized and deformed to fit the image data. Finally, lumen segmentation was dilated to initiate the adaptation procedure of outer wall tube. The algorithm was validated by determining: 1) its performance against manual tracing; 2) its interscan reproducibility in quantifying vessel wall thickness (VWT); 3) its capability of detecting VWT difference in hypertensive patients compared with healthy controls. Statistical analysis including Bland-Altman analysis, t-test, and sample size calculation were performed for the purpose of algorithm evaluation. The mean distance between the manual and automatically detected lumen/outer wall contours was 0.00 ± 0.23/0.09 ± 0.21 mm for CCA and 0.12 ± 0.24/0.14 ± 0.35 mm for DAO. No significant difference was observed between the interscan VWT assessment using automated segmentation for both CCA (P = 0.19) and DAO (P = 0.94). Both manual and automated segmentation detected significantly higher carotid (P = 0.016 and P = 0.005) and aortic (P < 0.001 and P = 0.021) wall thickness in the hypertensive patients. A reliable and reproducible pipeline for fully

Lidar Cloud Detection with Fully Convolutional Networks

Science.gov (United States)

Cromwell, E.; Flynn, D.

2017-12-01

The vertical distribution of clouds from active remote sensing instrumentation is a widely used data product from global atmospheric measuring sites. The presence of clouds can be expressed as a binary cloud mask and is a primary input for climate modeling efforts and cloud formation studies. Current cloud detection algorithms producing these masks do not accurately identify the cloud boundaries and tend to oversample or over-represent the cloud. This translates as uncertainty for assessing the radiative impact of clouds and tracking changes in cloud climatologies. The Atmospheric Radiation Measurement (ARM) program has over 20 years of micro-pulse lidar (MPL) and High Spectral Resolution Lidar (HSRL) instrument data and companion automated cloud mask product at the mid-latitude Southern Great Plains (SGP) and the polar North Slope of Alaska (NSA) atmospheric observatory. Using this data, we train a fully convolutional network (FCN) with semi-supervised learning to segment lidar imagery into geometric time-height cloud locations for the SGP site and MPL instrument. We then use transfer learning to train a FCN for (1) the MPL instrument at the NSA site and (2) for the HSRL. In our semi-supervised approach, we pre-train the classification layers of the FCN with weakly labeled lidar data. Then, we facilitate end-to-end unsupervised pre-training and transition to fully supervised learning with ground truth labeled data. Our goal is to improve the cloud mask accuracy and precision for the MPL instrument to 95% and 80%, respectively, compared to the current cloud mask algorithms of 89% and 50%. For the transfer learning based FCN for the HSRL instrument, our goal is to achieve a cloud mask accuracy of 90% and a precision of 80%.

Fully automated synthesis system of 3'-deoxy-3'-[18F]fluorothymidine

International Nuclear Information System (INIS)

Oh, Seung Jun; Mosdzianowski, Christoph; Chi, Dae Yoon; Kim, Jung Young; Kang, Se Hun; Ryu, Jin Sook; Yeo, Jeong Seok; Moon, Dae Hyuk

2004-01-01

We developed a new fully automated method for the synthesis of 3'-deoxy-3'-[ 18 F]fluorothymidine ([ 18 F]FLT), by modifying a commercial FDG synthesizer and its disposable fluid pathway. Optimal labeling condition was that 40 mg of precursor in acetonitrile (2 mL) was heated at 150 degree sign C for 100 sec, followed by heating at 85 degree sign C for 450 sec and hydrolysis with 1 N HCl at 105 degree sign C for 300 sec. Using 3.7 GBq of [ 18 F]F - as starting activity, [ 18 F]FLT was obtained with a yield of 50.5±5.2% (n=28, decay corrected) within 60.0±5.4 min including HPLC purification. With 37.0 GBq, we obtained 48.7±5.6% (n=10). The [ 18 F]FLT showed the good stability for 6 h. This new automated synthesis procedure combines high and reproducible yields with the benefits of a disposable cassette system

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method

Science.gov (United States)

McIntosh, Chris; Welch, Mattea; McNiven, Andrea; Jaffray, David A.; Purdie, Thomas G.

2017-08-01

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12-13 min without user interaction. It is a promising approach for fully automated treatment

Fully automated joint space width measurement and digital X-ray radiogrammetry in early RA.

Science.gov (United States)

Platten, Michael; Kisten, Yogan; Kälvesten, Johan; Arnaud, Laurent; Forslind, Kristina; van Vollenhoven, Ronald

2017-01-01

To study fully automated digital joint space width (JSW) and bone mineral density (BMD) in relation to a conventional radiographic scoring method in early rheumatoid arthritis (eRA). Radiographs scored by the modified Sharp van der Heijde score (SHS) in patients with eRA were acquired from the SWEdish FarmacOTherapy study. Fully automated JSW measurements of bilateral metacarpals 2, 3 and 4 were compared with the joint space narrowing (JSN) score in SHS. Multilevel mixed model statistics were applied to calculate the significance of the association between ΔJSW and ΔBMD over 1 year, and the JSW differences between damaged and undamaged joints as evaluated by the JSN. Based on 576 joints of 96 patients with eRA, a significant reduction from baseline to 1 year was observed in the JSW from 1.69 (±0.19) mm to 1.66 (±0.19) mm (p0) joints: 1.68 mm (95% CI 1.70 to 1.67) vs 1.54 mm (95% CI 1.63 to 1.46). Similarly the unadjusted multilevel model showed significant differences in JSW between undamaged (1.68 mm (95% CI 1.72 to 1.64)) and damaged joints (1.63 mm (95% CI 1.68 to 1.58)) (p=0.0048). This difference remained significant in the adjusted model: 1.66 mm (95% CI 1.70 to 1.61) vs 1.62 mm (95% CI 1.68 to 1.56) (p=0.042). To measure the JSW with this fully automated digital tool may be useful as a quick and observer-independent application for evaluating cartilage damage in eRA. NCT00764725.

Fast and Efficient Fragment-Based Lead Generation by Fully Automated Processing and Analysis of Ligand-Observed NMR Binding Data.

Science.gov (United States)

Peng, Chen; Frommlet, Alexandra; Perez, Manuel; Cobas, Carlos; Blechschmidt, Anke; Dominguez, Santiago; Lingel, Andreas

2016-04-14

NMR binding assays are routinely applied in hit finding and validation during early stages of drug discovery, particularly for fragment-based lead generation. To this end, compound libraries are screened by ligand-observed NMR experiments such as STD, T1ρ, and CPMG to identify molecules interacting with a target. The analysis of a high number of complex spectra is performed largely manually and therefore represents a limiting step in hit generation campaigns. Here we report a novel integrated computational procedure that processes and analyzes ligand-observed proton and fluorine NMR binding data in a fully automated fashion. A performance evaluation comparing automated and manual analysis results on (19)F- and (1)H-detected data sets shows that the program delivers robust, high-confidence hit lists in a fraction of the time needed for manual analysis and greatly facilitates visual inspection of the associated NMR spectra. These features enable considerably higher throughput, the assessment of larger libraries, and shorter turn-around times.

A fully automated conversational agent for promoting mental well-being: A pilot RCT using mixed methods

Directory of Open Access Journals (Sweden)

Kien Hoa Ly

2017-12-01

Full Text Available Fully automated self-help interventions can serve as highly cost-effective mental health promotion tools for massive amounts of people. However, these interventions are often characterised by poor adherence. One way to address this problem is to mimic therapy support by a conversational agent. The objectives of this study were to assess the effectiveness and adherence of a smartphone app, delivering strategies used in positive psychology and CBT interventions via an automated chatbot (Shim for a non-clinical population — as well as to explore participants' views and experiences of interacting with this chatbot. A total of 28 participants were randomized to either receive the chatbot intervention (n = 14 or to a wait-list control group (n = 14. Findings revealed that participants who adhered to the intervention (n = 13 showed significant interaction effects of group and time on psychological well-being (FS and perceived stress (PSS-10 compared to the wait-list control group, with small to large between effect sizes (Cohen's d range 0.14–1.06. Also, the participants showed high engagement during the 2-week long intervention, with an average open app ratio of 17.71 times for the whole period. This is higher compared to other studies on fully automated interventions claiming to be highly engaging, such as Woebot and the Panoply app. The qualitative data revealed sub-themes which, to our knowledge, have not been found previously, such as the moderating format of the chatbot. The results of this study, in particular the good adherence rate, validated the usefulness of replicating this study in the future with a larger sample size and an active control group. This is important, as the search for fully automated, yet highly engaging and effective digital self-help interventions for promoting mental health is crucial for the public health.

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

Science.gov (United States)

Kline, Timothy L; Korfiatis, Panagiotis; Edwards, Marie E; Blais, Jaime D; Czerwiec, Frank S; Harris, Peter C; King, Bernard F; Torres, Vicente E; Erickson, Bradley J

2017-08-01

Deep learning techniques are being rapidly applied to medical imaging tasks-from organ and lesion segmentation to tissue and tumor classification. These techniques are becoming the leading algorithmic approaches to solve inherently difficult image processing tasks. Currently, the most critical requirement for successful implementation lies in the need for relatively large datasets that can be used for training the deep learning networks. Based on our initial studies of MR imaging examinations of the kidneys of patients affected by polycystic kidney disease (PKD), we have generated a unique database of imaging data and corresponding reference standard segmentations of polycystic kidneys. In the study of PKD, segmentation of the kidneys is needed in order to measure total kidney volume (TKV). Automated methods to segment the kidneys and measure TKV are needed to increase measurement throughput and alleviate the inherent variability of human-derived measurements. We hypothesize that deep learning techniques can be leveraged to perform fast, accurate, reproducible, and fully automated segmentation of polycystic kidneys. Here, we describe a fully automated approach for segmenting PKD kidneys within MR images that simulates a multi-observer approach in order to create an accurate and robust method for the task of segmentation and computation of TKV for PKD patients. A total of 2000 cases were used for training and validation, and 400 cases were used for testing. The multi-observer ensemble method had mean ± SD percent volume difference of 0.68 ± 2.2% compared with the reference standard segmentations. The complete framework performs fully automated segmentation at a level comparable with interobserver variability and could be considered as a replacement for the task of segmentation of PKD kidneys by a human.

Effectiveness of a Web-Based Screening and Fully Automated Brief Motivational Intervention for Adolescent Substance Use

DEFF Research Database (Denmark)

Arnaud, Nicolas; Baldus, Christiane; Elgán, Tobias H.

2016-01-01

).Conclusions: Although the study is limited by a large drop-out, significant between-group effects for alcohol use indicate that targeted brief motivational intervention in a fully automated Web-based format can be effective to reduce drinking and lessen existing substance use service barriers for at...... of substance use among college students. However, the evidence is sparse among adolescents with at-risk use of alcohol and other drugs. Objective: This study evaluated the effectiveness of a targeted and fully automated Web-based brief motivational intervention with no face-to-face components on substance use......, and polydrug use. All outcome analyses were conducted with and without Expectation Maximization (EM) imputation of missing follow-up data. Results: In total, 2673 adolescents were screened and 1449 (54.2%) participants were randomized to the intervention or control group. After 3 months, 211 adolescents (14...

Effectiveness of a Web-Based Screening and Fully Automated Brief Motivational Intervention for Adolescent Substance Use

DEFF Research Database (Denmark)

Arnaud, Nicolas; Baldus, Christiane; Elgán, Tobias H.

2016-01-01

of substance use among college students. However, the evidence is sparse among adolescents with at-risk use of alcohol and other drugs. Objective: This study evaluated the effectiveness of a targeted and fully automated Web-based brief motivational intervention with no face-to-face components on substance use...... methods and screened online for at-risk substance use using the CRAFFT (Car, Relax, Alone, Forget, Friends, Trouble) screening instrument. Participants were randomized to a single session brief motivational intervention group or an assessment-only control group but not blinded. Primary outcome......).Conclusions: Although the study is limited by a large drop-out, significant between-group effects for alcohol use indicate that targeted brief motivational intervention in a fully automated Web-based format can be effective to reduce drinking and lessen existing substance use service barriers for at...

Automated Detection, Localization, and Classification of Traumatic Vertebral Body Fractures in the Thoracic and Lumbar Spine at CT.

Science.gov (United States)

Burns, Joseph E; Yao, Jianhua; Muñoz, Hector; Summers, Ronald M

2016-01-01

To design and validate a fully automated computer system for the detection and anatomic localization of traumatic thoracic and lumbar vertebral body fractures at computed tomography (CT). This retrospective study was HIPAA compliant. Institutional review board approval was obtained, and informed consent was waived. CT examinations in 104 patients (mean age, 34.4 years; range, 14-88 years; 32 women, 72 men), consisting of 94 examinations with positive findings for fractures (59 with vertebral body fractures) and 10 control examinations (without vertebral fractures), were performed. There were 141 thoracic and lumbar vertebral body fractures in the case set. The locations of fractures were marked and classified by a radiologist according to Denis column involvement. The CT data set was divided into training and testing subsets (37 and 67 subsets, respectively) for analysis by means of prototype software for fully automated spinal segmentation and fracture detection. Free-response receiver operating characteristic analysis was performed. Training set sensitivity for detection and localization of fractures within each vertebra was 0.82 (28 of 34 findings; 95% confidence interval [CI]: 0.68, 0.90), with a false-positive rate of 2.5 findings per patient. The sensitivity for fracture localization to the correct vertebra was 0.88 (23 of 26 findings; 95% CI: 0.72, 0.96), with a false-positive rate of 1.3. Testing set sensitivity for the detection and localization of fractures within each vertebra was 0.81 (87 of 107 findings; 95% CI: 0.75, 0.87), with a false-positive rate of 2.7. The sensitivity for fracture localization to the correct vertebra was 0.92 (55 of 60 findings; 95% CI: 0.79, 0.94), with a false-positive rate of 1.6. The most common cause of false-positive findings was nutrient foramina (106 of 272 findings [39%]). The fully automated computer system detects and anatomically localizes vertebral body fractures in the thoracic and lumbar spine on CT images with a

Experience of automation failures in training: effects on trust, automation bias, complacency and performance.

Science.gov (United States)

Sauer, Juergen; Chavaillaz, Alain; Wastell, David

2016-06-01

This work examined the effects of operators' exposure to various types of automation failures in training. Forty-five participants were trained for 3.5 h on a simulated process control environment. During training, participants either experienced a fully reliable, automatic fault repair facility (i.e. faults detected and correctly diagnosed), a misdiagnosis-prone one (i.e. faults detected but not correctly diagnosed) or a miss-prone one (i.e. faults not detected). One week after training, participants were tested for 3 h, experiencing two types of automation failures (misdiagnosis, miss). The results showed that automation bias was very high when operators trained on miss-prone automation encountered a failure of the diagnostic system. Operator errors resulting from automation bias were much higher when automation misdiagnosed a fault than when it missed one. Differences in trust levels that were instilled by the different training experiences disappeared during the testing session. Practitioner Summary: The experience of automation failures during training has some consequences. A greater potential for operator errors may be expected when an automatic system failed to diagnose a fault than when it failed to detect one.

Fully automated bone mineral density assessment from low-dose chest CT

Science.gov (United States)

Liu, Shuang; Gonzalez, Jessica; Zulueta, Javier; de-Torres, Juan P.; Yankelevitz, David F.; Henschke, Claudia I.; Reeves, Anthony P.

2018-02-01

A fully automated system is presented for bone mineral density (BMD) assessment from low-dose chest CT (LDCT). BMD assessment is central in the diagnosis and follow-up therapy monitoring of osteoporosis, which is characterized by low bone density and is estimated to affect 12.3 million US population aged 50 years or older, creating tremendous social and economic burdens. BMD assessment from DXA scans (BMDDXA) is currently the most widely used and gold standard technique for the diagnosis of osteoporosis and bone fracture risk estimation. With the recent large-scale implementation of annual lung cancer screening using LDCT, great potential emerges for the concurrent opportunistic osteoporosis screening. In the presented BMDCT assessment system, each vertebral body is first segmented and labeled with its anatomical name. Various 3D region of interest (ROI) inside the vertebral body are then explored for BMDCT measurements at different vertebral levels. The system was validated using 76 pairs of DXA and LDCT scans of the same subject. Average BMDDXA of L1-L4 was used as the reference standard. Statistically significant (p-value correlation is obtained between BMDDXA and BMDCT at all vertebral levels (T1 - L2). A Pearson correlation of 0.857 was achieved between BMDDXA and average BMDCT of T9-T11 by using a 3D ROI taking into account of both trabecular and cortical bone tissue. These encouraging results demonstrate the feasibility of fully automated quantitative BMD assessment and the potential of opportunistic osteoporosis screening with concurrent lung cancer screening using LDCT.

Implementation of a fully automated process purge-and-trap gas chromatograph at an environmental remediation site

International Nuclear Information System (INIS)

Blair, D.S.; Morrison, D.J.

1997-01-01

The AQUASCAN, a commercially available, fully automated purge-and-trap gas chromatograph from Sentex Systems Inc., was implemented and evaluated as an in-field, automated monitoring system of contaminated groundwater at an active DOE remediation site in Pinellas, FL. Though the AQUASCAN is designed as a stand alone process analytical unit, implementation at this site required additional hardware. The hardware included a sample dilution system and a method for delivering standard solution to the gas chromatograph for automated calibration. As a result of the evaluation the system was determined to be a reliable and accurate instrument. The AQUASCAN reported concentration values for methylene chloride, trichloroethylene, and toluene in the Pinellas ground water were within 20% of reference laboratory values

Automated Detection of Small Bodies by Space Based Observation

Science.gov (United States)

Bidstrup, P. R.; Grillmayer, G.; Andersen, A. C.; Haack, H.; Jorgensen, J. L.

The number of known comets and asteroids is increasing every year. Up till now this number is including approximately 250,000 of the largest minor planets, as they are usually referred. These discoveries are due to the Earth-based observation which has intensified over the previous decades. Additionally larger telescopes and arrays of telescopes are being used for exploring our Solar System. It is believed that all near- Earth and Main-Belt asteroids of diameters above 10 to 30 km have been discovered, leaving these groups of objects as observationally complete. However, the cataloguing of smaller bodies is incomplete as only a very small fraction of the expected number has been discovered. It is estimated that approximately 1010 main belt asteroids in the size range 1 m to 1 km are too faint to be observed using Earth-based telescopes. In order to observe these small bodies, space-based search must be initiated to remove atmospheric disturbances and to minimize the distance to the asteroids and thereby minimising the requirement for long camera integration times. A new method of space-based detection of moving non-stellar objects is currently being developed utilising the Advanced Stellar Compass (ASC) built for spacecraft attitude determination by Ørsted, Danish Technical University. The ASC serves as a backbone technology in the project as it is capable of fully automated distinction of known and unknown celestial objects. By only processing objects of particular interest, i.e. moving objects, it will be possible to discover small bodies with a minimum of ground control, with the ultimate ambition of a fully automated space search probe. Currently, the ASC is being mounted on the Flying Laptop satellite of the Institute of Space Systems, Universität Stuttgart. It will, after a launch into a low Earth polar orbit in 2008, test the detection method with the ASC equipment that already had significant in-flight experience. A future use of the ASC based automated

UBO Detector - A cluster-based, fully automated pipeline for extracting white matter hyperintensities.

Science.gov (United States)

Jiang, Jiyang; Liu, Tao; Zhu, Wanlin; Koncz, Rebecca; Liu, Hao; Lee, Teresa; Sachdev, Perminder S; Wen, Wei

2018-07-01

We present 'UBO Detector', a cluster-based, fully automated pipeline for extracting and calculating variables for regions of white matter hyperintensities (WMH) (available for download at https://cheba.unsw.edu.au/group/neuroimaging-pipeline). It takes T1-weighted and fluid attenuated inversion recovery (FLAIR) scans as input, and SPM12 and FSL functions are utilised for pre-processing. The candidate clusters are then generated by FMRIB's Automated Segmentation Tool (FAST). A supervised machine learning algorithm, k-nearest neighbor (k-NN), is applied to determine whether the candidate clusters are WMH or non-WMH. UBO Detector generates both image and text (volumes and the number of WMH clusters) outputs for whole brain, periventricular, deep, and lobar WMH, as well as WMH in arterial territories. The computation time for each brain is approximately 15 min. We validated the performance of UBO Detector by showing a) high segmentation (similarity index (SI) = 0.848) and volumetric (intraclass correlation coefficient (ICC) = 0.985) agreement between the UBO Detector-derived and manually traced WMH; b) highly correlated (r 2  > 0.9) and a steady increase of WMH volumes over time; and c) significant associations of periventricular (t = 22.591, p deep (t = 14.523, p < 0.001) WMH volumes generated by UBO Detector with Fazekas rating scores. With parallel computing enabled in UBO Detector, the processing can take advantage of multi-core CPU's that are commonly available on workstations. In conclusion, UBO Detector is a reliable, efficient and fully automated WMH segmentation pipeline. Copyright © 2018 Elsevier Inc. All rights reserved.

The worldwide NORM production and a fully automated gamma-ray spectrometer for their characterization

International Nuclear Information System (INIS)

Xhixha, G.; Callegari, I.; Guastaldi, E.; De Bianchi, S.; Fiorentini, G.; Universita di Ferrara, Ferrara; Istituto Nazionale di Fisica Nucleare; Kaceli Xhixha, M.

2013-01-01

Materials containing radionuclides of natural origin and being subject to regulation because of their radioactivity are known as Naturally Occurring Radioactive Material (NORM). By following International Atomic Energy Agency, we include in NORM those materials with an activity concentration, which is modified by human made processes. We present a brief review of the main categories of non-nuclear industries together with the levels of activity concentration in feed raw materials, products and waste, including mechanisms of radioisotope enrichments. The global management of NORM shows a high level of complexity, mainly due to different degrees of radioactivity enhancement and the huge amount of worldwide waste production. The future tendency of guidelines concerning environmental protection will require both a systematic monitoring based on the ever-increasing sampling and high performance of gamma-ray spectroscopy. On the ground of these requirements a new low-background fully automated high-resolution gamma-ray spectrometer MCA R ad has been developed. The design of lead and cooper shielding allowed to reach a background reduction of two order of magnitude with respect to laboratory radioactivity. A severe lowering of manpower cost is obtained through a fully automation system, which enables up to 24 samples to be measured without any human attendance. Two coupled HPGe detectors increase the detection efficiency, performing accurate measurements on small sample volume (180 cm 3 ) with a reduction of sample transport cost of material. Details of the instrument calibration method are presented. MCA R ad system can measure in less than one hour a typical NORM sample enriched in U and Th with some hundreds of Bq kg -1 , with an overall uncertainty less than 5 %. Quality control of this method has been tested. Measurements of three certified reference materials RGK-1, RGU-2 and RGTh-1 containing concentrations of potassium, uranium and thorium comparable to NORM have

A fully automated Drosophila olfactory classical conditioning and testing system for behavioral learning and memory assessment.

Science.gov (United States)

Jiang, Hui; Hanna, Eriny; Gatto, Cheryl L; Page, Terry L; Bhuva, Bharat; Broadie, Kendal

2016-03-01

Aversive olfactory classical conditioning has been the standard method to assess Drosophila learning and memory behavior for decades, yet training and testing are conducted manually under exceedingly labor-intensive conditions. To overcome this severe limitation, a fully automated, inexpensive system has been developed, which allows accurate and efficient Pavlovian associative learning/memory analyses for high-throughput pharmacological and genetic studies. The automated system employs a linear actuator coupled to an odorant T-maze with airflow-mediated transfer of animals between training and testing stages. Odorant, airflow and electrical shock delivery are automatically administered and monitored during training trials. Control software allows operator-input variables to define parameters of Drosophila learning, short-term memory and long-term memory assays. The approach allows accurate learning/memory determinations with operational fail-safes. Automated learning indices (immediately post-training) and memory indices (after 24h) are comparable to traditional manual experiments, while minimizing experimenter involvement. The automated system provides vast improvements over labor-intensive manual approaches with no experimenter involvement required during either training or testing phases. It provides quality control tracking of airflow rates, odorant delivery and electrical shock treatments, and an expanded platform for high-throughput studies of combinational drug tests and genetic screens. The design uses inexpensive hardware and software for a total cost of ∼$500US, making it affordable to a wide range of investigators. This study demonstrates the design, construction and testing of a fully automated Drosophila olfactory classical association apparatus to provide low-labor, high-fidelity, quality-monitored, high-throughput and inexpensive learning and memory behavioral assays. Copyright © 2015 Elsevier B.V. All rights reserved.

A fully-automated multiscale kernel graph cuts based particle localization scheme for temporal focusing two-photon microscopy

Science.gov (United States)

Huang, Xia; Li, Chunqiang; Xiao, Chuan; Sun, Wenqing; Qian, Wei

2017-03-01

The temporal focusing two-photon microscope (TFM) is developed to perform depth resolved wide field fluorescence imaging by capturing frames sequentially. However, due to strong nonignorable noises and diffraction rings surrounding particles, further researches are extremely formidable without a precise particle localization technique. In this paper, we developed a fully-automated scheme to locate particles positions with high noise tolerance. Our scheme includes the following procedures: noise reduction using a hybrid Kalman filter method, particle segmentation based on a multiscale kernel graph cuts global and local segmentation algorithm, and a kinematic estimation based particle tracking method. Both isolated and partial-overlapped particles can be accurately identified with removal of unrelated pixels. Based on our quantitative analysis, 96.22% isolated particles and 84.19% partial-overlapped particles were successfully detected.

Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease

Directory of Open Access Journals (Sweden)

Jing Wu

2016-01-01

Full Text Available In macular spectral domain optical coherence tomography (SD-OCT volumes, detection of the foveal center is required for accurate and reproducible follow-up studies, structure function correlation, and measurement grid positioning. However, disease can cause severe obscuring or deformation of the fovea, thus presenting a major challenge in automated detection. We propose a fully automated fovea detection algorithm to extract the fovea position in SD-OCT volumes of eyes with exudative maculopathy. The fovea is classified into 3 main appearances to both specify the detection algorithm used and reduce computational complexity. Based on foveal type classification, the fovea position is computed based on retinal nerve fiber layer thickness. Mean absolute distance between system and clinical expert annotated fovea positions from a dataset comprised of 240 SD-OCT volumes was 162.3 µm in cystoid macular edema and 262 µm in nAMD. The presented method has cross-vendor functionality, while demonstrating accurate and reliable performance close to typical expert interobserver agreement. The automatically detected fovea positions may be used as landmarks for intra- and cross-patient registration and to create a joint reference frame for extraction of spatiotemporal features in “big data.” Furthermore, reliable analyses of retinal thickness, as well as retinal structure function correlation, may be facilitated.

Development of a fully automated software system for rapid analysis/processing of the falling weight deflectometer data.

Science.gov (United States)

2009-02-01

The Office of Special Investigations at Iowa Department of Transportation (DOT) collects FWD data on regular basis to evaluate pavement structural conditions. The primary objective of this study was to develop a fully-automated software system for ra...

Automated detection of fundus photographic red lesions in diabetic retinopathy.

Science.gov (United States)

Larsen, Michael; Godt, Jannik; Larsen, Nicolai; Lund-Andersen, Henrik; Sjølie, Anne Katrin; Agardh, Elisabet; Kalm, Helle; Grunkin, Michael; Owens, David R

2003-02-01

To compare a fundus image-analysis algorithm for automated detection of hemorrhages and microaneurysms with visual detection of retinopathy in patients with diabetes. Four hundred fundus photographs (35-mm color transparencies) were obtained in 200 eyes of 100 patients with diabetes who were randomly selected from the Welsh Community Diabetic Retinopathy Study. A gold standard reference was defined by classifying each patient as having or not having diabetic retinopathy based on overall visual grading of the digitized transparencies. A single-lesion visual grading was made independently, comprising meticulous outlining of all single lesions in all photographs and used to develop the automated red lesion detection system. A comparison of visual and automated single-lesion detection in replicating the overall visual grading was then performed. Automated red lesion detection demonstrated a specificity of 71.4% and a resulting sensitivity of 96.7% in detecting diabetic retinopathy when applied at a tentative threshold setting for use in diabetic retinopathy screening. The accuracy of 79% could be raised to 85% by adjustment of a single user-supplied parameter determining the balance between the screening priorities, for which a considerable range of options was demonstrated by the receiver-operating characteristic (area under the curve 90.3%). The agreement of automated lesion detection with overall visual grading (0.659) was comparable to the mean agreement of six ophthalmologists (0.648). Detection of diabetic retinopathy by automated detection of single fundus lesions can be achieved with a performance comparable to that of experienced ophthalmologists. The results warrant further investigation of automated fundus image analysis as a tool for diabetic retinopathy screening.

A new fully automated FTIR system for total column measurements of greenhouse gases

Science.gov (United States)

Geibel, M. C.; Gerbig, C.; Feist, D. G.

2010-10-01

This article introduces a new fully automated FTIR system that is part of the Total Carbon Column Observing Network (TCCON). It will provide continuous ground-based measurements of column-averaged volume mixing ratio for CO2, CH4 and several other greenhouse gases in the tropics. Housed in a 20-foot shipping container it was developed as a transportable system that could be deployed almost anywhere in the world. We describe the automation concept which relies on three autonomous subsystems and their interaction. Crucial components like a sturdy and reliable solar tracker dome are described in detail. The automation software employs a new approach relying on multiple processes, database logging and web-based remote control. First results of total column measurements at Jena, Germany show that the instrument works well and can provide parts of the diurnal as well as seasonal cycle for CO2. Instrument line shape measurements with an HCl cell suggest that the instrument stays well-aligned over several months. After a short test campaign for side by side intercomaprison with an existing TCCON instrument in Australia, the system will be transported to its final destination Ascension Island.

Fully automated parallel oligonucleotide synthesizer

Czech Academy of Sciences Publication Activity Database

Lebl, M.; Burger, Ch.; Ellman, B.; Heiner, D.; Ibrahim, G.; Jones, A.; Nibbe, M.; Thompson, J.; Mudra, Petr; Pokorný, Vít; Poncar, Pavel; Ženíšek, Karel

2001-01-01

Roč. 66, č. 8 (2001), s. 1299-1314 ISSN 0010-0765 Institutional research plan: CEZ:AV0Z4055905 Keywords : automated oligonucleotide synthesizer Subject RIV: CC - Organic Chemistry Impact factor: 0.778, year: 2001

Automated baseline change detection phase I. Final report

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-12-01

The Automated Baseline Change Detection (ABCD) project is supported by the DOE Morgantown Energy Technology Center (METC) as part of its ER&WM cross-cutting technology program in robotics. Phase 1 of the Automated Baseline Change Detection project is summarized in this topical report. The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrel and on feature recognition in images. In support of this primary objective, there are secondary objectives to determine DOE operational inspection requirements and DOE system fielding requirements.

Automated baseline change detection phase I. Final report

International Nuclear Information System (INIS)

1995-12-01

The Automated Baseline Change Detection (ABCD) project is supported by the DOE Morgantown Energy Technology Center (METC) as part of its ER ampersand WM cross-cutting technology program in robotics. Phase 1 of the Automated Baseline Change Detection project is summarized in this topical report. The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrel and on feature recognition in images. In support of this primary objective, there are secondary objectives to determine DOE operational inspection requirements and DOE system fielding requirements

Automated early detection of diabetic retinopathy

NARCIS (Netherlands)

Abràmoff, M.D.; Reinhardt, J.M.; Russell, S.R.; Folk, J.C.; Mahajan, V.B.; Niemeijer, M.; Quellec, G.

2010-01-01

Purpose To compare the performance of automated diabetic retinopathy (DR) detection, using the algorithm that won the 2009 Retinopathy Online Challenge Competition in 2009, the Challenge2009, against that of the one currently used in EyeCheck, a large computer-aided early DR detection project.

A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology.

Science.gov (United States)

Al-Fahdawi, Shumoos; Qahwaji, Rami; Al-Waisy, Alaa S; Ipson, Stanley; Ferdousi, Maryam; Malik, Rayaz A; Brahma, Arun

2018-07-01

Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image. Copyright © 2018 Elsevier B.V. All rights reserved.

A quality assurance framework for the fully automated and objective evaluation of image quality in cone-beam computed tomography

International Nuclear Information System (INIS)

Steiding, Christian; Kolditz, Daniel; Kalender, Willi A.

2014-01-01

Purpose: Thousands of cone-beam computed tomography (CBCT) scanners for vascular, maxillofacial, neurological, and body imaging are in clinical use today, but there is no consensus on uniform acceptance and constancy testing for image quality (IQ) and dose yet. The authors developed a quality assurance (QA) framework for fully automated and time-efficient performance evaluation of these systems. In addition, the dependence of objective Fourier-based IQ metrics on direction and position in 3D volumes was investigated for CBCT. Methods: The authors designed a dedicated QA phantom 10 cm in length consisting of five compartments, each with a diameter of 10 cm, and an optional extension ring 16 cm in diameter. A homogeneous section of water-equivalent material allows measuring CT value accuracy, image noise and uniformity, and multidimensional global and local noise power spectra (NPS). For the quantitative determination of 3D high-contrast spatial resolution, the modulation transfer function (MTF) of centrally and peripherally positioned aluminum spheres was computed from edge profiles. Additional in-plane and axial resolution patterns were used to assess resolution qualitatively. The characterization of low-contrast detectability as well as CT value linearity and artifact behavior was tested by utilizing sections with soft-tissue-equivalent and metallic inserts. For an automated QA procedure, a phantom detection algorithm was implemented. All tests used in the dedicated QA program were initially verified in simulation studies and experimentally confirmed on a clinical dental CBCT system. Results: The automated IQ evaluation of volume data sets of the dental CBCT system was achieved with the proposed phantom requiring only one scan for the determination of all desired parameters. Typically, less than 5 min were needed for phantom set-up, scanning, and data analysis. Quantitative evaluation of system performance over time by comparison to previous examinations was also

A quality assurance framework for the fully automated and objective evaluation of image quality in cone-beam computed tomography.

Science.gov (United States)

Steiding, Christian; Kolditz, Daniel; Kalender, Willi A

2014-03-01

Thousands of cone-beam computed tomography (CBCT) scanners for vascular, maxillofacial, neurological, and body imaging are in clinical use today, but there is no consensus on uniform acceptance and constancy testing for image quality (IQ) and dose yet. The authors developed a quality assurance (QA) framework for fully automated and time-efficient performance evaluation of these systems. In addition, the dependence of objective Fourier-based IQ metrics on direction and position in 3D volumes was investigated for CBCT. The authors designed a dedicated QA phantom 10 cm in length consisting of five compartments, each with a diameter of 10 cm, and an optional extension ring 16 cm in diameter. A homogeneous section of water-equivalent material allows measuring CT value accuracy, image noise and uniformity, and multidimensional global and local noise power spectra (NPS). For the quantitative determination of 3D high-contrast spatial resolution, the modulation transfer function (MTF) of centrally and peripherally positioned aluminum spheres was computed from edge profiles. Additional in-plane and axial resolution patterns were used to assess resolution qualitatively. The characterization of low-contrast detectability as well as CT value linearity and artifact behavior was tested by utilizing sections with soft-tissue-equivalent and metallic inserts. For an automated QA procedure, a phantom detection algorithm was implemented. All tests used in the dedicated QA program were initially verified in simulation studies and experimentally confirmed on a clinical dental CBCT system. The automated IQ evaluation of volume data sets of the dental CBCT system was achieved with the proposed phantom requiring only one scan for the determination of all desired parameters. Typically, less than 5 min were needed for phantom set-up, scanning, and data analysis. Quantitative evaluation of system performance over time by comparison to previous examinations was also verified. The maximum

Fully automated synthesis of [(18) F]fluoro-dihydrotestosterone ([(18) F]FDHT) using the FlexLab module.

Science.gov (United States)

Ackermann, Uwe; Lewis, Jason S; Young, Kenneth; Morris, Michael J; Weickhardt, Andrew; Davis, Ian D; Scott, Andrew M

2016-08-01

Imaging of androgen receptor expression in prostate cancer using F-18 FDHT is becoming increasingly popular. With the radiolabelling precursor now commercially available, developing a fully automated synthesis of [(18) F] FDHT is important. We have fully automated the synthesis of F-18 FDHT using the iPhase FlexLab module using only commercially available components. Total synthesis time was 90 min, radiochemical yields were 25-33% (n = 11). Radiochemical purity of the final formulation was > 99% and specific activity was > 18.5 GBq/µmol for all batches. This method can be up-scaled as desired, thus making it possible to study multiple patients in a day. Furthermore, our procedure uses 4 mg of precursor only and is therefore cost-effective. The synthesis has now been validated at Austin Health and is currently used for [(18) F]FDHT studies in patients. We believe that this method can easily adapted by other modules to further widen the availability of [(18) F]FDHT. Copyright © 2016 John Wiley & Sons, Ltd.

Object Detection Based on Fast/Faster RCNN Employing Fully Convolutional Architectures

Directory of Open Access Journals (Sweden)

Yun Ren

2018-01-01

Full Text Available Modern object detectors always include two major parts: a feature extractor and a feature classifier as same as traditional object detectors. The deeper and wider convolutional architectures are adopted as the feature extractor at present. However, many notable object detection systems such as Fast/Faster RCNN only consider simple fully connected layers as the feature classifier. In this paper, we declare that it is beneficial for the detection performance to elaboratively design deep convolutional networks (ConvNets of various depths for feature classification, especially using the fully convolutional architectures. In addition, this paper also demonstrates how to employ the fully convolutional architectures in the Fast/Faster RCNN. Experimental results show that a classifier based on convolutional layer is more effective for object detection than that based on fully connected layer and that the better detection performance can be achieved by employing deeper ConvNets as the feature classifier.

Automation in airport security X-ray screening of cabin baggage: Examining benefits and possible implementations of automated explosives detection.

Science.gov (United States)

Hättenschwiler, Nicole; Sterchi, Yanik; Mendes, Marcia; Schwaninger, Adrian

2018-10-01

Bomb attacks on civil aviation make detecting improvised explosive devices and explosive material in passenger baggage a major concern. In the last few years, explosive detection systems for cabin baggage screening (EDSCB) have become available. Although used by a number of airports, most countries have not yet implemented these systems on a wide scale. We investigated the benefits of EDSCB with two different levels of automation currently being discussed by regulators and airport operators: automation as a diagnostic aid with an on-screen alarm resolution by the airport security officer (screener) or EDSCB with an automated decision by the machine. The two experiments reported here tested and compared both scenarios and a condition without automation as baseline. Participants were screeners at two international airports who differed in both years of work experience and familiarity with automation aids. Results showed that experienced screeners were good at detecting improvised explosive devices even without EDSCB. EDSCB increased only their detection of bare explosives. In contrast, screeners with less experience (tenure automated decision provided better human-machine detection performance than on-screen alarm resolution and no automation. This came at the cost of slightly higher false alarm rates on the human-machine system level, which would still be acceptable from an operational point of view. Results indicate that a wide-scale implementation of EDSCB would increase the detection of explosives in passenger bags and automated decision instead of automation as diagnostic aid with on screen alarm resolution should be considered. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

A two-dimensionally coincident second difference cosmic ray spike removal method for the fully automated processing of Raman spectra.

Science.gov (United States)

Schulze, H Georg; Turner, Robin F B

2014-01-01

Charge-coupled device detectors are vulnerable to cosmic rays that can contaminate Raman spectra with positive going spikes. Because spikes can adversely affect spectral processing and data analyses, they must be removed. Although both hardware-based and software-based spike removal methods exist, they typically require parameter and threshold specification dependent on well-considered user input. Here, we present a fully automated spike removal algorithm that proceeds without requiring user input. It is minimally dependent on sample attributes, and those that are required (e.g., standard deviation of spectral noise) can be determined with other fully automated procedures. At the core of the method is the identification and location of spikes with coincident second derivatives along both the spectral and spatiotemporal dimensions of two-dimensional datasets. The method can be applied to spectra that are relatively inhomogeneous because it provides fairly effective and selective targeting of spikes resulting in minimal distortion of spectra. Relatively effective spike removal obtained with full automation could provide substantial benefits to users where large numbers of spectra must be processed.

A new fully automated FTIR system for total column measurements of greenhouse gases

Directory of Open Access Journals (Sweden)

M. C. Geibel

2010-10-01

Full Text Available This article introduces a new fully automated FTIR system that is part of the Total Carbon Column Observing Network (TCCON. It will provide continuous ground-based measurements of column-averaged volume mixing ratio for CO₂, CH₄ and several other greenhouse gases in the tropics.

Housed in a 20-foot shipping container it was developed as a transportable system that could be deployed almost anywhere in the world. We describe the automation concept which relies on three autonomous subsystems and their interaction. Crucial components like a sturdy and reliable solar tracker dome are described in detail. The automation software employs a new approach relying on multiple processes, database logging and web-based remote control.

First results of total column measurements at Jena, Germany show that the instrument works well and can provide parts of the diurnal as well as seasonal cycle for CO₂. Instrument line shape measurements with an HCl cell suggest that the instrument stays well-aligned over several months.

After a short test campaign for side by side intercomaprison with an existing TCCON instrument in Australia, the system will be transported to its final destination Ascension Island.

Performance of a fully automated program for measurement of left ventricular ejection fraction

International Nuclear Information System (INIS)

Douglass, K.H.; Tibbits, P.; Kasecamp, W.; Han, S.T.; Koller, D.; Links, J.M.; Wagner, H.H. Jr.

1982-01-01

A fully automated program developed by us for measurement of left ventricular ejection fraction from equilibrium gated blood studies was evaluated in 130 additional patients. Both of 6-min (130 studies) and 2-min (142 studies in 31 patients) gated blood pool studies were acquired and processed. The program successfully generated ejection fractions in 86% of the studies. These automatically generated ejection fractions were compared with ejection fractions derived from manually drawn regions the interest. When studies were acquired for 6-min with the patient at rest, the correlation between automated and manual ejection fractions was 0.92. When studies were acquired for 2-min, both at rest and during bicycle exercise, the correlation was 0.81. In 25 studies from patients who also underwent contrast ventriculography, the program successfully generated regions of interest in 22 (88%). The correlation between the ejection fraction determined by contrast ventriculography and the automatically generated radionuclide ejection fraction was 0.79. (orig.)

Sensors and Automated Analyzers for Radionuclides

International Nuclear Information System (INIS)

Grate, Jay W.; Egorov, Oleg B.

2003-01-01

The production of nuclear weapons materials has generated large quantities of nuclear waste and significant environmental contamination. We have developed new, rapid, automated methods for determination of radionuclides using sequential injection methodologies to automate extraction chromatographic separations, with on-line flow-through scintillation counting for real time detection. This work has progressed in two main areas: radionuclide sensors for water monitoring and automated radiochemical analyzers for monitoring nuclear waste processing operations. Radionuclide sensors have been developed that collect and concentrate radionuclides in preconcentrating minicolumns with dual functionality: chemical selectivity for radionuclide capture and scintillation for signal output. These sensors can detect pertechnetate to below regulatory levels and have been engineered into a prototype for field testing. A fully automated process monitor has been developed for total technetium in nuclear waste streams. This instrument performs sample acidification, speciation adjustment, separation and detection in fifteen minutes or less

Fully Automated Data Collection Using PAM and the Development of PAM/SPACE Reversible Cassettes

Science.gov (United States)

Hiraki, Masahiko; Watanabe, Shokei; Chavas, Leonard M. G.; Yamada, Yusuke; Matsugaki, Naohiro; Igarashi, Noriyuki; Wakatsuki, Soichi; Fujihashi, Masahiro; Miki, Kunio; Baba, Seiki; Ueno, Go; Yamamoto, Masaki; Suzuki, Mamoru; Nakagawa, Atsushi; Watanabe, Nobuhisa; Tanaka, Isao

2010-06-01

To remotely control and automatically collect data in high-throughput X-ray data collection experiments, the Structural Biology Research Center at the Photon Factory (PF) developed and installed sample exchange robots PAM (PF Automated Mounting system) at PF macromolecular crystallography beamlines; BL-5A, BL-17A, AR-NW12A and AR-NE3A. We developed and installed software that manages the flow of the automated X-ray experiments; sample exchanges, loop-centering and X-ray diffraction data collection. The fully automated data collection function has been available since February 2009. To identify sample cassettes, PAM employs a two-dimensional bar code reader. New beamlines, BL-1A at the Photon Factory and BL32XU at SPring-8, are currently under construction as part of Targeted Proteins Research Program (TPRP) by the Ministry of Education, Culture, Sports, Science and Technology of Japan. However, different robots, PAM and SPACE (SPring-8 Precise Automatic Cryo-sample Exchanger), will be installed at BL-1A and BL32XU, respectively. For the convenience of the users of both facilities, pins and cassettes for PAM and SPACE are developed as part of the TPRP.

Reliability of fully automated versus visually controlled pre- and post-processing of resting-state EEG.

Science.gov (United States)

Hatz, F; Hardmeier, M; Bousleiman, H; Rüegg, S; Schindler, C; Fuhr, P

2015-02-01

To compare the reliability of a newly developed Matlab® toolbox for the fully automated, pre- and post-processing of resting state EEG (automated analysis, AA) with the reliability of analysis involving visually controlled pre- and post-processing (VA). 34 healthy volunteers (age: median 38.2 (20-49), 82% female) had three consecutive 256-channel resting-state EEG at one year intervals. Results of frequency analysis of AA and VA were compared with Pearson correlation coefficients, and reliability over time was assessed with intraclass correlation coefficients (ICC). Mean correlation coefficient between AA and VA was 0.94±0.07, mean ICC for AA 0.83±0.05 and for VA 0.84±0.07. AA and VA yield very similar results for spectral EEG analysis and are equally reliable. AA is less time-consuming, completely standardized, and independent of raters and their training. Automated processing of EEG facilitates workflow in quantitative EEG analysis. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Self-consistent hybrid functionals for solids: a fully-automated implementation

Science.gov (United States)

Erba, A.

2017-08-01

A fully-automated algorithm for the determination of the system-specific optimal fraction of exact exchange in self-consistent hybrid functionals of the density-functional-theory is illustrated, as implemented into the public Crystal program. The exchange fraction of this new class of functionals is self-consistently updated proportionally to the inverse of the dielectric response of the system within an iterative procedure (Skone et al 2014 Phys. Rev. B 89, 195112). Each iteration of the present scheme, in turn, implies convergence of a self-consistent-field (SCF) and a coupled-perturbed-Hartree-Fock/Kohn-Sham (CPHF/KS) procedure. The present implementation, beside improving the user-friendliness of self-consistent hybrids, exploits the unperturbed and electric-field perturbed density matrices from previous iterations as guesses for subsequent SCF and CPHF/KS iterations, which is documented to reduce the overall computational cost of the whole process by a factor of 2.

Development and evaluation of fully automated demand response in large facilities

Energy Technology Data Exchange (ETDEWEB)

Piette, Mary Ann; Sezgen, Osman; Watson, David S.; Motegi, Naoya; Shockman, Christine; ten Hope, Laurie

2004-03-30

This report describes the results of a research project to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. The two main drivers for widespread demand responsiveness are the prevention of future electricity crises and the reduction of electricity prices. Additional goals for price responsiveness include equity through cost of service pricing, and customer control of electricity usage and bills. The technology developed and evaluated in this report could be used to support numerous forms of DR programs and tariffs. For the purpose of this report, we have defined three levels of Demand Response automation. Manual Demand Response involves manually turning off lights or equipment; this can be a labor-intensive approach. Semi-Automated Response involves the use of building energy management control systems for load shedding, where a preprogrammed load shedding strategy is initiated by facilities staff. Fully-Automated Demand Response is initiated at a building or facility through receipt of an external communications signal--facility staff set up a pre-programmed load shedding strategy which is automatically initiated by the system without the need for human intervention. We have defined this approach to be Auto-DR. An important concept in Auto-DR is that a facility manager is able to ''opt out'' or ''override'' an individual DR event if it occurs at a time when the reduction in end-use services is not desirable. This project sought to improve the feasibility and nature of Auto-DR strategies in large facilities. The research focused on technology development, testing

Automated detection of exudates for diabetic retinopathy screening

International Nuclear Information System (INIS)

Fleming, Alan D; Philip, Sam; Goatman, Keith A; Williams, Graeme J; Olson, John A; Sharp, Peter F

2007-01-01

Automated image analysis is being widely sought to reduce the workload required for grading images resulting from diabetic retinopathy screening programmes. The recognition of exudates in retinal images is an important goal for automated analysis since these are one of the indicators that the disease has progressed to a stage requiring referral to an ophthalmologist. Candidate exudates were detected using a multi-scale morphological process. Based on local properties, the likelihoods of a candidate being a member of classes exudate, drusen or background were determined. This leads to a likelihood of the image containing exudates which can be thresholded to create a binary decision. Compared to a clinical reference standard, images containing exudates were detected with sensitivity 95.0% and specificity 84.6% in a test set of 13 219 images of which 300 contained exudates. Depending on requirements, this method could form part of an automated system to detect images showing either any diabetic retinopathy or referable diabetic retinopathy

Automated detection of exudates for diabetic retinopathy screening

Energy Technology Data Exchange (ETDEWEB)

Fleming, Alan D [Biomedical Physics, University of Aberdeen, Aberdeen, AB25 2ZD (United Kingdom); Philip, Sam [Diabetes Retinal Screening Service, David Anderson Building, Foresterhill Road, Aberdeen, AB25 2ZP (United Kingdom); Goatman, Keith A [Biomedical Physics, University of Aberdeen, Aberdeen, AB25 2ZD (United Kingdom); Williams, Graeme J [Diabetes Retinal Screening Service, David Anderson Building, Foresterhill Road, Aberdeen, AB25 2ZP (United Kingdom); Olson, John A [Diabetes Retinal Screening Service, David Anderson Building, Foresterhill Road, Aberdeen, AB25 2ZP (United Kingdom); Sharp, Peter F [Biomedical Physics, University of Aberdeen, Aberdeen, AB25 2ZD (United Kingdom)

2007-12-21

Automated image analysis is being widely sought to reduce the workload required for grading images resulting from diabetic retinopathy screening programmes. The recognition of exudates in retinal images is an important goal for automated analysis since these are one of the indicators that the disease has progressed to a stage requiring referral to an ophthalmologist. Candidate exudates were detected using a multi-scale morphological process. Based on local properties, the likelihoods of a candidate being a member of classes exudate, drusen or background were determined. This leads to a likelihood of the image containing exudates which can be thresholded to create a binary decision. Compared to a clinical reference standard, images containing exudates were detected with sensitivity 95.0% and specificity 84.6% in a test set of 13 219 images of which 300 contained exudates. Depending on requirements, this method could form part of an automated system to detect images showing either any diabetic retinopathy or referable diabetic retinopathy.

Automated detection of exudates for diabetic retinopathy screening

Science.gov (United States)

Fleming, Alan D.; Philip, Sam; Goatman, Keith A.; Williams, Graeme J.; Olson, John A.; Sharp, Peter F.

2007-12-01

Automated image analysis is being widely sought to reduce the workload required for grading images resulting from diabetic retinopathy screening programmes. The recognition of exudates in retinal images is an important goal for automated analysis since these are one of the indicators that the disease has progressed to a stage requiring referral to an ophthalmologist. Candidate exudates were detected using a multi-scale morphological process. Based on local properties, the likelihoods of a candidate being a member of classes exudate, drusen or background were determined. This leads to a likelihood of the image containing exudates which can be thresholded to create a binary decision. Compared to a clinical reference standard, images containing exudates were detected with sensitivity 95.0% and specificity 84.6% in a test set of 13 219 images of which 300 contained exudates. Depending on requirements, this method could form part of an automated system to detect images showing either any diabetic retinopathy or referable diabetic retinopathy.

Automated Detection of Sepsis Using Electronic Medical Record Data: A Systematic Review.

Science.gov (United States)

Despins, Laurel A

Severe sepsis and septic shock are global issues with high mortality rates. Early recognition and intervention are essential to optimize patient outcomes. Automated detection using electronic medical record (EMR) data can assist this process. This review describes automated sepsis detection using EMR data. PubMed retrieved publications between January 1, 2005 and January 31, 2015. Thirteen studies met study criteria: described an automated detection approach with the potential to detect sepsis or sepsis-related deterioration in real or near-real time; focused on emergency department and hospitalized neonatal, pediatric, or adult patients; and provided performance measures or results indicating the impact of automated sepsis detection. Detection algorithms incorporated systemic inflammatory response and organ dysfunction criteria. Systems in nine studies generated study or care team alerts. Care team alerts did not consistently lead to earlier interventions. Earlier interventions did not consistently translate to improved patient outcomes. Performance measures were inconsistent. Automated sepsis detection is potentially a means to enable early sepsis-related therapy but current performance variability highlights the need for further research.

3D model assisted fully automated scanning laser Doppler vibrometer measurements

Science.gov (United States)

Sels, Seppe; Ribbens, Bart; Bogaerts, Boris; Peeters, Jeroen; Vanlanduit, Steve

2017-12-01

In this paper, a new fully automated scanning laser Doppler vibrometer (LDV) measurement technique is presented. In contrast to existing scanning LDV techniques which use a 2D camera for the manual selection of sample points, we use a 3D Time-of-Flight camera in combination with a CAD file of the test object to automatically obtain measurements at pre-defined locations. The proposed procedure allows users to test prototypes in a shorter time because physical measurement locations are determined without user interaction. Another benefit from this methodology is that it incorporates automatic mapping between a CAD model and the vibration measurements. This mapping can be used to visualize measurements directly on a 3D CAD model. The proposed method is illustrated with vibration measurements of an unmanned aerial vehicle

Fully automated chest wall line segmentation in breast MRI by using context information

Science.gov (United States)

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.; Localio, A. Russell; Schnall, Mitchell D.; Kontos, Despina

2012-03-01

Breast MRI has emerged as an effective modality for the clinical management of breast cancer. Evidence suggests that computer-aided applications can further improve the diagnostic accuracy of breast MRI. A critical and challenging first step for automated breast MRI analysis, is to separate the breast as an organ from the chest wall. Manual segmentation or user-assisted interactive tools are inefficient, tedious, and error-prone, which is prohibitively impractical for processing large amounts of data from clinical trials. To address this challenge, we developed a fully automated and robust computerized segmentation method that intensively utilizes context information of breast MR imaging and the breast tissue's morphological characteristics to accurately delineate the breast and chest wall boundary. A critical component is the joint application of anisotropic diffusion and bilateral image filtering to enhance the edge that corresponds to the chest wall line (CWL) and to reduce the effect of adjacent non-CWL tissues. A CWL voting algorithm is proposed based on CWL candidates yielded from multiple sequential MRI slices, in which a CWL representative is generated and used through a dynamic time warping (DTW) algorithm to filter out inferior candidates, leaving the optimal one. Our method is validated by a representative dataset of 20 3D unilateral breast MRI scans that span the full range of the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) fibroglandular density categorization. A promising performance (average overlay percentage of 89.33%) is observed when the automated segmentation is compared to manually segmented ground truth obtained by an experienced breast imaging radiologist. The automated method runs time-efficiently at ~3 minutes for each breast MR image set (28 slices).

Validation of a fully automated robotic setup for preparation of whole blood samples for LC-MS toxicology analysis

DEFF Research Database (Denmark)

Andersen, David Wederkinck; Rasmussen, Brian; Linnet, Kristian

2012-01-01

A fully automated setup was developed for preparing whole blood samples using a Tecan Evo workstation. By integrating several add-ons to the robotic platform, the flexible setup was able to prepare samples from sample tubes to a 96-well sample plate ready for injection on liquid chromatography...

Multi-Branch Fully Convolutional Network for Face Detection

KAUST Repository

Bai, Yancheng; Ghanem, Bernard

2017-01-01

Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully

Automated radiometric detection of bacteria

International Nuclear Information System (INIS)

Waters, J.R.

1974-01-01

A new radiometric method called BACTEC, used for the detection of bacteria in cultures or in supposedly sterile samples, was discussed from the standpoint of methodology, both automated and semi-automated. Some of the results obtained so far were reported and some future applications and development possibilities were described. In this new method, the test sample is incubated in a sealed vial with a liquid culture medium containing a 14 C-labeled substrate. If bacteria are present, they break down the substrate, producing 14 CO 2 which is periodically extracted from the vial as a gas and is tested for radioactivity. If this gaseous radioactivity exceeds a threshold level, it is evidence of bacterial presence and growth in the test vial. The first application was for the detection of bacteria in the blood cultures of hospital patients. Data were presented showing typical results. Also discussed were future applications, such as rapid screening for bacteria in urine industrial sterility testing and the disposal of used 14 C substrates. (Mukohata, S.)

The role of haemorrhage and exudate detection in automated grading of diabetic retinopathy.

Science.gov (United States)

Fleming, Alan D; Goatman, Keith A; Philip, Sam; Williams, Graeme J; Prescott, Gordon J; Scotland, Graham S; McNamee, Paul; Leese, Graham P; Wykes, William N; Sharp, Peter F; Olson, John A

2010-06-01

Automated grading has the potential to improve the efficiency of diabetic retinopathy screening services. While disease/no disease grading can be performed using only microaneurysm detection and image-quality assessment, automated recognition of other types of lesions may be advantageous. This study investigated whether inclusion of automated recognition of exudates and haemorrhages improves the detection of observable/referable diabetic retinopathy. Images from 1253 patients with observable/referable retinopathy and 6333 patients with non-referable retinopathy were obtained from three grading centres. All images were reference-graded, and automated disease/no disease assessments were made based on microaneurysm detection and combined microaneurysm, exudate and haemorrhage detection. Introduction of algorithms for exudates and haemorrhages resulted in a statistically significant increase in the sensitivity for detection of observable/referable retinopathy from 94.9% (95% CI 93.5 to 96.0) to 96.6% (95.4 to 97.4) without affecting manual grading workload. Automated detection of exudates and haemorrhages improved the detection of observable/referable retinopathy.

Fully-automated in-syringe dispersive liquid-liquid microextraction for the determination of caffeine in coffee beverages.

Science.gov (United States)

Frizzarin, Rejane M; Maya, Fernando; Estela, José M; Cerdà, Víctor

2016-12-01

A novel fully-automated magnetic stirring-assisted lab-in-syringe analytical procedure has been developed for the fast and efficient dispersive liquid-liquid microextraction (DLLME) of caffeine in coffee beverages. The procedure is based on the microextraction of caffeine with a minute amount of dichloromethane, isolating caffeine from the sample matrix with no further sample pretreatment. Selection of the relevant extraction parameters such as the dispersive solvent, proportion of aqueous/organic phase, pH and flow rates have been carefully evaluated. Caffeine quantification was linear from 2 to 75mgL(-1), with detection and quantification limits of 0.46mgL(-1) and 1.54mgL(-1), respectively. A coefficient of variation (n=8; 5mgL(-1)) of a 2.1% and a sampling rate of 16h(-1), were obtained. The procedure was satisfactorily applied to the determination of caffeine in brewed, instant and decaf coffee samples, being the results for the sample analysis validated using high-performance liquid chromatography. Copyright © 2016 Elsevier Ltd. All rights reserved.

Toward fully automated genotyping: Allele assignment, pedigree construction, phase determination, and recombination detection in Duchenne muscular dystrophy

Energy Technology Data Exchange (ETDEWEB)

Perlin, M.W.; Burks, M.B. [Carnegie Mellon Univ., Pittsburgh, PA (United States); Hoop, R.C.; Hoffman, E.P. [Univ. of Pittsburgh School of Medicine, PA (United States)

1994-10-01

Human genetic maps have made quantum leaps in the past few years, because of the characterization of >2,000 CA dinucleotide repeat loci: these PCR-based markers offer extraordinarily high PIC, and within the next year their density is expected to reach intervals of a few centimorgans per marker. These new genetic maps open new avenues for disease gene research, including large-scale genotyping for both simple and complex disease loci. However, the allele patterns of many dinucleotide repeat loci can be complex and difficult to interpret, with genotyping errors a recognized problem. Furthermore, the possibility of genotyping individuals at hundreds or thousands of polymorphic loci requires improvements in data handling and analysis. The automation of genotyping and analysis of computer-derived haplotypes would remove many of the barriers preventing optimal use of dense and informative dinucleotide genetic maps. Toward this end, we have automated the allele identification, genotyping, phase determinations, and inheritance consistency checks generated by four CA repeats within the 2.5-Mbp, 10-cM X-linked dystrophin gene, using fluorescein-labeled multiplexed PCR products analyzed on automated sequencers. The described algorithms can deconvolute and resolve closely spaced alleles, despite interfering stutter noise; set phase in females; propagate the phase through the family; and identify recombination events. We show the implementation of these algorithms for the completely automated interpretation of allele data and risk assessment for five Duchenne/Becker muscular dystrophy families. The described approach can be scaled up to perform genome-based analyses with hundreds or thousands of CA-repeat loci, using multiple fluorophors on automated sequencers. 16 refs., 5 figs., 1 tab.

Fully automatic AI-based leak detection system

Energy Technology Data Exchange (ETDEWEB)

Tylman, Wojciech; Kolczynski, Jakub [Dept. of Microelectronics and Computer Science, Technical University of Lodz in Poland, ul. Wolczanska 221/223, Lodz (Poland); Anders, George J. [Kinectrics Inc., 800 Kipling Ave., Toronto, Ontario M8Z 6C4 (Canada)

2010-09-15

This paper presents a fully automatic system intended to detect leaks of dielectric fluid in underground high-pressure, fluid-filled (HPFF) cables. The system combines a number of artificial intelligence (AI) and data processing techniques to achieve high detection capabilities for various rates of leaks, including leaks as small as 15 l per hour. The system achieves this level of precision mainly thanks to a novel auto-tuning procedure, enabling learning of the Bayesian network - the decision-making component of the system - using simulated leaks of various rates. Significant new developments extending the capabilities of the original leak detection system described in and form the basis of this paper. Tests conducted on the real-life HPFF cable system in New York City are also discussed. (author)

FPGA-Based Real-Time Motion Detection for Automated Video Surveillance Systems

Directory of Open Access Journals (Sweden)

Sanjay Singh

2016-03-01

Full Text Available Design of automated video surveillance systems is one of the exigent missions in computer vision community because of their ability to automatically select frames of interest in incoming video streams based on motion detection. This research paper focuses on the real-time hardware implementation of a motion detection algorithm for such vision based automated surveillance systems. A dedicated VLSI architecture has been proposed and designed for clustering-based motion detection scheme. The working prototype of a complete standalone automated video surveillance system, including input camera interface, designed motion detection VLSI architecture, and output display interface, with real-time relevant motion detection capabilities, has been implemented on Xilinx ML510 (Virtex-5 FX130T FPGA platform. The prototyped system robustly detects the relevant motion in real-time in live PAL (720 × 576 resolution video streams directly coming from the camera.

A fully automated and scalable timing probe-based method for time alignment of the LabPET II scanners

Science.gov (United States)

Samson, Arnaud; Thibaudeau, Christian; Bouchard, Jonathan; Gaudin, Émilie; Paulin, Caroline; Lecomte, Roger; Fontaine, Réjean

2018-05-01

A fully automated time alignment method based on a positron timing probe was developed to correct the channel-to-channel coincidence time dispersion of the LabPET II avalanche photodiode-based positron emission tomography (PET) scanners. The timing probe was designed to directly detect positrons and generate an absolute time reference. The probe-to-channel coincidences are recorded and processed using firmware embedded in the scanner hardware to compute the time differences between detector channels. The time corrections are then applied in real-time to each event in every channel during PET data acquisition to align all coincidence time spectra, thus enhancing the scanner time resolution. When applied to the mouse version of the LabPET II scanner, the calibration of 6 144 channels was performed in less than 15 min and showed a 47% improvement on the overall time resolution of the scanner, decreasing from 7 ns to 3.7 ns full width at half maximum (FWHM).

A fully automated system for ultrasonic power measurement and simulation accordingly to IEC 61161:2006

International Nuclear Information System (INIS)

Costa-Felix, Rodrigo P B; Alvarenga, Andre V; Hekkenberg, Rob

2011-01-01

The ultrasonic power measurement, worldwide accepted, standard is the IEC 61161, presently in its 2nd edition (2006), but under review. To fulfil its requirements, considering that a radiation force balance is to be used as ultrasonic power detector, a large amount of raw data (mass measurement) shall be collected as function of time to perform all necessary calculations and corrections. Uncertainty determination demands calculation effort of raw and processed data. Although it is possible to be undertaken in an old-fashion way, using spread sheets and manual data collection, automation software are often used in metrology to provide a virtually error free environment concerning data acquisition and repetitive calculations and corrections. Considering that, a fully automate ultrasonic power measurement system was developed and comprehensively tested. A 0,1 mg of precision balance model CP224S (Sartorius, Germany) was used as measuring device and a calibrated continuous wave ultrasound check source (Precision Acoustics, UK) was the device under test. A 150 ml container filled with degassed water and containing an absorbing target at the bottom was placed on the balance pan. Besides the feature of automation software, a routine of power measurement simulation was implemented. It was idealized as a teaching tool of how ultrasonic power emission behaviour is with a radiation force balance equipped with an absorbing target. Automation software was considered as an effective tool for speeding up ultrasonic power measurement, while allowing accurate calculation and attractive graphical partial and final results.

A review on automated pavement distress detection methods

NARCIS (Netherlands)

Coenen, Tom B.J.; Golroo, Amir

2017-01-01

In recent years, extensive research has been conducted on pavement distress detection. A large part of these studies applied automated methods to capture different distresses. In this paper, a literature review on the distresses and related detection methods are presented. This review also includes

A fully automated FTIR system for remote sensing of greenhouse gases in the tropics

Science.gov (United States)

Geibel, M. C.; Gerbig, C.; Feist, D. G.

2010-07-01

This article introduces a new fully automated FTIR system that is part of the Total Carbon Column Observing Network. It will provide continuous ground-based measurements of column-averaged volume mixing ratio for CO2, CH4 and several other greenhouse gases in the tropics. Housed in a 20-foot shipping container it was developed as a transportable system that could be deployed almost anywhere in the world. We describe the automation concept which relies on three autonomous subsystems and their interaction. Crucial components like a sturdy and reliable solar tracker dome are described in detail. First results of total column measurements at Jena, Germany show that the instrument works well and can provide diurnal as well as seasonal cycle for CO2. Instrument line shape measurements with an HCl cell suggest that the instrument stays well-aligned over several months. After a short test campaign for side by side intercomaprison with an existing TCCON instrument in Australia, the system will be transported to its final destination Ascension Island.

A fully automated entanglement-based quantum cryptography system for telecom fiber networks

International Nuclear Information System (INIS)

Treiber, Alexander; Ferrini, Daniele; Huebel, Hannes; Zeilinger, Anton; Poppe, Andreas; Loruenser, Thomas; Querasser, Edwin; Matyus, Thomas; Hentschel, Michael

2009-01-01

We present in this paper a quantum key distribution (QKD) system based on polarization entanglement for use in telecom fibers. A QKD exchange up to 50 km was demonstrated in the laboratory with a secure key rate of 550 bits s -1 . The system is compact and portable with a fully automated start-up, and stabilization modules for polarization, synchronization and photon coupling allow hands-off operation. Stable and reliable key exchange in a deployed optical fiber of 16 km length was demonstrated. In this fiber network, we achieved over 2 weeks an automatic key generation with an average key rate of 2000 bits s -1 without manual intervention. During this period, the system had an average entanglement visibility of 93%, highlighting the technical level and stability achieved for entanglement-based quantum cryptography.

Driver Vigilance in Automated Vehicles: Hazard Detection Failures Are a Matter of Time.

Science.gov (United States)

Greenlee, Eric T; DeLucia, Patricia R; Newton, David C

2018-03-01

The primary aim of the current study was to determine whether monitoring the roadway for hazards during automated driving results in a vigilance decrement. Although automated vehicles are relatively novel, the nature of human-automation interaction within them has the classic hallmarks of a vigilance task. Drivers must maintain attention for prolonged periods of time to detect and respond to rare and unpredictable events, for example, roadway hazards that automation may be ill equipped to detect. Given the similarity with traditional vigilance tasks, we predicted that drivers of a simulated automated vehicle would demonstrate a vigilance decrement in hazard detection performance. Participants "drove" a simulated automated vehicle for 40 minutes. During that time, their task was to monitor the roadway for roadway hazards. As predicted, hazard detection rate declined precipitously, and reaction times slowed as the drive progressed. Further, subjective ratings of workload and task-related stress indicated that sustained monitoring is demanding and distressing and it is a challenge to maintain task engagement. Monitoring the roadway for potential hazards during automated driving results in workload, stress, and performance decrements similar to those observed in traditional vigilance tasks. To the degree that vigilance is required of automated vehicle drivers, performance errors and associated safety risks are likely to occur as a function of time on task. Vigilance should be a focal safety concern in the development of vehicle automation.

A device for fully automated on-site process monitoring and control of trihalomethane concentrations in drinking water

International Nuclear Information System (INIS)

Brown, Aaron W.; Simone, Paul S.; York, J.C.; Emmert, Gary L.

2015-01-01

Highlights: • Commercial device for on-line monitoring of trihalomethanes in drinking water. • Method detection limits for individual trihalomethanes range from 0.01–0.04 μg L –1 . • Rugged and robust device operates automatically for on-site process control. • Used for process mapping and process optimization to reduce treatment costs. • Hourly measurements of trihalomethanes made continuously for ten months. - Abstract: An instrument designed for fully automated on-line monitoring of trihalomethane concentrations in chlorinated drinking water is presented. The patented capillary membrane sampling device automatically samples directly from a water tap followed by injection of the sample into a gas chromatograph equipped with a nickel-63 electron capture detector. Detailed studies using individual trihalomethane species exhibited method detection limits ranging from 0.01–0.04 μg L −1 . Mean percent recoveries ranged from 77.1 to 86.5% with percent relative standard deviation values ranging from 1.2 to 4.6%. Out of more than 5200 samples analyzed, 95% of the concentration ranges were detectable, 86.5% were quantifiable. The failure rate was less than 2%. Using the data from the instrument, two different treatment processes were optimized so that total trihalomethane concentrations were maintained at acceptable levels while reducing treatment costs significantly. This ongoing trihalomethane monitoring program has been operating for more than ten months and has produced the longest continuous and most finely time-resolved data on trihalomethane concentrations reported in the literature

A device for fully automated on-site process monitoring and control of trihalomethane concentrations in drinking water

Energy Technology Data Exchange (ETDEWEB)

Brown, Aaron W. [The University of Memphis, Department of Chemistry, Memphis, TN 38152 (United States); Simone, Paul S. [The University of Memphis, Department of Chemistry, Memphis, TN 38152 (United States); Foundation Instruments, Inc., Collierville, TN 38017 (United States); York, J.C. [City of Lebanon, TN Water Treatment Plant, 7 Gilmore Hill Rd., Lebanon, TN 37087 (United States); Emmert, Gary L., E-mail: gemmert@memphis.edu [The University of Memphis, Department of Chemistry, Memphis, TN 38152 (United States); Foundation Instruments, Inc., Collierville, TN 38017 (United States)

2015-01-01

Highlights: • Commercial device for on-line monitoring of trihalomethanes in drinking water. • Method detection limits for individual trihalomethanes range from 0.01–0.04 μg L{sup –1}. • Rugged and robust device operates automatically for on-site process control. • Used for process mapping and process optimization to reduce treatment costs. • Hourly measurements of trihalomethanes made continuously for ten months. - Abstract: An instrument designed for fully automated on-line monitoring of trihalomethane concentrations in chlorinated drinking water is presented. The patented capillary membrane sampling device automatically samples directly from a water tap followed by injection of the sample into a gas chromatograph equipped with a nickel-63 electron capture detector. Detailed studies using individual trihalomethane species exhibited method detection limits ranging from 0.01–0.04 μg L{sup −1}. Mean percent recoveries ranged from 77.1 to 86.5% with percent relative standard deviation values ranging from 1.2 to 4.6%. Out of more than 5200 samples analyzed, 95% of the concentration ranges were detectable, 86.5% were quantifiable. The failure rate was less than 2%. Using the data from the instrument, two different treatment processes were optimized so that total trihalomethane concentrations were maintained at acceptable levels while reducing treatment costs significantly. This ongoing trihalomethane monitoring program has been operating for more than ten months and has produced the longest continuous and most finely time-resolved data on trihalomethane concentrations reported in the literature.

Fully automated synthesis of 11C-acetate as tumor PET tracer by simple modified solid-phase extraction purification

International Nuclear Information System (INIS)

Tang, Xiaolan; Tang, Ganghua; Nie, Dahong

2013-01-01

Introduction: Automated synthesis of 11 C-acetate ( 11 C-AC) as the most commonly used radioactive fatty acid tracer is performed by a simple, rapid, and modified solid-phase extraction (SPE) purification. Methods: Automated synthesis of 11 C-AC was implemented by carboxylation reaction of MeMgBr on a polyethylene Teflon loop ring with 11 C-CO 2 , followed by acidic hydrolysis with acid and SCX cartridge, and purification on SCX, AG11A8 and C18 SPE cartridges using a commercially available 11 C-tracer synthesizer. Quality control test and animals positron emission tomography (PET) imaging were also carried out. Results: A high and reproducible decay-uncorrected radiochemical yield of (41.0±4.6)% (n=10) was obtained from 11 C-CO 2 within the whole synthesis time about 8 min. The radiochemical purity of 11 C-AC was over 95% by high-performance liquid chromatography (HPLC) analysis. Quality control test and PET imaging showed that 11 C-AC injection produced by the simple SPE procedure was safe and efficient, and was in agreement with the current Chinese radiopharmaceutical quality control guidelines. Conclusion: The novel, simple, and rapid method is readily adapted to the fully automated synthesis of 11 C-AC on several existing commercial synthesis module. The method can be used routinely to produce 11 C-AC for preclinical and clinical studies with PET imaging. - Highlights: • A fully automated synthesis of 11 C-acetate by simple modified solid-phase extraction purification has been developed. • Typical non-decay-corrected yields were (41.0±4.6)% (n=10) • Radiochemical purity was determined by radio-HPLC analysis on a C18 column using the gradient program, instead of expensive organic acid column or anion column. • QC testing (RCP>99%)

Assessment of automated disease detection in diabetic retinopathy screening using two-field photography.

Science.gov (United States)

Goatman, Keith; Charnley, Amanda; Webster, Laura; Nussey, Stephen

2011-01-01

To assess the performance of automated disease detection in diabetic retinopathy screening using two field mydriatic photography. Images from 8,271 sequential patient screening episodes from a South London diabetic retinopathy screening service were processed by the Medalytix iGrading™ automated grading system. For each screening episode macular-centred and disc-centred images of both eyes were acquired and independently graded according to the English national grading scheme. Where discrepancies were found between the automated result and original manual grade, internal and external arbitration was used to determine the final study grades. Two versions of the software were used: one that detected microaneurysms alone, and one that detected blot haemorrhages and exudates in addition to microaneurysms. Results for each version were calculated once using both fields and once using the macula-centred field alone. Of the 8,271 episodes, 346 (4.2%) were considered unassessable. Referable disease was detected in 587 episodes (7.1%). The sensitivity of the automated system for detecting unassessable images ranged from 97.4% to 99.1% depending on configuration. The sensitivity of the automated system for referable episodes ranged from 98.3% to 99.3%. All the episodes that included proliferative or pre-proliferative retinopathy were detected by the automated system regardless of configuration (192/192, 95% confidence interval 98.0% to 100%). If implemented as the first step in grading, the automated system would have reduced the manual grading effort by between 2,183 and 3,147 patient episodes (26.4% to 38.1%). Automated grading can safely reduce the workload of manual grading using two field, mydriatic photography in a routine screening service.

Performance of a fully automated scatterometer for BRDF and BTDF measurements at visible and infrared wavelengths

International Nuclear Information System (INIS)

Anderson, S.; Shepard, D.F.; Pompea, S.M.; Castonguay, R.

1989-01-01

The general performance of a fully automated scatterometer shows that the instrument can make rapid, accurate BRDF (bidirectional reflectance distribution function) and BTDF (bidirectional transmittance distribution function) measurements of optical surfaces over a range of approximately ten orders of magnitude in BRDF. These measurements can be made for most surfaces even with the detector at the specular angle, because of beam-attenuation techniques. He-Ne and CO2 lasers are used as sources in conjunction with a reference detector and chopper

Automated Detection of HONcode Website Conformity Compared to Manual Detection: An Evaluation

OpenAIRE

Boyer, Célia; Dolamic, Ljiljana

2015-01-01

Background To earn HONcode certification, a website must conform to the 8 principles of the HONcode of Conduct In the current manual process of certification, a HONcode expert assesses the candidate website using precise guidelines for each principle. In the scope of the European project KHRESMOI, the Health on the Net (HON) Foundation has developed an automated system to assist in detecting a website?s HONcode conformity. Automated assistance in conducting HONcode reviews can expedite the cu...

Analysis of xanthines in beverages using a fully automated SPE-SPC-DAD hyphenated system

Energy Technology Data Exchange (ETDEWEB)

Medvedovici, A. [Bucarest Univ., Bucarest (Romania). Faculty of Chemistry, Dept. of Analytical Chemistry; David, F.; David, V.; Sandra, P. [Research Institute of Chromatography, Kortrijk (Belgium)

2000-08-01

Analysis of some xanthines (caffeine, theophylline and theobromine) in beverages has been achieved by a fully automated on-line Solid Phase Extraction - Supercritical Fluid Chromatography - Diode Array Detection (Spe - Sofc - Dad). Three adsorbents have been tested for the Spe procedure: octadecyl modified silicagel (ODS) and two types of styrene-divinylbenzen copolymer based materials, from which Porapack proved to be the most suitable adsorbent. Optimisation and correlation of both Spe and Sofc operational parameters are also discussed. By this technique, caffeine was determined in ice tea and Coca-Cola in a concentration of 0.15 ppm, theobromine - 1.5 ppb, and theophylline - 0.15 ppb. [Italian] Si e' realizzata l'analis di alcune xantine (caffeina, teofillina e teobromina) mediante un sistema, in linea, completamente automatizzato basato su Estrazione in Fase Solida - Cromatografia in Fase Supercritica - Rivelazione con Diode Array (Spe - Sfc - Dad). Per la procedura Spe sono stati valutati tre substrati: silice ottadecilica (ODS) e due tipi di materiali polimerici a base stirene-divinilbenzene, di cui, quello denominato PRP-1, e' risultato essere il piu' efficiente. Sono discusse sia l'ottimizzazione che la correlazione dei parametri operazionali per la Spe e la Sfc. Con questa tecnica sono state determinate, in te' ghiacciato e Coca-Cola, la caffeina, la teobromina e la teofillina alle concentrazini di 0.15, 1.5 e 0.15 ppm.

Fully-automated identification of fish species based on otolith contour: using short-time Fourier transform and discriminant analysis (STFT-DA).

Science.gov (United States)

Salimi, Nima; Loh, Kar Hoe; Kaur Dhillon, Sarinder; Chong, Ving Ching

2016-01-01

Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.

Fully automated segmentation of left ventricle using dual dynamic programming in cardiac cine MR images

Science.gov (United States)

Jiang, Luan; Ling, Shan; Li, Qiang

2016-03-01

Cardiovascular diseases are becoming a leading cause of death all over the world. The cardiac function could be evaluated by global and regional parameters of left ventricle (LV) of the heart. The purpose of this study is to develop and evaluate a fully automated scheme for segmentation of LV in short axis cardiac cine MR images. Our fully automated method consists of three major steps, i.e., LV localization, LV segmentation at end-diastolic phase, and LV segmentation propagation to the other phases. First, the maximum intensity projection image along the time phases of the midventricular slice, located at the center of the image, was calculated to locate the region of interest of LV. Based on the mean intensity of the roughly segmented blood pool in the midventricular slice at each phase, end-diastolic (ED) and end-systolic (ES) phases were determined. Second, the endocardial and epicardial boundaries of LV of each slice at ED phase were synchronously delineated by use of a dual dynamic programming technique. The external costs of the endocardial and epicardial boundaries were defined with the gradient values obtained from the original and enhanced images, respectively. Finally, with the advantages of the continuity of the boundaries of LV across adjacent phases, we propagated the LV segmentation from the ED phase to the other phases by use of dual dynamic programming technique. The preliminary results on 9 clinical cardiac cine MR cases show that the proposed method can obtain accurate segmentation of LV based on subjective evaluation.

Automated vehicle for railway track fault detection

Science.gov (United States)

Bhushan, M.; Sujay, S.; Tushar, B.; Chitra, P.

2017-11-01

For the safety reasons, railroad tracks need to be inspected on a regular basis for detecting physical defects or design non compliances. Such track defects and non compliances, if not detected in a certain interval of time, may eventually lead to severe consequences such as train derailments. Inspection must happen twice weekly by a human inspector to maintain safety standards as there are hundreds and thousands of miles of railroad track. But in such type of manual inspection, there are many drawbacks that may result in the poor inspection of the track, due to which accidents may cause in future. So to avoid such errors and severe accidents, this automated system is designed.Such a concept would surely introduce automation in the field of inspection process of railway track and can help to avoid mishaps and severe accidents due to faults in the track.

A survey on automated wheeze detection systems for asthmatic patients

Directory of Open Access Journals (Sweden)

Syamimi Mardiah Shaharum

2012-11-01

Full Text Available The purpose of this paper is to present an evidence of automated wheeze detection system by a survey that can be very beneficial for asthmatic patients. Generally, for detecting asthma in a patient, stethoscope is used for ascertaining wheezes present. This causes a major problem nowadays because a number of patients tend to delay the interpretation time, which can lead to misinterpretations and in some worst cases to death. Therefore, the development of automated system would ease the burden of medical personnel. A further discussion on automated wheezes detection system will be presented later in the paper. As for the methodology, a systematic search of articles published as early as 1985 to 2012 was conducted. Important details including the hardware used, placement of hardware, and signal processing methods have been presented clearly thus hope to help and encourage future researchers to develop commercial system that will improve the diagnosing and monitoring of asthmatic patients.

Towards an Automated Acoustic Detection System for Free Ranging Elephants.

Science.gov (United States)

Zeppelzauer, Matthias; Hensman, Sean; Stoeger, Angela S

The human-elephant conflict is one of the most serious conservation problems in Asia and Africa today. The involuntary confrontation of humans and elephants claims the lives of many animals and humans every year. A promising approach to alleviate this conflict is the development of an acoustic early warning system. Such a system requires the robust automated detection of elephant vocalizations under unconstrained field conditions. Today, no system exists that fulfills these requirements. In this paper, we present a method for the automated detection of elephant vocalizations that is robust to the diverse noise sources present in the field. We evaluate the method on a dataset recorded under natural field conditions to simulate a real-world scenario. The proposed method outperformed existing approaches and robustly and accurately detected elephants. It thus can form the basis for a future automated early warning system for elephants. Furthermore, the method may be a useful tool for scientists in bioacoustics for the study of wildlife recordings.

DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM.

Science.gov (United States)

Wang, Feng; Gong, Huichao; Liu, Gaochao; Li, Meijing; Yan, Chuangye; Xia, Tian; Li, Xueming; Zeng, Jianyang

2016-09-01

Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated electron cryo-microscopy (cryo-EM). Here we report a deep learning framework, called DeepPicker, to address this problem and fill the current gaps toward a fully automated cryo-EM pipeline. DeepPicker employs a novel cross-molecule training strategy to capture common features of particles from previously-analyzed micrographs, and thus does not require any human intervention during particle picking. Tests on the recently-published cryo-EM data of three complexes have demonstrated that our deep learning based scheme can successfully accomplish the human-level particle picking process and identify a sufficient number of particles that are comparable to those picked manually by human experts. These results indicate that DeepPicker can provide a practically useful tool to significantly reduce the time and manual effort spent in single-particle analysis and thus greatly facilitate high-resolution cryo-EM structure determination. DeepPicker is released as an open-source program, which can be downloaded from https://github.com/nejyeah/DeepPicker-python. Copyright © 2016 Elsevier Inc. All rights reserved.

Fully automated VMAT treatment planning for advanced-stage NSCLC patients

International Nuclear Information System (INIS)

Della Gala, Giuseppe; Dirkx, Maarten L.P.; Hoekstra, Nienke; Fransen, Dennie; Pol, Marjan van de; Heijmen, Ben J.M.; Lanconelli, Nico; Petit, Steven F.

2017-01-01

To develop a fully automated procedure for multicriterial volumetric modulated arc therapy (VMAT) treatment planning (autoVMAT) for stage III/IV non-small cell lung cancer (NSCLC) patients treated with curative intent. After configuring the developed autoVMAT system for NSCLC, autoVMAT plans were compared with manually generated clinically delivered intensity-modulated radiotherapy (IMRT) plans for 41 patients. AutoVMAT plans were also compared to manually generated VMAT plans in the absence of time pressure. For 16 patients with reduced planning target volume (PTV) dose prescription in the clinical IMRT plan (to avoid violation of organs at risk tolerances), the potential for dose escalation with autoVMAT was explored. Two physicians evaluated 35/41 autoVMAT plans (85%) as clinically acceptable. Compared to the manually generated IMRT plans, autoVMAT plans showed statistically significant improved PTV coverage (V_9_5_% increased by 1.1% ± 1.1%), higher dose conformity (R_5_0 reduced by 12.2% ± 12.7%), and reduced mean lung, heart, and esophagus doses (reductions of 0.9 Gy ± 1.0 Gy, 1.5 Gy ± 1.8 Gy, 3.6 Gy ± 2.8 Gy, respectively, all p [de

Automated detection of geomagnetic storms with heightened risk of GIC

Science.gov (United States)

Bailey, Rachel L.; Leonhardt, Roman

2016-06-01

Automated detection of geomagnetic storms is of growing importance to operators of technical infrastructure (e.g., power grids, satellites), which is susceptible to damage caused by the consequences of geomagnetic storms. In this study, we compare three methods for automated geomagnetic storm detection: a method analyzing the first derivative of the geomagnetic variations, another looking at the Akaike information criterion, and a third using multi-resolution analysis of the maximal overlap discrete wavelet transform of the variations. These detection methods are used in combination with an algorithm for the detection of coronal mass ejection shock fronts in ACE solar wind data prior to the storm arrival on Earth as an additional constraint for possible storm detection. The maximal overlap discrete wavelet transform is found to be the most accurate of the detection methods. The final storm detection software, implementing analysis of both satellite solar wind and geomagnetic ground data, detects 14 of 15 more powerful geomagnetic storms over a period of 2 years.

Designing a fully automated multi-bioreactor plant for fast DoE optimization of pharmaceutical protein production.

Science.gov (United States)

Fricke, Jens; Pohlmann, Kristof; Jonescheit, Nils A; Ellert, Andree; Joksch, Burkhard; Luttmann, Reiner

2013-06-01

The identification of optimal expression conditions for state-of-the-art production of pharmaceutical proteins is a very time-consuming and expensive process. In this report a method for rapid and reproducible optimization of protein expression in an in-house designed small-scale BIOSTAT® multi-bioreactor plant is described. A newly developed BioPAT® MFCS/win Design of Experiments (DoE) module (Sartorius Stedim Systems, Germany) connects the process control system MFCS/win and the DoE software MODDE® (Umetrics AB, Sweden) and enables therefore the implementation of fully automated optimization procedures. As a proof of concept, a commercial Pichia pastoris strain KM71H has been transformed for the expression of potential malaria vaccines. This approach has allowed a doubling of intact protein secretion productivity due to the DoE optimization procedure compared to initial cultivation results. In a next step, robustness regarding the sensitivity to process parameter variability has been proven around the determined optimum. Thereby, a pharmaceutical production process that is significantly improved within seven 24-hour cultivation cycles was established. Specifically, regarding the regulatory demands pointed out in the process analytical technology (PAT) initiative of the United States Food and Drug Administration (FDA), the combination of a highly instrumented, fully automated multi-bioreactor platform with proper cultivation strategies and extended DoE software solutions opens up promising benefits and opportunities for pharmaceutical protein production. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fully automated laboratory and field-portable goniometer used for performing accurate and precise multiangular reflectance measurements

Science.gov (United States)

Harms, Justin D.; Bachmann, Charles M.; Ambeau, Brittany L.; Faulring, Jason W.; Ruiz Torres, Andres J.; Badura, Gregory; Myers, Emily

2017-10-01

Field-portable goniometers are created for a wide variety of applications. Many of these applications require specific types of instruments and measurement schemes and must operate in challenging environments. Therefore, designs are based on the requirements that are specific to the application. We present a field-portable goniometer that was designed for measuring the hemispherical-conical reflectance factor (HCRF) of various soils and low-growing vegetation in austere coastal and desert environments and biconical reflectance factors in laboratory settings. Unlike some goniometers, this system features a requirement for "target-plane tracking" to ensure that measurements can be collected on sloped surfaces, without compromising angular accuracy. The system also features a second upward-looking spectrometer to measure the spatially dependent incoming illumination, an integrated software package to provide full automation, an automated leveling system to ensure a standard frame of reference, a design that minimizes the obscuration due to self-shading to measure the opposition effect, and the ability to record a digital elevation model of the target region. This fully automated and highly mobile system obtains accurate and precise measurements of HCRF in a wide variety of terrain and in less time than most other systems while not sacrificing consistency or repeatability in laboratory environments.

Advances toward fully automated in vivo assessment of oral epithelial dysplasia by nuclear endomicroscopy-A pilot study.

Science.gov (United States)

Liese, Jan; Winter, Karsten; Glass, Änne; Bertolini, Julia; Kämmerer, Peer Wolfgang; Frerich, Bernhard; Schiefke, Ingolf; Remmerbach, Torsten W

2017-11-01

Uncertainties in detection of oral epithelial dysplasia (OED) frequently result from sampling error especially in inflammatory oral lesions. Endomicroscopy allows non-invasive, "en face" imaging of upper oral epithelium, but parameters of OED are unknown. Mucosal nuclei were imaged in 34 toluidine blue-stained oral lesions with a commercial endomicroscopy. Histopathological diagnosis showed four biopsies in "dys-/neoplastic," 23 in "inflammatory," and seven in "others" disease groups. Strength of different assessment strategies of nuclear scoring, nuclear count, and automated nuclear analysis were measured by area under ROC curve (AUC) to identify histopathological "dys-/neoplastic" group. Nuclear objects from automated image analysis were visually corrected. Best-performing parameters of nuclear-to-image ratios were the count of large nuclei (AUC=0.986) and 6-nearest neighborhood relation (AUC=0.896), and best parameters of nuclear polymorphism were the count of atypical nuclei (AUC=0.996) and compactness of nuclei (AUC=0.922). Excluding low-grade OED, nuclear scoring and count reached 100% sensitivity and 98% specificity for detection of dys-/neoplastic lesions. In automated analysis, combination of parameters enhanced diagnostic strength. Sensitivity of 100% and specificity of 87% were seen for distances of 6-nearest neighbors and aspect ratios even in uncorrected objects. Correction improved measures of nuclear polymorphism only. The hue of background color was stronger than nuclear density (AUC=0.779 vs 0.687) to detect dys-/neoplastic group indicating that macroscopic aspect is biased. Nuclear-to-image ratios are applicable for automated optical in vivo diagnostics for oral potentially malignant disorders. Nuclear endomicroscopy may promote non-invasive, early detection of dys-/neoplastic lesions by reducing sampling error. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform

Science.gov (United States)

2018-01-01

ARL-TR-8270 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Morphological Filter...Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform by Kwok F Tom Sensors and Electron...1 October 2016–30 September 2017 4. TITLE AND SUBTITLE An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a

Automated detection of diabetic retinopathy lesions on ultrawidefield pseudocolour images.

Science.gov (United States)

Wang, Kang; Jayadev, Chaitra; Nittala, Muneeswar G; Velaga, Swetha B; Ramachandra, Chaithanya A; Bhaskaranand, Malavika; Bhat, Sandeep; Solanki, Kaushal; Sadda, SriniVas R

2018-03-01

We examined the sensitivity and specificity of an automated algorithm for detecting referral-warranted diabetic retinopathy (DR) on Optos ultrawidefield (UWF) pseudocolour images. Patients with diabetes were recruited for UWF imaging. A total of 383 subjects (754 eyes) were enrolled. Nonproliferative DR graded to be moderate or higher on the 5-level International Clinical Diabetic Retinopathy (ICDR) severity scale was considered as grounds for referral. The software automatically detected DR lesions using the previously trained classifiers and classified each image in the test set as referral-warranted or not warranted. Sensitivity, specificity and the area under the receiver operating curve (AUROC) of the algorithm were computed. The automated algorithm achieved a 91.7%/90.3% sensitivity (95% CI 90.1-93.9/80.4-89.4) with a 50.0%/53.6% specificity (95% CI 31.7-72.8/36.5-71.4) for detecting referral-warranted retinopathy at the patient/eye levels, respectively; the AUROC was 0.873/0.851 (95% CI 0.819-0.922/0.804-0.894). Diabetic retinopathy (DR) lesions were detected from Optos pseudocolour UWF images using an automated algorithm. Images were classified as referral-warranted DR with a high degree of sensitivity and moderate specificity. Automated analysis of UWF images could be of value in DR screening programmes and could allow for more complete and accurate disease staging. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

A fully automated multi-modal computer aided diagnosis approach to coronary calcium scoring of MSCT images

Science.gov (United States)

Wu, Jing; Ferns, Gordon; Giles, John; Lewis, Emma

2012-03-01

Inter- and intra- observer variability is a problem often faced when an expert or observer is tasked with assessing the severity of a disease. This issue is keenly felt in coronary calcium scoring of patients suffering from atherosclerosis where in clinical practice, the observer must identify firstly the presence, followed by the location of candidate calcified plaques found within the coronary arteries that may prevent oxygenated blood flow to the heart muscle. However, it can be difficult for a human observer to differentiate calcified plaques that are located in the coronary arteries from those found in surrounding anatomy such as the mitral valve or pericardium. In addition to the benefits to scoring accuracy, the use of fast, low dose multi-slice CT imaging to perform the cardiac scan is capable of acquiring the entire heart within a single breath hold. Thus exposing the patient to lower radiation dose, which for a progressive disease such as atherosclerosis where multiple scans may be required, is beneficial to their health. Presented here is a fully automated method for calcium scoring using both the traditional Agatston method, as well as the volume scoring method. Elimination of the unwanted regions of the cardiac image slices such as lungs, ribs, and vertebrae is carried out using adaptive heart isolation. Such regions cannot contain calcified plaques but can be of a similar intensity and their removal will aid detection. Removal of both the ascending and descending aortas, as they contain clinical insignificant plaques, is necessary before the final calcium scores are calculated and examined against ground truth scores of three averaged expert observer results. The results presented here are intended to show the feasibility and requirement for an automated scoring method to reduce the subjectivity and reproducibility error inherent with manual clinical calcium scoring.

A Framework for Fully Automated Performance Testing for Smart Buildings

DEFF Research Database (Denmark)

Markoska, Elena; Johansen, Aslak; Lazarova-Molnar, Sanja

2018-01-01

, setup of performance tests has been manual and labor-intensive and has required intimate knowledge of buildings’ complexity and systems. The emergence of the concept of smart buildings has provided an opportunity to overcome this restriction. In this paper, we propose a framework for automated......A significant proportion of energy consumption by buildings worldwide, estimated to ca. 40%, has yielded a high importance to studying buildings’ performance. Performance testing is a mean by which buildings can be continuously commissioned to ensure that they operate as designed. Historically...... performance testing of smart buildings that utilizes metadata models. The approach features automatic detection of applicable performance tests using metadata queries and their corresponding instantiation, as well as continuous commissioning based on metadata. The presented approach has been implemented...

Automated detection of a prostate Ni-Ti stent in electronic portal images.

Science.gov (United States)

Carl, Jesper; Nielsen, Henning; Nielsen, Jane; Lund, Bente; Larsen, Erik Hoejkjaer

2006-12-01

Planning target volumes (PTV) in fractionated radiotherapy still have to be outlined with wide margins to the clinical target volume due to uncertainties arising from daily shift of the prostate position. A recently proposed new method of visualization of the prostate is based on insertion of a thermo-expandable Ni-Ti stent. The current study proposes a new detection algorithm for automated detection of the Ni-Ti stent in electronic portal images. The algorithm is based on the Ni-Ti stent having a cylindrical shape with a fixed diameter, which was used as the basis for an automated detection algorithm. The automated method uses enhancement of lines combined with a grayscale morphology operation that looks for enhanced pixels separated with a distance similar to the diameter of the stent. The images in this study are all from prostate cancer patients treated with radiotherapy in a previous study. Images of a stent inserted in a humanoid phantom demonstrated a localization accuracy of 0.4-0.7 mm which equals the pixel size in the image. The automated detection of the stent was compared to manual detection in 71 pairs of orthogonal images taken in nine patients. The algorithm was successful in 67 of 71 pairs of images. The method is fast, has a high success rate, good accuracy, and has a potential for unsupervised localization of the prostate before radiotherapy, which would enable automated repositioning before treatment and allow for the use of very tight PTV margins.

Automated detection of a prostate Ni-Ti stent in electronic portal images

International Nuclear Information System (INIS)

Carl, Jesper; Nielsen, Henning; Nielsen, Jane; Lund, Bente; Larsen, Erik Hoejkjaer

2006-01-01

Planning target volumes (PTV) in fractionated radiotherapy still have to be outlined with wide margins to the clinical target volume due to uncertainties arising from daily shift of the prostate position. A recently proposed new method of visualization of the prostate is based on insertion of a thermo-expandable Ni-Ti stent. The current study proposes a new detection algorithm for automated detection of the Ni-Ti stent in electronic portal images. The algorithm is based on the Ni-Ti stent having a cylindrical shape with a fixed diameter, which was used as the basis for an automated detection algorithm. The automated method uses enhancement of lines combined with a grayscale morphology operation that looks for enhanced pixels separated with a distance similar to the diameter of the stent. The images in this study are all from prostate cancer patients treated with radiotherapy in a previous study. Images of a stent inserted in a humanoid phantom demonstrated a localization accuracy of 0.4-0.7 mm which equals the pixel size in the image. The automated detection of the stent was compared to manual detection in 71 pairs of orthogonal images taken in nine patients. The algorithm was successful in 67 of 71 pairs of images. The method is fast, has a high success rate, good accuracy, and has a potential for unsupervised localization of the prostate before radiotherapy, which would enable automated repositioning before treatment and allow for the use of very tight PTV margins

Full-text automated detection of surgical site infections secondary to neurosurgery in Rennes, France.

Science.gov (United States)

Campillo-Gimenez, Boris; Garcelon, Nicolas; Jarno, Pascal; Chapplain, Jean Marc; Cuggia, Marc

2013-01-01

The surveillance of Surgical Site Infections (SSI) contributes to the management of risk in French hospitals. Manual identification of infections is costly, time-consuming and limits the promotion of preventive procedures by the dedicated teams. The introduction of alternative methods using automated detection strategies is promising to improve this surveillance. The present study describes an automated detection strategy for SSI in neurosurgery, based on textual analysis of medical reports stored in a clinical data warehouse. The method consists firstly, of enrichment and concept extraction from full-text reports using NOMINDEX, and secondly, text similarity measurement using a vector space model. The text detection was compared to the conventional strategy based on self-declaration and to the automated detection using the diagnosis-related group database. The text-mining approach showed the best detection accuracy, with recall and precision equal to 92% and 40% respectively, and confirmed the interest of reusing full-text medical reports to perform automated detection of SSI.

Fully automated deformable registration of breast DCE-MRI and PET/CT

Science.gov (United States)

Dmitriev, I. D.; Loo, C. E.; Vogel, W. V.; Pengel, K. E.; Gilhuijs, K. G. A.

2013-02-01

Accurate characterization of breast tumors is important for the appropriate selection of therapy and monitoring of the response. For this purpose breast imaging and tissue biopsy are important aspects. In this study, a fully automated method for deformable registration of DCE-MRI and PET/CT of the breast is presented. The registration is performed using the CT component of the PET/CT and the pre-contrast T1-weighted non-fat suppressed MRI. Comparable patient setup protocols were used during the MRI and PET examinations in order to avoid having to make assumptions of biomedical properties of the breast during and after the application of chemotherapy. The registration uses a multi-resolution approach to speed up the process and to minimize the probability of converging to local minima. The validation was performed on 140 breasts (70 patients). From a total number of registration cases, 94.2% of the breasts were aligned within 4.0 mm accuracy (1 PET voxel). Fused information may be beneficial to obtain representative biopsy samples, which in turn will benefit the treatment of the patient.

Automated asteroseismic peak detections

Science.gov (United States)

García Saravia Ortiz de Montellano, Andrés; Hekker, S.; Themeßl, N.

2018-05-01

Space observatories such as Kepler have provided data that can potentially revolutionize our understanding of stars. Through detailed asteroseismic analyses we are capable of determining fundamental stellar parameters and reveal the stellar internal structure with unprecedented accuracy. However, such detailed analyses, known as peak bagging, have so far been obtained for only a small percentage of the observed stars while most of the scientific potential of the available data remains unexplored. One of the major challenges in peak bagging is identifying how many solar-like oscillation modes are visible in a power density spectrum. Identification of oscillation modes is usually done by visual inspection that is time-consuming and has a degree of subjectivity. Here, we present a peak-detection algorithm especially suited for the detection of solar-like oscillations. It reliably characterizes the solar-like oscillations in a power density spectrum and estimates their parameters without human intervention. Furthermore, we provide a metric to characterize the false positive and false negative rates to provide further information about the reliability of a detected oscillation mode or the significance of a lack of detected oscillation modes. The algorithm presented here opens the possibility for detailed and automated peak bagging of the thousands of solar-like oscillators observed by Kepler.

Toxicity assessment of ionic liquids with Vibrio fischeri: an alternative fully automated methodology.

Science.gov (United States)

Costa, Susana P F; Pinto, Paula C A G; Lapa, Rui A S; Saraiva, M Lúcia M F S

2015-03-02

A fully automated Vibrio fischeri methodology based on sequential injection analysis (SIA) has been developed. The methodology was based on the aspiration of 75 μL of bacteria and 50 μL of inhibitor followed by measurement of the luminescence of bacteria. The assays were conducted for contact times of 5, 15, and 30 min, by means of three mixing chambers that ensured adequate mixing conditions. The optimized methodology provided a precise control of the reaction conditions which is an asset for the analysis of a large number of samples. The developed methodology was applied to the evaluation of the impact of a set of ionic liquids (ILs) on V. fischeri and the results were compared with those provided by a conventional assay kit (Biotox(®)). The collected data evidenced the influence of different cation head groups and anion moieties on the toxicity of ILs. Generally, aromatic cations and fluorine-containing anions displayed higher impact on V. fischeri, evidenced by lower EC50. The proposed methodology was validated through statistical analysis which demonstrated a strong positive correlation (P>0.98) between assays. It is expected that the automated methodology can be tested for more classes of compounds and used as alternative to microplate based V. fischeri assay kits. Copyright © 2014 Elsevier B.V. All rights reserved.

Toward fully automated processing of dynamic susceptibility contrast perfusion MRI for acute ischemic cerebral stroke.

Science.gov (United States)

Kim, Jinsuh; Leira, Enrique C; Callison, Richard C; Ludwig, Bryan; Moritani, Toshio; Magnotta, Vincent A; Madsen, Mark T

2010-05-01

We developed fully automated software for dynamic susceptibility contrast (DSC) MR perfusion-weighted imaging (PWI) to efficiently and reliably derive critical hemodynamic information for acute stroke treatment decisions. Brain MR PWI was performed in 80 consecutive patients with acute nonlacunar ischemic stroke within 24h after onset of symptom from January 2008 to August 2009. These studies were automatically processed to generate hemodynamic parameters that included cerebral blood flow and cerebral blood volume, and the mean transit time (MTT). To develop reliable software for PWI analysis, we used computationally robust algorithms including the piecewise continuous regression method to determine bolus arrival time (BAT), log-linear curve fitting, arrival time independent deconvolution method and sophisticated motion correction methods. An optimal arterial input function (AIF) search algorithm using a new artery-likelihood metric was also developed. Anatomical locations of the automatically determined AIF were reviewed and validated. The automatically computed BAT values were statistically compared with estimated BAT by a single observer. In addition, gamma-variate curve-fitting errors of AIF and inter-subject variability of AIFs were analyzed. Lastly, two observes independently assessed the quality and area of hypoperfusion mismatched with restricted diffusion area from motion corrected MTT maps and compared that with time-to-peak (TTP) maps using the standard approach. The AIF was identified within an arterial branch and enhanced areas of perfusion deficit were visualized in all evaluated cases. Total processing time was 10.9+/-2.5s (mean+/-s.d.) without motion correction and 267+/-80s (mean+/-s.d.) with motion correction on a standard personal computer. The MTT map produced with our software adequately estimated brain areas with perfusion deficit and was significantly less affected by random noise of the PWI when compared with the TTP map. Results of image

Development of a fully automated network system for long-term health-care monitoring at home.

Science.gov (United States)

Motoi, K; Kubota, S; Ikarashi, A; Nogawa, M; Tanaka, S; Nemoto, T; Yamakoshi, K

2007-01-01

Daily monitoring of health condition at home is very important not only as an effective scheme for early diagnosis and treatment of cardiovascular and other diseases, but also for prevention and control of such diseases. From this point of view, we have developed a prototype room for fully automated monitoring of various vital signs. From the results of preliminary experiments using this room, it was confirmed that (1) ECG and respiration during bathing, (2) excretion weight and blood pressure, and (3) respiration and cardiac beat during sleep could be monitored with reasonable accuracy by the sensor system installed in bathtub, toilet and bed, respectively.

Underwater Topography Detection in Coastal Areas Using Fully Polarimetric SAR Data

Directory of Open Access Journals (Sweden)

Xiaolin Bian

2017-06-01

Full Text Available Fully polarimetric synthetic aperture radar (SAR can provide detailed information on scattering mechanisms that could enable the target or structure to be identified. This paper presents a method to detect underwater topography in coastal areas using high resolution fully polarimetric SAR data, while less prior information is required. The method is based on the shoaling and refraction of long surface gravity waves as they propagate shoreward. First, the surface scattering component is obtained by polarization decomposition. Then, wave fields are retrieved from the two-dimensional (2D spectra by the Fast Fourier Transformation (FFT. Finally, shallow water depths are estimated from the dispersion relation. Applicability and effectiveness of the proposed methodology are tested by using C-band fine quad-polarization mode RADARSAT-2 SAR data over the near-shore area of the Hainan province, China. By comparing with the values from an official electronic navigational chart (ENC, the estimated water depths are in good agreement with them. The average relative error of the detected results from the scattering mechanisms based method and single polarization SAR data are 9.73% and 11.53% respectively. The validation results indicate that the scattering mechanisms based methodology is more effective than only using the single polarization SAR data for underwater topography detection, and will inspire further research on underwater topography detection with fully polarimetric SAR data.

Fully automated SPE-based synthesis and purification of 2-[{sup 18}F]fluoroethyl-choline for human use

Energy Technology Data Exchange (ETDEWEB)

Schmaljohann, Joern [Department of Nuclear Medicine, University of Bonn, Bonn (Germany); Department of Nuclear Medicine, University of Aachen, Aachen (Germany); Schirrmacher, Esther [McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec (Canada); Waengler, Bjoern; Waengler, Carmen [Department of Nuclear Medicine, Ludwig-Maximilians University, Munich (Germany); Schirrmacher, Ralf, E-mail: ralf.schirrmacher@mcgill.c [McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec (Canada); Guhlke, Stefan, E-mail: stefan.guhlke@ukb.uni-bonn.d [Department of Nuclear Medicine, University of Bonn, Bonn (Germany)

2011-02-15

Introduction: 2-[{sup 18}F]Fluoroethyl-choline ([{sup 18}F]FECH) is a promising tracer for the detection of prostate cancer as well as brain tumors with positron emission tomography (PET). [{sup 18}F]FECH is actively transported into mammalian cells, becomes phosphorylated by choline kinase and gets incorporated into the cell membrane after being metabolized to phosphatidylcholine. So far, its synthesis is a two-step procedure involving at least one HPLC purification step. To allow a wider dissemination of this tracer, finding a purification method avoiding HPLC is highly desirable and would result in easier accessibility and more reliable production of [{sup 18}F]FECH. Methods: [{sup 18}F]FECH was synthesized by reaction of 2-bromo-1-[{sup 18}F]fluoroethane ([{sup 18}F]BFE) with dimethylaminoethanol (DMAE) in DMSO. We applied a novel and very reliable work-up procedure for the synthesis of [{sup 18}F]BFE. Based on a combination of three different solid-phase cartridges, the purification of [{sup 18}F]BFE from its precursor 2-bromoethyl-4-nitrobenzenesulfonate (BENos) could be achieved without using HPLC. Following the subsequent reaction of the purified [{sup 18}F]BFE with DMAE, the final product [{sup 18}F]FECH was obtained as a sterile solution by passing the crude reaction mixture through a combination of two CM plus cartridges and a sterile filter. The fully automated synthesis was performed using as well a Raytest SynChrom module (Raytest, Germany) or a Scintomics HotboxIII module (Scintomics, Germany). Results: The radiotracer [{sup 18}F]FECH can be synthesized in reliable radiochemical yields (RCY) of 37{+-}5% (Synchrom module) and 33{+-}5% (Hotbox III unit) in less than 1 h using these two fully automated commercially available synthesis units without HPLC involvement for purification. Detailed quality control of the final injectable [{sup 18}F]FECH solution proved the high radiochemical purity and the absence of Kryptofix2.2.2, DMAE and DMSO used in the

A Fully Automated Approach to Spike Sorting.

Science.gov (United States)

Chung, Jason E; Magland, Jeremy F; Barnett, Alex H; Tolosa, Vanessa M; Tooker, Angela C; Lee, Kye Y; Shah, Kedar G; Felix, Sarah H; Frank, Loren M; Greengard, Leslie F

2017-09-13

Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible. Copyright © 2017 Elsevier Inc. All rights reserved.

[Research and Design of a System for Detecting Automated External Defbrillator Performance Parameters].

Science.gov (United States)

Wang, Kewu; Xiao, Shengxiang; Jiang, Lina; Hu, Jingkai

2017-09-30

In order to regularly detect the performance parameters of automated external defibrillator (AED), to make sure it is safe before using the instrument, research and design of a system for detecting automated external defibrillator performance parameters. According to the research of the characteristics of its performance parameters, combing the STM32's stability and high speed with PWM modulation control, the system produces a variety of ECG normal and abnormal signals through the digital sampling methods. Completed the design of the hardware and software, formed a prototype. This system can accurate detect automated external defibrillator discharge energy, synchronous defibrillation time, charging time and other key performance parameters.

An automated procedure for covariation-based detection of RNA structure

International Nuclear Information System (INIS)

Winker, S.; Overbeek, R.; Woese, C.R.; Olsen, G.J.; Pfluger, N.

1989-12-01

This paper summarizes our investigations into the computational detection of secondary and tertiary structure of ribosomal RNA. We have developed a new automated procedure that not only identifies potential bondings of secondary and tertiary structure, but also provides the covariation evidence that supports the proposed bondings, and any counter-evidence that can be detected in the known sequences. A small number of previously unknown bondings have been detected in individual RNA molecules (16S rRNA and 7S RNA) through the use of our automated procedure. Currently, we are systematically studying mitochondrial rRNA. Our goal is to detect tertiary structure within 16S rRNA and quaternary structure between 16S and 23S rRNA. Our ultimate hope is that automated covariation analysis will contribute significantly to a refined picture of ribosome structure. Our colleagues in biology have begun experiments to test certain hypotheses suggested by an examination of our program's output. These experiments involve sequencing key portions of the 23S ribosomal RNA for species in which the known 16S ribosomal RNA exhibits variation (from the dominant pattern) at the site of a proposed bonding. The hope is that the 23S ribosomal RNA of these species will exhibit corresponding complementary variation or generalized covariation. 24 refs

An automated procedure for covariation-based detection of RNA structure

Energy Technology Data Exchange (ETDEWEB)

Winker, S.; Overbeek, R.; Woese, C.R.; Olsen, G.J.; Pfluger, N.

1989-12-01

This paper summarizes our investigations into the computational detection of secondary and tertiary structure of ribosomal RNA. We have developed a new automated procedure that not only identifies potential bondings of secondary and tertiary structure, but also provides the covariation evidence that supports the proposed bondings, and any counter-evidence that can be detected in the known sequences. A small number of previously unknown bondings have been detected in individual RNA molecules (16S rRNA and 7S RNA) through the use of our automated procedure. Currently, we are systematically studying mitochondrial rRNA. Our goal is to detect tertiary structure within 16S rRNA and quaternary structure between 16S and 23S rRNA. Our ultimate hope is that automated covariation analysis will contribute significantly to a refined picture of ribosome structure. Our colleagues in biology have begun experiments to test certain hypotheses suggested by an examination of our program's output. These experiments involve sequencing key portions of the 23S ribosomal RNA for species in which the known 16S ribosomal RNA exhibits variation (from the dominant pattern) at the site of a proposed bonding. The hope is that the 23S ribosomal RNA of these species will exhibit corresponding complementary variation or generalized covariation. 24 refs.

Performance evaluation of vertical feed fully automated TLD badge reader using 0.8 and 0.4 mm teflon embedded CaSO4:Dy dosimeters

International Nuclear Information System (INIS)

Ratna, P.; More, Vinay; Kulkarni, M.S.

2012-01-01

The personnel monitoring of more than 80,000 radiation workers in India is at present carried out by semi-automated TLD badge Reader systems (TLDBR-7B) developed by Radiation Safety Systems Division, Bhabha Atomic Research Centre. More than 60 such reader systems are in use in all the personnel monitoring centers in the country. Radiation Safety Systems Division also developed the fully automated TLD badge reader based on a new TLD badge having built-in machine readable ID code (in the form of 16x3 hole pattern). This automated reader is designed with minimum of changes in the electronics and mechanical hardware in the semiautomatic version (TLDBR-7B) so that such semi-automatic readers can be easily upgraded to the fully automated versions by using the new TLD badge with ID code. The reader was capable of reading 50 TLD cards in 90 minutes. Based on the feedback from the users, a new model of frilly automated TLD badge Reader (model VEFFA-10) is designed which is an improved version of the previously reported fully Automated TLD badge reader. This VEFFA-10 PC based Reader incorporates vertical loading of TLD bards having machine readable ID code. In this new reader, a vertical rack, which can hold 100 such cards, is mounted from the right side of the reader system. The TLD card falls into the channel by gravity from where it is taken to the reading position by rack and pinion method. After the readout, the TLD card is dropped in a eject tray. The reader employs hot N 2 gas heating method and the gas flow is controlled by a specially designed digital gas flow meter on the front panel of the reader system. The system design is very compact and simple and card stuck up problem is totally eliminated in the reader system. The reader has a number of self-diagnostic features to ensure a high degree of reliability. This paper reports the performance evaluation of the Reader using 0.4 mm thick Teflon embedded CaSO 4 :Dy TLD cards instead of 0.8 mm cards

Automated asteroseismic peak detections

DEFF Research Database (Denmark)

de Montellano, Andres Garcia Saravia Ortiz; Hekker, S.; Themessl, N.

2018-01-01

Space observatories such as Kepler have provided data that can potentially revolutionize our understanding of stars. Through detailed asteroseismic analyses we are capable of determining fundamental stellar parameters and reveal the stellar internal structure with unprecedented accuracy. However......, such detailed analyses, known as peak bagging, have so far been obtained for only a small percentage of the observed stars while most of the scientific potential of the available data remains unexplored. One of the major challenges in peak bagging is identifying how many solar-like oscillation modes are visible...... of detected oscillation modes. The algorithm presented here opens the possibility for detailed and automated peak bagging of the thousands of solar-like oscillators observed by Kepler....

Fully automated muscle quality assessment by Gabor filtering of second harmonic generation images

Science.gov (United States)

Paesen, Rik; Smolders, Sophie; Vega, José Manolo de Hoyos; Eijnde, Bert O.; Hansen, Dominique; Ameloot, Marcel

2016-02-01

Although structural changes on the sarcomere level of skeletal muscle are known to occur due to various pathologies, rigorous studies of the reduced sarcomere quality remain scarce. This can possibly be explained by the lack of an objective tool for analyzing and comparing sarcomere images across biological conditions. Recent developments in second harmonic generation (SHG) microscopy and increasing insight into the interpretation of sarcomere SHG intensity profiles have made SHG microscopy a valuable tool to study microstructural properties of sarcomeres. Typically, sarcomere integrity is analyzed by fitting a set of manually selected, one-dimensional SHG intensity profiles with a supramolecular SHG model. To circumvent this tedious manual selection step, we developed a fully automated image analysis procedure to map the sarcomere disorder for the entire image at once. The algorithm relies on a single-frequency wavelet-based Gabor approach and includes a newly developed normalization procedure allowing for unambiguous data interpretation. The method was validated by showing the correlation between the sarcomere disorder, quantified by the M-band size obtained from manually selected profiles, and the normalized Gabor value ranging from 0 to 1 for decreasing disorder. Finally, to elucidate the applicability of our newly developed protocol, Gabor analysis was used to study the effect of experimental autoimmune encephalomyelitis on the sarcomere regularity. We believe that the technique developed in this work holds great promise for high-throughput, unbiased, and automated image analysis to study sarcomere integrity by SHG microscopy.

A LabVIEW®-based software for the control of the AUTORAD platform. A fully automated multisequential flow injection analysis Lab-on-Valve (MSFIA-LOV) system for radiochemical analysis

International Nuclear Information System (INIS)

Barbesi, Donato; Vilas, Victor Vicente; Millet, Sylvain; Sandow, Miguel; Colle, Jean-Yves; Heras, Laura Aldave de las

2017-01-01

A LabVIEW®-based software for the control of the fully automated multi-sequential flow injection analysis Lab-on-Valve (MSFIA-LOV) platform AutoRAD performing radiochemical analysis is described. The analytical platform interfaces an Arduino®-based device triggering multiple detectors providing a flexible and fit for purpose choice of detection systems. The different analytical devices are interfaced to the PC running LabVIEW®VI software using USB and RS232 interfaces, both for sending commands and receiving confirmation or error responses. The AUTORAD platform has been successfully applied for the chemical separation and determination of Sr, an important fission product pertinent to nuclear waste. (author)

A LabVIEW®-based software for the control of the AUTORAD platform: a fully automated multisequential flow injection analysis Lab-on-Valve (MSFIA-LOV) system for radiochemical analysis.

Science.gov (United States)

Barbesi, Donato; Vicente Vilas, Víctor; Millet, Sylvain; Sandow, Miguel; Colle, Jean-Yves; Aldave de Las Heras, Laura

2017-01-01

A LabVIEW ® -based software for the control of the fully automated multi-sequential flow injection analysis Lab-on-Valve (MSFIA-LOV) platform AutoRAD performing radiochemical analysis is described. The analytical platform interfaces an Arduino ® -based device triggering multiple detectors providing a flexible and fit for purpose choice of detection systems. The different analytical devices are interfaced to the PC running LabVIEW ® VI software using USB and RS232 interfaces, both for sending commands and receiving confirmation or error responses. The AUTORAD platform has been successfully applied for the chemical separation and determination of Sr, an important fission product pertinent to nuclear waste.

Effects of Automation Types on Air Traffic Controller Situation Awareness and Performance

Science.gov (United States)

Sethumadhavan, A.

2009-01-01

The Joint Planning and Development Office has proposed the introduction of automated systems to help air traffic controllers handle the increasing volume of air traffic in the next two decades (JPDO, 2007). Because fully automated systems leave operators out of the decision-making loop (e.g., Billings, 1991), it is important to determine the right level and type of automation that will keep air traffic controllers in the loop. This study examined the differences in the situation awareness (SA) and collision detection performance of individuals when they worked with information acquisition, information analysis, decision and action selection and action implementation automation to control air traffic (Parasuraman, Sheridan, & Wickens, 2000). When the automation was unreliable, the time taken to detect an upcoming collision was significantly longer for all the automation types compared with the information acquisition automation. This poor performance following automation failure was mediated by SA, with lower SA yielding poor performance. Thus, the costs associated with automation failure are greater when automation is applied to higher order stages of information processing. Results have practical implications for automation design and development of SA training programs.

Enhanced detection levels in a semi-automated sandwich ...

African Journals Online (AJOL)

A peptide nucleic acid (PNA) signal probe was tested as a replacement for a typical DNA oligonucleotidebased signal probe in a semi-automated sandwich hybridisation assay designed to detect the harmful phytoplankton species Alexandrium tamarense. The PNA probe yielded consistently higher fluorescent signal ...

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Science.gov (United States)

Court, Laurence E.; Kisling, Kelly; McCarroll, Rachel; Zhang, Lifei; Yang, Jinzhong; Simonds, Hannah; du Toit, Monique; Trauernicht, Chris; Burger, Hester; Parkes, Jeannette; Mejia, Mike; Bojador, Maureen; Balter, Peter; Branco, Daniela; Steinmann, Angela; Baltz, Garrett; Gay, Skylar; Anderson, Brian; Cardenas, Carlos; Jhingran, Anuja; Shaitelman, Simona; Bogler, Oliver; Schmeller, Kathleen; Followill, David; Howell, Rebecca; Nelson, Christopher; Peterson, Christine; Beadle, Beth

2018-01-01

The Radiation Planning Assistant (RPA) is a system developed for the fully automated creation of radiotherapy treatment plans, including volume-modulated arc therapy (VMAT) plans for patients with head/neck cancer and 4-field box plans for patients with cervical cancer. It is a combination of specially developed in-house software that uses an application programming interface to communicate with a commercial radiotherapy treatment planning system. It also interfaces with a commercial secondary dose verification software. The necessary inputs to the system are a Treatment Plan Order, approved by the radiation oncologist, and a simulation computed tomography (CT) image, approved by the radiographer. The RPA then generates a complete radiotherapy treatment plan. For the cervical cancer treatment plans, no additional user intervention is necessary until the plan is complete. For head/neck treatment plans, after the normal tissue and some of the target structures are automatically delineated on the CT image, the radiation oncologist must review the contours, making edits if necessary. They also delineate the gross tumor volume. The RPA then completes the treatment planning process, creating a VMAT plan. Finally, the completed plan must be reviewed by qualified clinical staff. PMID:29708544

AUTOMATED PROCESS MONITORING: APPLYING PROVEN AUTOMATION TECHNIQUES TO INTERNATIONAL SAFEGUARDS NEEDS

International Nuclear Information System (INIS)

O'Hara, Matthew J.; Durst, Philip C.; Grate, Jay W.; Devol, Timothy A.; Egorov, Oleg; Clements, John P.

2008-01-01

Identification and quantification of specific alpha- and beta-emitting radionuclides in complex liquid matrices is highly challenging, and is typically accomplished through laborious wet chemical sample preparation and separations followed by analysis using a variety of detection methodologies (e.g., liquid scintillation, gas proportional counting, alpha energy analysis, mass spectrometry). Analytical results may take days or weeks to report. Chains of custody and sample security measures may also complicate or slow the analytical process. When an industrial process-scale plant requires the monitoring of specific radionuclides as an indication of the composition of its feed stream or of plant performance, radiochemical measurements must be fast, accurate, and reliable. Scientists at Pacific Northwest National Laboratory have assembled a fully automated prototype Process Monitor instrument capable of a variety of tasks: automated sampling directly from a feed stream, sample digestion/analyte redox adjustment, chemical separations, radiochemical detection and data analysis/reporting. The system is compact, its components are fluidically inter-linked, and analytical results could be immediately transmitted to on- or off-site locations. The development of a rapid radiochemical Process Monitor for 99Tc in Hanford tank waste processing streams, capable of performing several measurements per hour, will be discussed in detail. More recently, the automated platform was modified to perform measurements of 90Sr in Hanford tank waste stimulant. The system exemplifies how automation could be integrated into reprocessing facilities to support international nuclear safeguards needs

A fully automated system for quantification of background parenchymal enhancement in breast DCE-MRI

Science.gov (United States)

Ufuk Dalmiş, Mehmet; Gubern-Mérida, Albert; Borelli, Cristina; Vreemann, Suzan; Mann, Ritse M.; Karssemeijer, Nico

2016-03-01

Background parenchymal enhancement (BPE) observed in breast dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been identified as an important biomarker associated with risk for developing breast cancer. In this study, we present a fully automated framework for quantification of BPE. We initially segmented fibroglandular tissue (FGT) of the breasts using an improved version of an existing method. Subsequently, we computed BPEabs (volume of the enhancing tissue), BPErf (BPEabs divided by FGT volume) and BPErb (BPEabs divided by breast volume), using different relative enhancement threshold values between 1% and 100%. To evaluate and compare the previous and improved FGT segmentation methods, we used 20 breast DCE-MRI scans and we computed Dice similarity coefficient (DSC) values with respect to manual segmentations. For evaluation of the BPE quantification, we used a dataset of 95 breast DCE-MRI scans. Two radiologists, in individual reading sessions, visually analyzed the dataset and categorized each breast into minimal, mild, moderate and marked BPE. To measure the correlation between automated BPE values to the radiologists' assessments, we converted these values into ordinal categories and we used Spearman's rho as a measure of correlation. According to our results, the new segmentation method obtained an average DSC of 0.81 0.09, which was significantly higher (p<0.001) compared to the previous method (0.76 0.10). The highest correlation values between automated BPE categories and radiologists' assessments were obtained with the BPErf measurement (r=0.55, r=0.49, p<0.001 for both), while the correlation between the scores given by the two radiologists was 0.82 (p<0.001). The presented framework can be used to systematically investigate the correlation between BPE and risk in large screening cohorts.

An Automated Detection System for Microaneurysms That Is Effective across Different Racial Groups.

Science.gov (United States)

Saleh, George Michael; Wawrzynski, James; Caputo, Silvestro; Peto, Tunde; Al Turk, Lutfiah Ismail; Wang, Su; Hu, Yin; Da Cruz, Lyndon; Smith, Phil; Tang, Hongying Lilian

2016-01-01

Patients without diabetic retinopathy (DR) represent a large proportion of the caseload seen by the DR screening service so reliable recognition of the absence of DR in digital fundus images (DFIs) is a prime focus of automated DR screening research. We investigate the use of a novel automated DR detection algorithm to assess retinal DFIs for absence of DR. A retrospective, masked, and controlled image-based study was undertaken. 17,850 DFIs of patients from six different countries were assessed for DR by the automated system and by human graders. The system's performance was compared across DFIs from the different countries/racial groups. The sensitivities for detection of DR by the automated system were Kenya 92.8%, Botswana 90.1%, Norway 93.5%, Mongolia 91.3%, China 91.9%, and UK 90.1%. The specificities were Kenya 82.7%, Botswana 83.2%, Norway 81.3%, Mongolia 82.5%, China 83.0%, and UK 79%. There was little variability in the calculated sensitivities and specificities across the six different countries involved in the study. These data suggest the possible scalability of an automated DR detection platform that enables rapid identification of patients without DR across a wide range of races.

Proof of Concept of Automated Collision Detection Technology in Rugby Sevens.

Science.gov (United States)

Clarke, Anthea C; Anson, Judith M; Pyne, David B

2017-04-01

Clarke, AC, Anson, JM, and Pyne, DB. Proof of concept of automated collision detection technology in rugby sevens. J Strength Cond Res 31(4): 1116-1120, 2017-Developments in microsensor technology allow for automated detection of collisions in various codes of football, removing the need for time-consuming postprocessing of video footage. However, little research is available on the ability of microsensor technology to be used across various sports or genders. Game video footage was matched with microsensor-detected collisions (GPSports) in one men's (n = 12 players) and one women's (n = 12) rugby sevens match. True-positive, false-positive, and false-negative events between video and microsensor-detected collisions were used to calculate recall (ability to detect a collision) and precision (accurately identify a collision). The precision was similar between the men's and women's rugby sevens game (∼0.72; scale 0.00-1.00); however, the recall in the women's game (0.45) was less than that for the men's game (0.69). This resulted in 45% of collisions for men and 62% of collisions for women being incorrectly labeled. Currently, the automated collision detection system in GPSports microtechnology units has only modest utility in rugby sevens, and it seems that a rugby sevens-specific algorithm is needed. Differences in measures between the men's and women's game may be a result of physical size, and strength, and physicality, as well as technical and tactical factors.

Rapid access to compound libraries through flow technology: fully automated synthesis of a 3-aminoindolizine library via orthogonal diversification.

Science.gov (United States)

Lange, Paul P; James, Keith

2012-10-08

A novel methodology for the synthesis of druglike heterocycle libraries has been developed through the use of flow reactor technology. The strategy employs orthogonal modification of a heterocyclic core, which is generated in situ, and was used to construct both a 25-membered library of druglike 3-aminoindolizines, and selected examples of a 100-member virtual library. This general protocol allows a broad range of acylation, alkylation and sulfonamidation reactions to be performed in conjunction with a tandem Sonogashira coupling/cycloisomerization sequence. All three synthetic steps were conducted under full automation in the flow reactor, with no handling or isolation of intermediates, to afford the desired products in good yields. This fully automated, multistep flow approach opens the way to highly efficient generation of druglike heterocyclic systems as part of a lead discovery strategy or within a lead optimization program.

Visual Versus Fully Automated Analyses of 18F-FDG and Amyloid PET for Prediction of Dementia Due to Alzheimer Disease in Mild Cognitive Impairment.

Science.gov (United States)

Grimmer, Timo; Wutz, Carolin; Alexopoulos, Panagiotis; Drzezga, Alexander; Förster, Stefan; Förstl, Hans; Goldhardt, Oliver; Ortner, Marion; Sorg, Christian; Kurz, Alexander

2016-02-01

Biomarkers of Alzheimer disease (AD) can be imaged in vivo and can be used for diagnostic and prognostic purposes in people with cognitive decline and dementia. Indicators of amyloid deposition such as (11)C-Pittsburgh compound B ((11)C-PiB) PET are primarily used to identify or rule out brain diseases that are associated with amyloid pathology but have also been deployed to forecast the clinical course. Indicators of neuronal metabolism including (18)F-FDG PET demonstrate the localization and severity of neuronal dysfunction and are valuable for differential diagnosis and for predicting the progression from mild cognitive impairment (MCI) to dementia. It is a matter of debate whether to analyze these images visually or using automated techniques. Therefore, we compared the usefulness of both imaging methods and both analyzing strategies to predict dementia due to AD. In MCI participants, a baseline examination, including clinical and imaging assessments, and a clinical follow-up examination after a planned interval of 24 mo were performed. Of 28 MCI patients, 9 developed dementia due to AD, 2 developed frontotemporal dementia, and 1 developed moderate dementia of unknown etiology. The positive and negative predictive values and the accuracy of visual and fully automated analyses of (11)C-PiB for the prediction of progression to dementia due to AD were 0.50, 1.00, and 0.68, respectively, for the visual and 0.53, 1.00, and 0.71, respectively, for the automated analyses. Positive predictive value, negative predictive value, and accuracy of fully automated analyses of (18)F-FDG PET were 0.37, 0.78, and 0.50, respectively. Results of visual analyses were highly variable between raters but were superior to automated analyses. Both (18)F-FDG and (11)C-PiB imaging appear to be of limited use for predicting the progression from MCI to dementia due to AD in short-term follow-up, irrespective of the strategy of analysis. On the other hand, amyloid PET is extremely useful to

Operations management system advanced automation: Fault detection isolation and recovery prototyping

Science.gov (United States)

Hanson, Matt

1990-01-01

The purpose of this project is to address the global fault detection, isolation and recovery (FDIR) requirements for Operation's Management System (OMS) automation within the Space Station Freedom program. This shall be accomplished by developing a selected FDIR prototype for the Space Station Freedom distributed processing systems. The prototype shall be based on advanced automation methodologies in addition to traditional software methods to meet the requirements for automation. A secondary objective is to expand the scope of the prototyping to encompass multiple aspects of station-wide fault management (SWFM) as discussed in OMS requirements documentation.

Understanding reliance on automation: effects of error type, error distribution, age and experience

Science.gov (United States)

Sanchez, Julian; Rogers, Wendy A.; Fisk, Arthur D.; Rovira, Ericka

2015-01-01

An obstacle detection task supported by “imperfect” automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation. PMID:25642142

An Automated Detection System for Microaneurysms That Is Effective across Different Racial Groups

Directory of Open Access Journals (Sweden)

George Michael Saleh

2016-01-01

Full Text Available Patients without diabetic retinopathy (DR represent a large proportion of the caseload seen by the DR screening service so reliable recognition of the absence of DR in digital fundus images (DFIs is a prime focus of automated DR screening research. We investigate the use of a novel automated DR detection algorithm to assess retinal DFIs for absence of DR. A retrospective, masked, and controlled image-based study was undertaken. 17,850 DFIs of patients from six different countries were assessed for DR by the automated system and by human graders. The system’s performance was compared across DFIs from the different countries/racial groups. The sensitivities for detection of DR by the automated system were Kenya 92.8%, Botswana 90.1%, Norway 93.5%, Mongolia 91.3%, China 91.9%, and UK 90.1%. The specificities were Kenya 82.7%, Botswana 83.2%, Norway 81.3%, Mongolia 82.5%, China 83.0%, and UK 79%. There was little variability in the calculated sensitivities and specificities across the six different countries involved in the study. These data suggest the possible scalability of an automated DR detection platform that enables rapid identification of patients without DR across a wide range of races.

Parameter evaluation and fully-automated radiosynthesis of [(11)C]harmine for imaging of MAO-A for clinical trials.

Science.gov (United States)

Philippe, C; Zeilinger, M; Mitterhauser, M; Dumanic, M; Lanzenberger, R; Hacker, M; Wadsak, W

2015-03-01

The aim of the present study was the evaluation and automation of the radiosynthesis of [(11)C]harmine for clinical trials. The following parameters have been investigated: amount of base, precursor concentration, solvent, reaction temperature and time. The optimum reaction conditions were determined to be 2-3mg/mL precursor activated with 1eq. 5M NaOH in DMSO, 80°C reaction temperature and 2min reaction time. Under these conditions 6.1±1GBq (51.0±11% based on [(11)C]CH3I, corrected for decay) of [(11)C]harmine (n=72) were obtained. The specific activity was 101.32±28.2GBq/µmol (at EOS). All quality control parameters were in accordance with the standards for parenteral human application. Due to its reliability and high yields, this fully-automated synthesis method can be used as routine set-up. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Centrifugal LabTube platform for fully automated DNA purification and LAMP amplification based on an integrated, low-cost heating system.

Science.gov (United States)

Hoehl, Melanie M; Weißert, Michael; Dannenberg, Arne; Nesch, Thomas; Paust, Nils; von Stetten, Felix; Zengerle, Roland; Slocum, Alexander H; Steigert, Juergen

2014-06-01

This paper introduces a disposable battery-driven heating system for loop-mediated isothermal DNA amplification (LAMP) inside a centrifugally-driven DNA purification platform (LabTube). We demonstrate LabTube-based fully automated DNA purification of as low as 100 cell-equivalents of verotoxin-producing Escherichia coli (VTEC) in water, milk and apple juice in a laboratory centrifuge, followed by integrated and automated LAMP amplification with a reduction of hands-on time from 45 to 1 min. The heating system consists of two parallel SMD thick film resistors and a NTC as heating and temperature sensing elements. They are driven by a 3 V battery and controlled by a microcontroller. The LAMP reagents are stored in the elution chamber and the amplification starts immediately after the eluate is purged into the chamber. The LabTube, including a microcontroller-based heating system, demonstrates contamination-free and automated sample-to-answer nucleic acid testing within a laboratory centrifuge. The heating system can be easily parallelized within one LabTube and it is deployable for a variety of heating and electrical applications.

Deep Fully Convolutional Networks for the Detection of Informal Settlements in VHR Images

NARCIS (Netherlands)

Persello, Claudio; Stein, Alfred

2017-01-01

This letter investigates fully convolutional networks (FCNs) for the detection of informal settlements in very high resolution (VHR) satellite images. Informal settlements or slums are proliferating in developing countries and their detection and classification provides vital information for

Detecting and combating malicious email

CERN Document Server

Ryan, Julie JCH

2014-01-01

Malicious email is, simply put, email with a malicious purpose. The malicious purpose could be fraud, theft, espionage, or malware injection. The processes by which email execute the malicious activity vary widely, from fully manual (e.g. human-directed) to fully automated. One example of a malicious email is one that contains an attachment which the recipient is directed to open. When the attachment is opened, malicious software is installed on the recipient's computer. Because malicious email can vary so broadly in form and function, automated detection is only marginally helpful. The education of all users to detect potential malicious email is important to containing the threat and limiting the damage. It is increasingly necessary for all email users to understand how to recognize and combat malicious email. Detecting and Combating Malicious Email describes the different types of malicious email, shows how to differentiate malicious email from benign email, and suggest protective strategies for both perso...

Automated comparison of Bayesian reconstructions of experimental profiles with physical models

International Nuclear Information System (INIS)

Irishkin, Maxim

2014-01-01

In this work we developed an expert system that carries out in an integrated and fully automated way i) a reconstruction of plasma profiles from the measurements, using Bayesian analysis ii) a prediction of the reconstructed quantities, according to some models and iii) an intelligent comparison of the first two steps. This system includes systematic checking of the internal consistency of the reconstructed quantities, enables automated model validation and, if a well-validated model is used, can be applied to help detecting interesting new physics in an experiment. The work shows three applications of this quite general system. The expert system can successfully detect failures in the automated plasma reconstruction and provide (on successful reconstruction cases) statistics of agreement of the models with the experimental data, i.e. information on the model validity. (author) [fr

High throughput detection of Coxiella burnetii by real-time PCR with internal control system and automated DNA preparation

Directory of Open Access Journals (Sweden)

Kramme Stefanie

2008-05-01

Full Text Available Abstract Background Coxiella burnetii is the causative agent of Q-fever, a widespread zoonosis. Due to its high environmental stability and infectivity it is regarded as a category B biological weapon agent. In domestic animals infection remains either asymptomatic or presents as infertility or abortion. Clinical presentation in humans can range from mild flu-like illness to acute pneumonia and hepatitis. Endocarditis represents the most common form of chronic Q-fever. In humans serology is the gold standard for diagnosis but is inadequate for early case detection. In order to serve as a diagnostic tool in an eventual biological weapon attack or in local epidemics we developed a real-time 5'nuclease based PCR assay with an internal control system. To facilitate high-throughput an automated extraction procedure was evaluated. Results To determine the minimum number of copies that are detectable at 95% chance probit analysis was used. Limit of detection in blood was 2,881 copies/ml [95%CI, 2,188–4,745 copies/ml] with a manual extraction procedure and 4,235 copies/ml [95%CI, 3,143–7,428 copies/ml] with a fully automated extraction procedure, respectively. To demonstrate clinical application a total of 72 specimens of animal origin were compared with respect to manual and automated extraction. A strong correlation between both methods was observed rendering both methods suitable. Testing of 247 follow up specimens of animal origin from a local Q-fever epidemic rendered real-time PCR more sensitive than conventional PCR. Conclusion A sensitive and thoroughly evaluated real-time PCR was established. Its high-throughput mode may show a useful approach to rapidly screen samples in local outbreaks for other organisms relevant for humans or animals. Compared to a conventional PCR assay sensitivity of real-time PCR was higher after testing samples from a local Q-fever outbreak.

Extensible automated dispersive liquid–liquid microextraction

Energy Technology Data Exchange (ETDEWEB)

Li, Songqing; Hu, Lu; Chen, Ketao; Gao, Haixiang, E-mail: hxgao@cau.edu.cn

2015-05-04

Highlights: • An extensible automated dispersive liquid–liquid microextraction was developed. • A fully automatic SPE workstation with a modified operation program was used. • Ionic liquid-based in situ DLLME was used as model method. • SPE columns packed with nonwoven polypropylene fiber was used for phase separation. • The approach was applied to the determination of benzoylurea insecticides in water. - Abstract: In this study, a convenient and extensible automated ionic liquid-based in situ dispersive liquid–liquid microextraction (automated IL-based in situ DLLME) was developed. 1-Octyl-3-methylimidazolium bis[(trifluoromethane)sulfonyl]imide ([C{sub 8}MIM]NTf{sub 2}) is formed through the reaction between [C{sub 8}MIM]Cl and lithium bis[(trifluoromethane)sulfonyl]imide (LiNTf{sub 2}) to extract the analytes. Using a fully automatic SPE workstation, special SPE columns packed with nonwoven polypropylene (NWPP) fiber, and a modified operation program, the procedures of the IL-based in situ DLLME, including the collection of a water sample, injection of an ion exchange solvent, phase separation of the emulsified solution, elution of the retained extraction phase, and collection of the eluent into vials, can be performed automatically. The developed approach, coupled with high-performance liquid chromatography–diode array detection (HPLC–DAD), was successfully applied to the detection and concentration determination of benzoylurea (BU) insecticides in water samples. Parameters affecting the extraction performance were investigated and optimized. Under the optimized conditions, the proposed method achieved extraction recoveries of 80% to 89% for water samples. The limits of detection (LODs) of the method were in the range of 0.16–0.45 ng mL{sup −1}. The intra-column and inter-column relative standard deviations (RSDs) were <8.6%. Good linearity (r > 0.9986) was obtained over the calibration range from 2 to 500 ng mL{sup −1}. The proposed

Extensible automated dispersive liquid–liquid microextraction

International Nuclear Information System (INIS)

Li, Songqing; Hu, Lu; Chen, Ketao; Gao, Haixiang

2015-01-01

Highlights: • An extensible automated dispersive liquid–liquid microextraction was developed. • A fully automatic SPE workstation with a modified operation program was used. • Ionic liquid-based in situ DLLME was used as model method. • SPE columns packed with nonwoven polypropylene fiber was used for phase separation. • The approach was applied to the determination of benzoylurea insecticides in water. - Abstract: In this study, a convenient and extensible automated ionic liquid-based in situ dispersive liquid–liquid microextraction (automated IL-based in situ DLLME) was developed. 1-Octyl-3-methylimidazolium bis[(trifluoromethane)sulfonyl]imide ([C 8 MIM]NTf 2 ) is formed through the reaction between [C 8 MIM]Cl and lithium bis[(trifluoromethane)sulfonyl]imide (LiNTf 2 ) to extract the analytes. Using a fully automatic SPE workstation, special SPE columns packed with nonwoven polypropylene (NWPP) fiber, and a modified operation program, the procedures of the IL-based in situ DLLME, including the collection of a water sample, injection of an ion exchange solvent, phase separation of the emulsified solution, elution of the retained extraction phase, and collection of the eluent into vials, can be performed automatically. The developed approach, coupled with high-performance liquid chromatography–diode array detection (HPLC–DAD), was successfully applied to the detection and concentration determination of benzoylurea (BU) insecticides in water samples. Parameters affecting the extraction performance were investigated and optimized. Under the optimized conditions, the proposed method achieved extraction recoveries of 80% to 89% for water samples. The limits of detection (LODs) of the method were in the range of 0.16–0.45 ng mL −1 . The intra-column and inter-column relative standard deviations (RSDs) were <8.6%. Good linearity (r > 0.9986) was obtained over the calibration range from 2 to 500 ng mL −1 . The proposed method opens a new avenue

Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

Science.gov (United States)

Hopp, T.; Zapf, M.; Ruiter, N. V.

2014-03-01

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

Fully Automated Simultaneous Integrated Boosted-Intensity Modulated Radiation Therapy Treatment Planning Is Feasible for Head-and-Neck Cancer: A Prospective Clinical Study

Energy Technology Data Exchange (ETDEWEB)

Wu Binbin, E-mail: binbin.wu@gunet.georgetown.edu [Department of Radiation Oncology and Molecular Radiation Science, Johns Hopkins University, Baltimore, Maryland (United States); Department of Radiation Medicine, Georgetown University Hospital, Washington, DC (United States); McNutt, Todd [Department of Radiation Oncology and Molecular Radiation Science, Johns Hopkins University, Baltimore, Maryland (United States); Zahurak, Marianna [Department of Oncology Biostatistics, Johns Hopkins University, Baltimore, Maryland (United States); Simari, Patricio [Autodesk Research, Toronto, ON (Canada); Pang, Dalong [Department of Radiation Medicine, Georgetown University Hospital, Washington, DC (United States); Taylor, Russell [Department of Computer Science, Johns Hopkins University, Baltimore, Maryland (United States); Sanguineti, Giuseppe [Department of Radiation Oncology and Molecular Radiation Science, Johns Hopkins University, Baltimore, Maryland (United States)

2012-12-01

Purpose: To prospectively determine whether overlap volume histogram (OVH)-driven, automated simultaneous integrated boosted (SIB)-intensity-modulated radiation therapy (IMRT) treatment planning for head-and-neck cancer can be implemented in clinics. Methods and Materials: A prospective study was designed to compare fully automated plans (APs) created by an OVH-driven, automated planning application with clinical plans (CPs) created by dosimetrists in a 3-dose-level (70 Gy, 63 Gy, and 58.1 Gy), head-and-neck SIB-IMRT planning. Because primary organ sparing (cord, brain, brainstem, mandible, and optic nerve/chiasm) always received the highest priority in clinical planning, the study aimed to show the noninferiority of APs with respect to PTV coverage and secondary organ sparing (parotid, brachial plexus, esophagus, larynx, inner ear, and oral mucosa). The sample size was determined a priori by a superiority hypothesis test that had 85% power to detect a 4% dose decrease in secondary organ sparing with a 2-sided alpha level of 0.05. A generalized estimating equation (GEE) regression model was used for statistical comparison. Results: Forty consecutive patients were accrued from July to December 2010. GEE analysis indicated that in APs, overall average dose to the secondary organs was reduced by 1.16 (95% CI = 0.09-2.33) with P=.04, overall average PTV coverage was increased by 0.26% (95% CI = 0.06-0.47) with P=.02 and overall average dose to the primary organs was reduced by 1.14 Gy (95% CI = 0.45-1.8) with P=.004. A physician determined that all APs could be delivered to patients, and APs were clinically superior in 27 of 40 cases. Conclusions: The application can be implemented in clinics as a fast, reliable, and consistent way of generating plans that need only minor adjustments to meet specific clinical needs.

Fully Automated Simultaneous Integrated Boosted–Intensity Modulated Radiation Therapy Treatment Planning Is Feasible for Head-and-Neck Cancer: A Prospective Clinical Study

International Nuclear Information System (INIS)

Wu Binbin; McNutt, Todd; Zahurak, Marianna; Simari, Patricio; Pang, Dalong; Taylor, Russell; Sanguineti, Giuseppe

2012-01-01

Purpose: To prospectively determine whether overlap volume histogram (OVH)–driven, automated simultaneous integrated boosted (SIB)-intensity-modulated radiation therapy (IMRT) treatment planning for head-and-neck cancer can be implemented in clinics. Methods and Materials: A prospective study was designed to compare fully automated plans (APs) created by an OVH-driven, automated planning application with clinical plans (CPs) created by dosimetrists in a 3-dose-level (70 Gy, 63 Gy, and 58.1 Gy), head-and-neck SIB-IMRT planning. Because primary organ sparing (cord, brain, brainstem, mandible, and optic nerve/chiasm) always received the highest priority in clinical planning, the study aimed to show the noninferiority of APs with respect to PTV coverage and secondary organ sparing (parotid, brachial plexus, esophagus, larynx, inner ear, and oral mucosa). The sample size was determined a priori by a superiority hypothesis test that had 85% power to detect a 4% dose decrease in secondary organ sparing with a 2-sided alpha level of 0.05. A generalized estimating equation (GEE) regression model was used for statistical comparison. Results: Forty consecutive patients were accrued from July to December 2010. GEE analysis indicated that in APs, overall average dose to the secondary organs was reduced by 1.16 (95% CI = 0.09-2.33) with P=.04, overall average PTV coverage was increased by 0.26% (95% CI = 0.06-0.47) with P=.02 and overall average dose to the primary organs was reduced by 1.14 Gy (95% CI = 0.45-1.8) with P=.004. A physician determined that all APs could be delivered to patients, and APs were clinically superior in 27 of 40 cases. Conclusions: The application can be implemented in clinics as a fast, reliable, and consistent way of generating plans that need only minor adjustments to meet specific clinical needs.

Fully automated laser ray tracing system to measure changes in the crystalline lens GRIN profile.

Science.gov (United States)

Qiu, Chen; Maceo Heilman, Bianca; Kaipio, Jari; Donaldson, Paul; Vaghefi, Ehsan

2017-11-01

Measuring the lens gradient refractive index (GRIN) accurately and reliably has proven an extremely challenging technical problem. A fully automated laser ray tracing (LRT) system was built to address this issue. The LRT system captures images of multiple laser projections before and after traversing through an ex vivo lens. These LRT images, combined with accurate measurements of the lens geometry, are used to calculate the lens GRIN profile. Mathematically, this is an ill-conditioned problem; hence, it is essential to apply biologically relevant constraints to produce a feasible solution. The lens GRIN measurements were compared with previously published data. Our GRIN retrieval algorithm produces fast and accurate measurements of the lens GRIN profile. Experiments to study the optics of physiologically perturbed lenses are the future direction of this research.

A fully-automated neural network analysis of AFM force-distance curves for cancer tissue diagnosis

Science.gov (United States)

Minelli, Eleonora; Ciasca, Gabriele; Sassun, Tanya Enny; Antonelli, Manila; Palmieri, Valentina; Papi, Massimiliano; Maulucci, Giuseppe; Santoro, Antonio; Giangaspero, Felice; Delfini, Roberto; Campi, Gaetano; De Spirito, Marco

2017-10-01

Atomic Force Microscopy (AFM) has the unique capability of probing the nanoscale mechanical properties of biological systems that affect and are affected by the occurrence of many pathologies, including cancer. This capability has triggered growing interest in the translational process of AFM from physics laboratories to clinical practice. A factor still hindering the current use of AFM in diagnostics is related to the complexity of AFM data analysis, which is time-consuming and needs highly specialized personnel with a strong physical and mathematical background. In this work, we demonstrate an operator-independent neural-network approach for the analysis of surgically removed brain cancer tissues. This approach allowed us to distinguish—in a fully automated fashion—cancer from healthy tissues with high accuracy, also highlighting the presence and the location of infiltrating tumor cells.

Automated oil spill detection with multispectral imagery

Science.gov (United States)

Bradford, Brian N.; Sanchez-Reyes, Pedro J.

2011-06-01

In this publication we present an automated detection method for ocean surface oil, like that which existed in the Gulf of Mexico as a result of the April 20, 2010 Deepwater Horizon drilling rig explosion. Regions of surface oil in airborne imagery are isolated using red, green, and blue bands from multispectral data sets. The oil shape isolation procedure involves a series of image processing functions to draw out the visual phenomenological features of the surface oil. These functions include selective color band combinations, contrast enhancement and histogram warping. An image segmentation process then separates out contiguous regions of oil to provide a raster mask to an analyst. We automate the detection algorithm to allow large volumes of data to be processed in a short time period, which can provide timely oil coverage statistics to response crews. Geo-referenced and mosaicked data sets enable the largest identified oil regions to be mapped to exact geographic coordinates. In our simulation, multispectral imagery came from multiple sources including first-hand data collected from the Gulf. Results of the simulation show the oil spill coverage area as a raster mask, along with histogram statistics of the oil pixels. A rough square footage estimate of the coverage is reported if the image ground sample distance is available.

Automation of diagnostic genetic testing: mutation detection by cyclic minisequencing.

Science.gov (United States)

Alagrund, Katariina; Orpana, Arto K

2014-01-01

The rising role of nucleic acid testing in clinical decision making is creating a need for efficient and automated diagnostic nucleic acid test platforms. Clinical use of nucleic acid testing sets demands for shorter turnaround times (TATs), lower production costs and robust, reliable methods that can easily adopt new test panels and is able to run rare tests in random access principle. Here we present a novel home-brew laboratory automation platform for diagnostic mutation testing. This platform is based on the cyclic minisequecing (cMS) and two color near-infrared (NIR) detection. Pipetting is automated using Tecan Freedom EVO pipetting robots and all assays are performed in 384-well micro plate format. The automation platform includes a data processing system, controlling all procedures, and automated patient result reporting to the hospital information system. We have found automated cMS a reliable, inexpensive and robust method for nucleic acid testing for a wide variety of diagnostic tests. The platform is currently in clinical use for over 80 mutations or polymorphisms. Additionally to tests performed from blood samples, the system performs also epigenetic test for the methylation of the MGMT gene promoter, and companion diagnostic tests for analysis of KRAS and BRAF gene mutations from formalin fixed and paraffin embedded tumor samples. Automation of genetic test reporting is found reliable and efficient decreasing the work load of academic personnel.

Automated Micro-Object Detection for Mobile Diagnostics Using Lens-Free Imaging Technology

Directory of Open Access Journals (Sweden)

Mohendra Roy

2016-05-01

Full Text Available Lens-free imaging technology has been extensively used recently for microparticle and biological cell analysis because of its high throughput, low cost, and simple and compact arrangement. However, this technology still lacks a dedicated and automated detection system. In this paper, we describe a custom-developed automated micro-object detection method for a lens-free imaging system. In our previous work (Roy et al., we developed a lens-free imaging system using low-cost components. This system was used to generate and capture the diffraction patterns of micro-objects and a global threshold was used to locate the diffraction patterns. In this work we used the same setup to develop an improved automated detection and analysis algorithm based on adaptive threshold and clustering of signals. For this purpose images from the lens-free system were then used to understand the features and characteristics of the diffraction patterns of several types of samples. On the basis of this information, we custom-developed an automated algorithm for the lens-free imaging system. Next, all the lens-free images were processed using this custom-developed automated algorithm. The performance of this approach was evaluated by comparing the counting results with standard optical microscope results. We evaluated the counting results for polystyrene microbeads, red blood cells, and HepG2, HeLa, and MCF7 cells. The comparison shows good agreement between the systems, with a correlation coefficient of 0.91 and linearity slope of 0.877. We also evaluated the automated size profiles of the microparticle samples. This Wi-Fi-enabled lens-free imaging system, along with the dedicated software, possesses great potential for telemedicine applications in resource-limited settings.

Evaluation of a Fully Automated Analyzer for Rapid Measurement of Water Vapor Sorption Isotherms for Applications in Soil Science

DEFF Research Database (Denmark)

Arthur, Emmanuel; Tuller, Markus; Moldrup, Per

2014-01-01

The characterization and description of important soil processes such as water vapor transport, volatilization of pesticides, and hysteresis require accurate means for measuring the soil water characteristic (SWC) at low water potentials. Until recently, measurement of the SWC at low water...... potentials was constrained by hydraulic decoupling and long equilibration times when pressure plates or single-point, chilled-mirror instruments were used. A new, fully automated Vapor Sorption Analyzer (VSA) helps to overcome these challenges and allows faster measurement of highly detailed water vapor...

Buying Program of the Standard Automated Materiel Management System. Automated Small Purchase System: Defense Supply Center Philadelphia

National Research Council Canada - National Science Library

2001-01-01

The Standard Automated Materiel Management System Automated Small Purchase System is a fully automated micro-purchases system used by the General and Industrial Directorate at the Defense Supply Center Philadelphia...

Conflict Resolution Automation and Pilot Situation Awareness

Science.gov (United States)

Dao, Arik-Quang V.; Brandt, Summer L.; Bacon, Paige; Kraut, Josh; Nguyen, Jimmy; Minakata, Katsumi; Raza, Hamzah; Rozovski, David; Johnson, Walter W.

2010-01-01

This study compared pilot situation awareness across three traffic management concepts. The Concepts varied in terms of the allocation of traffic avoidance responsibility between the pilot on the flight deck, the air traffic controllers, and a conflict resolution automation system. In Concept 1, the flight deck was equipped with conflict resolution tools that enable them to fully handle the responsibility of weather avoidance and maintaining separation between ownship and surrounding traffic. In Concept 2, pilots were not responsible for traffic separation, but were provided tools for weather and traffic avoidance. In Concept 3, flight deck tools allowed pilots to deviate for weather, but conflict detection tools were disabled. In this concept pilots were dependent on ground based automation for conflict detection and resolution. Situation awareness of the pilots was measured using online probes. Results showed that individual situation awareness was highest in Concept 1, where the pilots were most engaged, and lowest in Concept 3, where automation was heavily used. These findings suggest that for conflict resolution tasks, situation awareness is improved when pilots remain in the decision-making loop.

Microaneurysm detection using fully convolutional neural networks.

Science.gov (United States)

Chudzik, Piotr; Majumdar, Somshubra; Calivá, Francesco; Al-Diri, Bashir; Hunter, Andrew

2018-05-01

Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper presents an automatic method for detecting microaneurysms in fundus photographies. A novel patch-based fully convolutional neural network with batch normalization layers and Dice loss function is proposed. Compared to other methods that require up to five processing stages, it requires only three. Furthermore, to the best of the authors' knowledge, this is the first paper that shows how to successfully transfer knowledge between datasets in the microaneurysm detection domain. The proposed method was evaluated using three publicly available and widely used datasets: E-Ophtha, DIARETDB1, and ROC. It achieved better results than state-of-the-art methods using the FROC metric. The proposed algorithm accomplished highest sensitivities for low false positive rates, which is particularly important for screening purposes. Performance, simplicity, and robustness of the proposed method demonstrates its suitability for diabetic retinopathy screening applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated data processing of high-resolution mass spectra

DEFF Research Database (Denmark)

Hansen, Michael Adsetts Edberg; Smedsgaard, Jørn

of the massive amounts of data. We present an automated data processing method to quantitatively compare large numbers of spectra from the analysis of complex mixtures, exploiting the full quality of high-resolution mass spectra. By projecting all detected ions - within defined intervals on both the time...... infusion of crude extracts into the source taking advantage of the high sensitivity, high mass resolution and accuracy and the limited fragmentation. Unfortunately, there has not been a comparable development in the data processing techniques to fully exploit gain in high resolution and accuracy...... infusion analyses of crude extract to find the relationship between species from several species terverticillate Penicillium, and also that the ions responsible for the segregation can be identified. Furthermore the process can automate the process of detecting unique species and unique metabolites....

Using microwave Doppler radar in automated manufacturing applications

Science.gov (United States)

Smith, Gregory C.

Since the beginning of the Industrial Revolution, manufacturers worldwide have used automation to improve productivity, gain market share, and meet growing or changing consumer demand for manufactured products. To stimulate further industrial productivity, manufacturers need more advanced automation technologies: "smart" part handling systems, automated assembly machines, CNC machine tools, and industrial robots that use new sensor technologies, advanced control systems, and intelligent decision-making algorithms to "see," "hear," "feel," and "think" at the levels needed to handle complex manufacturing tasks without human intervention. The investigator's dissertation offers three methods that could help make "smart" CNC machine tools and industrial robots possible: (1) A method for detecting acoustic emission using a microwave Doppler radar detector, (2) A method for detecting tool wear on a CNC lathe using a Doppler radar detector, and (3) An online non-contact method for detecting industrial robot position errors using a microwave Doppler radar motion detector. The dissertation studies indicate that microwave Doppler radar could be quite useful in automated manufacturing applications. In particular, the methods developed may help solve two difficult problems that hinder further progress in automating manufacturing processes: (1) Automating metal-cutting operations on CNC machine tools by providing a reliable non-contact method for detecting tool wear, and (2) Fully automating robotic manufacturing tasks by providing a reliable low-cost non-contact method for detecting on-line position errors. In addition, the studies offer a general non-contact method for detecting acoustic emission that may be useful in many other manufacturing and non-manufacturing areas, as well (e.g., monitoring and nondestructively testing structures, materials, manufacturing processes, and devices). By advancing the state of the art in manufacturing automation, the studies may help

Multi-Branch Fully Convolutional Network for Face Detection

KAUST Repository

Bai, Yancheng

2017-07-20

Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully convolutional network (MB-FCN) for face detection, which considers both efficiency and effectiveness in the design process. Our MB-FCN detector can deal with faces at all scale ranges with only a single pass through the backbone network. As such, our MB-FCN model saves computation and thus is more efficient, compared to previous methods that make multiple passes. For each branch, the specific skip connections of the convolutional feature maps at different layers are exploited to represent faces in specific scale ranges. Specifically, small faces can be represented with both shallow fine-grained and deep powerful coarse features. With this representation, superior improvement in performance is registered for the task of detecting small faces. We test our MB-FCN detector on two public face detection benchmarks, including FDDB and WIDER FACE. Extensive experiments show that our detector outperforms state-of-the-art methods on all these datasets in general and by a substantial margin on the most challenging among them (e.g. WIDER FACE Hard subset). Also, MB-FCN runs at 15 FPS on a GPU for images of size 640 x 480 with no assumption on the minimum detectable face size.

Automated gravity gradient tensor inversion for underwater object detection

International Nuclear Information System (INIS)

Wu, Lin; Tian, Jinwen

2010-01-01

Underwater abnormal object detection is a current need for the navigation security of autonomous underwater vehicles (AUVs). In this paper, an automated gravity gradient tensor inversion algorithm is proposed for the purpose of passive underwater object detection. Full-tensor gravity gradient anomalies induced by an object in the partial area can be measured with the technique of gravity gradiometry on an AUV. Then the automated algorithm utilizes the anomalies, using the inverse method to estimate the mass and barycentre location of the arbitrary-shaped object. A few tests on simple synthetic models will be illustrated, in order to evaluate the feasibility and accuracy of the new algorithm. Moreover, the method is applied to a complicated model of an abnormal object with gradiometer and AUV noise, and interference from a neighbouring illusive smaller object. In all cases tested, the estimated mass and barycentre location parameters are found to be in good agreement with the actual values

Automated quantification of proliferation with automated hot-spot selection in phosphohistone H3/MART1 dual-stained stage I/II melanoma.

Science.gov (United States)

Nielsen, Patricia Switten; Riber-Hansen, Rikke; Schmidt, Henrik; Steiniche, Torben

2016-04-09

Staging of melanoma includes quantification of a proliferation index, i.e., presumed melanocytic mitoses of H&E stains are counted manually in hot spots. Yet, its reproducibility and prognostic impact increases by immunohistochemical dual staining for phosphohistone H3 (PHH3) and MART1, which also may enable fully automated quantification by image analysis. To ensure manageable workloads and repeatable measurements in modern pathology, the study aimed to present an automated quantification of proliferation with automated hot-spot selection in PHH3/MART1-stained melanomas. Formalin-fixed, paraffin-embedded tissue from 153 consecutive stage I/II melanoma patients was immunohistochemically dual-stained for PHH3 and MART1. Whole slide images were captured, and the number of PHH3/MART1-positive cells was manually and automatically counted in the global tumor area and in a manually and automatically selected hot spot, i.e., a fixed 1-mm(2) square. Bland-Altman plots and hypothesis tests compared manual and automated procedures, and the Cox proportional hazards model established their prognostic impact. The mean difference between manual and automated global counts was 2.9 cells/mm(2) (P = 0.0071) and 0.23 cells per hot spot (P = 0.96) for automated counts in manually and automatically selected hot spots. In 77 % of cases, manual and automated hot spots overlapped. Fully manual hot-spot counts yielded the highest prognostic performance with an adjusted hazard ratio of 5.5 (95 % CI, 1.3-24, P = 0.024) as opposed to 1.3 (95 % CI, 0.61-2.9, P = 0.47) for automated counts with automated hot spots. The automated index and automated hot-spot selection were highly correlated to their manual counterpart, but altogether their prognostic impact was noticeably reduced. Because correct recognition of only one PHH3/MART1-positive cell seems important, extremely high sensitivity and specificity of the algorithm is required for prognostic purposes. Thus, automated

Clinical Evaluation of Fully Automated Elecsys® Syphilis Assay for the Detection of Antibodies of Treponema pallidum.

Science.gov (United States)

Li, Dongdong; An, Jingna; Wang, Tingting; Tao, Chuanmin; Wang, Lanlan

2016-11-01

The resurgence of syphilis in recent years has become a serious threat to the public health worldwide, and the serological detection of specific antibodies against Treponema pallidum (TP) remains the most reliable method for laboratory diagnosis of syphilis. The performance of the Elecsys ® Syphilis assay, a brand new electrochemiluminescene immunoassay (ECLIA), was assessed by large amounts of samples in this study. In comparison with InTec assay, the Elecsys ® Syphilis assay was evaluated in 146 preselected samples from patients with syphilis, 1803 clinical routine samples, and 175 preselected samples from specific populations with reportedly increased rates of false-positive syphilis test results. Discrepancy samples must be investigated by Mikrogen Syphilis recomline assay. There was an overall agreement of 99.58% between two assays (Kappa = 0.975). The sensitivity and specificity of the Elecsys ® Syphilis assay were 100.0% (95% CI, 96.8-100.0%) and 99.8% (95% CI, 99.5-100.0%), respectively. The Elecsys syphilis assay displays better sensitivity (100%), specificity (99.8%), PPV (98.7%), and NPV (100%) in 2124 samples enrolled, compared with the InTec assay. Considering the excellent ease of use and automation, high throughput, and its superior sensitivity, especially in primary syphilis, the Elecsys ® Syphilis assay could represent an outstanding choice for screening of syphilis in high-volume laboratories. However, more attention was still needed, or the results must be confirmed by other treponemal immunoassays. The new Elecsys ® Syphilis assay is applied to patients with malignant neoplasm or HIV infection. © 2016 Wiley Periodicals, Inc.

Fully Automated Atlas-Based Hippocampus Volumetry for Clinical Routine: Validation in Subjects with Mild Cognitive Impairment from the ADNI Cohort.

Science.gov (United States)

Suppa, Per; Hampel, Harald; Spies, Lothar; Fiebach, Jochen B; Dubois, Bruno; Buchert, Ralph

2015-01-01

Hippocampus volumetry based on magnetic resonance imaging (MRI) has not yet been translated into everyday clinical diagnostic patient care, at least in part due to limited availability of appropriate software tools. In the present study, we evaluate a fully-automated and computationally efficient processing pipeline for atlas based hippocampal volumetry using freely available Statistical Parametric Mapping (SPM) software in 198 amnestic mild cognitive impairment (MCI) subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI1). Subjects were grouped into MCI stable and MCI to probable Alzheimer's disease (AD) converters according to follow-up diagnoses at 12, 24, and 36 months. Hippocampal grey matter volume (HGMV) was obtained from baseline T1-weighted MRI and then corrected for total intracranial volume and age. Average processing time per subject was less than 4 minutes on a standard PC. The area under the receiver operator characteristic curve of the corrected HGMV for identification of MCI to probable AD converters within 12, 24, and 36 months was 0.78, 0.72, and 0.71, respectively. Thus, hippocampal volume computed with the fully-automated processing pipeline provides similar power for prediction of MCI to probable AD conversion as computationally more expensive methods. The whole processing pipeline has been made freely available as an SPM8 toolbox. It is easily set up and integrated into everyday clinical patient care.

Fully automated drug screening of dried blood spots using online LC-MS/MS analysis

Directory of Open Access Journals (Sweden)

Stefan Gaugler

2018-01-01

Full Text Available A new and fully automated workflow for the cost effective drug screening of large populations based on the dried blood spot (DBS technology was introduced in this study. DBS were prepared by spotting 15 μL of whole blood, previously spiked with alprazolam, amphetamine, cocaine, codeine, diazepam, fentanyl, lysergic acid diethylamide (LSD, 3,4-methylenedioxymethamphet-amine (MDMA, methadone, methamphetamine, morphine and oxycodone onto filter paper cards. The dried spots were scanned, spiked with deuterated standards and directly extracted. The extract was transferred online to an analytical LC column and then to the electrospray ionization tandem mass spectrometry system. All drugs were quantified at their cut-off level and good precision and correlation within the calibration range was obtained. The method was finally applied to DBS samples from two patients with back pain and codeine and oxycodone could be identified and quantified accurately below the level of misuse of 89.6 ng/mL and 39.6 ng/mL respectively.

Automated Selection of Hotspots (ASH): enhanced automated segmentation and adaptive step finding for Ki67 hotspot detection in adrenal cortical cancer.

Science.gov (United States)

Lu, Hao; Papathomas, Thomas G; van Zessen, David; Palli, Ivo; de Krijger, Ronald R; van der Spek, Peter J; Dinjens, Winand N M; Stubbs, Andrew P

2014-11-25

In prognosis and therapeutics of adrenal cortical carcinoma (ACC), the selection of the most active areas in proliferative rate (hotspots) within a slide and objective quantification of immunohistochemical Ki67 Labelling Index (LI) are of critical importance. In addition to intratumoral heterogeneity in proliferative rate i.e. levels of Ki67 expression within a given ACC, lack of uniformity and reproducibility in the method of quantification of Ki67 LI may confound an accurate assessment of Ki67 LI. We have implemented an open source toolset, Automated Selection of Hotspots (ASH), for automated hotspot detection and quantification of Ki67 LI. ASH utilizes NanoZoomer Digital Pathology Image (NDPI) splitter to convert the specific NDPI format digital slide scanned from the Hamamatsu instrument into a conventional tiff or jpeg format image for automated segmentation and adaptive step finding hotspots detection algorithm. Quantitative hotspot ranking is provided by the functionality from the open source application ImmunoRatio as part of the ASH protocol. The output is a ranked set of hotspots with concomitant quantitative values based on whole slide ranking. We have implemented an open source automated detection quantitative ranking of hotspots to support histopathologists in selecting the 'hottest' hotspot areas in adrenocortical carcinoma. To provide wider community easy access to ASH we implemented a Galaxy virtual machine (VM) of ASH which is available from http://bioinformatics.erasmusmc.nl/wiki/Automated_Selection_of_Hotspots . The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_216.

Accurate, fully-automated NMR spectral profiling for metabolomics.

Directory of Open Access Journals (Sweden)

Siamak Ravanbakhsh

Full Text Available Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile"-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D 1H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid, BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF, defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error, in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of

Automated Fault Detection for DIII-D Tokamak Experiments

International Nuclear Information System (INIS)

Walker, M.L.; Scoville, J.T.; Johnson, R.D.; Hyatt, A.W.; Lee, J.

1999-01-01

An automated fault detection software system has been developed and was used during 1999 DIII-D plasma operations. The Fault Identification and Communication System (FICS) executes automatically after every plasma discharge to check dozens of subsystems for proper operation and communicates the test results to the tokamak operator. This system is now used routinely during DIII-D operations and has led to an increase in tokamak productivity

Automated detection and categorization of genital injuries using digital colposcopy

DEFF Research Database (Denmark)

Fernandes, Kelwin; Cardoso, Jaime S.; Astrup, Birgitte Schmidt

2017-01-01

handcrafted features and deep learning techniques in the automated processing of colposcopic images for genital injury detection. Positive results where achieved by both paradigms in segmentation and classification subtasks, being traditional and deep models the best strategy for each subtask type...

Automated detection of microcalcification clusters in mammograms

Science.gov (United States)

Karale, Vikrant A.; Mukhopadhyay, Sudipta; Singh, Tulika; Khandelwal, Niranjan; Sadhu, Anup

2017-03-01

Mammography is the most efficient modality for detection of breast cancer at early stage. Microcalcifications are tiny bright spots in mammograms and can often get missed by the radiologist during diagnosis. The presence of microcalcification clusters in mammograms can act as an early sign of breast cancer. This paper presents a completely automated computer-aided detection (CAD) system for detection of microcalcification clusters in mammograms. Unsharp masking is used as a preprocessing step which enhances the contrast between microcalcifications and the background. The preprocessed image is thresholded and various shape and intensity based features are extracted. Support vector machine (SVM) classifier is used to reduce the false positives while preserving the true microcalcification clusters. The proposed technique is applied on two different databases i.e DDSM and private database. The proposed technique shows good sensitivity with moderate false positives (FPs) per image on both databases.

Efficient airport detection using region-based fully convolutional neural networks

Science.gov (United States)

Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

2018-04-01

This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

Automated detection of analyzable metaphase chromosome cells depicted on scanned digital microscopic images

Science.gov (United States)

Qiu, Yuchen; Wang, Xingwei; Chen, Xiaodong; Li, Yuhua; Liu, Hong; Li, Shibo; Zheng, Bin

2010-02-01

Visually searching for analyzable metaphase chromosome cells under microscopes is quite time-consuming and difficult. To improve detection efficiency, consistency, and diagnostic accuracy, an automated microscopic image scanning system was developed and tested to directly acquire digital images with sufficient spatial resolution for clinical diagnosis. A computer-aided detection (CAD) scheme was also developed and integrated into the image scanning system to search for and detect the regions of interest (ROI) that contain analyzable metaphase chromosome cells in the large volume of scanned images acquired from one specimen. Thus, the cytogeneticists only need to observe and interpret the limited number of ROIs. In this study, the high-resolution microscopic image scanning and CAD performance was investigated and evaluated using nine sets of images scanned from either bone marrow (three) or blood (six) specimens for diagnosis of leukemia. The automated CAD-selection results were compared with the visual selection. In the experiment, the cytogeneticists first visually searched for the analyzable metaphase chromosome cells from specimens under microscopes. The specimens were also automated scanned and followed by applying the CAD scheme to detect and save ROIs containing analyzable cells while deleting the others. The automated selected ROIs were then examined by a panel of three cytogeneticists. From the scanned images, CAD selected more analyzable cells than initially visual examinations of the cytogeneticists in both blood and bone marrow specimens. In general, CAD had higher performance in analyzing blood specimens. Even in three bone marrow specimens, CAD selected 50, 22, 9 ROIs, respectively. Except matching with the initially visual selection of 9, 7, and 5 analyzable cells in these three specimens, the cytogeneticists also selected 41, 15 and 4 new analyzable cells, which were missed in initially visual searching. This experiment showed the feasibility of

Automated structure solution, density modification and model building.

Science.gov (United States)

Terwilliger, Thomas C

2002-11-01

The approaches that form the basis of automated structure solution in SOLVE and RESOLVE are described. The use of a scoring scheme to convert decision making in macromolecular structure solution to an optimization problem has proven very useful and in many cases a single clear heavy-atom solution can be obtained and used for phasing. Statistical density modification is well suited to an automated approach to structure solution because the method is relatively insensitive to choices of numbers of cycles and solvent content. The detection of non-crystallographic symmetry (NCS) in heavy-atom sites and checking of potential NCS operations against the electron-density map has proven to be a reliable method for identification of NCS in most cases. Automated model building beginning with an FFT-based search for helices and sheets has been successful in automated model building for maps with resolutions as low as 3 A. The entire process can be carried out in a fully automatic fashion in many cases.

A Fully Automated Diabetes Prevention Program, Alive-PD: Program Design and Randomized Controlled Trial Protocol.

Science.gov (United States)

Block, Gladys; Azar, Kristen Mj; Block, Torin J; Romanelli, Robert J; Carpenter, Heather; Hopkins, Donald; Palaniappan, Latha; Block, Clifford H

2015-01-21

In the United States, 86 million adults have pre-diabetes. Evidence-based interventions that are both cost effective and widely scalable are needed to prevent diabetes. Our goal was to develop a fully automated diabetes prevention program and determine its effectiveness in a randomized controlled trial. Subjects with verified pre-diabetes were recruited to participate in a trial of the effectiveness of Alive-PD, a newly developed, 1-year, fully automated behavior change program delivered by email and Web. The program involves weekly tailored goal-setting, team-based and individual challenges, gamification, and other opportunities for interaction. An accompanying mobile phone app supports goal-setting and activity planning. For the trial, participants were randomized by computer algorithm to start the program immediately or after a 6-month delay. The primary outcome measures are change in HbA1c and fasting glucose from baseline to 6 months. The secondary outcome measures are change in HbA1c, glucose, lipids, body mass index (BMI), weight, waist circumference, and blood pressure at 3, 6, 9, and 12 months. Randomization and delivery of the intervention are independent of clinic staff, who are blinded to treatment assignment. Outcomes will be evaluated for the intention-to-treat and per-protocol populations. A total of 340 subjects with pre-diabetes were randomized to the intervention (n=164) or delayed-entry control group (n=176). Baseline characteristics were as follows: mean age 55 (SD 8.9); mean BMI 31.1 (SD 4.3); male 68.5%; mean fasting glucose 109.9 (SD 8.4) mg/dL; and mean HbA1c 5.6 (SD 0.3)%. Data collection and analysis are in progress. We hypothesize that participants in the intervention group will achieve statistically significant reductions in fasting glucose and HbA1c as compared to the control group at 6 months post baseline. The randomized trial will provide rigorous evidence regarding the efficacy of this Web- and Internet-based program in reducing or

An Intelligent Automation Platform for Rapid Bioprocess Design.

Science.gov (United States)

Wu, Tianyi; Zhou, Yuhong

2014-08-01

Bioprocess development is very labor intensive, requiring many experiments to characterize each unit operation in the process sequence to achieve product safety and process efficiency. Recent advances in microscale biochemical engineering have led to automated experimentation. A process design workflow is implemented sequentially in which (1) a liquid-handling system performs high-throughput wet lab experiments, (2) standalone analysis devices detect the data, and (3) specific software is used for data analysis and experiment design given the user's inputs. We report an intelligent automation platform that integrates these three activities to enhance the efficiency of such a workflow. A multiagent intelligent architecture has been developed incorporating agent communication to perform the tasks automatically. The key contribution of this work is the automation of data analysis and experiment design and also the ability to generate scripts to run the experiments automatically, allowing the elimination of human involvement. A first-generation prototype has been established and demonstrated through lysozyme precipitation process design. All procedures in the case study have been fully automated through an intelligent automation platform. The realization of automated data analysis and experiment design, and automated script programming for experimental procedures has the potential to increase lab productivity. © 2013 Society for Laboratory Automation and Screening.

Automated microaneurysm detection in diabetic retinopathy using curvelet transform

Science.gov (United States)

Ali Shah, Syed Ayaz; Laude, Augustinus; Faye, Ibrahima; Tang, Tong Boon

2016-10-01

Microaneurysms (MAs) are known to be the early signs of diabetic retinopathy (DR). An automated MA detection system based on curvelet transform is proposed for color fundus image analysis. Candidates of MA were extracted in two parallel steps. In step one, blood vessels were removed from preprocessed green band image and preliminary MA candidates were selected by local thresholding technique. In step two, based on statistical features, the image background was estimated. The results from the two steps allowed us to identify preliminary MA candidates which were also present in the image foreground. A collection set of features was fed to a rule-based classifier to divide the candidates into MAs and non-MAs. The proposed system was tested with Retinopathy Online Challenge database. The automated system detected 162 MAs out of 336, thus achieved a sensitivity of 48.21% with 65 false positives per image. Counting MA is a means to measure the progression of DR. Hence, the proposed system may be deployed to monitor the progression of DR at early stage in population studies.

Development of a phantom to test fully automated breast density software – A work in progress

International Nuclear Information System (INIS)

Waade, G.G.; Hofvind, S.; Thompson, J.D.; Highnam, R.; Hogg, P.

2017-01-01

Objectives: Mammographic density (MD) is an independent risk factor for breast cancer and may have a future role for stratified screening. Automated software can estimate MD but the relationship between breast thickness reduction and MD is not fully understood. Our aim is to develop a deformable breast phantom to assess automated density software and the impact of breast thickness reduction on MD. Methods: Several different configurations of poly vinyl alcohol (PVAL) phantoms were created. Three methods were used to estimate their density. Raw image data of mammographic images were processed using Volpara to estimate volumetric breast density (VBD%); Hounsfield units (HU) were measured on CT images; and physical density (g/cm 3 ) was calculated using a formula involving mass and volume. Phantom volume versus contact area and phantom volume versus phantom thickness was compared to values of real breasts. Results: Volpara recognized all deformable phantoms as female breasts. However, reducing the phantom thickness caused a change in phantom density and the phantoms were not able to tolerate same level of compression and thickness reduction experienced by female breasts during mammography. Conclusion: Our results are promising as all phantoms resulted in valid data for automated breast density measurement. Further work should be conducted on PVAL and other materials to produce deformable phantoms that mimic female breast structure and density with the ability of being compressed to the same level as female breasts. Advances in knowledge: We are the first group to have produced deformable phantoms that are recognized as breasts by Volpara software. - Highlights: • Several phantoms of different configurations were created. • Three methods to assess phantom density were implemented. • All phantoms were identified as breasts by the Volpara software. • Reducing phantom thickness caused a change in phantom density.

Clinical validation of fully automated computation of ejection fraction from gated equilibrium blood-pool scintigrams

International Nuclear Information System (INIS)

Reiber, J.H.C.; Lie, S.P.; Simoons, M.L.; Hoek, C.; Gerbrands, J.J.; Wijns, W.; Bakker, W.H.; Kooij, P.P.M.

1983-01-01

A fully automated procedure for the computation of left-ventricular ejection fraction (EF) from cardiac-gated Tc-99m blood-pool (GBP) scintigrams with fixed, dual, and variable ROI methods is described. By comparison with EF data from contrast ventriculography in 68 patients, the dual-ROI method (separate end-diastolic and end-systolic contours) was found to be the method of choice; processing time was 2 min. Success score of dual-ROI procedure was 92% as assessed from 100 GBP studies. Overall reproducibility of data acquisition and analysis was determined in 12 patients. Mean value and standard deviation of differences between repeat studies (average time interval 27 min) were 0.8% and 4.3% EF units, respectively, (r=0.98). The authors conclude that left-ventricular EF can be computed automatically from GBP scintigrams with minimal operator-interaction and good reproducibility; EFs are similar to those from contrast ventriculography

A user-friendly robotic sample preparation program for fully automated biological sample pipetting and dilution to benefit the regulated bioanalysis.

Science.gov (United States)

Jiang, Hao; Ouyang, Zheng; Zeng, Jianing; Yuan, Long; Zheng, Naiyu; Jemal, Mohammed; Arnold, Mark E

2012-06-01

Biological sample dilution is a rate-limiting step in bioanalytical sample preparation when the concentrations of samples are beyond standard curve ranges, especially when multiple dilution factors are needed in an analytical run. We have developed and validated a Microsoft Excel-based robotic sample preparation program (RSPP) that automatically transforms Watson worklist sample information (identification, sequence and dilution factor) to comma-separated value (CSV) files. The Freedom EVO liquid handler software imports and transforms the CSV files to executable worklists (.gwl files), allowing the robot to perform sample dilutions at variable dilution factors. The dynamic dilution range is 1- to 1000-fold and divided into three dilution steps: 1- to 10-, 11- to 100-, and 101- to 1000-fold. The whole process, including pipetting samples, diluting samples, and adding internal standard(s), is accomplished within 1 h for two racks of samples (96 samples/rack). This platform also supports online sample extraction (liquid-liquid extraction, solid-phase extraction, protein precipitation, etc.) using 96 multichannel arms. This fully automated and validated sample dilution and preparation process has been applied to several drug development programs. The results demonstrate that application of the RSPP for fully automated sample processing is efficient and rugged. The RSPP not only saved more than 50% of the time in sample pipetting and dilution but also reduced human errors. The generated bioanalytical data are accurate and precise; therefore, this application can be used in regulated bioanalysis.

Automation of cDNA Synthesis and Labelling Improves Reproducibility

Directory of Open Access Journals (Sweden)

Daniel Klevebring

2009-01-01

Full Text Available Background. Several technologies, such as in-depth sequencing and microarrays, enable large-scale interrogation of genomes and transcriptomes. In this study, we asses reproducibility and throughput by moving all laboratory procedures to a robotic workstation, capable of handling superparamagnetic beads. Here, we describe a fully automated procedure for cDNA synthesis and labelling for microarrays, where the purification steps prior to and after labelling are based on precipitation of DNA on carboxylic acid-coated paramagnetic beads. Results. The fully automated procedure allows for samples arrayed on a microtiter plate to be processed in parallel without manual intervention and ensuring high reproducibility. We compare our results to a manual sample preparation procedure and, in addition, use a comprehensive reference dataset to show that the protocol described performs better than similar manual procedures. Conclusions. We demonstrate, in an automated gene expression microarray experiment, a reduced variance between replicates, resulting in an increase in the statistical power to detect differentially expressed genes, thus allowing smaller differences between samples to be identified. This protocol can with minor modifications be used to create cDNA libraries for other applications such as in-depth analysis using next-generation sequencing technologies.

Automating Vendor Fraud Detection in Enterprise Systems

Directory of Open Access Journals (Sweden)

Kishore Singh

2013-06-01

Full Text Available Fraud is a multi-billion dollar industry that continues to grow annually. Many organisations are poorly prepared to prevent and detect fraud. Fraud detection strategies are intended to quickly and efficiently identify fraudulent activities that circumvent preventative measures. In this paper we adopt a Design-Science methodological framework to develop a model for detection of vendor fraud based on analysis of patterns or signatures identified in enterprise system audit trails. The concept is demonstrated be developing prototype software. Verification of the prototype is achieved by performing a series of experiments. Validation is achieved by independent reviews from auditing practitioners. Key findings of this study are: i automating routine data analytics improves auditor productivity and reduces time taken to identify potential fraud, and ii visualisations assist in promptly identifying potentially fraudulent user activities. The study makes the following contributions: i a model for proactive fraud detection, ii methods for visualising user activities in transaction data, iii a stand-alone MCL-based prototype.

Level of Automation and Failure Frequency Effects on Simulated Lunar Lander Performance

Science.gov (United States)

Marquez, Jessica J.; Ramirez, Margarita

2014-01-01

A human-in-the-loop experiment was conducted at the NASA Ames Research Center Vertical Motion Simulator, where instrument-rated pilots completed a simulated terminal descent phase of a lunar landing. Ten pilots participated in a 2 x 2 mixed design experiment, with level of automation as the within-subjects factor and failure frequency as the between subjects factor. The two evaluated levels of automation were high (fully automated landing) and low (manual controlled landing). During test trials, participants were exposed to either a high number of failures (75% failure frequency) or low number of failures (25% failure frequency). In order to investigate the pilots' sensitivity to changes in levels of automation and failure frequency, the dependent measure selected for this experiment was accuracy of failure diagnosis, from which D Prime and Decision Criterion were derived. For each of the dependent measures, no significant difference was found for level of automation and no significant interaction was detected between level of automation and failure frequency. A significant effect was identified for failure frequency suggesting failure frequency has a significant effect on pilots' sensitivity to failure detection and diagnosis. Participants were more likely to correctly identify and diagnose failures if they experienced the higher levels of failures, regardless of level of automation

Fully automated data acquisition, processing, and display in equilibrium radioventriculography

International Nuclear Information System (INIS)

Bourguignon, M.H.; Douglass, K.H.; Links, J.M.; Wagner, H.N. Jr.; Johns Hopkins Medical Institutions, Baltimore, MD

1981-01-01

A fully automated data acquisition, processing, and display procedure was developed for equilibrium radioventriculography. After a standardized acquisition, the study is automatically analyzed to yield both right and left ventricular time-activity curves. The program first creates a series of edge-enhanced images (difference between squared images and scaled original images). A marker point within each ventricle is then identified as that pixel with maximum counts to the patient's right and left of the count center of gravity of a stroke volume image. Regions of interest are selected on each frame as the first contour of local maxima of the two-dimensional second derivative (pseudo-Laplacian) which encloses the appropriate marker point, using a method developed by Goris. After shifting the left ventricular end-systolic region of interest four pixels to the patient's left, a background region of interest is generated as the crescent-shaped area of the shifted region of interest not intersected by the end systolic region. The average counts/pixel in this background region in the end systolic frame of the original study are subtracted from each pixel in all frames of the gated study. Right and left ventricular time-activity curves are then obtained by applying each region of interest to its corresponding background-subtracted frame, and the ejection fraction, end diastolic, end systolic, and stroke counts determined for both ventricles. In fourteen consecutive patients, in addition to the automatic ejection fractions, manually drawn regions of interest were used to obtain ejection fractions for both ventricles. The manual regions of interest were drawn twice, and the average obtained. (orig./TR)

Automated crack detection in conductive smart-concrete structures using a resistor mesh model

Science.gov (United States)

Downey, Austin; D'Alessandro, Antonella; Ubertini, Filippo; Laflamme, Simon

2018-03-01

Various nondestructive evaluation techniques are currently used to automatically detect and monitor cracks in concrete infrastructure. However, these methods often lack the scalability and cost-effectiveness over large geometries. A solution is the use of self-sensing carbon-doped cementitious materials. These self-sensing materials are capable of providing a measurable change in electrical output that can be related to their damage state. Previous work by the authors showed that a resistor mesh model could be used to track damage in structural components fabricated from electrically conductive concrete, where damage was located through the identification of high resistance value resistors in a resistor mesh model. In this work, an automated damage detection strategy that works through placing high value resistors into the previously developed resistor mesh model using a sequential Monte Carlo method is introduced. Here, high value resistors are used to mimic the internal condition of damaged cementitious specimens. The proposed automated damage detection method is experimentally validated using a 500 × 500 × 50 mm3 reinforced cement paste plate doped with multi-walled carbon nanotubes exposed to 100 identical impact tests. Results demonstrate that the proposed Monte Carlo method is capable of detecting and localizing the most prominent damage in a structure, demonstrating that automated damage detection in smart-concrete structures is a promising strategy for real-time structural health monitoring of civil infrastructure.

Automated acoustic analysis in detection of spontaneous swallows in Parkinson's disease.

Science.gov (United States)

Golabbakhsh, Marzieh; Rajaei, Ali; Derakhshan, Mahmoud; Sadri, Saeed; Taheri, Masoud; Adibi, Peyman

2014-10-01

Acoustic monitoring of swallow frequency has become important as the frequency of spontaneous swallowing can be an index for dysphagia and related complications. In addition, it can be employed as an objective quantification of ingestive behavior. Commonly, swallowing complications are manually detected using videofluoroscopy recordings, which require expensive equipment and exposure to radiation. In this study, a noninvasive automated technique is proposed that uses breath and swallowing recordings obtained via a microphone located over the laryngopharynx. Nonlinear diffusion filters were used in which a scale-space decomposition of recorded sound at different levels extract swallows from breath sounds and artifacts. This technique was compared to manual detection of swallows using acoustic signals on a sample of 34 subjects with Parkinson's disease. A speech language pathologist identified five subjects who showed aspiration during the videofluoroscopic swallowing study. The proposed automated method identified swallows with a sensitivity of 86.67 %, a specificity of 77.50 %, and an accuracy of 82.35 %. These results indicate the validity of automated acoustic recognition of swallowing as a fast and efficient approach to objectively estimate spontaneous swallow frequency.

Development of a fully automated adaptive unsharp masking technique in digital chest radiograph

International Nuclear Information System (INIS)

Abe, Katsumi; Katsuragawa, Shigehiko; Sasaki, Yasuo

1991-01-01

We are developing a fully automated adaptive unsharp masking technique with various parameters depending on regional image features of a digital chest radiograph. A chest radiograph includes various regions such as lung fields, retrocardiac area and spine in which their texture patterns and optical densities are extremely different. Therefore, it is necessary to enhance image contrast of each region by each optimum parameter. First, we investigated optimum weighting factors and mask sizes of unsharp masking technique in a digital chest radiograph. Then, a chest radiograph is automatically divided into three segments, one for the lung field, one for the retrocardiac area, and one for the spine, by using histogram analysis of pixel values. Finally, high frequency components of the lung field and retrocardiac area are selectively enhanced with a small mask size and mild weighting factors which are previously determined as optimum parameters. In addition, low frequency components of the spine are enhanced with a large mask size and adequate weighting factors. This processed image shows excellent depiction of the lung field, retrocardiac area and spine simultaneously with optimum contrast. Our image processing technique may be useful for diagnosis of chest radiographs. (author)

Systems and Methods for Automated Water Detection Using Visible Sensors

Science.gov (United States)

Rankin, Arturo L. (Inventor); Matthies, Larry H. (Inventor); Bellutta, Paolo (Inventor)

2016-01-01

Systems and methods are disclosed that include automated machine vision that can utilize images of scenes captured by a 3D imaging system configured to image light within the visible light spectrum to detect water. One embodiment includes autonomously detecting water bodies within a scene including capturing at least one 3D image of a scene using a sensor system configured to detect visible light and to measure distance from points within the scene to the sensor system, and detecting water within the scene using a processor configured to detect regions within each of the at least one 3D images that possess at least one characteristic indicative of the presence of water.

Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection.

Science.gov (United States)

Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

2017-10-01

Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

A new framework for analysing automated acoustic species-detection data: occupancy estimation and optimization of recordings post-processing

Science.gov (United States)

Chambert, Thierry A.; Waddle, J. Hardin; Miller, David A.W.; Walls, Susan; Nichols, James D.

2018-01-01

The development and use of automated species-detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide a cost- and time-effective means to process information-rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors.We developed a hierarchical modelling framework for estimating species occupancy from automated species-detection data. We explore design and optimization of data post-processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false positive errors and utilizes information about both occurrence and abundance of detections to improve estimation.Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders.When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post-validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post-validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated.Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species-detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programs.

Fully-automated computer-assisted method of CT brain scan analysis for the measurement of cerebrospinal fluid spaces and brain absorption density

Energy Technology Data Exchange (ETDEWEB)

Baldy, R.E.; Brindley, G.S.; Jacobson, R.R.; Reveley, M.A.; Lishman, W.A.; Ewusi-Mensah, I.; Turner, S.W.

1986-03-01

Computer-assisted methods of CT brain scan analysis offer considerable advantages over visual inspection, particularly in research; and several semi-automated methods are currently available. A new computer-assisted program is presented which provides fully automated processing of CT brain scans, depending on ''anatomical knowledge'' of where cerebrospinal fluid (CSF)-containing spaces are likely to lie. After identifying these regions of interest quantitative estimates are then provided of CSF content in each slice in cisterns, ventricles, Sylvian fissure and interhemispheric fissure. Separate measures are also provided of mean brain density in each slice. These estimates can be summated to provide total ventricular and total brain volumes. The program shows a high correlation with measures derived from mechanical planimetry and visual grading procedures, also when tested against a phantom brain of known ventricular volume. The advantages and limitations of the present program are discussed.

An Intelligent Automation Platform for Rapid Bioprocess Design

Science.gov (United States)

Wu, Tianyi

2014-01-01

Bioprocess development is very labor intensive, requiring many experiments to characterize each unit operation in the process sequence to achieve product safety and process efficiency. Recent advances in microscale biochemical engineering have led to automated experimentation. A process design workflow is implemented sequentially in which (1) a liquid-handling system performs high-throughput wet lab experiments, (2) standalone analysis devices detect the data, and (3) specific software is used for data analysis and experiment design given the user’s inputs. We report an intelligent automation platform that integrates these three activities to enhance the efficiency of such a workflow. A multiagent intelligent architecture has been developed incorporating agent communication to perform the tasks automatically. The key contribution of this work is the automation of data analysis and experiment design and also the ability to generate scripts to run the experiments automatically, allowing the elimination of human involvement. A first-generation prototype has been established and demonstrated through lysozyme precipitation process design. All procedures in the case study have been fully automated through an intelligent automation platform. The realization of automated data analysis and experiment design, and automated script programming for experimental procedures has the potential to increase lab productivity. PMID:24088579

FULLY AUTOMATED GENERATION OF ACCURATE DIGITAL SURFACE MODELS WITH SUB-METER RESOLUTION FROM SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

J. Wohlfeil

2012-07-01

Full Text Available Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images’ relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.

Automation in Clinical Microbiology

Science.gov (United States)

Ledeboer, Nathan A.

2013-01-01

Historically, the trend toward automation in clinical pathology laboratories has largely bypassed the clinical microbiology laboratory. In this article, we review the historical impediments to automation in the microbiology laboratory and offer insight into the reasons why we believe that we are on the cusp of a dramatic change that will sweep a wave of automation into clinical microbiology laboratories. We review the currently available specimen-processing instruments as well as the total laboratory automation solutions. Lastly, we outline the types of studies that will need to be performed to fully assess the benefits of automation in microbiology laboratories. PMID:23515547

Automated detection of actinic keratoses in clinical photographs.

Science.gov (United States)

Hames, Samuel C; Sinnya, Sudipta; Tan, Jean-Marie; Morze, Conrad; Sahebian, Azadeh; Soyer, H Peter; Prow, Tarl W

2015-01-01

Clinical diagnosis of actinic keratosis is known to have intra- and inter-observer variability, and there is currently no non-invasive and objective measure to diagnose these lesions. The aim of this pilot study was to determine if automatically detecting and circumscribing actinic keratoses in clinical photographs is feasible. Photographs of the face and dorsal forearms were acquired in 20 volunteers from two groups: the first with at least on actinic keratosis present on the face and each arm, the second with no actinic keratoses. The photographs were automatically analysed using colour space transforms and morphological features to detect erythema. The automated output was compared with a senior consultant dermatologist's assessment of the photographs, including the intra-observer variability. Performance was assessed by the correlation between total lesions detected by automated method and dermatologist, and whether the individual lesions detected were in the same location as the dermatologist identified lesions. Additionally, the ability to limit false positives was assessed by automatic assessment of the photographs from the no actinic keratosis group in comparison to the high actinic keratosis group. The correlation between the automatic and dermatologist counts was 0.62 on the face and 0.51 on the arms, compared to the dermatologist's intra-observer variation of 0.83 and 0.93 for the same. Sensitivity of automatic detection was 39.5% on the face, 53.1% on the arms. Positive predictive values were 13.9% on the face and 39.8% on the arms. Significantly more lesions (p<0.0001) were detected in the high actinic keratosis group compared to the no actinic keratosis group. The proposed method was inferior to assessment by the dermatologist in terms of sensitivity and positive predictive value. However, this pilot study used only a single simple feature and was still able to achieve sensitivity of detection of 53.1% on the arms.This suggests that image analysis is

Anesthesiology, automation, and artificial intelligence.

Science.gov (United States)

Alexander, John C; Joshi, Girish P

2018-01-01

There have been many attempts to incorporate automation into the practice of anesthesiology, though none have been successful. Fundamentally, these failures are due to the underlying complexity of anesthesia practice and the inability of rule-based feedback loops to fully master it. Recent innovations in artificial intelligence, especially machine learning, may usher in a new era of automation across many industries, including anesthesiology. It would be wise to consider the implications of such potential changes before they have been fully realized.

From drafting guideline to error detection: Automating style checking for legislative texts

OpenAIRE

Höfler Stefan; Sugisaki Kyoko

2012-01-01

This paper reports on the development of methods for the automated detection of violations of style guidelines for legislative texts, and their implementation in a prototypical tool. To this aim, the approach of error modelling employed in automated style checkers for technical writing is enhanced to meet the requirements of legislative editing. The paper identifies and discusses the two main sets of challenges that have to be tackled in this process: (i) the provision of domain-specific NLP ...

Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence.

Science.gov (United States)

Rajalakshmi, Ramachandran; Subashini, Radhakrishnan; Anjana, Ranjit Mohan; Mohan, Viswanathan

2018-06-01

To assess the role of artificial intelligence (AI)-based automated software for detection of diabetic retinopathy (DR) and sight-threatening DR (STDR) by fundus photography taken using a smartphone-based device and validate it against ophthalmologist's grading. Three hundred and one patients with type 2 diabetes underwent retinal photography with Remidio 'Fundus on phone' (FOP), a smartphone-based device, at a tertiary care diabetes centre in India. Grading of DR was performed by the ophthalmologists using International Clinical DR (ICDR) classification scale. STDR was defined by the presence of severe non-proliferative DR, proliferative DR or diabetic macular oedema (DME). The retinal photographs were graded using a validated AI DR screening software (EyeArt TM ) designed to identify DR, referable DR (moderate non-proliferative DR or worse and/or DME) or STDR. The sensitivity and specificity of automated grading were assessed and validated against the ophthalmologists' grading. Retinal images of 296 patients were graded. DR was detected by the ophthalmologists in 191 (64.5%) and by the AI software in 203 (68.6%) patients while STDR was detected in 112 (37.8%) and 146 (49.3%) patients, respectively. The AI software showed 95.8% (95% CI 92.9-98.7) sensitivity and 80.2% (95% CI 72.6-87.8) specificity for detecting any DR and 99.1% (95% CI 95.1-99.9) sensitivity and 80.4% (95% CI 73.9-85.9) specificity in detecting STDR with a kappa agreement of k = 0.78 (p < 0.001) and k = 0.75 (p < 0.001), respectively. Automated AI analysis of FOP smartphone retinal imaging has very high sensitivity for detecting DR and STDR and thus can be an initial tool for mass retinal screening in people with diabetes.

Automation of Classical QEEG Trending Methods for Early Detection of Delayed Cerebral Ischemia: More Work to Do.

Science.gov (United States)

Wickering, Ellis; Gaspard, Nicolas; Zafar, Sahar; Moura, Valdery J; Biswal, Siddharth; Bechek, Sophia; OʼConnor, Kathryn; Rosenthal, Eric S; Westover, M Brandon

2016-06-01

The purpose of this study is to evaluate automated implementations of continuous EEG monitoring-based detection of delayed cerebral ischemia based on methods used in classical retrospective studies. We studied 95 patients with either Fisher 3 or Hunt Hess 4 to 5 aneurysmal subarachnoid hemorrhage who were admitted to the Neurosciences ICU and underwent continuous EEG monitoring. We implemented several variations of two classical algorithms for automated detection of delayed cerebral ischemia based on decreases in alpha-delta ratio and relative alpha variability. Of 95 patients, 43 (45%) developed delayed cerebral ischemia. Our automated implementation of the classical alpha-delta ratio-based trending method resulted in a sensitivity and specificity (Se,Sp) of (80,27)%, compared with the values of (100,76)% reported in the classic study using similar methods in a nonautomated fashion. Our automated implementation of the classical relative alpha variability-based trending method yielded (Se,Sp) values of (65,43)%, compared with (100,46)% reported in the classic study using nonautomated analysis. Our findings suggest that improved methods to detect decreases in alpha-delta ratio and relative alpha variability are needed before an automated EEG-based early delayed cerebral ischemia detection system is ready for clinical use.

Automated Detection of Client-State Manipulation Vulnerabilities

DEFF Research Database (Denmark)

Møller, Anders; Schwarz, Mathias

2012-01-01

automated tools that can assist the programmers in the application development process by detecting weaknesses. Many vulnerabilities are related to web application code that stores references to application state in the generated HTML documents to work around the statelessness of the HTTP protocol....... In this paper, we show that such client-state manipulation vulnerabilities are amenable to tool supported detection. We present a static analysis for the widely used frameworks Java Servlets, JSP, and Struts. Given a web application archive as input, the analysis identifies occurrences of client state...... and infers the information flow between the client state and the shared application state on the server. This makes it possible to check how client-state manipulation performed by malicious users may affect the shared application state and cause leakage or modifications of sensitive information. The warnings...

Automated detection of cavities present in the high explosive filler of artillery shells

International Nuclear Information System (INIS)

Kruger, R.P.; Janney, D.H.; Breedlove, J.R. Jr.

1976-01-01

Initial research has been conducted into the use of digital image analysis techniques for automated detection and characterization of piping cavities present in the high explosive (HE) filler region of 105-mm artillery shells. Experimental work utilizing scene segmentation techniques followed by a sequential similarity detection algorithm for cavitation detection have yielded promising initial results. This work is described with examples of computer-detected defects

Fully automated synthesis of ¹¹C-acetate as tumor PET tracer by simple modified solid-phase extraction purification.

Science.gov (United States)

Tang, Xiaolan; Tang, Ganghua; Nie, Dahong

2013-12-01

Automated synthesis of (11)C-acetate ((11)C-AC) as the most commonly used radioactive fatty acid tracer is performed by a simple, rapid, and modified solid-phase extraction (SPE) purification. Automated synthesis of (11)C-AC was implemented by carboxylation reaction of MeMgBr on a polyethylene Teflon loop ring with (11)C-CO2, followed by acidic hydrolysis with acid and SCX cartridge, and purification on SCX, AG11A8 and C18 SPE cartridges using a commercially available (11)C-tracer synthesizer. Quality control test and animals positron emission tomography (PET) imaging were also carried out. A high and reproducible decay-uncorrected radiochemical yield of (41.0 ± 4.6)% (n=10) was obtained from (11)C-CO2 within the whole synthesis time about 8 min. The radiochemical purity of (11)C-AC was over 95% by high-performance liquid chromatography (HPLC) analysis. Quality control test and PET imaging showed that (11)C-AC injection produced by the simple SPE procedure was safe and efficient, and was in agreement with the current Chinese radiopharmaceutical quality control guidelines. The novel, simple, and rapid method is readily adapted to the fully automated synthesis of (11)C-AC on several existing commercial synthesis module. The method can be used routinely to produce (11)C-AC for preclinical and clinical studies with PET imaging. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Automated Assessment of Postural Stability: Balance Detection Algorithm.

Science.gov (United States)

Napoli, Alessandro; Glass, Stephen M; Tucker, Carole; Obeid, Iyad

2017-12-01

Impaired balance is a common indicator of mild traumatic brain injury, concussion and musculoskeletal injury. Given the clinical relevance of such injuries, especially in military settings, it is paramount to develop more accurate and reliable on-field evaluation tools. This work presents the design and implementation of the automated assessment of postural stability (AAPS) system, for on-field evaluations following concussion. The AAPS is a computer system, based on inexpensive off-the-shelf components and custom software, that aims to automatically and reliably evaluate balance deficits, by replicating a known on-field clinical test, namely, the Balance Error Scoring System (BESS). The AAPS main innovation is its balance error detection algorithm that has been designed to acquire data from a Microsoft Kinect ® sensor and convert them into clinically-relevant BESS scores, using the same detection criteria defined by the original BESS test. In order to assess the AAPS balance evaluation capability, a total of 15 healthy subjects (7 male, 8 female) were required to perform the BESS test, while simultaneously being tracked by a Kinect 2.0 sensor and a professional-grade motion capture system (Qualisys AB, Gothenburg, Sweden). High definition videos with BESS trials were scored off-line by three experienced observers for reference scores. AAPS performance was assessed by comparing the AAPS automated scores to those derived by three experienced observers. Our results show that the AAPS error detection algorithm presented here can accurately and precisely detect balance deficits with performance levels that are comparable to those of experienced medical personnel. Specifically, agreement levels between the AAPS algorithm and the human average BESS scores ranging between 87.9% (single-leg on foam) and 99.8% (double-leg on firm ground) were detected. Moreover, statistically significant differences in balance scores were not detected by an ANOVA test with alpha equal to 0

Integrating Electrochemical Detection with Centrifugal Microfluidics for Real-Time and Fully Automated Sample Testing

DEFF Research Database (Denmark)

Andreasen, Sune Zoëga; Kwasny, Dorota; Amato, Letizia

2015-01-01

Here we present a robust, stable and low-noise experimental set-up for performing electrochemical detection on a centrifugal microfluidic platform. By using a low-noise electronic component (electrical slip-ring) it is possible to achieve continuous, on-line monitoring of electrochemical experime......Here we present a robust, stable and low-noise experimental set-up for performing electrochemical detection on a centrifugal microfluidic platform. By using a low-noise electronic component (electrical slip-ring) it is possible to achieve continuous, on-line monitoring of electrochemical...

Fully automated intrinsic respiratory and cardiac gating for small animal CT

Energy Technology Data Exchange (ETDEWEB)

Kuntz, J; Baeuerle, T; Semmler, W; Bartling, S H [Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg (Germany); Dinkel, J [Department of Radiology, German Cancer Research Center, Heidelberg (Germany); Zwick, S [Department of Diagnostic Radiology, Medical Physics, Freiburg University (Germany); Grasruck, M [Siemens Healthcare, Forchheim (Germany); Kiessling, F [Chair of Experimental Molecular Imaging, RWTH-Aachen University, Medical Faculty, Aachen (Germany); Gupta, R [Department of Radiology, Massachusetts General Hospital, Boston, MA (United States)], E-mail: j.kuntz@dkfz.de

2010-04-07

A fully automated, intrinsic gating algorithm for small animal cone-beam CT is described and evaluated. A parameter representing the organ motion, derived from the raw projection images, is used for both cardiac and respiratory gating. The proposed algorithm makes it possible to reconstruct motion-corrected still images as well as to generate four-dimensional (4D) datasets representing the cardiac and pulmonary anatomy of free-breathing animals without the use of electrocardiogram (ECG) or respiratory sensors. Variation analysis of projections from several rotations is used to place a region of interest (ROI) on the diaphragm. The ROI is cranially extended to include the heart. The centre of mass (COM) variation within this ROI, the filtered frequency response and the local maxima are used to derive a binary motion-gating parameter for phase-sensitive gated reconstruction. This algorithm was implemented on a flat-panel-based cone-beam CT scanner and evaluated using a moving phantom and animal scans (seven rats and eight mice). Volumes were determined using a semiautomatic segmentation. In all cases robust gating signals could be obtained. The maximum volume error in phantom studies was less than 6%. By utilizing extrinsic gating via externally placed cardiac and respiratory sensors, the functional parameters (e.g. cardiac ejection fraction) and image quality were equivalent to this current gold standard. This algorithm obviates the necessity of both gating hardware and user interaction. The simplicity of the proposed algorithm enables adoption in a wide range of small animal cone-beam CT scanners.

Multi-scale Fully Convolutional Network for Face Detection in the Wild

KAUST Repository

Bai, Yancheng

2017-08-24

Face detection is a classical problem in computer vision. It is still a difficult task due to many nuisances that naturally occur in the wild. In this paper, we propose a multi-scale fully convolutional network for face detection. To reduce computation, the intermediate convolutional feature maps (conv) are shared by every scale model. We up-sample and down-sample the final conv map to approximate K levels of a feature pyramid, leading to a wide range of face scales that can be detected. At each feature pyramid level, a FCN is trained end-to-end to deal with faces in a small range of scale change. Because of the up-sampling, our method can detect very small faces (10×10 pixels). We test our MS-FCN detector on four public face detection datasets, including FDDB, WIDER FACE, AFW and PASCAL FACE. Extensive experiments show that it outperforms state-of-the-art methods. Also, MS-FCN runs at 23 FPS on a GPU for images of size 640×480 with no assumption on the minimum detectable face size.

Automated 3D-Printed Unibody Immunoarray for Chemiluminescence Detection of Cancer Biomarker Proteins

Science.gov (United States)

Tang, C. K.; Vaze, A.; Rusling, J. F.

2017-01-01

A low cost three-dimensional (3D) printed clear plastic microfluidic device was fabricated for fast, low cost automated protein detection. The unibody device features three reagent reservoirs, an efficient 3D network for passive mixing, and an optically transparent detection chamber housing a glass capture antibody array for measuring chemiluminescence output with a CCD camera. Sandwich type assays were built onto the glass arrays using a multi-labeled detection antibody-polyHRP (HRP = horseradish peroxidase). Total assay time was ~30 min in a complete automated assay employing a programmable syringe pump so that the protocol required minimal operator intervention. The device was used for multiplexed detection of prostate cancer biomarker proteins prostate specific antigen (PSA) and platelet factor 4 (PF-4). Detection limits of 0.5 pg mL−1 were achieved for these proteins in diluted serum with log dynamic ranges of four orders of magnitude. Good accuracy vs ELISA was validated by analyzing human serum samples. This prototype device holds good promise for further development as a point-of-care cancer diagnostics tool. PMID:28067370

Automation systems for radioimmunoassay

International Nuclear Information System (INIS)

Yamasaki, Paul

1974-01-01

The application of automation systems for radioimmunoassay (RIA) was discussed. Automated systems could be useful in the second step, of the four basic processes in the course of RIA, i.e., preparation of sample for reaction. There were two types of instrumentation, a semi-automatic pipete, and a fully automated pipete station, both providing for fast and accurate dispensing of the reagent or for the diluting of sample with reagent. Illustrations of the instruments were shown. (Mukohata, S.)

Fully automated one-pot radiosynthesis of O-(2-[{sup 18}F]fluoroethyl)-L-tyrosine on the TracerLab FX{sub FN} module

Energy Technology Data Exchange (ETDEWEB)

Bourdier, Thomas, E-mail: bts@ansto.gov.au [LifeSciences, Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC NSW 2232, Sydney (Australia); Greguric, Ivan [LifeSciences, Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC NSW 2232, Sydney (Australia); Roselt, Peter [Centre for Molecular Imaging, Peter MacCallum Cancer Centre, 12 St Andrew' s Place, East Melbourne, VIC, 3002 (Australia); Jackson, Tim; Faragalla, Jane; Katsifis, Andrew [LifeSciences, Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC NSW 2232, Sydney (Australia)

2011-07-15

Introduction: An efficient fully automated method for the radiosynthesis of enantiomerically pure O-(2-[{sup 18}F]fluoroethyl)-L-tyrosine ([{sup 18}F]FET) using the GE TracerLab FX{sub FN} synthesis module via the O-(2-tosyloxyethyl)-N-trityl-L-tyrosine tert-butylester precursor has been developed. Methods: The radiolabelling of [{sup 18}F]FET involved a classical [{sup 18}F]fluoride nucleophilic substitution performed in acetonitrile using potassium carbonate and Kryptofix 222, followed by acid hydrolysis using 2N hydrochloric acid. Results: [{sup 18}F]FET was produced in 35{+-}5% (n=22) yield non-decay-corrected (55{+-}5% decay-corrected) and with radiochemical and enantiomeric purity of >99% with a specific activity of >90 GBq/{mu}mol after 63 min of radiosynthesis including HPLC purification and formulation. Conclusion: The automated radiosynthesis provides high and reproducible yields suitable for routine clinical use.

A fully-automated computer-assisted method of CT brain scan analysis for the measurement of cerebrospinal fluid spaces and brain absorption density

International Nuclear Information System (INIS)

Baldy, R.E.; Brindley, G.S.; Jacobson, R.R.; Reveley, M.A.; Lishman, W.A.; Ewusi-Mensah, I.; Turner, S.W.

1986-01-01

Computer-assisted methods of CT brain scan analysis offer considerable advantages over visual inspection, particularly in research; and several semi-automated methods are currently available. A new computer-assisted program is presented which provides fully automated processing of CT brain scans, depending on ''anatomical knowledge'' of where cerebrospinal fluid (CSF)-containing spaces are likely to lie. After identifying these regions of interest quantitative estimates are then provided of CSF content in each slice in cisterns, ventricles, Sylvian fissure and interhemispheric fissure. Separate measures are also provided of mean brain density in each slice. These estimates can be summated to provide total ventricular and total brain volumes. The program shows a high correlation with measures derived from mechanical planimetry and visual grading procedures, also when tested against a phantom brain of known ventricular volume. The advantages and limitations of the present program are discussed. (orig.)

On transcending the impasse of respiratory motion correction applications in routine clinical imaging - a consideration of a fully automated data driven motion control framework

International Nuclear Information System (INIS)

Kesner, Adam L; Schleyer, Paul J; Büther, Florian; Walter, Martin A; Schäfers, Klaus P; Koo, Phillip J

2014-01-01

Positron emission tomography (PET) is increasingly used for the detection, characterization, and follow-up of tumors located in the thorax. However, patient respiratory motion presents a unique limitation that hinders the application of high-resolution PET technology for this type of imaging. Efforts to transcend this limitation have been underway for more than a decade, yet PET remains for practical considerations a modality vulnerable to motion-induced image degradation. Respiratory motion control is not employed in routine clinical operations. In this article, we take an opportunity to highlight some of the recent advancements in data-driven motion control strategies and how they may form an underpinning for what we are presenting as a fully automated data-driven motion control framework. This framework represents an alternative direction for future endeavors in motion control and can conceptually connect individual focused studies with a strategy for addressing big picture challenges and goals. The online version of this article (doi:10.1186/2197-7364-1-8) contains supplementary material, which is available to authorized users.

Parameter evaluation and fully-automated radiosynthesis of [11C]harmine for imaging of MAO-A for clinical trials

International Nuclear Information System (INIS)

Philippe, C.; Zeilinger, M.; Mitterhauser, M.; Dumanic, M.; Lanzenberger, R.; Hacker, M.; Wadsak, W.

2015-01-01

The aim of the present study was the evaluation and automation of the radiosynthesis of [ 11 C]harmine for clinical trials. The following parameters have been investigated: amount of base, precursor concentration, solvent, reaction temperature and time. The optimum reaction conditions were determined to be 2–3 mg/mL precursor activated with 1 eq. 5 M NaOH in DMSO, 80 °C reaction temperature and 2 min reaction time. Under these conditions 6.1±1 GBq (51.0±11% based on [ 11 C]CH 3 I, corrected for decay) of [ 11 C]harmine (n=72) were obtained. The specific activity was 101.32±28.2 GBq/µmol (at EOS). All quality control parameters were in accordance with the standards for parenteral human application. Due to its reliability and high yields, this fully-automated synthesis method can be used as routine set-up. - Highlights: • Preparation of [ 11 C]harmine on a commercially available synthesizer for the routine application. • High reliability: only 4 out of 72 failed syntheses; 5% due to technical problems. • High yields: 6.1±1 GBq overall yield (EOS). • High specific activities: 101.32±28.2 GBq/µmol

Comparison of subjective and fully automated methods for measuring mammographic density.

Science.gov (United States)

Moshina, Nataliia; Roman, Marta; Sebuødegård, Sofie; Waade, Gunvor G; Ursin, Giske; Hofvind, Solveig

2018-02-01

Background Breast radiologists of the Norwegian Breast Cancer Screening Program subjectively classified mammographic density using a three-point scale between 1996 and 2012 and changed into the fourth edition of the BI-RADS classification since 2013. In 2015, an automated volumetric breast density assessment software was installed at two screening units. Purpose To compare volumetric breast density measurements from the automated method with two subjective methods: the three-point scale and the BI-RADS density classification. Material and Methods Information on subjective and automated density assessment was obtained from screening examinations of 3635 women recalled for further assessment due to positive screening mammography between 2007 and 2015. The score of the three-point scale (I = fatty; II = medium dense; III = dense) was available for 2310 women. The BI-RADS density score was provided for 1325 women. Mean volumetric breast density was estimated for each category of the subjective classifications. The automated software assigned volumetric breast density to four categories. The agreement between BI-RADS and volumetric breast density categories was assessed using weighted kappa (k w ). Results Mean volumetric breast density was 4.5%, 7.5%, and 13.4% for categories I, II, and III of the three-point scale, respectively, and 4.4%, 7.5%, 9.9%, and 13.9% for the BI-RADS density categories, respectively ( P for trend density categories was k w  = 0.5 (95% CI = 0.47-0.53; P density increased with increasing density category of the subjective classifications. The agreement between BI-RADS and volumetric breast density categories was moderate.

A self-adapting system for the automated detection of inter-ictal epileptiform discharges.

Directory of Open Access Journals (Sweden)

Shaun S Lodder

Full Text Available PURPOSE: Scalp EEG remains the standard clinical procedure for the diagnosis of epilepsy. Manual detection of inter-ictal epileptiform discharges (IEDs is slow and cumbersome, and few automated methods are used to assist in practice. This is mostly due to low sensitivities, high false positive rates, or a lack of trust in the automated method. In this study we aim to find a solution that will make computer assisted detection more efficient than conventional methods, while preserving the detection certainty of a manual search. METHODS: Our solution consists of two phases. First, a detection phase finds all events similar to epileptiform activity by using a large database of template waveforms. Individual template detections are combined to form "IED nominations", each with a corresponding certainty value based on the reliability of their contributing templates. The second phase uses the ten nominations with highest certainty and presents them to the reviewer one by one for confirmation. Confirmations are used to update certainty values of the remaining nominations, and another iteration is performed where ten nominations with the highest certainty are presented. This continues until the reviewer is satisfied with what has been seen. Reviewer feedback is also used to update template accuracies globally and improve future detections. KEY FINDINGS: Using the described method and fifteen evaluation EEGs (241 IEDs, one third of all inter-ictal events were shown after one iteration, half after two iterations, and 74%, 90%, and 95% after 5, 10 and 15 iterations respectively. Reviewing fifteen iterations for the 20-30 min recordings 1 took approximately 5 min. SIGNIFICANCE: The proposed method shows a practical approach for combining automated detection with visual searching for inter-ictal epileptiform activity. Further evaluation is needed to verify its clinical feasibility and measure the added value it presents.

Fully automated radiosynthesis of [11C]PBR28, a radiopharmaceutical for the translocator protein (TSPO) 18 kDa, using a GE TRACERlab FXC-Pro

International Nuclear Information System (INIS)

Hoareau, Raphaël; Shao, Xia; Henderson, Bradford D.; Scott, Peter J.H.

2012-01-01

In order to image the translocator protein (TSPO) 18 kDa in the clinic using positron emission tomography (PET) imaging, we had a cause to prepare [ 11 C]PBR28. In this communication we highlight our novel, recently developed, one-pot synthesis of the desmethyl-PBR28 precursor, as well as present an optimized fully automated preparation of [ 11 C]PBR28 using a GE TRACERlab FX C-Pro . Following radiolabelling, purification is achieved by HPLC and, to the best of our knowledge, the first reported example of reconstituting [ 11 C]PBR28 into ethanolic saline using solid-phase extraction (SPE). This procedure is operationally simple, and provides high quality doses of [ 11 C]PBR28 suitable for use in clinical PET imaging studies. Typical radiochemical yield using the optimized method is 3.6% yield (EOS, n=3), radiochemical and chemical purity are consistently >99%, and specific activities are 14,523 Ci/mmol. Highlights: ► This paper reports a fully automated synthesis of [ 11 C]PBR28 using a TRACERlab FXc-pro. ► We report a solid-phase extraction technique for the reconstitution of [ 11 C]PBR28. ► ICP-MS data for PBR28 precursor is reported confirming suitability for clinical use.

Toward fully automated genotyping: Genotyping microsatellite markers by deconvolution

Energy Technology Data Exchange (ETDEWEB)

Perlin, M.W.; Lancia, G.; See-Kiong, Ng [Carnegie Mellon Univ., Pittsburgh, PA (United States)

1995-11-01

Dense genetic linkage maps have been constructed for the human and mouse genomes, with average densities of 2.9 cM and 0.35 cM, respectively. These genetic maps are crucial for mapping both Mendelian and complex traits and are useful in clinical genetic diagnosis. Current maps are largely comprised of abundant, easily assayed, and highly polymorphic PCR-based microsatellite markers, primarily dinucleotide (CA){sub n} repeats. One key limitation of these length polymorphisms is the PCR stutter (or slippage) artifact that introduces additional stutter bands. With two (or more) closely spaced alleles, the stutter bands overlap, and it is difficult to accurately determine the correct alleles; this stutter phenomenon has all but precluded full automation, since a human must visually inspect the allele data. We describe here novel deconvolution methods for accurate genotyping that mathematically remove PCR stutter artifact from microsatellite markers. These methods overcome the manual interpretation bottleneck and thereby enable full automation of genetic map construction and use. New functionalities, including the pooling of DNAs and the pooling of markers, are described that may greatly reduce the associated experimentation requirements. 32 refs., 5 figs., 3 tabs.

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

International Nuclear Information System (INIS)

Wahi-Anwar, M; Lo, P; Kim, H; Brown, M; McNitt-Gray, M

2016-01-01

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifies the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

Energy Technology Data Exchange (ETDEWEB)

Wahi-Anwar, M; Lo, P; Kim, H; Brown, M; McNitt-Gray, M [UCLA Radiological Sciences, Los Angeles, CA (United States)

2016-06-15

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifies the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel

Automated Incident Detection Using Real-Time Floating Car Data

Directory of Open Access Journals (Sweden)

Maarten Houbraken

2017-01-01

Full Text Available The aim of this paper is to demonstrate the feasibility of a live Automated Incident Detection (AID system using only Floating Car Data (FCD in one of the first large-scale FCD AID field trials. AID systems detect traffic events and alert upcoming drivers to improve traffic safety without human monitoring. These automated systems traditionally rely on traffic monitoring sensors embedded in the road. FCD allows for finer spatial granularity of traffic monitoring. However, low penetration rates of FCD probe vehicles and the data latency have historically hindered FCD AID deployment. We use a live country-wide FCD system monitoring an estimated 5.93% of all vehicles. An FCD AID system is presented and compared to the installed AID system (using loop sensor data on 2 different highways in Netherlands. Our results show the FCD AID can adequately monitor changing traffic conditions and follow the AID benchmark. The presented FCD AID is integrated with the road operator systems as part of an innovation project, making this, to the best of our knowledge, the first full chain technical feasibility trial of an FCD-only AID system. Additionally, FCD allows for AID on roads without installed sensors, allowing road safety improvements at low cost.

Automated image based prominent nucleoli detection.

Science.gov (United States)

Yap, Choon K; Kalaw, Emarene M; Singh, Malay; Chong, Kian T; Giron, Danilo M; Huang, Chao-Hui; Cheng, Li; Law, Yan N; Lee, Hwee Kuan

2015-01-01

Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings.

Automated image based prominent nucleoli detection

Directory of Open Access Journals (Sweden)

Choon K Yap

2015-01-01

Full Text Available Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings.

CEST ANALYSIS: AUTOMATED CHANGE DETECTION FROM VERY-HIGH-RESOLUTION REMOTE SENSING IMAGES

Directory of Open Access Journals (Sweden)

M. Ehlers

2012-08-01

Full Text Available A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST of the change algorithms is applied to calculate the probability of change for a particular location. CEST

Early detection of pharmacovigilance signals with automated methods based on false discovery rates: a comparative study.

Science.gov (United States)

Ahmed, Ismaïl; Thiessard, Frantz; Miremont-Salamé, Ghada; Haramburu, Françoise; Kreft-Jais, Carmen; Bégaud, Bernard; Tubert-Bitter, Pascale

2012-06-01

Improving the detection of drug safety signals has led several pharmacovigilance regulatory agencies to incorporate automated quantitative methods into their spontaneous reporting management systems. The three largest worldwide pharmacovigilance databases are routinely screened by the lower bound of the 95% confidence interval of proportional reporting ratio (PRR₀₂.₅), the 2.5% quantile of the Information Component (IC₀₂.₅) or the 5% quantile of the Gamma Poisson Shrinker (GPS₀₅). More recently, Bayesian and non-Bayesian False Discovery Rate (FDR)-based methods were proposed that address the arbitrariness of thresholds and allow for a built-in estimate of the FDR. These methods were also shown through simulation studies to be interesting alternatives to the currently used methods. The objective of this work was twofold. Based on an extensive retrospective study, we compared PRR₀₂.₅, GPS₀₅ and IC₀₂.₅ with two FDR-based methods derived from the Fisher's exact test and the GPS model (GPS(pH0) [posterior probability of the null hypothesis H₀ calculated from the Gamma Poisson Shrinker model]). Secondly, restricting the analysis to GPS(pH0), we aimed to evaluate the added value of using automated signal detection tools compared with 'traditional' methods, i.e. non-automated surveillance operated by pharmacovigilance experts. The analysis was performed sequentially, i.e. every month, and retrospectively on the whole French pharmacovigilance database over the period 1 January 1996-1 July 2002. Evaluation was based on a list of 243 reference signals (RSs) corresponding to investigations launched by the French Pharmacovigilance Technical Committee (PhVTC) during the same period. The comparison of detection methods was made on the basis of the number of RSs detected as well as the time to detection. Results comparing the five automated quantitative methods were in favour of GPS(pH0) in terms of both number of detections of true signals and

Real-time direct cell concentration and viability determination using a fully automated microfluidic platform for standalone process monitoring

DEFF Research Database (Denmark)

Rodrigues de Sousa Nunes, Pedro André; Kjaerulff, S.; Dufva, Martin

2015-01-01

system performance by monitoring in real time the cell concentration and viability of yeast extracted directly from an in-house made bioreactor. This is the first demonstration of using the Dean drag force, generated due to the implementation of a curved microchannel geometry in conjunction with high...... flow rates, to promote passive mixing of cell samples and thus homogenization of the diluted cell plug. The autonomous operation of the fluidics furthermore allows implementation of intelligent protocols for administering air bubbles from the bioreactor in the microfluidic system, so...... and thereby ensure optimal cell production, by prolonging the fermentation cycle and increasing the bioreactor output. In this work, we report on the development of a fully automated microfluidic system capable of extracting samples directly from a bioreactor, diluting the sample, staining the cells...

Automated evaluation of ultrasonic indications

International Nuclear Information System (INIS)

Hansch, M.K.T.; Stegemann, D.

1994-01-01

Future requirements of reliability and reproducibility in quality assurance demand computer evaluation of defect indications. The ultrasonic method with its large field of applications and a high potential for automation provides all preconditions for fully automated inspection. The survey proposes several desirable hardware improvements, data acquisition requirements and software configurations. (orig.) [de

A fully automated mass spectrometer for the analysis of organic solids

International Nuclear Information System (INIS)

Hillig, H.; Kueper, H.; Riepe, W.

1979-01-01

Automation of a mass spectrometer-computer system makes it possible to process up to 30 samples without attention after sample loading. An automatic sample changer introduces the samples successively into the ion source by means of a direct inlet probe. A process control unit determines the operation sequence. Computer programs are available for the hardware support, system supervision and evaluation of the spectrometer signals. The most essential precondition for automation - automatic evaporation of the sample material by electronic control of the total ion current - is confirmed to be satisfactory. The system operates routinely overnight in an industrial laboratory, so that day work can be devoted to difficult analytical problems. The cost of routine analyses is halved. (Auth.)

Automated detection of acute haemorrhagic stroke in non-contrasted CT images

International Nuclear Information System (INIS)

Meetz, K.; Buelow, T.

2007-01-01

An efficient treatment of stroke patients implies a profound differential diagnosis that includes the detection of acute haematoma. The proposed approach provides an automated detection of acute haematoma, assisting the non-stroke expert in interpreting non-contrasted CT images. It consists of two steps: First, haematoma candidates are detected applying multilevel region growing approach based on a typical grey value characteristic. Second, true haematomas are differentiated from partial volume artefacts, relying on spatial features derived from distance-based histograms. This approach achieves a specificity of 77% and a sensitivity of 89.7% in detecting acute haematoma in non-contrasted CT images when applied to a set of 25 non-contrasted CT images. (orig.)

A Comparison of Fully Automated Methods of Data Analysis and Computer Assisted Heuristic Methods in an Electrode Kinetic Study of the Pathologically Variable [Fe(CN) 6 ] 3–/4– Process by AC Voltammetry

KAUST Repository

Morris, Graham P.

2013-12-17

Fully automated and computer assisted heuristic data analysis approaches have been applied to a series of AC voltammetric experiments undertaken on the [Fe(CN)6]3-/4- process at a glassy carbon electrode in 3 M KCl aqueous electrolyte. The recovered parameters in all forms of data analysis encompass E0 (reversible potential), k0 (heterogeneous charge transfer rate constant at E0), α (charge transfer coefficient), Ru (uncompensated resistance), and Cdl (double layer capacitance). The automated method of analysis employed time domain optimization and Bayesian statistics. This and all other methods assumed the Butler-Volmer model applies for electron transfer kinetics, planar diffusion for mass transport, Ohm\\'s Law for Ru, and a potential-independent Cdl model. Heuristic approaches utilize combinations of Fourier Transform filtering, sensitivity analysis, and simplex-based forms of optimization applied to resolved AC harmonics and rely on experimenter experience to assist in experiment-theory comparisons. Remarkable consistency of parameter evaluation was achieved, although the fully automated time domain method provided consistently higher α values than those based on frequency domain data analysis. The origin of this difference is that the implemented fully automated method requires a perfect model for the double layer capacitance. In contrast, the importance of imperfections in the double layer model is minimized when analysis is performed in the frequency domain. Substantial variation in k0 values was found by analysis of the 10 data sets for this highly surface-sensitive pathologically variable [Fe(CN) 6]3-/4- process, but remarkably, all fit the quasi-reversible model satisfactorily. © 2013 American Chemical Society.

Comparison and clinical utility evaluation of four multiple allergen simultaneous tests including two newly introduced fully automated analyzers

Directory of Open Access Journals (Sweden)

John Hoon Rim

2016-04-01

Full Text Available Background: We compared the diagnostic performances of two newly introduced fully automated multiple allergen simultaneous tests (MAST analyzers with two conventional MAST assays. Methods: The serum samples from a total of 53 and 104 patients were tested for food panels and inhalant panels, respectively, in four analyzers including AdvanSure AlloScreen (LG Life Science, Korea, AdvanSure Allostation Smart II (LG Life Science, PROTIA Allergy-Q (ProteomeTech, Korea, and RIDA Allergy Screen (R-Biopharm, Germany. We compared not only the total agreement percentages but also positive propensities among four analyzers. Results: Evaluation of AdvanSure Allostation Smart II as upgraded version of AdvanSure AlloScreen revealed good concordance with total agreement percentages of 93.0% and 92.2% in food and inhalant panel, respectively. Comparisons of AdvanSure Allostation Smart II or PROTIA Allergy-Q with RIDA Allergy Screen also showed good concordance performance with positive propensities of two new analyzers for common allergens (Dermatophagoides farina and Dermatophagoides pteronyssinus. The changes of cut-off level resulted in various total agreement percentage fluctuations among allergens by different analyzers, although current cut-off level of class 2 appeared to be generally suitable. Conclusions: AdvanSure Allostation Smart II and PROTIA Allergy-Q presented favorable agreement performances with RIDA Allergy Screen, although positive propensities were noticed in common allergens. Keywords: Multiple allergen simultaneous test, Automated analyzer

Toward Fully Automated Multicriterial Plan Generation: A Prospective Clinical Study

International Nuclear Information System (INIS)

Voet, Peter W.J.; Dirkx, Maarten L.P.; Breedveld, Sebastiaan; Fransen, Dennie; Levendag, Peter C.; Heijmen, Ben J.M.

2013-01-01

Purpose: To prospectively compare plans generated with iCycle, an in-house-developed algorithm for fully automated multicriterial intensity modulated radiation therapy (IMRT) beam profile and beam orientation optimization, with plans manually generated by dosimetrists using the clinical treatment planning system. Methods and Materials: For 20 randomly selected head-and-neck cancer patients with various tumor locations (of whom 13 received sequential boost treatments), we offered the treating physician the choice between an automatically generated iCycle plan and a manually optimized plan using standard clinical procedures. Although iCycle used a fixed “wish list” with hard constraints and prioritized objectives, the dosimetrists manually selected the beam configuration and fine tuned the constraints and objectives for each IMRT plan. Dosimetrists were not informed in advance whether a competing iCycle plan was made. The 2 plans were simultaneously presented to the physician, who then selected the plan to be used for treatment. For the patient group, differences in planning target volume coverage and sparing of critical tissues were quantified. Results: In 32 of 33 plan comparisons, the physician selected the iCycle plan for treatment. This highly consistent preference for the automatically generated plans was mainly caused by the improved sparing for the large majority of critical structures. With iCycle, the normal tissue complication probabilities for the parotid and submandibular glands were reduced by 2.4% ± 4.9% (maximum, 18.5%, P=.001) and 6.5% ± 8.3% (maximum, 27%, P=.005), respectively. The reduction in the mean oral cavity dose was 2.8 ± 2.8 Gy (maximum, 8.1 Gy, P=.005). For the swallowing muscles, the esophagus and larynx, the mean dose reduction was 3.3 ± 1.1 Gy (maximum, 9.2 Gy, P<.001). For 15 of the 20 patients, target coverage was also improved. Conclusions: In 97% of cases, automatically generated plans were selected for treatment because of

Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection

International Nuclear Information System (INIS)

Linguraru, Marius George; Panjwani, Neil; Fletcher, Joel G.; Summer, Ronald M.

2011-01-01

Purpose: To evaluate the performance of a computer-aided detection (CAD) system for detecting colonic polyps at noncathartic computed tomography colonography (CTC) in conjunction with an automated image-based colon cleansing algorithm. Methods: An automated colon cleansing algorithm was designed to detect and subtract tagged-stool, accounting for heterogeneity and poor tagging, to be used in conjunction with a colon CAD system. The method is locally adaptive and combines intensity, shape, and texture analysis with probabilistic optimization. CTC data from cathartic-free bowel preparation were acquired for testing and training the parameters. Patients underwent various colonic preparations with barium or Gastroview in divided doses over 48 h before scanning. No laxatives were administered and no dietary modifications were required. Cases were selected from a polyp-enriched cohort and included scans in which at least 90% of the solid stool was visually estimated to be tagged and each colonic segment was distended in either the prone or supine view. The CAD system was run comparatively with and without the stool subtraction algorithm. Results: The dataset comprised 38 CTC scans from prone and/or supine scans of 19 patients containing 44 polyps larger than 10 mm (22 unique polyps, if matched between prone and supine scans). The results are robust on fine details around folds, thin-stool linings on the colonic wall, near polyps and in large fluid/stool pools. The sensitivity of the CAD system is 70.5% per polyp at a rate of 5.75 false positives/scan without using the stool subtraction module. This detection improved significantly (p = 0.009) after automated colon cleansing on cathartic-free data to 86.4% true positive rate at 5.75 false positives/scan. Conclusions: An automated image-based colon cleansing algorithm designed to overcome the challenges of the noncathartic colon significantly improves the sensitivity of colon CAD by approximately 15%.

Multiplex RT-PCR and Automated Microarray for Detection of Eight Bovine Viruses.

Science.gov (United States)

Lung, O; Furukawa-Stoffer, T; Burton Hughes, K; Pasick, J; King, D P; Hodko, D

2017-12-01

Microarrays can be a useful tool for pathogen detection as it allow for simultaneous interrogation of the presence of a large number of genetic sequences in a sample. However, conventional microarrays require extensive manual handling and multiple pieces of equipment for printing probes, hybridization, washing and signal detection. In this study, a reverse transcription (RT)-PCR with an accompanying novel automated microarray for simultaneous detection of eight viruses that affect cattle [vesicular stomatitis virus (VSV), bovine viral diarrhoea virus type 1 and type 2, bovine herpesvirus 1, bluetongue virus, malignant catarrhal fever virus, rinderpest virus (RPV) and parapox viruses] is described. The assay accurately identified a panel of 37 strains of the target viruses and identified a mixed infection. No non-specific reactions were observed with a panel of 23 non-target viruses associated with livestock. Vesicular stomatitis virus was detected as early as 2 days post-inoculation in oral swabs from experimentally infected animals. The limit of detection of the microarray assay was as low as 1 TCID 50 /ml for RPV. The novel microarray platform automates the entire post-PCR steps of the assay and integrates electrophoretic-driven capture probe printing in a single user-friendly instrument that allows array layout and assay configuration to be user-customized on-site. © 2016 Her Majesty the Queen in Right of Canada.

Accuracy of automated software-guided detection of significant coronary artery stenosis by CT angiography: comparison with invasive catheterisation

International Nuclear Information System (INIS)

Anders, Katharina; Uder, Michael; Achenbach, Stephan; Petit, Isabel; Daniel, Werner G.; Pflederer, Tobias

2013-01-01

True automated detection of coronary artery stenoses might be useful whenever expert evaluation is not available, or as a ''second reader'' to enhance diagnostic confidence. We evaluated the accuracy of a PC-based stenosis detection tool alone and combined with expert interpretation. One hundred coronary CT angiography datasets were evaluated with the automated software alone, by manual interpretation (axial images, multiplanar reformations and maximum intensity projections in free double-oblique planes), and by expert interpretation aware of the automated findings. Stenoses ≥ 50 % were noted per-vessel and per-patient, and compared with invasive angiography. Automated post-processing was successful in 90 % of patients (88 % of vessels). When excluding uninterpretable datasets, per-patient sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 89 %, 79 %, 74 % and 92 % (per-vessel: 82 %, 85 %, 48 % and 96 %). All 100 datasets were evaluable by expert interpretation. Per-patient sensitivity, specificity, PPV and NPV were 95 %, 95 %, 93 % and 97 % (per-vessel: 89 %,98 %, 88 % and 98 %). Knowing the results of automated interpretation did not improve the performance of expert readers. Automated off-line post-processing of coronary CT angiography shows adequate sensitivity, but relatively low specificity in coronary stenosis detection. It does not increase accuracy of expert interpretation. Failure of post-processing in 10 % of all patients necessitates additional manual image work-up. (orig.)

Automated detection of macular drusen using geometric background leveling and threshold selection.

Science.gov (United States)

Smith, R Theodore; Chan, Jackie K; Nagasaki, Takayuki; Ahmad, Umer F; Barbazetto, Irene; Sparrow, Janet; Figueroa, Marta; Merriam, Joanna

2005-02-01

Age-related macular degeneration (ARMD) is the most prevalent cause of visual loss in patients older than 60 years in the United States. Observation of drusen is the hallmark finding in the clinical evaluation of ARMD. To segment and quantify drusen found in patients with ARMD using image analysis and to compare the efficacy of image analysis segmentation with that of stereoscopic manual grading of drusen. Retrospective study. University referral center.Patients Photographs were randomly selected from an available database of patients with known ARMD in the ongoing Columbia University Macular Genetics Study. All patients were white and older than 60 years. Twenty images from 17 patients were selected as representative of common manifestations of drusen. Image preprocessing included automated color balancing and, where necessary, manual segmentation of confounding lesions such as geographic atrophy (3 images). The operator then chose among 3 automated processing options suggested by predominant drusen type. Automated processing consisted of elimination of background variability by a mathematical model and subsequent histogram-based threshold selection. A retinal specialist using a graphic tablet while viewing stereo pairs constructed digital drusen drawings for each image. The sensitivity and specificity of drusen segmentation using the automated method with respect to manual stereoscopic drusen drawings were calculated on a rigorous pixel-by-pixel basis. The median sensitivity and specificity of automated segmentation were 70% and 81%, respectively. After preprocessing and option choice, reproducibility of automated drusen segmentation was necessarily 100%. Automated drusen segmentation can be reliably performed on digital fundus photographs and result in successful quantification of drusen in a more precise manner than is traditionally possible with manual stereoscopic grading of drusen. With only minor preprocessing requirements, this automated detection

Automated volumetry for unilateral hippocampal sclerosis detection in patients with temporal lobe epilepsy.

Science.gov (United States)

Martins, Cristina; Moreira da Silva, Nadia; Silva, Guilherme; Rozanski, Verena E; Silva Cunha, Joao Paulo

2016-08-01

Hippocampal sclerosis (HS) is the most common cause of temporal lobe epilepsy (TLE) and can be identified in magnetic resonance imaging as hippocampal atrophy and subsequent volume loss. Detecting this kind of abnormalities through simple radiological assessment could be difficult, even for experienced radiologists. For that reason, hippocampal volumetry is generally used to support this kind of diagnosis. Manual volumetry is the traditional approach but it is time consuming and requires the physician to be familiar with neuroimaging software tools. In this paper, we propose an automated method, written as a script that uses FSL-FIRST, to perform hippocampal segmentation and compute an index to quantify hippocampi asymmetry (HAI). We compared the automated detection of HS (left or right) based on the HAI with the agreement of two experts in a group of 19 patients and 15 controls, achieving 84.2% sensitivity, 86.7% specificity and a Cohen's kappa coefficient of 0.704. The proposed method is integrated in the "Advanced Brain Imaging Lab" (ABrIL) cloud neurocomputing platform. The automated procedure is 77% (on average) faster to compute vs. the manual volumetry segmentation performed by an experienced physician.

Automated Radioanalytical Chemistry: Applications For The Laboratory And Industrial Process Monitoring

International Nuclear Information System (INIS)

O'Hara, Matthew J.; Farawila, Anne F.; Grate, Jay W.

2009-01-01

The identification and quantification of targeted α- and β-emitting radionuclides via destructive analysis in complex radioactive liquid matrices is highly challenging. Analyses are typically accomplished at on- or off-site laboratories through laborious sample preparation steps and extensive chemical separations followed by analysis using a variety of detection methodologies (e.g., liquid scintillation, alpha energy spectroscopy, mass spectrometry). Analytical results may take days or weeks to report. When an industrial-scale plant requires periodic or continuous monitoring of radionuclides as an indication of the composition of its feed stream, diversion of safeguarded nuclides, or of plant operational conditions (for example), radiochemical measurements should be rapid, but not at the expense of precision and accuracy. Scientists at Pacific Northwest National Laboratory have developed and characterized a host of automated radioanalytical systems designed to perform reproducible and rapid radioanalytical processes. Platforms have been assembled for (1) automation and acceleration of sample analysis in the laboratory and (2) automated monitors for monitoring industrial scale nuclear processes on-line with near-real time results. These methods have been applied to the analysis of environmental-level actinides and fission products to high-level nuclear process fluids. Systems have been designed to integrate a number of discrete sample handling steps, including sample pretreatment (e.g., digestion and valence state adjustment) and chemical separations. The systems have either utilized on-line analyte detection or have collected the purified analyte fractions for off-line measurement applications. One PNNL system of particular note is a fully automated prototype on-line radioanalytical system designed for the Waste Treatment Plant at Hanford, WA, USA. This system demonstrated nearly continuous destructive analysis of the soft β-emitting radionuclide 99Tc in nuclear

SU-C-201-04: Quantification of Perfusion Heterogeneity Based On Texture Analysis for Fully Automatic Detection of Ischemic Deficits From Myocardial Perfusion Imaging

International Nuclear Information System (INIS)

Fang, Y; Huang, H; Su, T

2015-01-01

Purpose: Texture-based quantification of image heterogeneity has been a popular topic for imaging studies in recent years. As previous studies mainly focus on oncological applications, we report our recent efforts of applying such techniques on cardiac perfusion imaging. A fully automated procedure has been developed to perform texture analysis for measuring the image heterogeneity. Clinical data were used to evaluate the preliminary performance of such methods. Methods: Myocardial perfusion images of Thallium-201 scans were collected from 293 patients with suspected coronary artery disease. Each subject underwent a Tl-201 scan and a percutaneous coronary intervention (PCI) within three months. The PCI Result was used as the gold standard of coronary ischemia of more than 70% stenosis. Each Tl-201 scan was spatially normalized to an image template for fully automatic segmentation of the LV. The segmented voxel intensities were then carried into the texture analysis with our open-source software Chang Gung Image Texture Analysis toolbox (CGITA). To evaluate the clinical performance of the image heterogeneity for detecting the coronary stenosis, receiver operating characteristic (ROC) analysis was used to compute the overall accuracy, sensitivity and specificity as well as the area under curve (AUC). Those indices were compared to those obtained from the commercially available semi-automatic software QPS. Results: With the fully automatic procedure to quantify heterogeneity from Tl-201 scans, we were able to achieve a good discrimination with good accuracy (74%), sensitivity (73%), specificity (77%) and AUC of 0.82. Such performance is similar to those obtained from the semi-automatic QPS software that gives a sensitivity of 71% and specificity of 77%. Conclusion: Based on fully automatic procedures of data processing, our preliminary data indicate that the image heterogeneity of myocardial perfusion imaging can provide useful information for automatic determination

FahamecV1:A Low Cost Automated Metaphase Detection System

Directory of Open Access Journals (Sweden)

H. Yilmaz

2017-12-01

Full Text Available In this study, FahamecV1 is introduced and investigated as a low cost and high accuracy solution for metaphase detection. Chromosome analysis is performed at the metaphase stage and high accuracy and automated detection of the metaphase stage plays an active role in decreasing analysis time. FahamecV1 includes an optic microscope, a motorized microscope stage, an electronic control unit, a camera, a computer and a software application. Printing components of the motorized microscope stage (using a 3D printer is of the main reasons for cost reduction. Operations such as stepper motor calibration, are detection, focusing, scanning, metaphase detection and saving of coordinates into a database are automatically performed. To detect metaphases, a filter named Metafilter is developed and applied. Average scanning time per preparate is 77 sec/cm2. True positive rate is calculated as 95.1%, true negative rate is calculated as 99.0% and accuracy is calculated as 98.8%.

Home Automation

OpenAIRE

Ahmed, Zeeshan

2010-01-01

In this paper I briefly discuss the importance of home automation system. Going in to the details I briefly present a real time designed and implemented software and hardware oriented house automation research project, capable of automating house's electricity and providing a security system to detect the presence of unexpected behavior.

Transient electromagnetic detecting technique for water hazard to the roof of fully mechanized sub-level caving face

Energy Technology Data Exchange (ETDEWEB)

Yu Jing-cun; Liu Zhi-xin; Tang Jin-yun; Wang Yang-zhou [China University of Mining & Technology, Xuzhou (China). School of Resources and Geoscience Science

2007-07-01

In coal mining, with the popularization of fully mechanized equipment, the roof control becomes more and more important. The development of water body in roofs may seriously affect the efficiency of the fully mechanized mining, quite possible to cause an accident in working face. Therefore, to make clear the position of a water body located in roofs so as to provide a basis for water drainage borehole layout is an urgent problem to be solved by geophysical exploration. Based on the transient electromagnetic theory and the technique used on ground surface and on the actual situation in underground coal mines, a square superimposed loop device (2 m in side length) which is non-contact and multi-turns was developed to detect the water bodies in coal seam roofs. Based on the 'smoke ring effect' theory and the physical simulation criterion, the mathematical model for calculating the apparent resistivity of full space transient electromagnetism is deduced. In addition, the water detection technology for the roof of fully mechanized sub-level caving face was researched and applied in several coal mines, which has been verified by boreholes and mining practice, indicating that this method is very effective in detecting the water source in the roof of fully mechanized sub-level caving face. 11 refs., 5 figs.

Fully automatic detection of corresponding anatomical landmarks in volume scans of different respiratory state

International Nuclear Information System (INIS)

Berlinger, Kajetan; Roth, Michael; Sauer, Otto; Vences, Lucia; Schweikard, Achim

2006-01-01

A method is described which provides fully automatic detection of corresponding anatomical landmarks in volume scans taken at different respiratory states. The resulting control points are needed for creating a volumetric deformation model for motion compensation in radiotherapy. Prior to treatment two CT volumes are taken, one scan during inhalation, one during exhalation. These scans and the detected control point pairs are taken as input for creating the four-dimensional model by using thin-plate splines

Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods

DEFF Research Database (Denmark)

Warby, Simon C.; Wendt, Sabrina Lyngbye; Welinder, Peter

2014-01-01

to crowdsource spindle identification by human experts and non-experts, and we compared their performance with that of automated detection algorithms in data from middle- to older-aged subjects from the general population. We also refined methods for forming group consensus and evaluating the performance...... of event detectors in physiological data such as electroencephalographic recordings from polysomnography. Compared to the expert group consensus gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. This analysis showed...... that crowdsourcing the scoring of sleep data is an efficient method to collect large data sets, even for difficult tasks such as spindle identification. Further refinements to spindle detection algorithms are needed for middle- to older-aged subjects....

A fully automated fast analysis system for capillary gas chromatography. Part 1. Automation of system control

NARCIS (Netherlands)

Snijders, H.M.J.; Rijks, J.P.E.M.; Bombeeck, A.J.; Rijks, J.A.; Sandra, P.; Lee, M.L.

1992-01-01

This paper is dealing with the design, the automation and evaluation of a high speed capillary gas chromatographic system. A combination of software and hardware was developed for a new cold trap/reinjection device that allows selective solvent eliminating and on column sample enrichment and an

Automated microaneurysm detection algorithms applied to diabetic retinopathy retinal images

Directory of Open Access Journals (Sweden)

Akara Sopharak

2013-07-01

Full Text Available Diabetic retinopathy is the commonest cause of blindness in working age people. It is characterised and graded by the development of retinal microaneurysms, haemorrhages and exudates. The damage caused by diabetic retinopathy can be prevented if it is treated in its early stages. Therefore, automated early detection can limit the severity of the disease, improve the follow-up management of diabetic patients and assist ophthalmologists in investigating and treating the disease more efficiently. This review focuses on microaneurysm detection as the earliest clinically localised characteristic of diabetic retinopathy, a frequently observed complication in both Type 1 and Type 2 diabetes. Algorithms used for microaneurysm detection from retinal images are reviewed. A number of features used to extract microaneurysm are summarised. Furthermore, a comparative analysis of reported methods used to automatically detect microaneurysms is presented and discussed. The performance of methods and their complexity are also discussed.

Sunglass detection method for automation of video surveillance system

Science.gov (United States)

Sikandar, Tasriva; Samsudin, Wan Nur Azhani W.; Hawari Ghazali, Kamarul; Mohd, Izzeldin I.; Fazle Rabbi, Mohammad

2018-04-01

Wearing sunglass to hide face from surveillance camera is a common activity in criminal incidences. Therefore, sunglass detection from surveillance video has become a demanding issue in automation of security systems. In this paper we propose an image processing method to detect sunglass from surveillance images. Specifically, a unique feature using facial height and width has been employed to identify the covered region of the face. The presence of covered area by sunglass is evaluated using facial height-width ratio. Threshold value of covered area percentage is used to classify the glass wearing face. Two different types of glasses have been considered i.e. eye glass and sunglass. The results of this study demonstrate that the proposed method is able to detect sunglasses in two different illumination conditions such as, room illumination as well as in the presence of sunlight. In addition, due to the multi-level checking in facial region, this method has 100% accuracy of detecting sunglass. However, in an exceptional case where fabric surrounding the face has similar color as skin, the correct detection rate was found 93.33% for eye glass.

Automation in Immunohematology

Directory of Open Access Journals (Sweden)

Meenu Bajpai

2012-01-01

Full Text Available There have been rapid technological advances in blood banking in South Asian region over the past decade with an increasing emphasis on quality and safety of blood products. The conventional test tube technique has given way to newer techniques such as column agglutination technique, solid phase red cell adherence assay, and erythrocyte-magnetized technique. These new technologies are adaptable to automation and major manufacturers in this field have come up with semi and fully automated equipments for immunohematology tests in the blood bank. Automation improves the objectivity and reproducibility of tests. It reduces human errors in patient identification and transcription errors. Documentation and traceability of tests, reagents and processes and archiving of results is another major advantage of automation. Shifting from manual methods to automation is a major undertaking for any transfusion service to provide quality patient care with lesser turnaround time for their ever increasing workload. This article discusses the various issues involved in the process.

Foreign object detection and removal to improve automated analysis of chest radiographs

International Nuclear Information System (INIS)

Hogeweg, Laurens; Sánchez, Clara I.; Melendez, Jaime; Maduskar, Pragnya; Ginneken, Bram van; Story, Alistair; Hayward, Andrew

2013-01-01

Purpose: Chest radiographs commonly contain projections of foreign objects, such as buttons, brassier clips, jewellery, or pacemakers and wires. The presence of these structures can substantially affect the output of computer analysis of these images. An automated method is presented to detect, segment, and remove foreign objects from chest radiographs.Methods: Detection is performed using supervised pixel classification with a kNN classifier, resulting in a probability estimate per pixel to belong to a projected foreign object. Segmentation is performed by grouping and post-processing pixels with a probability above a certain threshold. Next, the objects are replaced by texture inpainting.Results: The method is evaluated in experiments on 257 chest radiographs. The detection at pixel level is evaluated with receiver operating characteristic analysis on pixels within the unobscured lung fields and an A z value of 0.949 is achieved. Free response operator characteristic analysis is performed at the object level, and 95.6% of objects are detected with on average 0.25 false positive detections per image. To investigate the effect of removing the detected objects through inpainting, a texture analysis system for tuberculosis detection is applied to images with and without pathology and with and without foreign object removal. Unprocessed, the texture analysis abnormality score of normal images with foreign objects is comparable to those with pathology. After removing foreign objects, the texture score of normal images with and without foreign objects is similar, while abnormal images, whether they contain foreign objects or not, achieve on average higher scores.Conclusions: The authors conclude that removal of foreign objects from chest radiographs is feasible and beneficial for automated image analysis

Technical Note: A fully automated purge and trap GC-MS system for quantification of volatile organic compound (VOC fluxes between the ocean and atmosphere

Directory of Open Access Journals (Sweden)

S. J. Andrews

2015-04-01

Full Text Available The oceans are a key source of a number of atmospherically important volatile gases. The accurate and robust determination of trace gases in seawater is a significant analytical challenge, requiring reproducible and ideally automated sample handling, a high efficiency of seawater–air transfer, removal of water vapour from the sample stream, and high sensitivity and selectivity of the analysis. Here we describe a system that was developed for the fully automated analysis of dissolved very short-lived halogenated species (VSLS sampled from an under-way seawater supply. The system can also be used for semi-automated batch sampling from Niskin bottles filled during CTD (conductivity, temperature, depth profiles. The essential components comprise a bespoke, automated purge and trap (AutoP & T unit coupled to a commercial thermal desorption and gas chromatograph mass spectrometer (TD-GC-MS. The AutoP & T system has completed five research cruises, from the tropics to the poles, and collected over 2500 oceanic samples to date. It is able to quantify >25 species over a boiling point range of 34–180 °C with Henry's law coefficients of 0.018 and greater (CH22l, kHcc dimensionless gas/aqueous and has been used to measure organic sulfurs, hydrocarbons, halocarbons and terpenes. In the eastern tropical Pacific, the high sensitivity and sampling frequency provided new information regarding the distribution of VSLS, including novel measurements of a photolytically driven diurnal cycle of CH22l within the surface ocean water.

Shape indexes for semi-automated detection of windbreaks in thematic tree cover maps from the central United States

Science.gov (United States)

Greg C. Liknes; Dacia M. Meneguzzo; Todd A. Kellerman

2017-01-01

Windbreaks are an important ecological resource across the large expanse of agricultural land in the central United States and are often planted in straight-line or L-shaped configurations to serve specific functions. As high-resolution (i.e., <5 m) land cover datasets become more available for these areas, semi-or fully-automated methods for distinguishing...

Automated detection of optical counterparts to GRBs with RAPTOR

International Nuclear Information System (INIS)

Wozniak, P. R.; Vestrand, W. T.; Evans, S.; White, R.; Wren, J.

2006-01-01

The RAPTOR system (RAPid Telescopes for Optical Response) is an array of several distributed robotic telescopes that automatically respond to GCN localization alerts. Raptor-S is a 0.4-m telescope with 24 arc min. field of view employing a 1k x 1k Marconi CCD detector, and has already detected prompt optical emission from several GRBs within the first minute of the explosion. We present a real-time data analysis and alert system for automated identification of optical transients in Raptor-S GRB response data down to the sensitivity limit of ∼ 19 mag. Our custom data processing pipeline is designed to minimize the time required to reliably identify transients and extract actionable information. The system utilizes a networked PostgreSQL database server for catalog access and distributes email alerts with successful detections

Automated detection of a prostate Ni-Ti stent in electronic portal images

OpenAIRE

Carl, Jesper; Nielsen, Henning; Nielsen, Jane; Lund, Bente; Larsen, Erik Hoejkjaer

2006-01-01

  Udgivelsesdato: DEC  Planning target volumes (PTV) in fractionated radiotherapy still have to be outlined with wide margins to the clinical target volume due to uncertainties arising from daily shift of the prostate position. A recently proposed new method of visualization of the prostate is based on insertion of a thermo-expandable Ni-Ti stent. The current study proposes a new detection algorithm for automated detection of the Ni-Ti stent in electronic portal images. The algorithm is ba...

Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case-Control Study.

Science.gov (United States)

Kerlikowske, Karla; Scott, Christopher G; Mahmoudzadeh, Amir P; Ma, Lin; Winham, Stacey; Jensen, Matthew R; Wu, Fang Fang; Malkov, Serghei; Pankratz, V Shane; Cummings, Steven R; Shepherd, John A; Brandt, Kathleen R; Miglioretti, Diana L; Vachon, Celine M

2018-06-05

In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead. To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures. Case-control. San Francisco Mammography Registry and Mayo Clinic. 1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants. Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity. Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screen-detected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively. Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method. Automated and clinical BI

Automated mammographic breast density estimation using a fully convolutional network.

Science.gov (United States)

Lee, Juhun; Nishikawa, Robert M

2018-03-01

The purpose of this study was to develop a fully automated algorithm for mammographic breast density estimation using deep learning. Our algorithm used a fully convolutional network, which is a deep learning framework for image segmentation, to segment both the breast and the dense fibroglandular areas on mammographic images. Using the segmented breast and dense areas, our algorithm computed the breast percent density (PD), which is the faction of dense area in a breast. Our dataset included full-field digital screening mammograms of 604 women, which included 1208 mediolateral oblique (MLO) and 1208 craniocaudal (CC) views. We allocated 455, 58, and 91 of 604 women and their exams into training, testing, and validation datasets, respectively. We established ground truth for the breast and the dense fibroglandular areas via manual segmentation and segmentation using a simple thresholding based on BI-RADS density assessments by radiologists, respectively. Using the mammograms and ground truth, we fine-tuned a pretrained deep learning network to train the network to segment both the breast and the fibroglandular areas. Using the validation dataset, we evaluated the performance of the proposed algorithm against radiologists' BI-RADS density assessments. Specifically, we conducted a correlation analysis between a BI-RADS density assessment of a given breast and its corresponding PD estimate by the proposed algorithm. In addition, we evaluated our algorithm in terms of its ability to classify the BI-RADS density using PD estimates, and its ability to provide consistent PD estimates for the left and the right breast and the MLO and CC views of the same women. To show the effectiveness of our algorithm, we compared the performance of our algorithm against a state of the art algorithm, laboratory for individualized breast radiodensity assessment (LIBRA). The PD estimated by our algorithm correlated well with BI-RADS density ratings by radiologists. Pearson's rho values of

Automated image analysis of lateral lumber X-rays by a form model

International Nuclear Information System (INIS)

Mahnken, A.H.; Kohnen, M.; Steinberg, S.; Wein, B.B.; Guenther, R.W.

2001-01-01

Development of a software for fully automated image analysis of lateral lumbar spine X-rays. Material and method: Using the concept of active shape models, we developed a software that produces a form model of the lumbar spine from lateral lumbar spine radiographs and runs an automated image segmentation. This model is able to detect lumbar vertebrae automatically after the filtering of digitized X-ray images. The model was trained with 20 lateral lumbar spine radiographs with no pathological findings before we evaluated the software with 30 further X-ray images which were sorted by image quality ranging from one (best) to three (worst). There were 10 images for each quality. Results: Image recognition strongly depended on image quality. In group one 52 and in group two 51 out of 60 vertebral bodies including the sacrum were recognized, but in group three only 18 vertebral bodies were properly identified. Conclusion: Fully automated and reliable recognition of vertebral bodies from lateral spine radiographs using the concept of active shape models is possible. The precision of this technique is limited by the superposition of different structures. Further improvements are necessary. Therefore standardized image quality and enlargement of the training data set are required. (orig.) [de

A fully robust PARAFAC method for analyzing fluorescence data

DEFF Research Database (Denmark)

Engelen, Sanne; Frosch, Stina; Jørgensen, Bo

2009-01-01

and Rayleigh scatter. Recently, a robust PARAFAC method that circumvents the harmful effects of outlying samples has been developed. For removing the scatter effects on the final PARAFAC model, different techniques exist. Newly, an automated scatter identification tool has been constructed. However......, there still exists no robust method for handling fluorescence data encountering both outlying EEM landscapes and scatter. In this paper, we present an iterative algorithm where the robust PARAFAC method and the scatter identification tool are alternately performed. A fully automated robust PARAFAC method...

Human-Automation Cooperation for Separation Assurance in Future NextGen Environments

Science.gov (United States)

Mercer, Joey; Homola, Jeffrey; Cabrall, Christopher; Martin, Lynne; Morey, Susan; Gomez, Ashley; Prevot, Thomas

2014-01-01

A 2012 Human-In-The-Loop air traffic control simulation investigated a gradual paradigm-shift in the allocation of functions between operators and automation. Air traffic controllers staffed five adjacent high-altitude en route sectors, and during the course of a two-week experiment, worked traffic under different function-allocation approaches aligned with four increasingly mature NextGen operational environments. These NextGen time-frames ranged from near current-day operations to nearly fully-automated control, in which the ground systems automation was responsible for detecting conflicts, issuing strategic and tactical resolutions, and alerting the controller to exceptional circumstances. Results indicate that overall performance was best in the most automated NextGen environment. Safe operations were achieved in this environment for twice todays peak airspace capacity, while being rated by the controllers as highly acceptable. However, results show that sector operations were not always safe; separation violations did in fact occur. This paper will describe in detail the simulation conducted, as well discuss important results and their implications.

Fully automated quantification of regional cerebral blood flow with three-dimensional stereotaxic region of interest template. Validation using magnetic resonance imaging. Technical note

Energy Technology Data Exchange (ETDEWEB)

Takeuchi, Ryo; Katayama, Shigenori; Takeda, Naoya; Fujita, Katsuzo [Nishi-Kobe Medical Center (Japan); Yonekura, Yoshiharu [Fukui Medical Univ., Matsuoka (Japan); Konishi, Junji [Kyoto Univ. (Japan). Graduate School of Medicine

2003-03-01

The previously reported three-dimensional stereotaxic region of interest (ROI) template (3DSRT-t) for the analysis of anatomically standardized technetium-99m-L,L-ethyl cysteinate dimer ({sup 99m}Tc-ECD) single photon emission computed tomography (SPECT) images was modified for use in a fully automated regional cerebral blood flow (rCBF) quantification software, 3DSRT, incorporating an anatomical standardization engine transplanted from statistical parametric mapping 99 and ROIs for quantification based on 3DSRT-t. Three-dimensional T{sub 2}-weighted magnetic resonance images of 10 patients with localized infarcted areas were compared with the ROI contour of 3DSRT, and the positions of the central sulcus in the primary sensorimotor area were also estimated. All positions of the 20 lesions were in strict accordance with the ROI delineation of 3DSRT. The central sulcus was identified on at least one side of 210 paired ROIs and in the middle of 192 (91.4%) of these 210 paired ROIs among the 273 paired ROIs of the primary sensorimotor area. The central sulcus was recognized in the middle of more than 71.4% of the ROIs in which the central sulcus was identifiable in the respective 28 slices of the primary sensorimotor area. Fully automated accurate ROI delineation on anatomically standardized images is possible with 3DSRT, which enables objective quantification of rCBF and vascular reserve in only a few minutes using {sup 99m}Tc-ECD SPECT images obtained by the resting and vascular reserve (RVR) method. (author)

Fully automated quantification of regional cerebral blood flow with three-dimensional stereotaxic region of interest template. Validation using magnetic resonance imaging. Technical note

International Nuclear Information System (INIS)

Takeuchi, Ryo; Katayama, Shigenori; Takeda, Naoya; Fujita, Katsuzo; Yonekura, Yoshiharu; Konishi, Junji

2003-01-01

The previously reported three-dimensional stereotaxic region of interest (ROI) template (3DSRT-t) for the analysis of anatomically standardized technetium-99m-L,L-ethyl cysteinate dimer ( 99m Tc-ECD) single photon emission computed tomography (SPECT) images was modified for use in a fully automated regional cerebral blood flow (rCBF) quantification software, 3DSRT, incorporating an anatomical standardization engine transplanted from statistical parametric mapping 99 and ROIs for quantification based on 3DSRT-t. Three-dimensional T 2 -weighted magnetic resonance images of 10 patients with localized infarcted areas were compared with the ROI contour of 3DSRT, and the positions of the central sulcus in the primary sensorimotor area were also estimated. All positions of the 20 lesions were in strict accordance with the ROI delineation of 3DSRT. The central sulcus was identified on at least one side of 210 paired ROIs and in the middle of 192 (91.4%) of these 210 paired ROIs among the 273 paired ROIs of the primary sensorimotor area. The central sulcus was recognized in the middle of more than 71.4% of the ROIs in which the central sulcus was identifiable in the respective 28 slices of the primary sensorimotor area. Fully automated accurate ROI delineation on anatomically standardized images is possible with 3DSRT, which enables objective quantification of rCBF and vascular reserve in only a few minutes using 99m Tc-ECD SPECT images obtained by the resting and vascular reserve (RVR) method. (author)

Computer-aided detection and automated CT volumetry of pulmonary nodules

International Nuclear Information System (INIS)

Marten, Katharina; Engelke, Christoph

2007-01-01

With use of multislice computed tomography (MSCT), small pulmonary nodules are being detected in vast numbers, constituting the majority of all noncalcified lung nodules. Although the prevalence of lung cancers among such lesions in lung cancer screening populations is low, their isolation may contribute to increased patient survival. Computer-aided diagnosis (CAD) has emerged as a diverse set of diagnostic tools to handle the large number of images in MSCT datasets and most importantly, includes automated detection and volumetry of pulmonary nodules. Current CAD systems can significantly enhance experienced radiologists' performance and outweigh human limitations in identifying small lesions and manually measuring their diameters, augment observer consistency in the interpretation of such examinations and may thus help to detect significantly higher rates of early malignomas and give more precise estimates on chemotherapy response than can radiologists alone. In this review, we give an overview of current CAD in lung nodule detection and volumetry and discuss their relative merits and limitations. (orig.)

Automated MAD and MIR structure solution

International Nuclear Information System (INIS)

Terwilliger, Thomas C.; Berendzen, Joel

1999-01-01

A fully automated procedure for solving MIR and MAD structures has been developed using a scoring scheme to convert the structure-solution process into an optimization problem. Obtaining an electron-density map from X-ray diffraction data can be difficult and time-consuming even after the data have been collected, largely because MIR and MAD structure determinations currently require many subjective evaluations of the qualities of trial heavy-atom partial structures before a correct heavy-atom solution is obtained. A set of criteria for evaluating the quality of heavy-atom partial solutions in macromolecular crystallography have been developed. These have allowed the conversion of the crystal structure-solution process into an optimization problem and have allowed its automation. The SOLVE software has been used to solve MAD data sets with as many as 52 selenium sites in the asymmetric unit. The automated structure-solution process developed is a major step towards the fully automated structure-determination, model-building and refinement procedure which is needed for genomic scale structure determinations

Automated Detection of Oscillating Regions in the Solar Atmosphere

Science.gov (United States)

Ireland, J.; Marsh, M. S.; Kucera, T. A.; Young, C. A.

2010-01-01

Recently observed oscillations in the solar atmosphere have been interpreted and modeled as magnetohydrodynamic wave modes. This has allowed for the estimation of parameters that are otherwise hard to derive, such as the coronal magnetic-field strength. This work crucially relies on the initial detection of the oscillations, which is commonly done manually. The volume of Solar Dynamics Observatory (SDO) data will make manual detection inefficient for detecting all of the oscillating regions. An algorithm is presented that automates the detection of areas of the solar atmosphere that support spatially extended oscillations. The algorithm identifies areas in the solar atmosphere whose oscillation content is described by a single, dominant oscillation within a user-defined frequency range. The method is based on Bayesian spectral analysis of time series and image filtering. A Bayesian approach sidesteps the need for an a-priori noise estimate to calculate rejection criteria for the observed signal, and it also provides estimates of oscillation frequency, amplitude, and noise, and the error in all of these quantities, in a self-consistent way. The algorithm also introduces the notion of quality measures to those regions for which a positive detection is claimed, allowing for simple post-detection discrimination by the user. The algorithm is demonstrated on two Transition Region and Coronal Explorer (TRACE) datasets, and comments regarding its suitability for oscillation detection in SDO are made.

AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES.

Science.gov (United States)

Kong, Jun; Wang, Fusheng; Teodoro, George; Liang, Yanhui; Zhu, Yangyang; Tucker-Burden, Carol; Brat, Daniel J

2015-04-01

A large number of cell-oriented cancer investigations require an effective and reliable cell segmentation method on three dimensional (3D) fluorescence microscopic images for quantitative analysis of cell biological properties. In this paper, we present a fully automated cell segmentation method that can detect cells from 3D fluorescence microscopic images. Enlightened by fluorescence imaging techniques, we regulated the image gradient field by gradient vector flow (GVF) with interpolated and smoothed data volume, and grouped voxels based on gradient modes identified by tracking GVF field. Adaptive thresholding was then applied to voxels associated with the same gradient mode where voxel intensities were enhanced by a multiscale cell filter. We applied the method to a large volume of 3D fluorescence imaging data of human brain tumor cells with (1) small cell false detection and missing rates for individual cells; and (2) trivial over and under segmentation incidences for clustered cells. Additionally, the concordance of cell morphometry structure between automated and manual segmentation was encouraging. These results suggest a promising 3D cell segmentation method applicable to cancer studies.

Performance evaluation of three automated identification systems in detecting carbapenem-resistant Enterobacteriaceae.

Science.gov (United States)

He, Qingwen; Chen, Weiyuan; Huang, Liya; Lin, Qili; Zhang, Jingling; Liu, Rui; Li, Bin

2016-06-21

Carbapenem-resistant Enterobacteriaceae (CRE) is prevalent around the world. Rapid and accurate detection of CRE is urgently needed to provide effective treatment. Automated identification systems have been widely used in clinical microbiology laboratories for rapid and high-efficient identification of pathogenic bacteria. However, critical evaluation and comparison are needed to determine the specificity and accuracy of different systems. The aim of this study was to evaluate the performance of three commonly used automated identification systems on the detection of CRE. A total of 81 non-repetitive clinical CRE isolates were collected from August 2011 to August 2012 in a Chinese university hospital, and all the isolates were confirmed to be resistant to carbapenems by the agar dilution method. The potential presence of carbapenemase genotypes of the 81 isolates was detected by PCR and sequencing. Using 81 clinical CRE isolates, we evaluated and compared the performance of three automated identification systems, MicroScan WalkAway 96 Plus, Phoenix 100, and Vitek 2 Compact, which are commonly used in China. To identify CRE, the comparator methodology was agar dilution method, while the PCR and sequencing was the comparator one to identify CPE. PCR and sequencing analysis showed that 48 of the 81 CRE isolates carried carbapenemase genes, including 23 (28.4 %) IMP-4, 14 (17.3 %) IMP-8, 5 (6.2 %) NDM-1, and 8 (9.9 %) KPC-2. Notably, one Klebsiella pneumoniae isolate produced both IMP-4 and NDM-1. One Klebsiella oxytoca isolate produced both KPC-2 and IMP-8. Of the 81 clinical CRE isolates, 56 (69.1 %), 33 (40.7 %) and 77 (95.1 %) were identified as CRE by MicroScan WalkAway 96 Plus, Phoenix 100, and Vitek 2 Compact, respectively. The sensitivities/specificities of MicroScan WalkAway, Phoenix 100 and Vitek 2 were 93.8/42.4 %, 54.2/66.7 %, and 75.0/36.4 %, respectively. The MicroScan WalkAway and Viteck2 systems are more reliable in clinical identification of

Automated detection of unfilled pauses in speech of healthy and brain-damaged individuals

NARCIS (Netherlands)

Ossewaarde, Roelant; Jonkers, Roel; Jalvingh, Fedor; Bastiaanse, Yvonne

Automated detection of un lled pauses in speech of healthy and brain-damaged individuals Roelant Ossewaardea,b, Roel Jonkersa, Fedor Jalvingha,c, Roelien Bastiaansea aCenter for Language and Cognition, University of Groningen; bInstitute for ICT, HU University of Applied Science, Utrecht; cSt.

Safe interaction between cyclists, pedestrians and automated vehicles : what do we know and what do we need to know?

NARCIS (Netherlands)

Vissers, L. Kint, S. van der Schagen, I.N.L.G. van & Hagenzieker, M.P.

2017-01-01

Automated vehicles are gradually entering our roadway system. Before our roads will be solely used by fully automated vehicles, a long transition period is to be expected in which fully automated vehicles, partly automated vehicles and manually-driven vehicles have to share our roads. The current

Automated electrochemical detection of iron ions in erythrocytes from melim minipigs suffering from melanoma

Czech Academy of Sciences Publication Activity Database

Kremplová, M.; Krejcová, l.; Hynek, D.; Barath, P.; Majzlík, P.; Horák, Vratislav; Adam, V.; Sochor, J.; Cernei, N.; Hubálek, J.; Vrba, R.; Kižek, R.

2012-01-01

Roč. 7, č. 7 (2012), s. 5893-5909 ISSN 1452-3981 Institutional research plan: CEZ:AV0Z50450515 Keywords : Automation * Biological sample * Electrochemical detection Subject RIV: CG - Electrochemistry Impact factor: 3.729, year: 2011

Costs and consequences of automated algorithms versus manual grading for the detection of referable diabetic retinopathy.

Science.gov (United States)

Scotland, G S; McNamee, P; Fleming, A D; Goatman, K A; Philip, S; Prescott, G J; Sharp, P F; Williams, G J; Wykes, W; Leese, G P; Olson, J A

2010-06-01

To assess the cost-effectiveness of an improved automated grading algorithm for diabetic retinopathy against a previously described algorithm, and in comparison with manual grading. Efficacy of the alternative algorithms was assessed using a reference graded set of images from three screening centres in Scotland (1253 cases with observable/referable retinopathy and 6333 individuals with mild or no retinopathy). Screening outcomes and grading and diagnosis costs were modelled for a cohort of 180 000 people, with prevalence of referable retinopathy at 4%. Algorithm (b), which combines image quality assessment with detection algorithms for microaneurysms (MA), blot haemorrhages and exudates, was compared with a simpler algorithm (a) (using image quality assessment and MA/dot haemorrhage (DH) detection), and the current practice of manual grading. Compared with algorithm (a), algorithm (b) would identify an additional 113 cases of referable retinopathy for an incremental cost of pound 68 per additional case. Compared with manual grading, automated grading would be expected to identify between 54 and 123 fewer referable cases, for a grading cost saving between pound 3834 and pound 1727 per case missed. Extrapolation modelling over a 20-year time horizon suggests manual grading would cost between pound 25,676 and pound 267,115 per additional quality adjusted life year gained. Algorithm (b) is more cost-effective than the algorithm based on quality assessment and MA/DH detection. With respect to the value of introducing automated detection systems into screening programmes, automated grading operates within the recommended national standards in Scotland and is likely to be considered a cost-effective alternative to manual disease/no disease grading.

Adapting the γ-H2AX assay for automated processing in human lymphocytes. 1. Technological aspects.

Science.gov (United States)

Turner, Helen C; Brenner, David J; Chen, Youhua; Bertucci, Antonella; Zhang, Jian; Wang, Hongliang; Lyulko, Oleksandra V; Xu, Yanping; Shuryak, Igor; Schaefer, Julia; Simaan, Nabil; Randers-Pehrson, Gerhard; Yao, Y Lawrence; Amundson, Sally A; Garty, Guy

2011-03-01

The immunofluorescence-based detection of γ-H2AX is a reliable and sensitive method for quantitatively measuring DNA double-strand breaks (DSBs) in irradiated samples. Since H2AX phosphorylation is highly linear with radiation dose, this well-established biomarker is in current use in radiation biodosimetry. At the Center for High-Throughput Minimally Invasive Radiation Biodosimetry, we have developed a fully automated high-throughput system, the RABIT (Rapid Automated Biodosimetry Tool), that can be used to measure γ-H2AX yields from fingerstick-derived samples of blood. The RABIT workstation has been designed to fully automate the γ-H2AX immunocytochemical protocol, from the isolation of human blood lymphocytes in heparin-coated PVC capillaries to the immunolabeling of γ-H2AX protein and image acquisition to determine fluorescence yield. High throughput is achieved through the use of purpose-built robotics, lymphocyte handling in 96-well filter-bottomed plates, and high-speed imaging. The goal of the present study was to optimize and validate the performance of the RABIT system for the reproducible and quantitative detection of γ-H2AX total fluorescence in lymphocytes in a multiwell format. Validation of our biodosimetry platform was achieved by the linear detection of a dose-dependent increase in γ-H2AX fluorescence in peripheral blood samples irradiated ex vivo with γ rays over the range 0 to 8 Gy. This study demonstrates for the first time the optimization and use of our robotically based biodosimetry workstation to successfully quantify γ-H2AX total fluorescence in irradiated peripheral lymphocytes.

Phase II: Automated System for Aneuploidy Detection in Sperm Final Report CRADA No. TC-1554-98

Energy Technology Data Exchange (ETDEWEB)

Wyrobek, W. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Dunlay, R. T. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-09-28

This was a collaborative effort between the University of California, Lawrence Livermore National Laboratory (LLNL) and Cellomics, Inc. (formerly BioDx and Biological Detection, Inc.) to develop an automated system for detecting human sperm aneuploidy. Aneuploidy (an abnormal number of chromosomes) is one of the major categories of chromosomally abnormal sperm, which results in chromosomally defective pregnancies and babies. An automated system would be used for testing the effects of toxic agents and for other research and clinical applications. This collaborated effort was funded by a National Institutes of Environmental Health Services, Phase II, Small Business Innovation Research Program (SBIR) grant to Cellornics (Contract No. N44-ES-82004).

Automated processing integrated with a microflow cytometer for pathogen detection in clinical matrices.

Science.gov (United States)

Golden, J P; Verbarg, J; Howell, P B; Shriver-Lake, L C; Ligler, F S

2013-02-15

A spinning magnetic trap (MagTrap) for automated sample processing was integrated with a microflow cytometer capable of simultaneously detecting multiple targets to provide an automated sample-to-answer diagnosis in 40 min. After target capture on fluorescently coded magnetic microspheres, the magnetic trap automatically concentrated the fluorescently coded microspheres, separated the captured target from the sample matrix, and exposed the bound target sequentially to biotinylated tracer molecules and streptavidin-labeled phycoerythrin. The concentrated microspheres were then hydrodynamically focused in a microflow cytometer capable of 4-color analysis (two wavelengths for microsphere identification, one for light scatter to discriminate single microspheres and one for phycoerythrin bound to the target). A three-fold decrease in sample preparation time and an improved detection limit, independent of target preconcentration, was demonstrated for detection of Escherichia coli 0157:H7 using the MagTrap as compared to manual processing. Simultaneous analysis of positive and negative controls, along with the assay reagents specific for the target, was used to obtain dose-response curves, demonstrating the potential for quantification of pathogen load in buffer and serum. Published by Elsevier B.V.

An automated detection for axonal boutons in vivo two-photon imaging of mouse

Science.gov (United States)

Li, Weifu; Zhang, Dandan; Xie, Qiwei; Chen, Xi; Han, Hua

2017-02-01

Activity-dependent changes in the synaptic connections of the brain are tightly related to learning and memory. Previous studies have shown that essentially all new synaptic contacts were made by adding new partners to existing synaptic elements. To further explore synaptic dynamics in specific pathways, concurrent imaging of pre and postsynaptic structures in identified connections is required. Consequently, considerable attention has been paid for the automated detection of axonal boutons. Different from most previous methods proposed in vitro data, this paper considers a more practical case in vivo neuron images which can provide real time information and direct observation of the dynamics of a disease process in mouse. Additionally, we present an automated approach for detecting axonal boutons by starting with deconvolving the original images, then thresholding the enhanced images, and reserving the regions fulfilling a series of criteria. Experimental result in vivo two-photon imaging of mouse demonstrates the effectiveness of our proposed method.

A longitudinal evaluation of performance of automated BCR-ABL1 quantitation using cartridge-based detection system.

Science.gov (United States)

Enjeti, Anoop; Granter, Neil; Ashraf, Asma; Fletcher, Linda; Branford, Susan; Rowlings, Philip; Dooley, Susan

2015-10-01

An automated cartridge-based detection system (GeneXpert; Cepheid) is being widely adopted in low throughput laboratories for monitoring BCR-ABL1 transcript in chronic myelogenous leukaemia. This Australian study evaluated the longitudinal performance specific characteristics of the automated system.The automated cartridge-based system was compared prospectively with the manual qRT-PCR-based reference method at SA Pathology, Adelaide, over a period of 2.5 years. A conversion factor determination was followed by four re-validations. Peripheral blood samples (n = 129) with international scale (IS) values within detectable range were selected for assessment. The mean bias, proportion of results within specified fold difference (2-, 3- and 5-fold), the concordance rate of major molecular remission (MMR) and concordance across a range of IS values on paired samples were evaluated.The initial conversion factor for the automated system was determined as 0.43. Except for the second re-validation, where a negative bias of 1.9-fold was detected, all other biases fell within desirable limits. A cartridge-specific conversion factor and efficiency value was introduced and the conversion factor was confirmed to be stable in subsequent re-validation cycles. Concordance with the reference method/laboratory at >0.1-≤10 IS was 78.2% and at ≤0.001 was 80%, compared to 86.8% in the >0.01-≤0.1 IS range. The overall and MMR concordance were 85.7% and 94% respectively, for samples that fell within ± 5-fold of the reference laboratory value over the entire period of study.Conversion factor and performance specific characteristics for the automated system were longitudinally stable in the clinically relevant range, following introduction by the manufacturer of lot specific efficiency values.

A Comparison of Fully Automated Methods of Data Analysis and Computer Assisted Heuristic Methods in an Electrode Kinetic Study of the Pathologically Variable [Fe(CN) 6 ] 3–/4– Process by AC Voltammetry

KAUST Repository

Morris, Graham P.; Simonov, Alexandr N.; Mashkina, Elena A.; Bordas, Rafel; Gillow, Kathryn; Baker, Ruth E.; Gavaghan, David J.; Bond, Alan M.

2013-01-01

Fully automated and computer assisted heuristic data analysis approaches have been applied to a series of AC voltammetric experiments undertaken on the [Fe(CN)6]3-/4- process at a glassy carbon electrode in 3 M KCl aqueous electrolyte. The recovered

A fully automated temperature-dependent resistance measurement setup using van der Pauw method

Science.gov (United States)

Pandey, Shivendra Kumar; Manivannan, Anbarasu

2018-03-01

The van der Pauw (VDP) method is widely used to identify the resistance of planar homogeneous samples with four contacts placed on its periphery. We have developed a fully automated thin film resistance measurement setup using the VDP method with the capability of precisely measuring a wide range of thin film resistances from few mΩ up to 10 GΩ under controlled temperatures from room-temperature up to 600 °C. The setup utilizes a robust, custom-designed switching network board (SNB) for measuring current-voltage characteristics automatically at four different source-measure configurations based on the VDP method. Moreover, SNB is connected with low noise shielded coaxial cables that reduce the effect of leakage current as well as the capacitance in the circuit thereby enhancing the accuracy of measurement. In order to enable precise and accurate resistance measurement of the sample, wide range of sourcing currents/voltages are pre-determined with the capability of auto-tuning for ˜12 orders of variation in the resistances. Furthermore, the setup has been calibrated with standard samples and also employed to investigate temperature dependent resistance (few Ω-10 GΩ) measurements for various chalcogenide based phase change thin films (Ge2Sb2Te5, Ag5In5Sb60Te30, and In3SbTe2). This setup would be highly helpful for measurement of temperature-dependent resistance of wide range of materials, i.e., metals, semiconductors, and insulators illuminating information about structural change upon temperature as reflected by change in resistances, which are useful for numerous applications.

Fully automated whole-head segmentation with improved smoothness and continuity, with theory reviewed.

Directory of Open Access Journals (Sweden)

Yu Huang

Full Text Available Individualized current-flow models are needed for precise targeting of brain structures using transcranial electrical or magnetic stimulation (TES/TMS. The same is true for current-source reconstruction in electroencephalography and magnetoencephalography (EEG/MEG. The first step in generating such models is to obtain an accurate segmentation of individual head anatomy, including not only brain but also cerebrospinal fluid (CSF, skull and soft tissues, with a field of view (FOV that covers the whole head. Currently available automated segmentation tools only provide results for brain tissues, have a limited FOV, and do not guarantee continuity and smoothness of tissues, which is crucially important for accurate current-flow estimates. Here we present a tool that addresses these needs. It is based on a rigorous Bayesian inference framework that combines image intensity model, anatomical prior (atlas and morphological constraints using Markov random fields (MRF. The method is evaluated on 20 simulated and 8 real head volumes acquired with magnetic resonance imaging (MRI at 1 mm3 resolution. We find improved surface smoothness and continuity as compared to the segmentation algorithms currently implemented in Statistical Parametric Mapping (SPM. With this tool, accurate and morphologically correct modeling of the whole-head anatomy for individual subjects may now be feasible on a routine basis. Code and data are fully integrated into SPM software tool and are made publicly available. In addition, a review on the MRI segmentation using atlas and the MRF over the last 20 years is also provided, with the general mathematical framework clearly derived.

Fully automated whole-head segmentation with improved smoothness and continuity, with theory reviewed.

Science.gov (United States)

Huang, Yu; Parra, Lucas C

2015-01-01

Individualized current-flow models are needed for precise targeting of brain structures using transcranial electrical or magnetic stimulation (TES/TMS). The same is true for current-source reconstruction in electroencephalography and magnetoencephalography (EEG/MEG). The first step in generating such models is to obtain an accurate segmentation of individual head anatomy, including not only brain but also cerebrospinal fluid (CSF), skull and soft tissues, with a field of view (FOV) that covers the whole head. Currently available automated segmentation tools only provide results for brain tissues, have a limited FOV, and do not guarantee continuity and smoothness of tissues, which is crucially important for accurate current-flow estimates. Here we present a tool that addresses these needs. It is based on a rigorous Bayesian inference framework that combines image intensity model, anatomical prior (atlas) and morphological constraints using Markov random fields (MRF). The method is evaluated on 20 simulated and 8 real head volumes acquired with magnetic resonance imaging (MRI) at 1 mm3 resolution. We find improved surface smoothness and continuity as compared to the segmentation algorithms currently implemented in Statistical Parametric Mapping (SPM). With this tool, accurate and morphologically correct modeling of the whole-head anatomy for individual subjects may now be feasible on a routine basis. Code and data are fully integrated into SPM software tool and are made publicly available. In addition, a review on the MRI segmentation using atlas and the MRF over the last 20 years is also provided, with the general mathematical framework clearly derived.

Evaluation of a New Digital Automated Glycemic Pattern Detection Tool.

Science.gov (United States)

Comellas, María José; Albiñana, Emma; Artes, Maite; Corcoy, Rosa; Fernández-García, Diego; García-Alemán, Jorge; García-Cuartero, Beatriz; González, Cintia; Rivero, María Teresa; Casamira, Núria; Weissmann, Jörg

2017-11-01

Blood glucose meters are reliable devices for data collection, providing electronic logs of historical data easier to interpret than handwritten logbooks. Automated tools to analyze these data are necessary to facilitate glucose pattern detection and support treatment adjustment. These tools emerge in a broad variety in a more or less nonevaluated manner. The aim of this study was to compare eDetecta, a new automated pattern detection tool, to nonautomated pattern analysis in terms of time investment, data interpretation, and clinical utility, with the overarching goal to identify early in development and implementation of tool areas of improvement and potential safety risks. Multicenter web-based evaluation in which 37 endocrinologists were asked to assess glycemic patterns of 4 real reports (2 continuous subcutaneous insulin infusion [CSII] and 2 multiple daily injection [MDI]). Endocrinologist and eDetecta analyses were compared on time spent to analyze each report and agreement on the presence or absence of defined patterns. eDetecta module markedly reduced the time taken to analyze each case on the basis of the emminens eConecta reports (CSII: 18 min; MDI: 12.5), compared to the automatic eDetecta analysis. Agreement between endocrinologists and eDetecta varied depending on the patterns, with high level of agreement in patterns of glycemic variability. Further analysis of low level of agreement led to identifying areas where algorithms used could be improved to optimize trend pattern identification. eDetecta was a useful tool for glycemic pattern detection, helping clinicians to reduce time required to review emminens eConecta glycemic reports. No safety risks were identified during the study.

Fully automated pipeline for detection of sex linked genes using RNA-Seq data.

Science.gov (United States)

Michalovova, Monika; Kubat, Zdenek; Hobza, Roman; Vyskot, Boris; Kejnovsky, Eduard

2015-03-11

Sex chromosomes present a genomic region which to some extent, differs between the genders of a single species. Reliable high-throughput methods for detection of sex chromosomes specific markers are needed, especially in species where genome information is limited. Next generation sequencing (NGS) opens the door for identification of unique sequences or searching for nucleotide polymorphisms between datasets. A combination of classical genetic segregation analysis along with RNA-Seq data can present an ideal tool to map and identify sex chromosome-specific expressed markers. To address this challenge, we established genetic cross of dioecious plant Rumex acetosa and generated RNA-Seq data from both parental generation and male and female offspring. We present a pipeline for detection of sex linked genes based on nucleotide polymorphism analysis. In our approach, tracking of nucleotide polymorphisms is carried out using a cross of preferably distant populations. For this reason, only 4 datasets are needed - reads from high-throughput sequencing platforms for parent generation (mother and father) and F1 generation (male and female progeny). Our pipeline uses custom scripts together with external assembly, mapping and variant calling software. Given the resource-intensive nature of the computation, servers with high capacity are a requirement. Therefore, in order to keep this pipeline easily accessible and reproducible, we implemented it in Galaxy - an open, web-based platform for data-intensive biomedical research. Our tools are present in the Galaxy Tool Shed, from which they can be installed to any local Galaxy instance. As an output of the pipeline, user gets a FASTA file with candidate transcriptionally active sex-linked genes, sorted by their relevance. At the same time, a BAM file with identified genes and alignment of reads is also provided. Thus, polymorphisms following segregation pattern can be easily visualized, which significantly enhances primer design

A new TLD badge with machine readable ID for fully automated readout

International Nuclear Information System (INIS)

Kannan, S. Ratna P.; Kulkarni, M.S.

2003-01-01

The TLD badge currently being used for personnel monitoring of more than 40,000 radiation workers has a few drawbacks such as lack of on-badge machine readable ID code, delicate two-point clamping of dosimeters on an aluminium card with the chances of dosimeters falling off during handling or readout, projections on one side making automation of readout difficult etc. A new badge has been designed with a 8-digit identification code in the form of an array of holes and smooth exteriors to enable full automation of readout. The new badge also permits changing of dosimeters when necessary. The new design does not affect the readout time or the dosimetric characteristics. The salient features and the dosimetric characteristics are discussed. (author)

Development of on-chip fully automated immunoassay system "μTASWako i30" to measure the changes in glycosylation profiles of alpha-fetoprotein in patients with hepatocellular carcinoma.

Science.gov (United States)

Kurosawa, Tatsuo; Watanabe, Mitsuo

2016-12-01

Glycosylation profiles significantly change during oncogenesis. Aberrant glycosylation can be used as a cancer biomarker in clinical settings. Different glycoforms can be separately detected using lectin affinity electrophoresis and lectin array-based methods. However, most methodologies and procedures need experienced technique to perform the assays and expertise to interpret the results. To apply glycomarkers for clinical practice, a robust assay system with an easy-to-use workflow is required. Wako's μTASWako i30, a fully automated immunoanalyzer, was developed for in vitro diagnostics based on microfluidic technology. It utilizes the principles of liquid-phase binding assay, where immunoreactions are performed in a liquid phase, and electrokinetic analyte transport assay. Capillary electrophoresis on microfluidic chip has enabled the detection of different glycoform types of alpha-fetoprotein (AFP), a serum biomarker for hepatocellular carcinoma. AFP with altered glycosylation can be separated based on the reactivity to Lens culinaris agglutinin on electrophoresis. The glycoform AFP-L3 was reportedly more specific in hepatocellular carcinoma. This assay system can provide a high sensitivity and rapid results in 9 min. The test results for ratio of AFP-L3 to total AFP using μTASWako i30 are correlated with those of conventional methodology. The μTASWako assay system and the technology can be utilized for glycosylation analysis in the postgenomic era. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fully automated VMAT treatment planning for advanced-stage NSCLC patients

Energy Technology Data Exchange (ETDEWEB)

Della Gala, Giuseppe [Erasmus MC Cancer Institute, Department of Radiation Oncology, Rotterdam (Netherlands); Universita di Bologna, Scuola di Scienze, Alma Mater Studiorum, Bologna (Italy); Dirkx, Maarten L.P.; Hoekstra, Nienke; Fransen, Dennie; Pol, Marjan van de; Heijmen, Ben J.M. [Erasmus MC Cancer Institute, Department of Radiation Oncology, Rotterdam (Netherlands); Lanconelli, Nico [Universita di Bologna, Scuola di Scienze, Alma Mater Studiorum, Bologna (Italy); Petit, Steven F. [Erasmus MC Cancer Institute, Department of Radiation Oncology, Rotterdam (Netherlands); Massachusetts General Hospital - Harvard Medical School, Department of Radiation Oncology, Boston, MA (United States)

2017-05-15

To develop a fully automated procedure for multicriterial volumetric modulated arc therapy (VMAT) treatment planning (autoVMAT) for stage III/IV non-small cell lung cancer (NSCLC) patients treated with curative intent. After configuring the developed autoVMAT system for NSCLC, autoVMAT plans were compared with manually generated clinically delivered intensity-modulated radiotherapy (IMRT) plans for 41 patients. AutoVMAT plans were also compared to manually generated VMAT plans in the absence of time pressure. For 16 patients with reduced planning target volume (PTV) dose prescription in the clinical IMRT plan (to avoid violation of organs at risk tolerances), the potential for dose escalation with autoVMAT was explored. Two physicians evaluated 35/41 autoVMAT plans (85%) as clinically acceptable. Compared to the manually generated IMRT plans, autoVMAT plans showed statistically significant improved PTV coverage (V{sub 95%} increased by 1.1% ± 1.1%), higher dose conformity (R{sub 50} reduced by 12.2% ± 12.7%), and reduced mean lung, heart, and esophagus doses (reductions of 0.9 Gy ± 1.0 Gy, 1.5 Gy ± 1.8 Gy, 3.6 Gy ± 2.8 Gy, respectively, all p < 0.001). To render the six remaining autoVMAT plans clinically acceptable, a dosimetrist needed less than 10 min hands-on time for fine-tuning. AutoVMAT plans were also considered equivalent or better than manually optimized VMAT plans. For 6/16 patients, autoVMAT allowed tumor dose escalation of 5-10 Gy. Clinically deliverable, high-quality autoVMAT plans can be generated fully automatically for the vast majority of advanced-stage NSCLC patients. For a subset of patients, autoVMAT allowed for tumor dose escalation. (orig.) [German] Entwicklung einer vollautomatisierten, auf multiplen Kriterien basierenden volumenmodulierten Arc-Therapie-(VMAT-)Behandlungsplanung (autoVMAT) fuer kurativ behandelte Patienten mit nicht-kleinzelligem Bronchialkarzinom (NSCLC) im Stadium III/IV. Nach Konfiguration unseres auto

Screening for anabolic steroids in urine of forensic cases using fully automated solid phase extraction and LC-MS-MS.

Science.gov (United States)

Andersen, David W; Linnet, Kristian

2014-01-01

A screening method for 18 frequently measured exogenous anabolic steroids and the testosterone/epitestosterone (T/E) ratio in forensic cases has been developed and validated. The method involves a fully automated sample preparation including enzyme treatment, addition of internal standards and solid phase extraction followed by analysis by liquid chromatography-tandem mass spectrometry (LC-MS-MS) using electrospray ionization with adduct formation for two compounds. Urine samples from 580 forensic cases were analyzed to determine the T/E ratio and occurrence of exogenous anabolic steroids. Extraction recoveries ranged from 77 to 95%, matrix effects from 48 to 78%, overall process efficiencies from 40 to 54% and the lower limit of identification ranged from 2 to 40 ng/mL. In the 580 urine samples analyzed from routine forensic cases, 17 (2.9%) were found positive for one or more anabolic steroids. Only seven different steroids including testosterone were found in the material, suggesting that only a small number of common steroids are likely to occur in a forensic context. The steroids were often in high concentrations (>100 ng/mL), and a combination of steroids and/or other drugs of abuse were seen in the majority of cases. The method presented serves as a fast and automated screening procedure, proving the suitability of LC-MS-MS for analyzing anabolic steroids. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Automated biphasic morphological assessment of hepatitis B-related liver fibrosis using second harmonic generation microscopy

Science.gov (United States)

Wang, Tong-Hong; Chen, Tse-Ching; Teng, Xiao; Liang, Kung-Hao; Yeh, Chau-Ting

2015-08-01

Liver fibrosis assessment by biopsy and conventional staining scores is based on histopathological criteria. Variations in sample preparation and the use of semi-quantitative histopathological methods commonly result in discrepancies between medical centers. Thus, minor changes in liver fibrosis might be overlooked in multi-center clinical trials, leading to statistically non-significant data. Here, we developed a computer-assisted, fully automated, staining-free method for hepatitis B-related liver fibrosis assessment. In total, 175 liver biopsies were divided into training (n = 105) and verification (n = 70) cohorts. Collagen was observed using second harmonic generation (SHG) microscopy without prior staining, and hepatocyte morphology was recorded using two-photon excitation fluorescence (TPEF) microscopy. The training cohort was utilized to establish a quantification algorithm. Eleven of 19 computer-recognizable SHG/TPEF microscopic morphological features were significantly correlated with the ISHAK fibrosis stages (P 0.82 for liver cirrhosis detection. Since no subjective gradings are needed, interobserver discrepancies could be avoided using this fully automated method.

Automated multi-lesion detection for referable diabetic retinopathy in indigenous health care.

Science.gov (United States)

Pires, Ramon; Carvalho, Tiago; Spurling, Geoffrey; Goldenstein, Siome; Wainer, Jacques; Luckie, Alan; Jelinek, Herbert F; Rocha, Anderson

2015-01-01

Diabetic Retinopathy (DR) is a complication of diabetes mellitus that affects more than one-quarter of the population with diabetes, and can lead to blindness if not discovered in time. An automated screening enables the identification of patients who need further medical attention. This study aimed to classify retinal images of Aboriginal and Torres Strait Islander peoples utilizing an automated computer-based multi-lesion eye screening program for diabetic retinopathy. The multi-lesion classifier was trained on 1,014 images from the São Paulo Eye Hospital and tested on retinal images containing no DR-related lesion, single lesions, or multiple types of lesions from the Inala Aboriginal and Torres Strait Islander health care centre. The automated multi-lesion classifier has the potential to enhance the efficiency of clinical practice delivering diabetic retinopathy screening. Our program does not necessitate image samples for training from any specific ethnic group or population being assessed and is independent of image pre- or post-processing to identify retinal lesions. In this Aboriginal and Torres Strait Islander population, the program achieved 100% sensitivity and 88.9% specificity in identifying bright lesions, while detection of red lesions achieved a sensitivity of 67% and specificity of 95%. When both bright and red lesions were present, 100% sensitivity with 88.9% specificity was obtained. All results obtained with this automated screening program meet WHO standards for diabetic retinopathy screening.

TU-H-CAMPUS-JeP1-02: Fully Automatic Verification of Automatically Contoured Normal Tissues in the Head and Neck

Energy Technology Data Exchange (ETDEWEB)

McCarroll, R [UT MD Anderson Cancer Center, Houston, TX (United States); UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX (United States); Beadle, B; Yang, J; Zhang, L; Kisling, K; Balter, P; Stingo, F; Nelson, C; Followill, D; Court, L [UT MD Anderson Cancer Center, Houston, TX (United States); Mejia, M [University of Santo Tomas Hospital, Manila, Metro Manila (Philippines)

2016-06-15

Purpose: To investigate and validate the use of an independent deformable-based contouring algorithm for automatic verification of auto-contoured structures in the head and neck towards fully automated treatment planning. Methods: Two independent automatic contouring algorithms [(1) Eclipse’s Smart Segmentation followed by pixel-wise majority voting, (2) an in-house multi-atlas based method] were used to create contours of 6 normal structures of 10 head-and-neck patients. After rating by a radiation oncologist, the higher performing algorithm was selected as the primary contouring method, the other used for automatic verification of the primary. To determine the ability of the verification algorithm to detect incorrect contours, contours from the primary method were shifted from 0.5 to 2cm. Using a logit model the structure-specific minimum detectable shift was identified. The models were then applied to a set of twenty different patients and the sensitivity and specificity of the models verified. Results: Per physician rating, the multi-atlas method (4.8/5 point scale, with 3 rated as generally acceptable for planning purposes) was selected as primary and the Eclipse-based method (3.5/5) for verification. Mean distance to agreement and true positive rate were selected as covariates in an optimized logit model. These models, when applied to a group of twenty different patients, indicated that shifts could be detected at 0.5cm (brain), 0.75cm (mandible, cord), 1cm (brainstem, cochlea), or 1.25cm (parotid), with sensitivity and specificity greater than 0.95. If sensitivity and specificity constraints are reduced to 0.9, detectable shifts of mandible and brainstem were reduced by 0.25cm. These shifts represent additional safety margins which might be considered if auto-contours are used for automatic treatment planning without physician review. Conclusion: Automatically contoured structures can be automatically verified. This fully automated process could be used to

AN AUTOMATED ROAD ROUGHNESS DETECTION FROM MOBILE LASER SCANNING DATA

Directory of Open Access Journals (Sweden)

P. Kumar

2017-05-01

Full Text Available Rough roads influence the safety of the road users as accident rate increases with increasing unevenness of the road surface. Road roughness regions are required to be efficiently detected and located in order to ensure their maintenance. Mobile Laser Scanning (MLS systems provide a rapid and cost-effective alternative by providing accurate and dense point cloud data along route corridor. In this paper, an automated algorithm is presented for detecting road roughness from MLS data. The presented algorithm is based on interpolating smooth intensity raster surface from LiDAR point cloud data using point thinning process. The interpolated surface is further processed using morphological and multi-level Otsu thresholding operations to identify candidate road roughness regions. The candidate regions are finally filtered based on spatial density and standard deviation of elevation criteria to detect the roughness along the road surface. The test results of road roughness detection algorithm on two road sections are presented. The developed approach can be used to provide comprehensive information to road authorities in order to schedule maintenance and ensure maximum safety conditions for road users.

An Automated Road Roughness Detection from Mobile Laser Scanning Data

Science.gov (United States)

Kumar, P.; Angelats, E.

2017-05-01

Rough roads influence the safety of the road users as accident rate increases with increasing unevenness of the road surface. Road roughness regions are required to be efficiently detected and located in order to ensure their maintenance. Mobile Laser Scanning (MLS) systems provide a rapid and cost-effective alternative by providing accurate and dense point cloud data along route corridor. In this paper, an automated algorithm is presented for detecting road roughness from MLS data. The presented algorithm is based on interpolating smooth intensity raster surface from LiDAR point cloud data using point thinning process. The interpolated surface is further processed using morphological and multi-level Otsu thresholding operations to identify candidate road roughness regions. The candidate regions are finally filtered based on spatial density and standard deviation of elevation criteria to detect the roughness along the road surface. The test results of road roughness detection algorithm on two road sections are presented. The developed approach can be used to provide comprehensive information to road authorities in order to schedule maintenance and ensure maximum safety conditions for road users.

[Automated detection and volumetric segmentation of the spleen in CT scans].

Science.gov (United States)

Hammon, M; Dankerl, P; Kramer, M; Seifert, S; Tsymbal, A; Costa, M J; Janka, R; Uder, M; Cavallaro, A

2012-08-01

To introduce automated detection and volumetric segmentation of the spleen in spiral CT scans with the THESEUS-MEDICO software. The consistency between automated volumetry (aV), estimated volume determination (eV) and manual volume segmentation (mV) was evaluated. Retrospective evaluation of the CAD system based on methods like "marginal space learning" and "boosting algorithms". 3 consecutive spiral CT scans (thoraco-abdominal; portal-venous contrast agent phase; 1 or 5 mm slice thickness) of 15 consecutive lymphoma patients were included. The eV: 30 cm³ + 0.58 (width × length × thickness of the spleen) and the mV as the reference standard were determined by an experienced radiologist. The aV could be performed in all CT scans within 15.2 (± 2.4) seconds. The average splenic volume measured by aV was 268.21 ± 114.67 cm³ compared to 281.58 ± 130.21 cm³ in mV and 268.93 ± 104.60 cm³ in eV. The correlation coefficient was 0.99 (coefficient of determination (R²) = 0.98) for aV and mV, 0.91 (R² = 0.83) for mV and eV and 0.91 (R² = 0.82) for aV and eV. There was an almost perfect correlation of the changes in splenic volume measured with the new aV and mV (0.92; R² = 0.84), mV and eV (0.95; R² = 0.91) and aV and eV (0.83; R² = 0.69) between two time points. The automated detection and volumetric segmentation software rapidly provides an accurate measurement of the splenic volume in CT scans. Knowledge about splenic volume and its change between two examinations provides valuable clinical information without effort for the radiologist. © Georg Thieme Verlag KG Stuttgart · New York.

Automated detection and volumetric segmentation of the spleen in CT scans

International Nuclear Information System (INIS)

Hammon, M.; Dankerl, P.; Janka, R.; Uder, M.; Cavallaro, A.; Kramer, M.; Seifert, S.; Tsymbal, A.; Costa, M.J.

2012-01-01

To introduce automated detection and volumetric segmentation of the spleen in spiral CT scans with the THESEUS-MEDICO software. The consistency between automated volumetry (aV), estimated volume determination (eV) and manual volume segmentation (mV) was evaluated. Retrospective evaluation of the CAD system based on methods like ''marginal space learning'' and ''boosting algorithms''. 3 consecutive spiral CT scans (thoraco-abdominal; portal-venous contrast agent phase; 1 or 5 mm slice thickness) of 15 consecutive lymphoma patients were included. The eV: 30 cm 3 + 0.58 (width x length x thickness of the spleen) and the mV as the reference standard were determined by an experienced radiologist. The aV could be performed in all CT scans within 15.2 (± 2.4) seconds. The average splenic volume measured by aV was 268.21 ± 114.67 cm 3 compared to 281.58 ± 130.21 cm 3 in mV and 268.93 ± 104.60 cm 3 in eV. The correlation coefficient was 0.99 (coefficient of determination (R 2 ) = 0.98) for aV and mV, 0.91 (R 2 = 0.83) for mV and eV and 0.91 (R 2 = 0.82) for aV and eV. There was an almost perfect correlation of the changes in splenic volume measured with the new aV and mV (0.92; R 2 = 0.84), mV and eV (0.95; R 2 = 0.91) and aV and eV (0.83; R 2 = 0.69) between two time points. The automated detection and volumetric segmentation software rapidly provides an accurate measurement of the splenic volume in CT scans. Knowledge about splenic volume and its change between two examinations provides valuable clinical information without effort for the radiologist. (orig.)

Development of a fully automated open-column chemical-separation system—COLUMNSPIDER—and its application to Sr-Nd-Pb isotope analyses of igneous rock samples

Science.gov (United States)

Miyazaki, Takashi; Vaglarov, Bogdan Stefanov; Takei, Masakazu; Suzuki, Masahiro; Suzuki, Hiroaki; Ohsawa, Kouzou; Chang, Qing; Takahashi, Toshiro; Hirahara, Yuka; Hanyu, Takeshi; Kimura, Jun-Ichi; Tatsumi, Yoshiyuki

A fully automated open-column resin-bed chemical-separation system, named COLUMNSPIDER, has been developed. The system consists of a programmable micropipetting robot that dispenses chemical reagents and sample solutions into an open-column resin bed for elemental separation. After the initial set up of resin columns, chemical reagents, and beakers for the separated chemical components, all separation procedures are automated. As many as ten samples can be eluted in parallel in a single automated run. Many separation procedures, such as radiogenic isotope ratio analyses for Sr and Nd, involve the use of multiple column separations with different resin columns, chemical reagents, and beakers of various volumes. COLUMNSPIDER completes these separations using multiple runs. Programmable functions, including the positioning of the micropipetter, reagent volume, and elution time, enable flexible operation. Optimized movements for solution take-up and high-efficiency column flushing allow the system to perform as precisely as when carried out manually by a skilled operator. Procedural blanks, examined for COLUMNSPIDER separations of Sr, Nd, and Pb, are low and negligible. The measured Sr, Nd, and Pb isotope ratios for JB-2 and Nd isotope ratios for JB-3 and BCR-2 rock standards all fall within the ranges reported previously in high-accuracy analyses. COLUMNSPIDER is a versatile tool for the efficient elemental separation of igneous rock samples, a process that is both labor intensive and time consuming.

FPGA-based fully digital fast power switch fault detection and compensation for three-phase shunt active filters

Energy Technology Data Exchange (ETDEWEB)

Karimi, S.; Saadate, S. [Groupe de Recherche en Electrotechnique et Electronique de Nancy, GREEN-UHP, CNRS UMR 7037 (France); Poure, P. [Laboratoire d' Instrumentation Electronique de Nancy, LIEN, EA 3440, France Nancy Universite - Universite Henri Poincare de Nancy I, BP 239, 54506 Vandoeuvre les Nancy cedex (France)

2008-11-15

This paper discusses the design, implementation, experimental validation and performances of a fully digital fast power switch fault detection and compensation for three-phase shunt active power filters. The approach introduced in this paper minimizes the time interval between the fault occurrence and its diagnosis. This paper demonstrates the possibility to detect a faulty switch of the active filter in less than 10 {mu}s by using simultaneously a ''time criterion'' and a ''voltage criterion''. In order to attain this fast detection time a FPGA (Field Programmable Gate Array) is used. The other feature introduced in this approach is that the control scheme used to compensate the current load harmonics and fault tolerant scheme are both programmed in only one FPGA. ''FPGA in the loop'' prototyping results and fully experimental results based on a real active power filter verify satisfactory performances of the proposed method. (author)

Shuttlecock detection system for fully-autonomous badminton robot with two high-speed video cameras

Science.gov (United States)

Masunari, T.; Yamagami, K.; Mizuno, M.; Une, S.; Uotani, M.; Kanematsu, T.; Demachi, K.; Sano, S.; Nakamura, Y.; Suzuki, S.

2017-02-01

Two high-speed video cameras are successfully used to detect the motion of a flying shuttlecock of badminton. The shuttlecock detection system is applied to badminton robots that play badminton fully autonomously. The detection system measures the three dimensional position and velocity of a flying shuttlecock, and predicts the position where the shuttlecock falls to the ground. The badminton robot moves quickly to the position where the shuttle-cock falls to, and hits the shuttlecock back into the opponent's side of the court. In the game of badminton, there is a large audience, and some of them move behind a flying shuttlecock, which are a kind of background noise and makes it difficult to detect the motion of the shuttlecock. The present study demonstrates that such noises can be eliminated by the method of stereo imaging with two high-speed cameras.

Development and Evaluation of an Automated, Home-Based, Electronic Questionnaire for Detecting COPD Exacerbations

Directory of Open Access Journals (Sweden)

Francisco de B. Velazquez-Peña

2015-01-01

Full Text Available Collaboration between patients and their medical and technical experts enabled the development of an automated questionnaire for the early detection of COPD exacerbations (AQCE. The questionnaire consisted of fourteen questions and was implemented on a computer system for use by patients at home in an un-supervised environment. Psychometric evaluation was conducted after a 6-month field trial. Fifty-two patients were involved in the development of the questionnaire. Reproducibility was studied using 19 patients (ICC = 0.94. Sixteen out of the 19 subjects started the 6 month-field trial with the computer application. Cronbach’s alpha of 0.81 was achieved. In the concurrent validity analysis, a correlation of 0.80 (p = 0.002 with the CCQ was reported. The results suggest that AQCE is a valid and reliable questionnaire, showing that an automated home-based electronic questionnaire may enable early detection of exacerbations of COPD.

Time-Motion Analysis of Four Automated Systems for the Detection of Chlamydia trachomatis and Neisseria gonorrhoeae by Nucleic Acid Amplification Testing.

Science.gov (United States)

Williams, James A; Eddleman, Laura; Pantone, Amy; Martinez, Regina; Young, Stephen; Van Der Pol, Barbara

2014-08-01

Next-generation diagnostics for Chlamydia trachomatis and Neisseria gonorrhoeae are available on semi- or fully-automated platforms. These systems require less hands-on time than older platforms and are user friendly. Four automated systems, the ABBOTT m2000 system, Becton Dickinson Viper System with XTR Technology, Gen-Probe Tigris DTS system, and Roche cobas 4800 system, were evaluated for total run time, hands-on time, and walk-away time. All of the systems evaluated in this time-motion study were able to complete a diagnostic test run within an 8-h work shift, instrument setup and operation were straightforward and uncomplicated, and walk-away time ranged from approximately 90 to 270 min in a head-to-head comparison of each system. All of the automated systems provide technical staff with increased time to perform other tasks during the run, offer easy expansion of the diagnostic test menu, and have the ability to increase specimen throughput. © 2013 Society for Laboratory Automation and Screening.

Automating Trend Analysis for Spacecraft Constellations

Science.gov (United States)

Davis, George; Cooter, Miranda; Updike, Clark; Carey, Everett; Mackey, Jennifer; Rykowski, Timothy; Powers, Edward I. (Technical Monitor)

2001-01-01

Spacecraft trend analysis is a vital mission operations function performed by satellite controllers and engineers, who perform detailed analyses of engineering telemetry data to diagnose subsystem faults and to detect trends that may potentially lead to degraded subsystem performance or failure in the future. It is this latter function that is of greatest importance, for careful trending can often predict or detect events that may lead to a spacecraft's entry into safe-hold. Early prediction and detection of such events could result in the avoidance of, or rapid return to service from, spacecraft safing, which not only results in reduced recovery costs but also in a higher overall level of service for the satellite system. Contemporary spacecraft trending activities are manually intensive and are primarily performed diagnostically after a fault occurs, rather than proactively to predict its occurrence. They also tend to rely on information systems and software that are oudated when compared to current technologies. When coupled with the fact that flight operations teams often have limited resources, proactive trending opportunities are limited, and detailed trend analysis is often reserved for critical responses to safe holds or other on-orbit events such as maneuvers. While the contemporary trend analysis approach has sufficed for current single-spacecraft operations, it will be unfeasible for NASA's planned and proposed space science constellations. Missions such as the Dynamics, Reconnection and Configuration Observatory (DRACO), for example, are planning to launch as many as 100 'nanospacecraft' to form a homogenous constellation. A simple extrapolation of resources and manpower based on single-spacecraft operations suggests that trending for such a large spacecraft fleet will be unmanageable, unwieldy, and cost-prohibitive. It is therefore imperative that an approach to automating the spacecraft trend analysis function be studied, developed, and applied to

Screening for illicit and medicinal drugs in whole blood using fully automated SPE and ultra-high-performance liquid chromatography with TOF-MS with data-independent acquisition.

Science.gov (United States)

Pedersen, Anders Just; Dalsgaard, Petur Weihe; Rode, Andrej Jaroslav; Rasmussen, Brian Schou; Müller, Irene Breum; Johansen, Sys Stybe; Linnet, Kristian

2013-07-01

A broad forensic screening method for 256 analytes in whole blood based on a fully automated SPE robotic extraction and ultra-high-performance liquid chromatography (UHPLC) with TOF-MS with data-independent acquisition has been developed. The limit of identification was evaluated for all 256 compounds and 95 of these compounds were validated with regard to matrix effects, extraction recovery, and process efficiency. The limit of identification ranged from 0.001 to 0.1 mg/kg, and the process efficiency exceeded 50% for 73 of the 95 analytes. As an example of application, 1335 forensic traffic cases were analyzed with the presented screening method. Of these, 992 cases (74%) were positive for one or more traffic-relevant drugs above the Danish legal limits. Commonly abused drugs such as amphetamine, cocaine, and frequent types of benzodiazepines were the major findings. Nineteen less frequently encountered drugs were detected e.g. buprenorphine, butylone, cathine, fentanyl, lysergic acid diethylamide, m-chlorophenylpiperazine, 3,4-methylenedioxypyrovalerone, mephedrone, 4-methylamphetamine, p-fluoroamphetamine, and p-methoxy-N-methylamphetamine. In conclusion, using UHPLC-TOF-MS screening with data-independent acquisition resulted in the detection of common drugs of abuse as well as new designer drugs and more rarely occurring drugs. Thus, TOF-MS screening of blood samples constitutes a practical way for screening traffic cases, with the exception of δ-9-tetrahydrocannabinol, which should be handled in a separate method. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated Breast Ultrasound Lesions Detection using Convolutional Neural Networks.

Science.gov (United States)

Yap, Moi Hoon; Pons, Gerard; Marti, Joan; Ganau, Sergi; Sentis, Melcior; Zwiggelaar, Reyer; Davison, Adrian K; Marti, Robert

2017-08-07

Breast lesion detection using ultrasound imaging is considered an important step of Computer-Aided Diagnosis systems. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. However, the lack of a common dataset impedes research when comparing the performance of such algorithms. This paper proposes the use of deep learning approaches for breast ultrasound lesion detection and investigates three different methods: a Patch-based LeNet, a U-Net, and a transfer learning approach with a pretrained FCN-AlexNet. Their performance is compared against four state-of-the-art lesion detection algorithms (i.e. Radial Gradient Index, Multifractal Filtering, Rule-based Region Ranking and Deformable Part Models). In addition, this paper compares and contrasts two conventional ultrasound image datasets acquired from two different ultrasound systems. Dataset A comprises 306 (60 malignant and 246 benign) images and Dataset B comprises 163 (53 malignant and 110 benign) images. To overcome the lack of public datasets in this domain, Dataset B will be made available for research purposes. The results demonstrate an overall improvement by the deep learning approaches when assessed on both datasets in terms of True Positive Fraction, False Positives per image, and F-measure.

Multicenter Evaluation of a Novel Automated Rapid Detection System of BRAF Status in Formalin-Fixed, Paraffin-Embedded Tissues.

Science.gov (United States)

Schiefer, Ana-Iris; Parlow, Laura; Gabler, Lisa; Mesteri, Ildiko; Koperek, Oskar; von Deimling, Andreas; Streubel, Berthold; Preusser, Matthias; Lehmann, Annika; Kellner, Udo; Pauwels, Patrick; Lambin, Suzan; Dietel, Manfred; Hummel, Michael; Klauschen, Frederick; Birner, Peter; Möbs, Markus

2016-05-01

The mutated BRAF oncogene represents a therapeutic target in malignant melanoma. Because BRAF mutations are also involved in the pathogenesis of other human malignancies, the use of specific BRAF inhibitors might also be extended to other diseases in the future. A prerequisite for the clinical application of BRAF inhibitors is the reliable detection of activating BRAF mutations in routine histopathological samples. In a multicenter approach, we evaluated a novel and fully automated PCR-based system (Idylla) capable of detecting BRAF V600 mutations in formalin-fixed, paraffin-embedded tissue within 90 minutes with high sensitivity. We analyzed a total of 436 samples with the Idylla system. Valid results were obtained in 421 cases (96.56%). Its performance was compared with conventional methods (pyrosequencing or Sanger sequencing). Concordant results were obtained in 406 cases (96.90%). Reanalysis of eight discordant samples by next-generation sequencing and/or pyrosequencing with newly extracted DNA and the BRAF RGQ Kit confirmed the Idylla result in seven cases, resulting in an overall agreement of 98.57%. In conclusion, the Idylla system is a highly reliable and sensitive platform for detection of BRAF V600 mutations in formalin-fixed, paraffin-embedded material, providing an efficient alternative to conventional diagnostic methods, particularly for routine diagnostics laboratories with limited experience in molecular pathology. Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Infrared thermal imaging for automated detection of diabetic foot complications.

Science.gov (United States)

van Netten, Jaap J; van Baal, Jeff G; Liu, Chanjuan; van der Heijden, Ferdi; Bus, Sicco A

2013-09-01

Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had diffuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). No differences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with diffuse complications, mean temperature differences of >3 °C between ipsilateral and contralateral foot were found. With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or diffuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings. © 2013 Diabetes Technology Society.

Bayesian ISOLA: new tool for automated centroid moment tensor inversion

Science.gov (United States)

Vackář, Jiří; Burjánek, Jan; Gallovič, František; Zahradník, Jiří; Clinton, John

2017-04-01

Focal mechanisms are important for understanding seismotectonics of a region, and they serve as a basic input for seismic hazard assessment. Usually, the point source approximation and the moment tensor (MT) are used. We have developed a new, fully automated tool for the centroid moment tensor (CMT) inversion in a Bayesian framework. It includes automated data retrieval, data selection where station components with various instrumental disturbances and high signal-to-noise are rejected, and full-waveform inversion in a space-time grid around a provided hypocenter. The method is innovative in the following aspects: (i) The CMT inversion is fully automated, no user interaction is required, although the details of the process can be visually inspected latter on many figures which are automatically plotted.(ii) The automated process includes detection of disturbances based on MouseTrap code, so disturbed recordings do not affect inversion.(iii) A data covariance matrix calculated from pre-event noise yields an automated weighting of the station recordings according to their noise levels and also serves as an automated frequency filter suppressing noisy frequencies.(iv) Bayesian approach is used, so not only the best solution is obtained, but also the posterior probability density function.(v) A space-time grid search effectively combined with the least-squares inversion of moment tensor components speeds up the inversion and allows to obtain more accurate results compared to stochastic methods. The method has been tested on synthetic and observed data. It has been tested by comparison with manually processed moment tensors of all events greater than M≥3 in the Swiss catalogue over 16 years using data available at the Swiss data center (http://arclink.ethz.ch). The quality of the results of the presented automated process is comparable with careful manual processing of data. The software package programmed in Python has been designed to be as versatile as possible in

Quest for automated land cover change detection using satellite time series data

CSIR Research Space (South Africa)

Salmon, BP

2009-07-01

Full Text Available and surface climate in the next fifty years,” Global Change Biology, vol. 8, no. 5, pp. 438–458, May 2002. [3] J. A. Foley et al., “Global consequences of land use,” Science, vol. 309, no. 5734, pp. 570–574, July 2005. [4] R. S. Lunetta et al., “Land... (class 1). These four subsets were used to produce a confusion matrix to test if the operational MLP can detect change reliably in an automated fashion on subsets 1 and 2, while not falsely detecting change for subsets 3 and 4. This particular splic...

Transitioning Resolution Responsibility between the Controller and Automation Team in Simulated NextGen Separation Assurance

Science.gov (United States)

Cabrall, C.; Gomez, A.; Homola, J.; Hunt, S..; Martin, L.; Merccer, J.; Prevott, T.

2013-01-01

As part of an ongoing research effort on separation assurance and functional allocation in NextGen, a controller- in-the-loop study with ground-based automation was conducted at NASA Ames' Airspace Operations Laboratory in August 2012 to investigate the potential impact of introducing self-separating aircraft in progressively advanced NextGen timeframes. From this larger study, the current exploratory analysis of controller-automation interaction styles focuses on the last and most far-term time frame. Measurements were recorded that firstly verified the continued operational validity of this iteration of the ground-based functional allocation automation concept in forecast traffic densities up to 2x that of current day high altitude en-route sectors. Additionally, with greater levels of fully automated conflict detection and resolution as well as the introduction of intervention functionality, objective and subjective analyses showed a range of passive to active controller- automation interaction styles between the participants. Not only did the controllers work with the automation to meet their safety and capacity goals in the simulated future NextGen timeframe, they did so in different ways and with different attitudes of trust/use of the automation. Taken as a whole, the results showed that the prototyped controller-automation functional allocation framework was very flexible and successful overall.

Automated detection and characterization of harmonic tremor in continuous seismic data

Science.gov (United States)

Roman, Diana C.

2017-06-01

Harmonic tremor is a common feature of volcanic, hydrothermal, and ice sheet seismicity and is thus an important proxy for monitoring changes in these systems. However, no automated methods for detecting harmonic tremor currently exist. Because harmonic tremor shares characteristics with speech and music, digital signal processing techniques for analyzing these signals can be adapted. I develop a novel pitch-detection-based algorithm to automatically identify occurrences of harmonic tremor and characterize their frequency content. The algorithm is applied to seismic data from Popocatepetl Volcano, Mexico, and benchmarked against a monthlong manually detected catalog of harmonic tremor events. During a period of heightened eruptive activity from December 2014 to May 2015, the algorithm detects 1465 min of harmonic tremor, which generally precede periods of heightened explosive activity. These results demonstrate the algorithm's ability to accurately characterize harmonic tremor while highlighting the need for additional work to understand its causes and implications at restless volcanoes.

Fully automated laboratory for the assay of plutonium in wastes and recoverable scraps

International Nuclear Information System (INIS)

Guiberteau, P.; Michaut, F.; Bergey, C.; Debruyne, T.

1990-01-01

To determine the plutonium content of wastes and recoverable scraps in intermediate size containers (ten liters) an automated laboratory has been carried out. Two passive methods of measurement are used. Gamma ray spectrometry allows plutonium isotopic analysis, americium determination and plutonium assay in wastes and poor scraps. Calorimetry is used for accurate (± 3%) plutonium determination in rich scraps. A full automation was realized with a barcode management and a supply robot to feed the eight assay set-ups. The laboratory works on a 24 hours per day and 365 days per year basis and has a capacity of 8,000 assays per year

Automated Detection of Heuristics and Biases among Pathologists in a Computer-Based System

Science.gov (United States)

Crowley, Rebecca S.; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia

2013-01-01

The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to…

Filament Chirality over an Entire Cycle Determined with an Automated Detection Module -- a Neat Surprise!

Science.gov (United States)

Martens, Petrus C.; Yeates, A. R.; Mackay, D.; Pillai, K. G.

2013-07-01

Using metadata produced by automated solar feature detection modules developed for SDO (Martens et al. 2012) we have discovered some trends in filament chirality and filament-sigmoid relations that are new and in part contradict the current consensus. Automated detection of solar features has the advantage over manual detection of having the detection criteria applied consistently, and in being able to deal with enormous amounts of data, like the 1 Terabyte per day that SDO produces. Here we use the filament detection module developed by Bernasconi, which has metadata from 2000 on, and the sigmoid sniffer, which has been producing metadata from AIA 94 A images since October 2011. The most interesting result we find is that the hemispheric chirality preference for filaments (dextral in the north, and v.v.), studied in detail for a three year period by Pevtsov et al. (2003) seems to disappear during parts of the decline of cycle 23 and during the extended solar minimum that followed. Moreover the hemispheric chirality rule seems to be much less pronounced during the onset of cycle 24. For sigmoids we find the expected correlation between chirality and handedness (S or Z) shape but not as strong as expected.

Automated detection of multiple sclerosis lesions in serial brain MRI

International Nuclear Information System (INIS)

Llado, Xavier; Ganiler, Onur; Oliver, Arnau; Marti, Robert; Freixenet, Jordi; Valls, Laia; Vilanova, Joan C.; Ramio-Torrenta, Lluis; Rovira, Alex

2012-01-01

Multiple sclerosis (MS) is a serious disease typically occurring in the brain whose diagnosis and efficacy of treatment monitoring are vital. Magnetic resonance imaging (MRI) is frequently used in serial brain imaging due to the rich and detailed information provided. Time-series analysis of images is widely used for MS diagnosis and patient follow-up. However, conventional manual methods are time-consuming, subjective, and error-prone. Thus, the development of automated techniques for the detection and quantification of MS lesions is a major challenge. This paper presents an up-to-date review of the approaches which deal with the time-series analysis of brain MRI for detecting active MS lesions and quantifying lesion load change. We provide a comprehensive reference source for researchers in which several approaches to change detection and quantification of MS lesions are investigated and classified. We also analyze the results provided by the approaches, discuss open problems, and point out possible future trends. Lesion detection approaches are required for the detection of static lesions and for diagnostic purposes, while either quantification of detected lesions or change detection algorithms are needed to follow up MS patients. However, there is not yet a single approach that can emerge as a standard for the clinical practice, automatically providing an accurate MS lesion evolution quantification. Future trends will focus on combining the lesion detection in single studies with the analysis of the change detection in serial MRI. (orig.)

Automated detection of multiple sclerosis lesions in serial brain MRI

Energy Technology Data Exchange (ETDEWEB)

Llado, Xavier; Ganiler, Onur; Oliver, Arnau; Marti, Robert; Freixenet, Jordi [University of Girona, Computer Vision and Robotics Group, Girona (Spain); Valls, Laia [Dr. Josep Trueta University Hospital, Department of Radiology, Girona (Spain); Vilanova, Joan C. [Girona Magnetic Resonance Center, Girona (Spain); Ramio-Torrenta, Lluis [Dr. Josep Trueta University Hospital, Institut d' Investigacio Biomedica de Girona, Multiple Sclerosis and Neuroimmunology Unit, Girona (Spain); Rovira, Alex [Vall d' Hebron University Hospital, Magnetic Resonance Unit, Department of Radiology, Barcelona (Spain)

2012-08-15

Multiple sclerosis (MS) is a serious disease typically occurring in the brain whose diagnosis and efficacy of treatment monitoring are vital. Magnetic resonance imaging (MRI) is frequently used in serial brain imaging due to the rich and detailed information provided. Time-series analysis of images is widely used for MS diagnosis and patient follow-up. However, conventional manual methods are time-consuming, subjective, and error-prone. Thus, the development of automated techniques for the detection and quantification of MS lesions is a major challenge. This paper presents an up-to-date review of the approaches which deal with the time-series analysis of brain MRI for detecting active MS lesions and quantifying lesion load change. We provide a comprehensive reference source for researchers in which several approaches to change detection and quantification of MS lesions are investigated and classified. We also analyze the results provided by the approaches, discuss open problems, and point out possible future trends. Lesion detection approaches are required for the detection of static lesions and for diagnostic purposes, while either quantification of detected lesions or change detection algorithms are needed to follow up MS patients. However, there is not yet a single approach that can emerge as a standard for the clinical practice, automatically providing an accurate MS lesion evolution quantification. Future trends will focus on combining the lesion detection in single studies with the analysis of the change detection in serial MRI. (orig.)

Detecting Changes in Forest Structure over Time with Bi-Temporal Terrestrial Laser Scanning Data

Directory of Open Access Journals (Sweden)

Timo Melkas

2012-10-01

Full Text Available Changes to stems caused by natural forces and timber harvesting constitute an essential input for many forestry-related applications and ecological studies, especially forestry inventories based on the use of permanent sample plots. Conventional field measurement is widely acknowledged as being time-consuming and labor-intensive. More automated and efficient alternatives or supportive methods are needed. Terrestrial laser scanning (TLS has been demonstrated to be a promising method in forestry field inventories. Nevertheless, the applicability of TLS in recording changes in the structure of forest plots has not been studied in detail. This paper presents a fully automated method for detecting changes in forest structure over time using bi-temporal TLS data. The developed method was tested on five densely populated forest plots including 137 trees and 50 harvested trees in point clouds. The present study demonstrated that 90 percent of tree stem changes could be automatically located from single-scan TLS data. These changes accounted for 92 percent of the changed basal area. The results indicate that the processing of TLS data collected at different times to detect tree stem changes can be fully automated.

An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation.

Science.gov (United States)

Dereymaeker, Anneleen; Pillay, Kirubin; Vervisch, Jan; Van Huffel, Sabine; Naulaers, Gunnar; Jansen, Katrien; De Vos, Maarten

2017-09-01

Sleep state development in preterm neonates can provide crucial information regarding functional brain maturation and give insight into neurological well being. However, visual labeling of sleep stages from EEG requires expertise and is very time consuming, prompting the need for an automated procedure. We present a robust method for automated detection of preterm sleep from EEG, over a wide postmenstrual age ([Formula: see text] age) range, focusing first on Quiet Sleep (QS) as an initial marker for sleep assessment. Our algorithm, CLuster-based Adaptive Sleep Staging (CLASS), detects QS if it remains relatively more discontinuous than non-QS over PMA. CLASS was optimized on a training set of 34 recordings aged 27-42 weeks PMA, and performance then assessed on a distinct test set of 55 recordings of the same age range. Results were compared to visual QS labeling from two independent raters (with inter-rater agreement [Formula: see text]), using Sensitivity, Specificity, Detection Factor ([Formula: see text] of visual QS periods correctly detected by CLASS) and Misclassification Factor ([Formula: see text] of CLASS-detected QS periods that are misclassified). CLASS performance proved optimal across recordings at 31-38 weeks (median [Formula: see text], median MF 0-0.25, median Sensitivity 0.93-1.0, and median Specificity 0.80-0.91 across this age range), with minimal misclassifications at 35-36 weeks (median [Formula: see text]). To illustrate the potential of CLASS in facilitating clinical research, normal maturational trends over PMA were derived from CLASS-estimated QS periods, visual QS estimates, and nonstate specific periods (containing QS and non-QS) in the EEG recording. CLASS QS trends agreed with those from visual QS, with both showing stronger correlations than nonstate specific trends. This highlights the benefit of automated QS detection for exploring brain maturation.

Lung Nodule Detection in CT Images using Neuro Fuzzy Classifier

Directory of Open Access Journals (Sweden)

M. Usman Akram

2013-07-01

Full Text Available Automated lung cancer detection using computer aided diagnosis (CAD is an important area in clinical applications. As the manual nodule detection is very time consuming and costly so computerized systems can be helpful for this purpose. In this paper, we propose a computerized system for lung nodule detection in CT scan images. The automated system consists of two stages i.e. lung segmentation and enhancement, feature extraction and classification. The segmentation process will result in separating lung tissue from rest of the image, and only the lung tissues under examination are considered as candidate regions for detecting malignant nodules in lung portion. A feature vector for possible abnormal regions is calculated and regions are classified using neuro fuzzy classifier. It is a fully automatic system that does not require any manual intervention and experimental results show the validity of our system.

Microbleed detection using automated segmentation (MIDAS): a new method applicable to standard clinical MR images.

Science.gov (United States)

Seghier, Mohamed L; Kolanko, Magdalena A; Leff, Alexander P; Jäger, Hans R; Gregoire, Simone M; Werring, David J

2011-03-23

Cerebral microbleeds, visible on gradient-recalled echo (GRE) T2* MRI, have generated increasing interest as an imaging marker of small vessel diseases, with relevance for intracerebral bleeding risk or brain dysfunction. Manual rating methods have limited reliability and are time-consuming. We developed a new method for microbleed detection using automated segmentation (MIDAS) and compared it with a validated visual rating system. In thirty consecutive stroke service patients, standard GRE T2* images were acquired and manually rated for microbleeds by a trained observer. After spatially normalizing each patient's GRE T2* images into a standard stereotaxic space, the automated microbleed detection algorithm (MIDAS) identified cerebral microbleeds by explicitly incorporating an "extra" tissue class for abnormal voxels within a unified segmentation-normalization model. The agreement between manual and automated methods was assessed using the intraclass correlation coefficient (ICC) and Kappa statistic. We found that MIDAS had generally moderate to good agreement with the manual reference method for the presence of lobar microbleeds (Kappa = 0.43, improved to 0.65 after manual exclusion of obvious artefacts). Agreement for the number of microbleeds was very good for lobar regions: (ICC = 0.71, improved to ICC = 0.87). MIDAS successfully detected all patients with multiple (≥2) lobar microbleeds. MIDAS can identify microbleeds on standard MR datasets, and with an additional rapid editing step shows good agreement with a validated visual rating system. MIDAS may be useful in screening for multiple lobar microbleeds.

Molecular Detection of Bladder Cancer by Fluorescence Microsatellite Analysis and an Automated Genetic Analyzing System

Directory of Open Access Journals (Sweden)

Sarel Halachmi

2007-01-01

Full Text Available To investigate the ability of an automated fluorescent analyzing system to detect microsatellite alterations, in patients with bladder cancer. We investigated 11 with pathology proven bladder Transitional Cell Carcinoma (TCC for microsatellite alterations in blood, urine, and tumor biopsies. DNA was prepared by standard methods from blood, urine and resected tumor specimens, and was used for microsatellite analysis. After the primers were fluorescent labeled, amplification of the DNA was performed with PCR. The PCR products were placed into the automated genetic analyser (ABI Prism 310, Perkin Elmer, USA and were subjected to fluorescent scanning with argon ion laser beams. The fluorescent signal intensity measured by the genetic analyzer measured the product size in terms of base pairs. We found loss of heterozygocity (LOH or microsatellite alterations (a loss or gain of nucleotides, which alter the original normal locus size in all the patients by using fluorescent microsatellite analysis and an automated analyzing system. In each case the genetic changes found in urine samples were identical to those found in the resected tumor sample. The studies demonstrated the ability to detect bladder tumor non-invasively by fluorescent microsatellite analysis of urine samples. Our study supports the worldwide trend for the search of non-invasive methods to detect bladder cancer. We have overcome major obstacles that prevented the clinical use of an experimental system. With our new tested system microsatellite analysis can be done cheaper, faster, easier and with higher scientific accuracy.

Human-automation collaboration in manufacturing: identifying key implementation factors

OpenAIRE

Charalambous, George; Fletcher, Sarah; Webb, Philip

2013-01-01

Human-automation collaboration refers to the concept of human operators and intelligent automation working together interactively within the same workspace without conventional physical separation. This concept has commanded significant attention in manufacturing because of the potential applications, such as the installation of large sub-assemblies. However, the key human factors relevant to human-automation collaboration have not yet been fully investigated. To maximise effective implement...

Automated detection of retinal whitening in malarial retinopathy

Science.gov (United States)

Joshi, V.; Agurto, C.; Barriga, S.; Nemeth, S.; Soliz, P.; MacCormick, I.; Taylor, T.; Lewallen, S.; Harding, S.

2016-03-01

Cerebral malaria (CM) is a severe neurological complication associated with malarial infection. Malaria affects approximately 200 million people worldwide, and claims 600,000 lives annually, 75% of whom are African children under five years of age. Because most of these mortalities are caused by the high incidence of CM misdiagnosis, there is a need for an accurate diagnostic to confirm the presence of CM. The retinal lesions associated with malarial retinopathy (MR) such as retinal whitening, vessel discoloration, and hemorrhages, are highly specific to CM, and their detection can improve the accuracy of CM diagnosis. This paper will focus on development of an automated method for the detection of retinal whitening which is a unique sign of MR that manifests due to retinal ischemia resulting from CM. We propose to detect the whitening region in retinal color images based on multiple color and textural features. First, we preprocess the image using color and textural features of the CMYK and CIE-XYZ color spaces to minimize camera reflex. Next, we utilize color features of the HSL, CMYK, and CIE-XYZ channels, along with the structural features of difference of Gaussians. A watershed segmentation algorithm is used to assign each image region a probability of being inside the whitening, based on extracted features. The algorithm was applied to a dataset of 54 images (40 with whitening and 14 controls) that resulted in an image-based (binary) classification with an AUC of 0.80. This provides 88% sensitivity at a specificity of 65%. For a clinical application that requires a high specificity setting, the algorithm can be tuned to a specificity of 89% at a sensitivity of 82%. This is the first published method for retinal whitening detection and combining it with the detection methods for vessel discoloration and hemorrhages can further improve the detection accuracy for malarial retinopathy.

The development of a fully automated radioimmunoassay instrument - micromedic systems concept 4

International Nuclear Information System (INIS)

Painter, K.

1977-01-01

The fully automatic RIA system Concept 4 by Micromedic is described in detail. The system uses antibody-coated test tubes to take up the samples. It has a maximum capacity of 200 tubes including standards and control tubes. Its advantages are, in particular, high flow rate, reproducibility, and fully automatic testing i.e. low personnel requirements. Its disadvantage are difficulties in protein assays. (ORU) [de

Automated multi-lesion detection for referable diabetic retinopathy in indigenous health care.

Directory of Open Access Journals (Sweden)

Ramon Pires

Full Text Available Diabetic Retinopathy (DR is a complication of diabetes mellitus that affects more than one-quarter of the population with diabetes, and can lead to blindness if not discovered in time. An automated screening enables the identification of patients who need further medical attention. This study aimed to classify retinal images of Aboriginal and Torres Strait Islander peoples utilizing an automated computer-based multi-lesion eye screening program for diabetic retinopathy. The multi-lesion classifier was trained on 1,014 images from the São Paulo Eye Hospital and tested on retinal images containing no DR-related lesion, single lesions, or multiple types of lesions from the Inala Aboriginal and Torres Strait Islander health care centre. The automated multi-lesion classifier has the potential to enhance the efficiency of clinical practice delivering diabetic retinopathy screening. Our program does not necessitate image samples for training from any specific ethnic group or population being assessed and is independent of image pre- or post-processing to identify retinal lesions. In this Aboriginal and Torres Strait Islander population, the program achieved 100% sensitivity and 88.9% specificity in identifying bright lesions, while detection of red lesions achieved a sensitivity of 67% and specificity of 95%. When both bright and red lesions were present, 100% sensitivity with 88.9% specificity was obtained. All results obtained with this automated screening program meet WHO standards for diabetic retinopathy screening.

Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging.

Science.gov (United States)

Patel, Tapan P; Man, Karen; Firestein, Bonnie L; Meaney, David F

2015-03-30

Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s-1000+neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. Copyright © 2015. Published by Elsevier B.V.

Automated detection of microaneurysms using robust blob descriptors

Science.gov (United States)

Adal, K.; Ali, S.; Sidibé, D.; Karnowski, T.; Chaum, E.; Mériaudeau, F.

2013-03-01

Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fundus images. Then, Hessian-based candidate selection algorithm is applied to extract image regions which are more likely to be MAs. For each candidate region, robust low-level blob descriptors such as Speeded Up Robust Features (SURF) and Intensity Normalized Radon Transform are extracted to characterize candidate MA regions. The combined features are then classified using SVM which has been trained using ten manually annotated training images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. Preliminary results show the competitiveness of the proposed candidate selection techniques against state-of-the art methods as well as the promising future for the proposed descriptors to be used in the localization of MAs from fundus images.

Automated lung module detection at low-dose CT: preliminary experience

International Nuclear Information System (INIS)

Goo, Jin-Mo; Lee, Jeong-Won; Lee, Hyun-Ju; Kim, Seung-Wan; Kim, Jong-Hyo; Im, Jung-Gi

2003-01-01

To determine the usefulness of a computer-aided diagnosis (CAD) system for the automated detection of lung nodules at low-dose CT. A CAD system developed for detecting lung nodules was used to process the data provided by 50 consecutive low-dose CT scans. The results of an initial report, a second look review by two chest radiologists, and those obtained by the CAD system were compared, and by reviewing all of these, a gold standard was established. By applying the gold standard, a total of 52 nodules were identified (26 with a diameter ≤ 5 mm; 26 with a diameter > 5 mm). Compared to an initial report, four additional nodules were detected by the CAD system. Three of these, identified only at CAD, formed part of the data used to derive the gold standard. For the detection of nodules > 5 mm in diameter, sensitivity was 77% for the initial report, for the second look review, and 88% for the second look review,and 65% for the CAD system. There were 8.0 ± 5.2 false-positive CAD results per CT study. These preliminary results indicate that a CAD system may improve the detection of pulmonary nodules at low-dose CT

The MMP inhibitor (R)-2-(N-benzyl-4-(2-[18F]fluoroethoxy)phenylsulphonamido) -N-hydroxy-3-methylbutanamide: Improved precursor synthesis and fully automated radiosynthesis

International Nuclear Information System (INIS)

Wagner, Stefan; Faust, Andreas; Breyholz, Hans-Joerg; Schober, Otmar; Schaefers, Michael; Kopka, Klaus

2011-01-01

Summary: The CGS 25966 derivative (R)-2-(N-Benzyl-4-(2-[ 18 F]fluoroethoxy)phenyl-sulphonamido) -N-hydroxy-3-methylbutanamide [ 18 F]9 represents a very potent radiolabelled matrix metalloproteinase inhibitor. For first human PET studies it is mandatory to have a fully automated radiosynthesis and a straightforward precursor synthesis available. The realisation of both requirements is reported herein. In particular, the corresponding precursor 8 was obtained in a reliable 7 step synthesis with an overall chemical yield of 2.3%. Furthermore, the target compound [ 18 F]9 was prepared with a radiochemical yield of 14.8±3.9% (not corrected for decay).

SU-G-201-03: Automation of High Dose Rate Brachytherapy Quality Assurance: Development of a Radioluminescent Detection System for Simultaneous Detection of Activity, Timing, and Positioning

Energy Technology Data Exchange (ETDEWEB)

Jenkins, C; Xing, L; Fahimian, B [Stanford University, Stanford, CA (United States)

2016-06-15

Purpose: Accuracy of positioning, timing and activity is of critical importance for High Dose Rate (HDR) brachytherapy delivery. Respective measurements via film autoradiography, stop-watches and well chambers can be cumbersome, crude or lack dynamic source evaluation capabilities. To address such limitations, a single device radioluminescent detection system enabling automated real-time quantification of activity, position and timing accuracy is presented and experimentally evaluated. Methods: A radioluminescent sheet was fabricated by mixing Gd?O?S:Tb with PDMS and incorporated into a 3D printed device where it was fixated below a CMOS digital camera. An Ir-192 HDR source (VS2000, VariSource iX) with an effective active length of 5 mm was introduced using a 17-gauge stainless steel needle below the sheet. Pixel intensity values for determining activity were taken from an ROI centered on the source location. A calibration curve relating intensity values to activity was generated and used to evaluate automated activity determination with data gathered over 6 weeks. Positioning measurements were performed by integrating images for an entire delivery and fitting peaks to the resulting profile. Timing measurements were performed by evaluating source location and timestamps from individual images. Results: Average predicted activity error over 6 weeks was .35 ± .5%. The distance between four dwell positions was determined by the automated system to be 1.99 ± .02 cm. The result from autoradiography was 2.00 ± .03 cm. The system achieved a time resolution of 10 msec and determined the dwell time to be 1.01 sec ± .02 sec. Conclusion: The system was able to successfully perform automated detection of activity, positioning and timing concurrently under a single setup. Relative to radiochromic and radiographic film-based autoradiography, which can only provide a static evaluation positioning, optical detection of temporary radiation induced luminescence enables dynamic

Digital tripwire: a small automated human detection system

Science.gov (United States)

Fischer, Amber D.; Redd, Emmett; Younger, A. Steven

2009-05-01

A low cost, lightweight, easily deployable imaging sensor that can dependably discriminate threats from other activities within its field of view and, only then, alert the distant duty officer by transmitting a visual confirmation of the threat would provide a valuable asset to modern defense. At present, current solutions suffer from a multitude of deficiencies - size, cost, power endurance, but most notably, an inability to assess an image and conclude that it contains a threat. The human attention span cannot maintain critical surveillance over banks of displays constantly conveying such images from the field. DigitalTripwire is a small, self-contained, automated human-detection system capable of running for 1-5 days on two AA batteries. To achieve such long endurance, the DigitalTripwire system utilizes an FPGA designed with sleep functionality. The system uses robust vision algorithms, such as a partially unsupervised innovative backgroundmodeling algorithm, which employ several data reduction strategies to operate in real-time, and achieve high detection rates. When it detects human activity, either mounted or dismounted, it sends an alert including images to notify the command center. In this paper, we describe the hardware and software design of the DigitalTripwire system. In addition, we provide detection and false alarm rates across several challenging data sets demonstrating the performance of the vision algorithms in autonomously analyzing the video stream and classifying moving objects into four primary categories - dismounted human, vehicle, non-human, or unknown. Performance results across several challenging data sets are provided.

Automated brightfield dual-color in situ hybridization for detection of mouse double minute 2 gene amplification in sarcomas.

Science.gov (United States)

Zhang, Wenjun; McElhinny, Abigail; Nielsen, Alma; Wang, Maria; Miller, Melanie; Singh, Shalini; Rueger, Ruediger; Rubin, Brian P; Wang, Zhen; Tubbs, Raymond R; Nagle, Raymond B; Roche, Pat; Wu, Ping; Pestic-Dragovich, Lidija

2011-01-01

The human homolog of the mouse double minute 2 (MDM2) oncogene is amplified in about 20% of sarcomas. The measurement of the MDM2 amplification can aid in classification and may provide a predictive value for recently formulated therapies targeting MDM2. We have developed and validated an automated bright field dual-color in situ hybridization application to detect MDM2 gene amplification. A repeat-depleted MDM2 probe was constructed to target the MDM2 gene region at 12q15. A chromosome 12-specific probe (CHR12) was generated from a pα12H8 plasmid. The in situ hybridization assay was developed by using a dinitrophenyl-labeled MDM2 probe and a digoxigenin-labeled CHR12 probe on the Ventana Medical Systems' automated slide-staining platforms. The specificity of the MDM2 and CHR12 probes was shown on metaphase spreads and further validated against controls, including normal human tonsil and known MDM2-amplified samples. The assay performance was evaluated on a cohort of 100 formalin-fixed, paraffin-embedded specimens by using a conventional bright field microscope. Simultaneous hybridization and signal detection for MDM2 and CHR12 showed that both DNA targets were present in the same cells. One hundred soft tissue specimens were stained for MDM2 and CHR12. Although 26 of 29 lipomas were nonamplified and eusomic, MDM2 amplification was noted in 78% of atypical lipomatous tumors or well-differentiated liposarcomas. Five of 6 dedifferentiated liposarcoma cases were amplified for MDM2. MDM2 amplification was observed in 1 of 8 osteosarcomas; 3 showed CHR12 aneusomy. MDM2 amplification was present in 1 of 4 chondrosarcomas. Nine of 10 synovial sarcomas displayed no evidence of MDM2 amplification in most tumor cells. In pleomorphic sarcoma, not otherwise specified (pleomorphic malignant fibrous histiocytoma), MDM2 was amplified in 38% of cases, whereas 92% were aneusomic for CHR12. One alveolar rhabdomyosarcoma and 2 embryonal rhabdomyosarcomas displayed low-level aneusomy

Sensitivity of hemozoin detection by automated flow cytometry in non- and semi-immune malaria patients

NARCIS (Netherlands)

Grobusch, Martin P.; Hänscheid, Thomas; Krämer, Benedikt; Neukammer, Jörg; May, Jürgen; Seybold, Joachim; Kun, Jürgen F. J.; Suttorp, Norbert

2003-01-01

BACKGROUND: Cell-Dyn automated blood cell analyzers use laser flow cytometry technology, allowing detection of malaria pigment (hemozoin) in monocytes. We evaluated the value of such an instrument to diagnose malaria in febrile travelers returning to Berlin, Germany, the relation between the

Automated surveillance of healthcare-associated infections : state of the art

NARCIS (Netherlands)

Sips, Meander E; Bonten, Marc J M; van Mourik, Maaike S M

PURPOSE OF REVIEW: This review describes recent advances in the field of automated surveillance of healthcare-associated infections (HAIs), with a focus on data sources and the development of semiautomated or fully automated algorithms. RECENT FINDINGS: The availability of high-quality data in

Automated night/day standoff detection, tracking, and identification of personnel for installation protection

Science.gov (United States)

Lemoff, Brian E.; Martin, Robert B.; Sluch, Mikhail; Kafka, Kristopher M.; McCormick, William; Ice, Robert

2013-06-01

The capability to positively and covertly identify people at a safe distance, 24-hours per day, could provide a valuable advantage in protecting installations, both domestically and in an asymmetric warfare environment. This capability would enable installation security officers to identify known bad actors from a safe distance, even if they are approaching under cover of darkness. We will describe an active-SWIR imaging system being developed to automatically detect, track, and identify people at long range using computer face recognition. The system illuminates the target with an eye-safe and invisible SWIR laser beam, to provide consistent high-resolution imagery night and day. SWIR facial imagery produced by the system is matched against a watch-list of mug shots using computer face recognition algorithms. The current system relies on an operator to point the camera and to review and interpret the face recognition results. Automation software is being developed that will allow the system to be cued to a location by an external system, automatically detect a person, track the person as they move, zoom in on the face, select good facial images, and process the face recognition results, producing alarms and sharing data with other systems when people are detected and identified. Progress on the automation of this system will be presented along with experimental night-time face recognition results at distance.

AuTom: a novel automatic platform for electron tomography reconstruction

KAUST Repository

Han, Renmin

2017-07-26

We have developed a software package towards automatic electron tomography (ET): Automatic Tomography (AuTom). The presented package has the following characteristics: accurate alignment modules for marker-free datasets containing substantial biological structures; fully automatic alignment modules for datasets with fiducial markers; wide coverage of reconstruction methods including a new iterative method based on the compressed-sensing theory that suppresses the “missing wedge” effect; and multi-platform acceleration solutions that support faster iterative algebraic reconstruction. AuTom aims to achieve fully automatic alignment and reconstruction for electron tomography and has already been successful for a variety of datasets. AuTom also offers user-friendly interface and auxiliary designs for file management and workflow management, in which fiducial marker-based datasets and marker-free datasets are addressed with totally different subprocesses. With all of these features, AuTom can serve as a convenient and effective tool for processing in electron tomography.

Integrating Test-Form Formatting into Automated Test Assembly

Science.gov (United States)

Diao, Qi; van der Linden, Wim J.

2013-01-01

Automated test assembly uses the methodology of mixed integer programming to select an optimal set of items from an item bank. Automated test-form generation uses the same methodology to optimally order the items and format the test form. From an optimization point of view, production of fully formatted test forms directly from the item pool using…

Detection of weed locations in leaf occluded cereal crops using a fully convolutional neural network

DEFF Research Database (Denmark)

Dyrmann, Mads; Nyholm Jørgensen, Rasmus; Midtiby, Henrik Skov

2017-01-01

This pap er presents a metho d for au tomating weed detectio n in colour images despite heavy lea f occlusion. A fully convolu tio n al neural network is used to detect the weed s. The netwo rk is trained and validated on a tot al of more than 17,000 ann otations of w eeds in images from wint er w...

A nationwide web-based automated system for early outbreak detection and rapid response in China

Directory of Open Access Journals (Sweden)

Yilan Liao

2011-03-01

Full Text Available Timely reporting, effective analyses and rapid distribution of surveillance data can assist in detecting the aberration of disease occurrence and further facilitate a timely response. In China, a new nationwide web-based automated system for outbreak detection and rapid response was developed in 2008. The China Infectious Disease Automated-alert and Response System (CIDARS was developed by the Chinese Center for Disease Control and Prevention based on the surveillance data from the existing electronic National Notifiable Infectious Diseases Reporting Information System (NIDRIS started in 2004. NIDRIS greatly improved the timeliness and completeness of data reporting with real time reporting information via the Internet. CIDARS further facilitates the data analysis, aberration detection, signal dissemination, signal response and information communication needed by public health departments across the country. In CIDARS, three aberration detection methods are used to detect the unusual occurrence of 28 notifiable infectious diseases at the county level and to transmit that information either in real-time or on a daily basis. The Internet, computers and mobile phones are used to accomplish rapid signal generation and dissemination, timely reporting and reviewing of the signal response results. CIDARS has been used nationwide since 2008; all Centers for Disease Control and Prevention (CDC in China at the county, prefecture, provincial and national levels are involved in the system. It assists with early outbreak detection at the local level and prompts reporting of unusual disease occurrences or potential outbreaks to CDCs throughout the country.

Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin

Directory of Open Access Journals (Sweden)

Mohsen Ghafoorian

2017-01-01

In this paper, we propose an automated two-stage method using deep convolutional neural networks (CNN. We show that this method has good performance and can considerably benefit readers. We first use a fully convolutional neural network to detect initial candidates. In the second step, we employ a 3D CNN as a false positive reduction tool. As the location information is important to the analysis of candidate structures, we further equip the network with contextual information using multi-scale analysis and integration of explicit location features. We trained, validated and tested our networks on a large dataset of 1075 cases obtained from two different studies. Subsequently, we conducted an observer study with four trained observers and compared our method with them using a free-response operating characteristic analysis. Shown on a test set of 111 cases, the resulting CAD system exhibits performance similar to the trained human observers and achieves a sensitivity of 0.974 with 0.13 false positives per slice. A feasibility study also showed that a trained human observer would considerably benefit once aided by the CAD system.

Intelligent Machine Vision for Automated Fence Intruder Detection Using Self-organizing Map

OpenAIRE

Veldin A. Talorete Jr.; Sherwin A Guirnaldo

2017-01-01

This paper presents an intelligent machine vision for automated fence intruder detection. A series of still captured images that contain fence events using Internet Protocol cameras was used as input data to the system. Two classifiers were used; the first is to classify human posture and the second one will classify intruder location. The system classifiers were implemented using Self-Organizing Map after the implementation of several image segmentation processes. The human posture classifie...

Medical ADP Systems: Automated Medical Records Hold Promise to Improve Patient Care

Science.gov (United States)

1991-01-01

automated medical records. The report discusses the potential benefits that automation could make to the quality of patient care and the factors that impede...information systems, but no organization has fully automated one of the most critical types of information, patient medical records. The patient medical record...its review of automated medical records. GAO’s objectives in this study were to identify the (1) benefits of automating patient records and (2) factors

Twelve automated thresholding methods for segmentation of PET images: a phantom study

International Nuclear Information System (INIS)

Prieto, Elena; Peñuelas, Iván; Martí-Climent, Josep M; Lecumberri, Pablo; Gómez, Marisol; Pagola, Miguel; Bilbao, Izaskun; Ecay, Margarita

2012-01-01

Tumor volume delineation over positron emission tomography (PET) images is of great interest for proper diagnosis and therapy planning. However, standard segmentation techniques (manual or semi-automated) are operator dependent and time consuming while fully automated procedures are cumbersome or require complex mathematical development. The aim of this study was to segment PET images in a fully automated way by implementing a set of 12 automated thresholding algorithms, classical in the fields of optical character recognition, tissue engineering or non-destructive testing images in high-tech structures. Automated thresholding algorithms select a specific threshold for each image without any a priori spatial information of the segmented object or any special calibration of the tomograph, as opposed to usual thresholding methods for PET. Spherical 18 F-filled objects of different volumes were acquired on clinical PET/CT and on a small animal PET scanner, with three different signal-to-background ratios. Images were segmented with 12 automatic thresholding algorithms and results were compared with the standard segmentation reference, a threshold at 42% of the maximum uptake. Ridler and Ramesh thresholding algorithms based on clustering and histogram-shape information, respectively, provided better results that the classical 42%-based threshold (p < 0.05). We have herein demonstrated that fully automated thresholding algorithms can provide better results than classical PET segmentation tools. (paper)

Robotic and nuclear safety for an automated/teleoperated glove box system

International Nuclear Information System (INIS)

Domning, E.E.; McMahon, T.T.; Sievers, R.H.

1991-09-01

Lawrence Livermore National Laboratory (LLNL) is developing a fully automated system to handle the processing of special nuclear materials (SNM). This work is performed in response to the new goals at the Department of Energy (DOE) for hazardous waste minimization and radiation dose reduction. This fully automated system, called the automated test bed (ATB), consists of an IBM gantry robot and automated processing equipment sealed within a glove box. While the ATB is a cold system, we are designing it as a prototype of the future hot system. We recognized that identification and application of safety requirements early in the design phase will lead to timely installation and approval of the hot system. This paper identifies these safety issues as well as the general safety requirements necessary for the safe operation of the ATB. 4 refs., 2 figs

[Automated analyzer of enzyme immunoassay].

Science.gov (United States)

Osawa, S

1995-09-01

Automated analyzers for enzyme immunoassay can be classified by several points of view: the kind of labeled antibodies or enzymes, detection methods, the number of tests per unit time, analytical time and speed per run. In practice, it is important for us consider the several points such as detection limits, the number of tests per unit time, analytical range, and precision. Most of the automated analyzers on the market can randomly access and measure samples. I will describe the recent advance of automated analyzers reviewing their labeling antibodies and enzymes, the detection methods, the number of test per unit time and analytical time and speed per test.

Automated analysis for detecting beams in laser wakefield simulations

International Nuclear Information System (INIS)

Ushizima, Daniela M.; Rubel, Oliver; Prabhat, Mr.; Weber, Gunther H.; Bethel, E. Wes; Aragon, Cecilia R.; Geddes, Cameron G.R.; Cormier-Michel, Estelle; Hamann, Bernd; Messmer, Peter; Hagen, Hans

2008-01-01

Laser wakefield particle accelerators have shown the potential to generate electric fields thousands of times higher than those of conventional accelerators. The resulting extremely short particle acceleration distance could yield a potential new compact source of energetic electrons and radiation, with wide applications from medicine to physics. Physicists investigate laser-plasma internal dynamics by running particle-in-cell simulations; however, this generates a large dataset that requires time-consuming, manual inspection by experts in order to detect key features such as beam formation. This paper describes a framework to automate the data analysis and classification of simulation data. First, we propose a new method to identify locations with high density of particles in the space-time domain, based on maximum extremum point detection on the particle distribution. We analyze high density electron regions using a lifetime diagram by organizing and pruning the maximum extrema as nodes in a minimum spanning tree. Second, we partition the multivariate data using fuzzy clustering to detect time steps in a experiment that may contain a high quality electron beam. Finally, we combine results from fuzzy clustering and bunch lifetime analysis to estimate spatially confined beams. We demonstrate our algorithms successfully on four different simulation datasets

Vertebral Body Compression Fractures and Bone Density: Automated Detection and Classification on CT Images.

Science.gov (United States)

Burns, Joseph E; Yao, Jianhua; Summers, Ronald M

2017-09-01

Purpose To create and validate a computer system with which to detect, localize, and classify compression fractures and measure bone density of thoracic and lumbar vertebral bodies on computed tomographic (CT) images. Materials and Methods Institutional review board approval was obtained, and informed consent was waived in this HIPAA-compliant retrospective study. A CT study set of 150 patients (mean age, 73 years; age range, 55-96 years; 92 women, 58 men) with (n = 75) and without (n = 75) compression fractures was assembled. All case patients were age and sex matched with control subjects. A total of 210 thoracic and lumbar vertebrae showed compression fractures and were electronically marked and classified by a radiologist. Prototype fully automated spinal segmentation and fracture detection software were then used to analyze the study set. System performance was evaluated with free-response receiver operating characteristic analysis. Results Sensitivity for detection or localization of compression fractures was 95.7% (201 of 210; 95% confidence interval [CI]: 87.0%, 98.9%), with a false-positive rate of 0.29 per patient. Additionally, sensitivity was 98.7% and specificity was 77.3% at case-based receiver operating characteristic curve analysis. Accuracy for classification by Genant type (anterior, middle, or posterior height loss) was 0.95 (107 of 113; 95% CI: 0.89, 0.98), with weighted κ of 0.90 (95% CI: 0.81, 0.99). Accuracy for categorization by Genant height loss grade was 0.68 (77 of 113; 95% CI: 0.59, 0.76), with a weighted κ of 0.59 (95% CI: 0.47, 0.71). The average bone attenuation for T12-L4 vertebrae was 146 HU ± 29 (standard deviation) in case patients and 173 HU ± 42 in control patients; this difference was statistically significant (P high sensitivity and with a low false-positive rate, as well as to calculate vertebral bone density, on CT images. © RSNA, 2017 Online supplemental material is available for this article.

Application of Novel Software Algorithms to Spectral-Domain Optical Coherence Tomography for Automated Detection of Diabetic Retinopathy.

Science.gov (United States)

Adhi, Mehreen; Semy, Salim K; Stein, David W; Potter, Daniel M; Kuklinski, Walter S; Sleeper, Harry A; Duker, Jay S; Waheed, Nadia K

2016-05-01

To present novel software algorithms applied to spectral-domain optical coherence tomography (SD-OCT) for automated detection of diabetic retinopathy (DR). Thirty-one diabetic patients (44 eyes) and 18 healthy, nondiabetic controls (20 eyes) who underwent volumetric SD-OCT imaging and fundus photography were retrospectively identified. A retina specialist independently graded DR stage. Trained automated software generated a retinal thickness score signifying macular edema and a cluster score signifying microaneurysms and/or hard exudates for each volumetric SD-OCT. Of 44 diabetic eyes, 38 had DR and six eyes did not have DR. Leave-one-out cross-validation using a linear discriminant at missed detection/false alarm ratio of 3.00 computed software sensitivity and specificity of 92% and 69%, respectively, for DR detection when compared to clinical assessment. Novel software algorithms applied to commercially available SD-OCT can successfully detect DR and may have potential as a viable screening tool for DR in future. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:410-417.]. Copyright 2016, SLACK Incorporated.

SAMPO 90 high resolution interactive gamma-spectrum analysis including automation with macros

International Nuclear Information System (INIS)

Aarnio, P.A.; Nikkinen, M.T.; Routti, J.T.

1992-01-01

SAMPO 90 is high performance gamma-spectrum analysis program for personal computers. It uses color graphics to display calibrations, spectra, fitting results as multiplet components, and analysis results. All the analysis phases can be done either under full interactive user control or macros and programmable function keys can be used for completely automated measurement and analysis sequences including the control of MACs and sample changers. Accurate peak area determination of even the most complex multiplets, of up to 32 components, is accomplished using linear and mixed mode fitting. Nuclide identification is done using associated lines techniques allowing interference correction for fully overlapping peaks. Peaked Background Subtraction can be performed and Minimum Detectable Activities calculated. The analysis reports and program parameters are fully customizable. (author) 13 refs.; 1 fig

Pedestrian detection in video surveillance using fully convolutional YOLO neural network

Science.gov (United States)

Molchanov, V. V.; Vishnyakov, B. V.; Vizilter, Y. V.; Vishnyakova, O. V.; Knyaz, V. A.

2017-06-01

More than 80% of video surveillance systems are used for monitoring people. Old human detection algorithms, based on background and foreground modelling, could not even deal with a group of people, to say nothing of a crowd. Recent robust and highly effective pedestrian detection algorithms are a new milestone of video surveillance systems. Based on modern approaches in deep learning, these algorithms produce very discriminative features that can be used for getting robust inference in real visual scenes. They deal with such tasks as distinguishing different persons in a group, overcome problem with sufficient enclosures of human bodies by the foreground, detect various poses of people. In our work we use a new approach which enables to combine detection and classification tasks into one challenge using convolution neural networks. As a start point we choose YOLO CNN, whose authors propose a very efficient way of combining mentioned above tasks by learning a single neural network. This approach showed competitive results with state-of-the-art models such as FAST R-CNN, significantly overcoming them in speed, which allows us to apply it in real time video surveillance and other video monitoring systems. Despite all advantages it suffers from some known drawbacks, related to the fully-connected layers that obstruct applying the CNN to images with different resolution. Also it limits the ability to distinguish small close human figures in groups which is crucial for our tasks since we work with rather low quality images which often include dense small groups of people. In this work we gradually change network architecture to overcome mentioned above problems, train it on a complex pedestrian dataset and finally get the CNN detecting small pedestrians in real scenes.

Developing an Automated Machine Learning Marine Oil Spill Detection System with Synthetic Aperture Radar

Science.gov (United States)

Pinales, J. C.; Graber, H. C.; Hargrove, J. T.; Caruso, M. J.

2016-02-01

Previous studies have demonstrated the ability to detect and classify marine hydrocarbon films with spaceborne synthetic aperture radar (SAR) imagery. The dampening effects of hydrocarbon discharges on small surface capillary-gravity waves renders the ocean surface "radar dark" compared with the standard wind-borne ocean surfaces. Given the scope and impact of events like the Deepwater Horizon oil spill, the need for improved, automated and expedient monitoring of hydrocarbon-related marine anomalies has become a pressing and complex issue for governments and the extraction industry. The research presented here describes the development, training, and utilization of an algorithm that detects marine oil spills in an automated, semi-supervised manner, utilizing X-, C-, or L-band SAR data as the primary input. Ancillary datasets include related radar-borne variables (incidence angle, etc.), environmental data (wind speed, etc.) and textural descriptors. Shapefiles produced by an experienced human-analyst served as targets (validation) during the training portion of the investigation. Training and testing datasets were chosen for development and assessment of algorithm effectiveness as well as optimal conditions for oil detection in SAR data. The algorithm detects oil spills by following a 3-step methodology: object detection, feature extraction, and classification. Previous oil spill detection and classification methodologies such as machine learning algorithms, artificial neural networks (ANN), and multivariate classification methods like partial least squares-discriminant analysis (PLS-DA) are evaluated and compared. Statistical, transform, and model-based image texture techniques, commonly used for object mapping directly or as inputs for more complex methodologies, are explored to determine optimal textures for an oil spill detection system. The influence of the ancillary variables is explored, with a particular focus on the role of strong vs. weak wind forcing.

Automatic laser beam alignment using blob detection for an environment monitoring spectroscopy

Science.gov (United States)

Khidir, Jarjees; Chen, Youhua; Anderson, Gary

2013-05-01

This paper describes a fully automated system to align an infra-red laser beam with a small retro-reflector over a wide range of distances. The component development and test were especially used for an open-path spectrometer gas detection system. Using blob detection under OpenCV library, an automatic alignment algorithm was designed to achieve fast and accurate target detection in a complex background environment. Test results are presented to show that the proposed algorithm has been successfully applied to various target distances and environment conditions.

AMSNEXRAD-Automated detection of meteorite strewnfields in doppler weather radar

Science.gov (United States)

Hankey, Michael; Fries, Marc; Matson, Rob; Fries, Jeff

2017-09-01

For several years meteorite recovery in the United States has been greatly enhanced by using Doppler weather radar images to determine possible fall zones for meteorites produced by witnessed fireballs. While most fireball events leave no record on the Doppler radar, some large fireballs do. Based on the successful recovery of 10 meteorite falls 'under the radar', and the discovery of radar on more than 10 historic falls, it is believed that meteoritic dust and or actual meteorites falling to the ground have been recorded on Doppler weather radar (Fries et al., 2014). Up until this point, the process of detecting the radar signatures associated with meteorite falls has been a manual one and dependent on prior accurate knowledge of the fall time and estimated ground track. This manual detection process is labor intensive and can take several hours per event. Recent technological developments by NOAA now help enable the automation of these tasks. This in combination with advancements by the American Meteor Society (Hankey et al., 2014) in the tracking and plotting of witnessed fireballs has opened the possibility for automatic detection of meteorites in NEXRAD Radar Archives. Here in the processes for fireball triangulation, search area determination, radar interfacing, data extraction, storage, search, detection and plotting are explained.

Development of Raman microspectroscopy for automated detection and imaging of basal cell carcinoma

Science.gov (United States)

Larraona-Puy, Marta; Ghita, Adrian; Zoladek, Alina; Perkins, William; Varma, Sandeep; Leach, Iain H.; Koloydenko, Alexey A.; Williams, Hywel; Notingher, Ioan

2009-09-01

We investigate the potential of Raman microspectroscopy (RMS) for automated evaluation of excised skin tissue during Mohs micrographic surgery (MMS). The main aim is to develop an automated method for imaging and diagnosis of basal cell carcinoma (BCC) regions. Selected Raman bands responsible for the largest spectral differences between BCC and normal skin regions and linear discriminant analysis (LDA) are used to build a multivariate supervised classification model. The model is based on 329 Raman spectra measured on skin tissue obtained from 20 patients. BCC is discriminated from healthy tissue with 90+/-9% sensitivity and 85+/-9% specificity in a 70% to 30% split cross-validation algorithm. This multivariate model is then applied on tissue sections from new patients to image tumor regions. The RMS images show excellent correlation with the gold standard of histopathology sections, BCC being detected in all positive sections. We demonstrate the potential of RMS as an automated objective method for tumor evaluation during MMS. The replacement of current histopathology during MMS by a ``generalization'' of the proposed technique may improve the feasibility and efficacy of MMS, leading to a wider use according to clinical need.

Comparison of manual & automated analysis methods for corneal endothelial cell density measurements by specular microscopy.

Science.gov (United States)

Huang, Jianyan; Maram, Jyotsna; Tepelus, Tudor C; Modak, Cristina; Marion, Ken; Sadda, SriniVas R; Chopra, Vikas; Lee, Olivia L

2017-08-07

To determine the reliability of corneal endothelial cell density (ECD) obtained by automated specular microscopy versus that of validated manual methods and factors that predict such reliability. Sharp central images from 94 control and 106 glaucomatous eyes were captured with Konan specular microscope NSP-9900. All images were analyzed by trained graders using Konan CellChek Software, employing the fully- and semi-automated methods as well as Center Method. Images with low cell count (input cells number <100) and/or guttata were compared with the Center and Flex-Center Methods. ECDs were compared and absolute error was used to assess variation. The effect on ECD of age, cell count, cell size, and cell size variation was evaluated. No significant difference was observed between the Center and Flex-Center Methods in corneas with guttata (p=0.48) or low ECD (p=0.11). No difference (p=0.32) was observed in ECD of normal controls <40 yrs old between the fully-automated method and manual Center Method. However, in older controls and glaucomatous eyes, ECD was overestimated by the fully-automated method (p=0.034) and semi-automated method (p=0.025) as compared to manual method. Our findings show that automated analysis significantly overestimates ECD in the eyes with high polymegathism and/or large cell size, compared to the manual method. Therefore, we discourage reliance upon the fully-automated method alone to perform specular microscopy analysis, particularly if an accurate ECD value is imperative. Copyright © 2017. Published by Elsevier España, S.L.U.

Automated approach to detecting behavioral states using EEG-DABS

Directory of Open Access Journals (Sweden)

Zachary B. Loris

2017-07-01

Full Text Available Electrocorticographic (ECoG signals represent cortical electrical dipoles generated by synchronous local field potentials that result from simultaneous firing of neurons at distinct frequencies (brain waves. Since different brain waves correlate to different behavioral states, ECoG signals presents a novel strategy to detect complex behaviors. We developed a program, EEG Detection Analysis for Behavioral States (EEG-DABS that advances Fast Fourier Transforms through ECoG signals time series, separating it into (user defined frequency bands and normalizes them to reduce variability. EEG-DABS determines events if segments of an experimental ECoG record have significantly different power bands than a selected control pattern of EEG. Events are identified at every epoch and frequency band and then are displayed as output graphs by the program. Certain patterns of events correspond to specific behaviors. Once a predetermined pattern was selected for a behavioral state, EEG-DABS correctly identified the desired behavioral event. The selection of frequency band combinations for detection of the behavior affects accuracy of the method. All instances of certain behaviors, such as freezing, were correctly identified from the event patterns generated with EEG-DABS. Detecting behaviors is typically achieved by visually discerning unique animal phenotypes, a process that is time consuming, unreliable, and subjective. EEG-DABS removes variability by using defined parameters of EEG/ECoG for a desired behavior over chronic recordings. EEG-DABS presents a simple and automated approach to quantify different behavioral states from ECoG signals.

Intelligent Machine Vision for Automated Fence Intruder Detection Using Self-organizing Map

Directory of Open Access Journals (Sweden)

Veldin A. Talorete Jr.

2017-03-01

Full Text Available This paper presents an intelligent machine vision for automated fence intruder detection. A series of still captured images that contain fence events using Internet Protocol cameras was used as input data to the system. Two classifiers were used; the first is to classify human posture and the second one will classify intruder location. The system classifiers were implemented using Self-Organizing Map after the implementation of several image segmentation processes. The human posture classifier is in charge of classifying the detected subject’s posture patterns from subject’s silhouette. Moreover, the Intruder Localization Classifier is in charge of classifying the detected pattern’s location classifier will estimate the location of the intruder with respect to the fence using geometric feature from images as inputs. The system is capable of activating the alarm, display the actual image and depict the location of the intruder when an intruder is detected. In detecting intruder posture, the system’s success rate of 88%. Overall system accuracy for day-time intruder localization is 83% and an accuracy of 88% for night-time intruder localization

Comparing a Perceptual and an Automated Vision-Based Method for Lie Detection in Younger Children.

Science.gov (United States)

Serras Pereira, Mariana; Cozijn, Reinier; Postma, Eric; Shahid, Suleman; Swerts, Marc

2016-01-01

The present study investigates how easily it can be detected whether a child is being truthful or not in a game situation, and it explores the cue validity of bodily movements for such type of classification. To achieve this, we introduce an innovative methodology - the combination of perception studies (in which eye-tracking technology is being used) and automated movement analysis. Film fragments from truthful and deceptive children were shown to human judges who were given the task to decide whether the recorded child was being truthful or not. Results reveal that judges are able to accurately distinguish truthful clips from lying clips in both perception studies. Even though the automated movement analysis for overall and specific body regions did not yield significant results between the experimental conditions, we did find a positive correlation between the amount of movement in a child and the perception of lies, i.e., the more movement the children exhibited during a clip, the higher the chance that the clip was perceived as a lie. The eye-tracking study revealed that, even when there is movement happening in different body regions, judges tend to focus their attention mainly on the face region. This is the first study that compares a perceptual and an automated method for the detection of deceptive behavior in children whose data have been elicited through an ecologically valid paradigm.

[Automated detection of estrus and mastitis in dairy cows].

Science.gov (United States)

de Mol, R M

2001-02-15

The development and test of detection models for oestrus and mastitis in dairy cows is described in a PhD thesis that was defended in Wageningen on June 5, 2000. These models were based on sensors for milk yield, milk temperature, electrical conductivity of milk, and cow activity and concentrate intake, and on combined processing of the sensor data. The models alert farmers to cows that need attention, because of possible oestrus or mastitis. A first detection model for cows, milked twice a day, was based on time series models for the sensor variables. A time series model describes the dependence between successive observations. The parameters of the time series models were fitted on-line for each cow after each milking by means of a Kalman filter, a mathematical method to estimate the state of a system on-line. The Kalman filter gives the best estimate of the current state of a system based on all preceding observations. This model was tested for 2 years on two experimental farms, and under field conditions on four farms over several years. A second detection model, for cow milked in an automatic milking system (AMS), was based on a generalization of the first model. Two data sets (one small, one large) were used for testing. The results for oestrus detection were good for both models. The results for mastitis detection were varying (in some cases good, in other cases moderate). Fuzzy logic was used to classify mastitis and oestrus alerts with both detection models, to reduce the number of false positive alerts. Fuzzy logic makes approximate reasoning possible, where statements can be partly true or false. Input for the fuzzy logic model were alerts from the detection models and additional information. The number of false positive alerts decreased considerably, while the number of detected cases remained at the same level. These models make automated detection possible in practice.

Pyrochemical processing automation at Lawrence Livermore National Laboratory

International Nuclear Information System (INIS)

Dennison, D.K.; Domning, E.E.; Seivers, R.

1991-01-01

Lawrence Livermore National Laboratory (LLNL) is developing a fully automated system for pyrochemical processing of special nuclear materials (SNM). The system utilizes a glove box, an automated tilt-pour furnace (TPF), an IBM developed gantry robot, and specialized automation tooling. All material handling within the glove box (i.e., furnace loading, furnace unloading, product and slag separation, and product packaging) is performed automatically. The objectives of the effort are to increase process productivity, decrease operator radiation, reduce process wastes, and demonstrate system reliability and availability. This paper provides an overview of the automated system hardware, outlines the overall operations sequence, and discusses the current status

1st workshop on situational awareness in semi-Automated vehicles

NARCIS (Netherlands)

McCall, R.; Baumann, M.; Politis, I.; Borojeni, S.S.; Alvarez, I.; Mirnig, A.; Meschtscherjakov, A.; Tscheligi, M.; Chuang, L.; Terken, J.M.B.

2016-01-01

This workshop will focus on the problem of occupant and vehicle situational awareness with respect to automated vehicles when the driver must take over control. It will explore the future of fully automated and mixed traffic situations where vehicles are assumed to be operating at level 3 or above.

Automated seismic detection of landslides at regional scales: a Random Forest based detection algorithm

Science.gov (United States)

Hibert, C.; Michéa, D.; Provost, F.; Malet, J. P.; Geertsema, M.

2017-12-01

of continuous seismic record by the Alaskan permanent seismic network and Hi-Climb trans-Himalayan seismic network. The processing chain we developed also opens the possibility for a near-real time seismic detection of landslides, in association with remote-sensing automated detection from Sentinel 2 images for example.

Robust Automated Image Co-Registration of Optical Multi-Sensor Time Series Data: Database Generation for Multi-Temporal Landslide Detection

Directory of Open Access Journals (Sweden)

Robert Behling

2014-03-01

Full Text Available Reliable multi-temporal landslide detection over longer periods of time requires multi-sensor time series data characterized by high internal geometric stability, as well as high relative and absolute accuracy. For this purpose, a new methodology for fully automated co-registration has been developed allowing efficient and robust spatial alignment of standard orthorectified data products originating from a multitude of optical satellite remote sensing data of varying spatial resolution. Correlation-based co-registration uses world-wide available terrain corrected Landsat Level 1T time series data as the spatial reference, ensuring global applicability. The developed approach has been applied to a multi-sensor time series of 592 remote sensing datasets covering an approximately 12,000 km2 area in Southern Kyrgyzstan (Central Asia strongly affected by landslides. The database contains images acquired during the last 26 years by Landsat (ETM, ASTER, SPOT and RapidEye sensors. Analysis of the spatial shifts obtained from co-registration has revealed sensor-specific alignments ranging between 5 m and more than 400 m. Overall accuracy assessment of these alignments has resulted in a high relative image-to-image accuracy of 17 m (RMSE and a high absolute accuracy of 23 m (RMSE for the whole co-registered database, making it suitable for multi-temporal landslide detection at a regional scale in Southern Kyrgyzstan.

A Novel Automated Method for Analyzing Cylindrical Computed Tomography Data

Science.gov (United States)

Roth, D. J.; Burke, E. R.; Rauser, R. W.; Martin, R. E.

2011-01-01

A novel software method is presented that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography. This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2-D sheets in the vertical direction in addition to volume rendering and normal plane views provided by traditional CT software. The method is based on interior and exterior surface edge detection and under proper conditions, is FULLY AUTOMATED and requires no input from the user except the correct voxel dimension from the CT scan. The software is available from NASA in 32- and 64-bit versions that can be applied to gigabyte-sized data sets, processing data either in random access memory or primarily on the computer hard drive. Please inquire with the presenting author if further interested. This software differentiates itself in total from other possible re-slicing software solutions due to complete automation and advanced processing and analysis capabilities.

Electrochemical Detection in Stacked Paper Networks.

Science.gov (United States)

Liu, Xiyuan; Lillehoj, Peter B

2015-08-01

Paper-based electrochemical biosensors are a promising technology that enables rapid, quantitative measurements on an inexpensive platform. However, the control of liquids in paper networks is generally limited to a single sample delivery step. Here, we propose a simple method to automate the loading and delivery of liquid samples to sensing electrodes on paper networks by stacking multiple layers of paper. Using these stacked paper devices (SPDs), we demonstrate a unique strategy to fully immerse planar electrodes by aqueous liquids via capillary flow. Amperometric measurements of xanthine oxidase revealed that electrochemical sensors on four-layer SPDs generated detection signals up to 75% higher compared with those on single-layer paper devices. Furthermore, measurements could be performed with minimal user involvement and completed within 30 min. Due to its simplicity, enhanced automation, and capability for quantitative measurements, stacked paper electrochemical biosensors can be useful tools for point-of-care testing in resource-limited settings. © 2015 Society for Laboratory Automation and Screening.

Fully-Automated High-Throughput NMR System for Screening of Haploid Kernels of Maize (Corn by Measurement of Oil Content.

Directory of Open Access Journals (Sweden)

Hongzhi Wang

Full Text Available One of the modern crop breeding techniques uses doubled haploid plants that contain an identical pair of chromosomes in order to accelerate the breeding process. Rapid haploid identification method is critical for large-scale selections of double haploids. The conventional methods based on the color of the endosperm and embryo seeds are slow, manual and prone to error. On the other hand, there exists a significant difference between diploid and haploid seeds generated by high oil inducer, which makes it possible to use oil content to identify the haploid. This paper describes a fully-automated high-throughput NMR screening system for maize haploid kernel identification. The system is comprised of a sampler unit to select a single kernel to feed for measurement of NMR and weight, and a kernel sorter to distribute the kernel according to the measurement result. Tests of the system show a consistent accuracy of 94% with an average screening time of 4 seconds per kernel. Field test result is described and the directions for future improvement are discussed.

Fully-Automated High-Throughput NMR System for Screening of Haploid Kernels of Maize (Corn) by Measurement of Oil Content

Science.gov (United States)

Xu, Xiaoping; Huang, Qingming; Chen, Shanshan; Yang, Peiqiang; Chen, Shaojiang; Song, Yiqiao

2016-01-01

One of the modern crop breeding techniques uses doubled haploid plants that contain an identical pair of chromosomes in order to accelerate the breeding process. Rapid haploid identification method is critical for large-scale selections of double haploids. The conventional methods based on the color of the endosperm and embryo seeds are slow, manual and prone to error. On the other hand, there exists a significant difference between diploid and haploid seeds generated by high oil inducer, which makes it possible to use oil content to identify the haploid. This paper describes a fully-automated high-throughput NMR screening system for maize haploid kernel identification. The system is comprised of a sampler unit to select a single kernel to feed for measurement of NMR and weight, and a kernel sorter to distribute the kernel according to the measurement result. Tests of the system show a consistent accuracy of 94% with an average screening time of 4 seconds per kernel. Field test result is described and the directions for future improvement are discussed. PMID:27454427

Evaluation of an Automated Analysis Tool for Prostate Cancer Prediction Using Multiparametric Magnetic Resonance Imaging.

Directory of Open Access Journals (Sweden)

Matthias C Roethke

Full Text Available To evaluate the diagnostic performance of an automated analysis tool for the assessment of prostate cancer based on multiparametric magnetic resonance imaging (mpMRI of the prostate.A fully automated analysis tool was used for a retrospective analysis of mpMRI sets (T2-weighted, T1-weighted dynamic contrast-enhanced, and diffusion-weighted sequences. The software provided a malignancy prediction value for each image pixel, defined as Malignancy Attention Index (MAI that can be depicted as a colour map overlay on the original images. The malignancy maps were compared to histopathology derived from a combination of MRI-targeted and systematic transperineal MRI/TRUS-fusion biopsies.In total, mpMRI data of 45 patients were evaluated. With a sensitivity of 85.7% (with 95% CI of 65.4-95.0, a specificity of 87.5% (with 95% CI of 69.0-95.7 and a diagnostic accuracy of 86.7% (with 95% CI of 73.8-93.8 for detection of prostate cancer, the automated analysis results corresponded well with the reported diagnostic accuracies by human readers based on the PI-RADS system in the current literature.The study revealed comparable diagnostic accuracies for the detection of prostate cancer of a user-independent MAI-based automated analysis tool and PI-RADS-scoring-based human reader analysis of mpMRI. Thus, the analysis tool could serve as a detection support system for less experienced readers. The results of the study also suggest the potential of MAI-based analysis for advanced lesion assessments, such as cancer extent and staging prediction.

Automated eddy-current installation AVD-01 for detecting flaws in fuel element cans

International Nuclear Information System (INIS)

Varvaritsa, V.P.; Martishchenko, L.G.; Popov, V.K.; Romanov, M.L.; Shlepnev, I.O.; Shmatok, V.P.

1986-01-01

This paper describes an automated installation for eddy-current flaw detection in thin-walled pipes with small diameter; its unified transport system makes it possible to use the installation in inspection lines and production lines of fuel elements. The article describes the structural diagrams of the installation and presents the results of investigations connected with the selection for establishing the optimum regimes and sensitivity of feedthrough transducers with focusing screens

Fully automated dual-frequency three-pulse-echo 2DIR spectrometer accessing spectral range from 800 to 4000 wavenumbers

Energy Technology Data Exchange (ETDEWEB)

Leger, Joel D.; Nyby, Clara M.; Varner, Clyde; Tang, Jianan; Rubtsova, Natalia I.; Yue, Yuankai; Kireev, Victor V.; Burtsev, Viacheslav D.; Qasim, Layla N.; Rubtsov, Igor V., E-mail: irubtsov@tulane.edu [Department of Chemistry, Tulane University, New Orleans, Louisiana 70118 (United States); Rubtsov, Grigory I. [Institute for Nuclear Research of the Russian Academy of Sciences, Moscow 117312 (Russian Federation)

2014-08-15

A novel dual-frequency two-dimensional infrared instrument is designed and built that permits three-pulse heterodyned echo measurements of any cross-peak within a spectral range from 800 to 4000 cm{sup −1} to be performed in a fully automated fashion. The superior sensitivity of the instrument is achieved by a combination of spectral interferometry, phase cycling, and closed-loop phase stabilization accurate to ∼70 as. The anharmonicity of smaller than 10{sup −4} cm{sup −1} was recorded for strong carbonyl stretching modes using 800 laser shot accumulations. The novel design of the phase stabilization scheme permits tuning polarizations of the mid-infrared (m-IR) pulses, thus supporting measurements of the angles between vibrational transition dipoles. The automatic frequency tuning is achieved by implementing beam direction stabilization schemes for each m-IR beam, providing better than 50 μrad beam stability, and novel scheme for setting the phase-matching geometry for the m-IR beams at the sample. The errors in the cross-peak amplitudes associated with imperfect phase matching conditions and alignment are found to be at the level of 20%. The instrument can be used by non-specialists in ultrafast spectroscopy.

Anomaly detection in an automated safeguards system using neural networks

International Nuclear Information System (INIS)

Whiteson, R.; Howell, J.A.

1992-01-01

An automated safeguards system must be able to detect an anomalous event, identify the nature of the event, and recommend a corrective action. Neural networks represent a new way of thinking about basic computational mechanisms for intelligent information processing. In this paper, we discuss the issues involved in applying a neural network model to the first step of this process: anomaly detection in materials accounting systems. We extend our previous model to a 3-tank problem and compare different neural network architectures and algorithms. We evaluate the computational difficulties in training neural networks and explore how certain design principles affect the problems. The issues involved in building a neural network architecture include how the information flows, how the network is trained, how the neurons in a network are connected, how the neurons process information, and how the connections between neurons are modified. Our approach is based on the demonstrated ability of neural networks to model complex, nonlinear, real-time processes. By modeling the normal behavior of the processes, we can predict how a system should be behaving and, therefore, detect when an abnormality occurs

Bioprocessing automation in cell therapy manufacturing: Outcomes of special interest group automation workshop.

Science.gov (United States)

Ball, Oliver; Robinson, Sarah; Bure, Kim; Brindley, David A; Mccall, David

2018-04-01

Phacilitate held a Special Interest Group workshop event in Edinburgh, UK, in May 2017. The event brought together leading stakeholders in the cell therapy bioprocessing field to identify present and future challenges and propose potential solutions to automation in cell therapy bioprocessing. Here, we review and summarize discussions from the event. Deep biological understanding of a product, its mechanism of action and indication pathogenesis underpin many factors relating to bioprocessing and automation. To fully exploit the opportunities of bioprocess automation, therapeutics developers must closely consider whether an automation strategy is applicable, how to design an 'automatable' bioprocess and how to implement process modifications with minimal disruption. Major decisions around bioprocess automation strategy should involve all relevant stakeholders; communication between technical and business strategy decision-makers is of particular importance. Developers should leverage automation to implement in-process testing, in turn applicable to process optimization, quality assurance (QA)/ quality control (QC), batch failure control, adaptive manufacturing and regulatory demands, but a lack of precedent and technical opportunities can complicate such efforts. Sparse standardization across product characterization, hardware components and software platforms is perceived to complicate efforts to implement automation. The use of advanced algorithmic approaches such as machine learning may have application to bioprocess and supply chain optimization. Automation can substantially de-risk the wider supply chain, including tracking and traceability, cryopreservation and thawing and logistics. The regulatory implications of automation are currently unclear because few hardware options exist and novel solutions require case-by-case validation, but automation can present attractive regulatory incentives. Copyright © 2018 International Society for Cellular Therapy

Comparison of automated processing of flocked swabs with manual processing of fiber swabs for detection of nasal carriage of Staphylococcus aureus.

Science.gov (United States)

Jones, Gillian; Matthews, Roger; Cunningham, Richard; Jenks, Peter

2011-07-01

The sensitivity of automated culture of Staphylococcus aureus from flocked swabs versus that of manual culture of fiber swabs was prospectively compared using nasal swabs from 867 patients. Automated culture from flocked swabs significantly increased the detection rate, by 13.1% for direct culture and 10.2% for enrichment culture.

A wearable device for a fully automated in-hospital staff and patient identification.

Science.gov (United States)

Cavalleri, M; Morstabilini, R; Reni, G

2004-01-01

In the health care context, devices for automated staff / patient identification provide multiple benefits, including error reduction in drug administration, an easier and faster use of the Electronic Health Record, enhanced security and control features when accessing confidential data, etc. Current identification systems (e.g. smartcards, bar codes) are not completely seamless to users and require mechanical operations that sometimes are difficult to perform for impaired subjects. Emerging wireless RFID technologies are encouraging, but cannot still be introduced in health care environments due to their electromagnetic emissions and the need for large size antenna to operate at reasonable distances. The present work describes a prototype of wearable device for automated staff and patient identification which is small in size and complies with the in-hospital electromagnetic requirements. This prototype also implements an anti-counterfeit option. Its experimental application allowed the introduction of some security functions for confidential data management.

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

International Nuclear Information System (INIS)

Young, S; Lo, P; Hoffman, J; Wahi-Anwar, M; Brown, M; McNitt-Gray, M; Noo, F

2016-01-01

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modules in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT_wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

Energy Technology Data Exchange (ETDEWEB)

Young, S; Lo, P; Hoffman, J; Wahi-Anwar, M; Brown, M; McNitt-Gray, M [UCLA School of Medicine, Los Angeles, CA (United States); Noo, F [University of Utah, Salt Lake City, UT (United States)

2016-06-15

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modules in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT-wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range

Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts

International Nuclear Information System (INIS)

Drukker, Karen; Sennett, Charlene A.; Giger, Maryellen L.

2014-01-01

Purpose: Develop a computer-aided detection method and investigate its feasibility for detection of breast cancer in automated 3D ultrasound images of women with dense breasts. Methods: The HIPAA compliant study involved a dataset of volumetric ultrasound image data, “views,” acquired with an automated U-Systems Somo•V ® ABUS system for 185 asymptomatic women with dense breasts (BI-RADS Composition/Density 3 or 4). For each patient, three whole-breast views (3D image volumes) per breast were acquired. A total of 52 patients had breast cancer (61 cancers), diagnosed through any follow-up at most 365 days after the original screening mammogram. Thirty-one of these patients (32 cancers) had a screening-mammogram with a clinically assigned BI-RADS Assessment Category 1 or 2, i.e., were mammographically negative. All software used for analysis was developed in-house and involved 3 steps: (1) detection of initial tumor candidates, (2) characterization of candidates, and (3) elimination of false-positive candidates. Performance was assessed by calculating the cancer detection sensitivity as a function of the number of “marks” (detections) per view. Results: At a single mark per view, i.e., six marks per patient, the median detection sensitivity by cancer was 50.0% (16/32) ± 6% for patients with a screening mammogram-assigned BI-RADS category 1 or 2—similar to radiologists’ performance sensitivity (49.9%) for this dataset from a prior reader study—and 45.9% (28/61) ± 4% for all patients. Conclusions: Promising detection sensitivity was obtained for the computer on a 3D ultrasound dataset of women with dense breasts at a rate of false-positive detections that may be acceptable for clinical implementation

Rig automation: where it's been and where it's going

Energy Technology Data Exchange (ETDEWEB)

Rinaldi, R.

1982-06-01

For over 30 years dreamers, tinkerers and engineers have attempted to automate various drilling functions. Now this effort is paying off, and a partially automated rig is no longer a curiosity. Fully automated and computerized rigs are on the way. For the contractor this means higher productivity, but more maintenance and training responsibilities.

MISENS DEVICE AS A NEW AUTOMATED BIOSENSING PLATFORM BASED ON REAL-TIME ELECTROCHEMICAL PROFILING (REP

Directory of Open Access Journals (Sweden)

yıldız uludağ

2016-09-01

Full Text Available In various fields like health, environmental control, food security and military defense; there is an increasing demand for on-site detection, fast identification and urgent response which brings the necessity to employ laboratory detection procedures on standalone automatic devices. In response to that TUBITAK BILGEM’s Bioelectronic Devices and Systems Group has been developing portable and fully automated biosensor devices using optical and electrochemical biosensor detection techniques. Here we describe a new integrated and fully automated lab-on-a-chip based biosensor device ‘MiSens’. The key features of the MiSens include a new electrode array, an integrated microfluidic system and real-time amperometric measurements during the flow of enzyme substrate. While simple protocols can be controlled from the LCD display on the device, other main device control procedures can be run wireless by a tablet/PC using the MiCont™ software developed by the team. For the device, a new plug and play type sensor chip docking station has been designed that with one move it enables the formation of a ~ 7-10 µl capacity flow cell on the electrode array with the necessary microfluidic and electronic connections. The MiSens device has been developed by our multi-disciplinary team by integrating and automatising the earlier developed sensing platform REP™ (Real-time Electrochemical Profiling. The performance of the MiSens device has been tested using cyclic voltammetry and amperometry tests and the results were compared with an of the shelf potantiostat.

Fully-Automated μMRI Morphometric Phenotyping of the Tc1 Mouse Model of Down Syndrome.

Directory of Open Access Journals (Sweden)

Nick M Powell

Full Text Available We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to the Tc1 mouse model of Down syndrome, to identify new morphological phenotypes in the brain of this first transchromosomic animal carrying human chromosome 21. We incorporate an accessible approach for simultaneously scanning multiple ex vivo brains, requiring only a 3D-printed brain holder, and novel image processing steps for their separation and orientation. We employ clinically established multi-atlas techniques-superior to single-atlas methods-together with publicly-available atlas databases for automatic skull-stripping and tissue segmentation, providing high-quality, subject-specific tissue maps. We follow these steps with group-wise registration, structural parcellation and both Voxel- and Tensor-Based Morphometry-advantageous for their ability to highlight morphological differences without the laborious delineation of regions of interest. We show the application of freely available open-source software developed for clinical MRI analysis to mouse brain data: NiftySeg for segmentation and NiftyReg for registration, and discuss atlases and parameters suitable for the preclinical paradigm. We used this pipeline to compare 29 Tc1 brains with 26 wild-type littermate controls, imaged ex vivo at 9.4T. We show an unexpected increase in Tc1 total intracranial volume and, controlling for this, local volume and grey matter density reductions in the Tc1 brain compared to the wild-types, most prominently in the cerebellum, in agreement with human DS and previous histological findings.

Automated rice leaf disease detection using color image analysis

Science.gov (United States)

Pugoy, Reinald Adrian D. L.; Mariano, Vladimir Y.

2011-06-01

In rice-related institutions such as the International Rice Research Institute, assessing the health condition of a rice plant through its leaves, which is usually done as a manual eyeball exercise, is important to come up with good nutrient and disease management strategies. In this paper, an automated system that can detect diseases present in a rice leaf using color image analysis is presented. In the system, the outlier region is first obtained from a rice leaf image to be tested using histogram intersection between the test and healthy rice leaf images. Upon obtaining the outlier, it is then subjected to a threshold-based K-means clustering algorithm to group related regions into clusters. Then, these clusters are subjected to further analysis to finally determine the suspected diseases of the rice leaf.

Systematic review automation technologies

Science.gov (United States)

2014-01-01

Systematic reviews, a cornerstone of evidence-based medicine, are not produced quickly enough to support clinical practice. The cost of production, availability of the requisite expertise and timeliness are often quoted as major contributors for the delay. This detailed survey of the state of the art of information systems designed to support or automate individual tasks in the systematic review, and in particular systematic reviews of randomized controlled clinical trials, reveals trends that see the convergence of several parallel research projects. We surveyed literature describing informatics systems that support or automate the processes of systematic review or each of the tasks of the systematic review. Several projects focus on automating, simplifying and/or streamlining specific tasks of the systematic review. Some tasks are already fully automated while others are still largely manual. In this review, we describe each task and the effect that its automation would have on the entire systematic review process, summarize the existing information system support for each task, and highlight where further research is needed for realizing automation for the task. Integration of the systems that automate systematic review tasks may lead to a revised systematic review workflow. We envisage the optimized workflow will lead to system in which each systematic review is described as a computer program that automatically retrieves relevant trials, appraises them, extracts and synthesizes data, evaluates the risk of bias, performs meta-analysis calculations, and produces a report in real time. PMID:25005128

Automated tracking for advanced satellite laser ranging systems

Science.gov (United States)

McGarry, Jan F.; Degnan, John J.; Titterton, Paul J., Sr.; Sweeney, Harold E.; Conklin, Brion P.; Dunn, Peter J.

1996-06-01

NASA's Satellite Laser Ranging Network was originally developed during the 1970's to track satellites carrying corner cube reflectors. Today eight NASA systems, achieving millimeter ranging precision, are part of a global network of more than 40 stations that track 17 international satellites. To meet the tracking demands of a steadily growing satellite constellation within existing resources, NASA is embarking on a major automation program. While manpower on the current systems will be reduced to a single operator, the fully automated SLR2000 system is being designed to operate for months without human intervention. Because SLR2000 must be eyesafe and operate in daylight, tracking is often performed in a low probability of detection and high noise environment. The goal is to automatically select the satellite, setup the tracking and ranging hardware, verify acquisition, and close the tracking loop to optimize data yield. TO accomplish the autotracking tasks, we are investigating (1) improved satellite force models, (2) more frequent updates of orbital ephemerides, (3) lunar laser ranging data processing techniques to distinguish satellite returns from noise, and (4) angular detection and search techniques to acquire the satellite. A Monte Carlo simulator has been developed to allow optimization of the autotracking algorithms by modeling the relevant system errors and then checking performance against system truth. A combination of simulator and preliminary field results will be presented.

Automated detection and classification of cryptographic algorithms in binary programs through machine learning

OpenAIRE

Hosfelt, Diane Duros

2015-01-01

Threats from the internet, particularly malicious software (i.e., malware) often use cryptographic algorithms to disguise their actions and even to take control of a victim's system (as in the case of ransomware). Malware and other threats proliferate too quickly for the time-consuming traditional methods of binary analysis to be effective. By automating detection and classification of cryptographic algorithms, we can speed program analysis and more efficiently combat malware. This thesis wil...

Towards fully automated structure-based NMR resonance assignment of 15N-labeled proteins from automatically picked peaks

KAUST Repository

Jang, Richard; Gao, Xin; Li, Ming

2011-01-01

In NMR resonance assignment, an indispensable step in NMR protein studies, manually processed peaks from both N-labeled and C-labeled spectra are typically used as inputs. However, the use of homologous structures can allow one to use only N-labeled NMR data and avoid the added expense of using C-labeled data. We propose a novel integer programming framework for structure-based backbone resonance assignment using N-labeled data. The core consists of a pair of integer programming models: one for spin system forming and amino acid typing, and the other for backbone resonance assignment. The goal is to perform the assignment directly from spectra without any manual intervention via automatically picked peaks, which are much noisier than manually picked peaks, so methods must be error-tolerant. In the case of semi-automated/manually processed peak data, we compare our system with the Xiong-Pandurangan-Bailey- Kellogg's contact replacement (CR) method, which is the most error-tolerant method for structure-based resonance assignment. Our system, on average, reduces the error rate of the CR method by five folds on their data set. In addition, by using an iterative algorithm, our system has the added capability of using the NOESY data to correct assignment errors due to errors in predicting the amino acid and secondary structure type of each spin system. On a publicly available data set for human ubiquitin, where the typing accuracy is 83%, we achieve 91% accuracy, compared to the 59% accuracy obtained without correcting for such errors. In the case of automatically picked peaks, using assignment information from yeast ubiquitin, we achieve a fully automatic assignment with 97% accuracy. To our knowledge, this is the first system that can achieve fully automatic structure-based assignment directly from spectra. This has implications in NMR protein mutant studies, where the assignment step is repeated for each mutant. © Copyright 2011, Mary Ann Liebert, Inc.

Towards fully automated structure-based NMR resonance assignment of 15N-labeled proteins from automatically picked peaks

KAUST Repository

Jang, Richard

2011-03-01

In NMR resonance assignment, an indispensable step in NMR protein studies, manually processed peaks from both N-labeled and C-labeled spectra are typically used as inputs. However, the use of homologous structures can allow one to use only N-labeled NMR data and avoid the added expense of using C-labeled data. We propose a novel integer programming framework for structure-based backbone resonance assignment using N-labeled data. The core consists of a pair of integer programming models: one for spin system forming and amino acid typing, and the other for backbone resonance assignment. The goal is to perform the assignment directly from spectra without any manual intervention via automatically picked peaks, which are much noisier than manually picked peaks, so methods must be error-tolerant. In the case of semi-automated/manually processed peak data, we compare our system with the Xiong-Pandurangan-Bailey- Kellogg\\'s contact replacement (CR) method, which is the most error-tolerant method for structure-based resonance assignment. Our system, on average, reduces the error rate of the CR method by five folds on their data set. In addition, by using an iterative algorithm, our system has the added capability of using the NOESY data to correct assignment errors due to errors in predicting the amino acid and secondary structure type of each spin system. On a publicly available data set for human ubiquitin, where the typing accuracy is 83%, we achieve 91% accuracy, compared to the 59% accuracy obtained without correcting for such errors. In the case of automatically picked peaks, using assignment information from yeast ubiquitin, we achieve a fully automatic assignment with 97% accuracy. To our knowledge, this is the first system that can achieve fully automatic structure-based assignment directly from spectra. This has implications in NMR protein mutant studies, where the assignment step is repeated for each mutant. © Copyright 2011, Mary Ann Liebert, Inc.

Automated Detection of Branch Shaking Locations for Robotic Cherry Harvesting Using Machine Vision

Directory of Open Access Journals (Sweden)

Suraj Amatya

2017-10-01

Full Text Available Automation in cherry harvesting is essential to reduce the demand for seasonal labor for cherry picking and reduce the cost of production. The mechanical shaking of tree branches is one of the widely studied and used techniques for harvesting small tree fruit crops like cherries. To automate the branch shaking operation, different methods of detecting branches and cherries in full foliage canopies of the cherry tree have been developed previously. The next step in this process is the localization of shaking positions in the detected tree branches for mechanical shaking. In this study, a method of locating shaking positions for automated cherry harvesting was developed based on branch and cherry pixel locations determined using RGB images and 3D camera images. First, branch and cherry regions were located in 2D RGB images. Depth information provided by a 3D camera was then mapped on to the RGB images using a standard stereo calibration method. The overall root mean square error in estimating the distance to desired shaking points was 0.064 m. Cherry trees trained in two different canopy architectures, Y-trellis and vertical trellis systems, were used in this study. Harvesting testing was carried out by shaking tree branches at the locations selected by the algorithm. For the Y-trellis system, the maximum fruit removal efficiency of 92.9% was achieved using up to five shaking events per branch. However, maximum fruit removal efficiency for the vertical trellis system was 86.6% with up to four shakings per branch. However, it was found that only three shakings per branch would achieve a fruit removal percentage of 92.3% and 86.4% in Y and vertical trellis systems respectively.

An automated and integrated framework for dust storm detection based on ogc web processing services

Science.gov (United States)

Xiao, F.; Shea, G. Y. K.; Wong, M. S.; Campbell, J.

2014-11-01

Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data

Fully Automated Laser Ablation Liquid Capture Sample Analysis using NanoElectrospray Ionization Mass Spectrometry

Energy Technology Data Exchange (ETDEWEB)

Lorenz, Matthias [ORNL; Ovchinnikova, Olga S [ORNL; Van Berkel, Gary J [ORNL

2014-01-01

RATIONALE: Laser ablation provides for the possibility of sampling a large variety of surfaces with high spatial resolution. This type of sampling when employed in conjunction with liquid capture followed by nanoelectrospray ionization provides the opportunity for sensitive and prolonged interrogation of samples by mass spectrometry as well as the ability to analyze surfaces not amenable to direct liquid extraction. METHODS: A fully automated, reflection geometry, laser ablation liquid capture spot sampling system was achieved by incorporating appropriate laser fiber optics and a focusing lens into a commercially available, liquid extraction surface analysis (LESA ) ready Advion TriVersa NanoMate system. RESULTS: Under optimized conditions about 10% of laser ablated material could be captured in a droplet positioned vertically over the ablation region using the NanoMate robot controlled pipette. The sampling spot size area with this laser ablation liquid capture surface analysis (LA/LCSA) mode of operation (typically about 120 m x 160 m) was approximately 50 times smaller than that achievable by direct liquid extraction using LESA (ca. 1 mm diameter liquid extraction spot). The set-up was successfully applied for the analysis of ink on glass and paper as well as the endogenous components in Alstroemeria Yellow King flower petals. In a second mode of operation with a comparable sampling spot size, termed laser ablation/LESA , the laser system was used to drill through, penetrate, or otherwise expose material beneath a solvent resistant surface. Once drilled, LESA was effective in sampling soluble material exposed at that location on the surface. CONCLUSIONS: Incorporating the capability for different laser ablation liquid capture spot sampling modes of operation into a LESA ready Advion TriVersa NanoMate enhanced the spot sampling spatial resolution of this device and broadened the surface types amenable to analysis to include absorbent and solvent resistant

Semi-automated, occupationally safe immunofluorescence microtip sensor for rapid detection of Mycobacterium cells in sputum.

Directory of Open Access Journals (Sweden)

Shinnosuke Inoue

Full Text Available An occupationally safe (biosafe sputum liquefaction protocol was developed for use with a semi-automated antibody-based microtip immunofluorescence sensor. The protocol effectively liquefied sputum and inactivated microorganisms including Mycobacterium tuberculosis, while preserving the antibody-binding activity of Mycobacterium cell surface antigens. Sputum was treated with a synergistic chemical-thermal protocol that included moderate concentrations of NaOH and detergent at 60°C for 5 to 10 min. Samples spiked with M. tuberculosis complex cells showed approximately 10(6-fold inactivation of the pathogen after treatment. Antibody binding was retained post-treatment, as determined by analysis with a microtip immunosensor. The sensor correctly distinguished between Mycobacterium species and other cell types naturally present in biosafe-treated sputum, with a detection limit of 100 CFU/mL for M. tuberculosis, in a 30-minute sample-to-result process. The microtip device was also semi-automated and shown to be compatible with low-cost, LED-powered fluorescence microscopy. The device and biosafe sputum liquefaction method opens the door to rapid detection of tuberculosis in settings with limited laboratory infrastructure.

ROBOCAL: An automated NDA [nondestructive analysis] calorimetry and gamma isotopic system

International Nuclear Information System (INIS)

Hurd, J.R.; Powell, W.D.; Ostenak, C.A.

1989-01-01

ROBOCAL, which is presently being developed and tested at Los Alamos National Laboratory, is a full-scale, prototype robotic system for remote calorimetric and gamma-ray analysis of special nuclear materials. It integrates a fully automated, multidrawer, vertical stacker-retriever system for staging unmeasured nuclear materials, and a fully automated gantry robot for computer-based selection and transfer of nuclear materials to calorimetric and gamma-ray measurement stations. Since ROBOCAL is designed for minimal operator intervention, a completely programmed user interface is provided to interact with the automated mechanical and assay systems. The assay system is designed to completely integrate calorimetric and gamma-ray data acquisition and to perform state-of-the-art analyses on both homogeneous and heterogeneous distributions of nuclear materials in a wide variety of matrices

Automated genotyping of dinucleotide repeat markers

Energy Technology Data Exchange (ETDEWEB)

Perlin, M.W.; Hoffman, E.P. [Carnegie Mellon Univ., Pittsburgh, PA (United States)]|[Univ. of Pittsburgh, PA (United States)

1994-09-01

The dinucleotide repeats (i.e., microsatellites) such as CA-repeats are a highly polymorphic, highly abundant class of PCR-amplifiable markers that have greatly streamlined genetic mapping experimentation. It is expected that over 30,000 such markers (including tri- and tetranucleotide repeats) will be characterized for routine use in the next few years. Since only size determination, and not sequencing, is required to determine alleles, in principle, dinucleotide repeat genotyping is easily performed on electrophoretic gels, and can be automated using DNA sequencers. Unfortunately, PCR stuttering with these markers generates not one band for each allele, but a pattern of bands. Since closely spaced alleles must be disambiguated by human scoring, this poses a key obstacle to full automation. We have developed methods that overcome this obstacle. Our model is that the observed data is generated by arithmetic superposition (i.e., convolution) of multiple allele patterns. By quantitatively measuring the size of each component band, and exploiting the unique stutter pattern associated with each marker, closely spaced alleles can be deconvolved; this unambiguously reconstructs the {open_quotes}true{close_quotes} allele bands, with stutter artifact removed. We used this approach in a system for automated diagnosis of (X-linked) Duchenne muscular dystrophy; four multiplexed CA-repeats within the dystrophin gene were assayed on a DNA sequencer. Our method accurately detected small variations in gel migration that shifted the allele size estimate. In 167 nonmutated alleles, 89% (149/167) showed no size variation, 9% (15/167) showed 1 bp variation, and 2% (3/167) showed 2 bp variation. We are currently developing a library of dinucleotide repeat patterns; together with our deconvolution methods, this library will enable fully automated genotyping of dinucleotide repeats from sizing data.

Histograms of Oriented 3D Gradients for Fully Automated Fetal Brain Localization and Robust Motion Correction in 3 T Magnetic Resonance Images.

Science.gov (United States)

Serag, Ahmed; Macnaught, Gillian; Denison, Fiona C; Reynolds, Rebecca M; Semple, Scott I; Boardman, James P

2017-01-01

Fetal brain magnetic resonance imaging (MRI) is a rapidly emerging diagnostic imaging tool. However, automated fetal brain localization is one of the biggest obstacles in expediting and fully automating large-scale fetal MRI processing. We propose a method for automatic localization of fetal brain in 3 T MRI when the images are acquired as a stack of 2D slices that are misaligned due to fetal motion. First, the Histogram of Oriented Gradients (HOG) feature descriptor is extended from 2D to 3D images. Then, a sliding window is used to assign a score to all possible windows in an image, depending on the likelihood of it containing a brain, and the window with the highest score is selected. In our evaluation experiments using a leave-one-out cross-validation strategy, we achieved 96% of complete brain localization using a database of 104 MRI scans at gestational ages between 34 and 38 weeks. We carried out comparisons against template matching and random forest based regression methods and the proposed method showed superior performance. We also showed the application of the proposed method in the optimization of fetal motion correction and how it is essential for the reconstruction process. The method is robust and does not rely on any prior knowledge of fetal brain development.

Histograms of Oriented 3D Gradients for Fully Automated Fetal Brain Localization and Robust Motion Correction in 3 T Magnetic Resonance Images

Directory of Open Access Journals (Sweden)

Ahmed Serag

2017-01-01

Full Text Available Fetal brain magnetic resonance imaging (MRI is a rapidly emerging diagnostic imaging tool. However, automated fetal brain localization is one of the biggest obstacles in expediting and fully automating large-scale fetal MRI processing. We propose a method for automatic localization of fetal brain in 3 T MRI when the images are acquired as a stack of 2D slices that are misaligned due to fetal motion. First, the Histogram of Oriented Gradients (HOG feature descriptor is extended from 2D to 3D images. Then, a sliding window is used to assign a score to all possible windows in an image, depending on the likelihood of it containing a brain, and the window with the highest score is selected. In our evaluation experiments using a leave-one-out cross-validation strategy, we achieved 96% of complete brain localization using a database of 104 MRI scans at gestational ages between 34 and 38 weeks. We carried out comparisons against template matching and random forest based regression methods and the proposed method showed superior performance. We also showed the application of the proposed method in the optimization of fetal motion correction and how it is essential for the reconstruction process. The method is robust and does not rely on any prior knowledge of fetal brain development.

Model-based automated testing of critical PLC programs.

CERN Document Server

Fernández Adiego, B; Tournier, J-C; González Suárez, V M; Bliudze, S

2014-01-01

Testing of critical PLC (Programmable Logic Controller) programs remains a challenging task for control system engineers as it can rarely be automated. This paper proposes a model based approach which uses the BIP (Behavior, Interactions and Priorities) framework to perform automated testing of PLC programs developed with the UNICOS (UNified Industrial COntrol System) framework. This paper defines the translation procedure and rules from UNICOS to BIP which can be fully automated in order to hide the complexity of the underlying model from the control engineers. The approach is illustrated and validated through the study of a water treatment process.

Automating the radiographic NDT process

International Nuclear Information System (INIS)

Aman, J.K.

1986-01-01

Automation, the removal of the human element in inspection, has not been generally applied to film radiographic NDT. The justication for automating is not only productivity but also reliability of results. Film remains in the automated system of the future because of its extremely high image content, approximately 8 x 10 9 bits per 14 x 17. The equivalent to 2200 computer floppy discs. Parts handling systems and robotics applied for manufacturing and some NDT modalities, should now be applied to film radiographic NDT systems. Automatic film handling can be achieved with the daylight NDT film handling system. Automatic film processing is becoming the standard in industry and can be coupled to the daylight system. Robots offer the opportunity to automate fully the exposure step. Finally, computer aided interpretation appears on the horizon. A unit which laser scans a 14 x 17 (inch) film in 6 - 8 seconds can digitize film information for further manipulation and possible automatic interrogations (computer aided interpretation). The system called FDRS (for Film Digital Radiography System) is moving toward 50 micron (*approx* 16 lines/mm) resolution. This is believed to meet the need of the majority of image content needs. We expect the automated system to appear first in parts (modules) as certain operations are automated. The future will see it all come together in an automated film radiographic NDT system (author) [pt

3S-R10 automated RBS system

International Nuclear Information System (INIS)

Norton, G.A.; Schroeder, J.B.; Klody, G.M.; Strathman, M.D.

1989-01-01

The NEC 3S-R10 automated RBS spectrometer system includes the features required for routine application of Rutherford backscattering (RBS) and related techniques for materials analysis in both research and industrial settings. The NEC Model 3SDH Pelletron accelerator system provides stable, monoenergetic beams of helium ions up to 3.3 MeV and protons to 2.2 MeV and has heavy ion capability. The analytical end station is the fully computerized Charles Evans and Associates Model RBS-400. Automated features include sample positioning (precision 4-axis goniometer), channeling alignment, polar plot generation, and data acquisition and reduction. Computer automation of accelerator and chamber functions includes storage and recall of operating parameters. Unattended data acquisition, e.g., overnight or over a weekend, is possible for up to 100 samples per batch for random orientation, rotating random or channeling analyses at any sample location. Single samples may be up to 50 cm in diameter. A laser for sample alignment and a TV for video monitoring are included. Simultaneous detection (up to 4 detectors) at normal and grazing angles, external control of grazing angle detector position, and transmission scattering capabiltiy enhance system flexibility. The system is also compatible with PIXE, NRA, and hydrogen forward-backscattering analyses. Data reduction is part of the computer system, which features displays (several formats) and manipulation of up to five spectra at one time using constant multipliers or point by point operations between spectra. (orig.)