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Sample records for fully automated quantitative

Cardiac imaging: working towards fully-automated machine analysis & interpretation.

PubMed

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-03-01

Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.
Cardiac imaging: working towards fully-automated machine analysis & interpretation

PubMed Central

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-01-01

Introduction Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation. PMID:28277804
Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

PubMed

Liu, Fang; Zhou, Zhaoye; Jang, Hyungseok; Samsonov, Alexey; Zhao, Gengyan; Kijowski, Richard

2018-04-01

To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint. A fully automated segmentation pipeline was built by combining a semantic segmentation CNN and 3D simplex deformable modeling. A CNN technique called SegNet was applied as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification. The 3D simplex deformable modeling refined the output from SegNet to preserve the overall shape and maintain a desirable smooth surface for musculoskeletal structure. The fully automated segmentation method was tested using a publicly available knee image data set to compare with currently used state-of-the-art segmentation methods. The fully automated method was also evaluated on two different data sets, which include morphological and quantitative MR images with different tissue contrasts. The proposed fully automated segmentation method provided good segmentation performance with segmentation accuracy superior to most of state-of-the-art methods in the publicly available knee image data set. The method also demonstrated versatile segmentation performance on both morphological and quantitative musculoskeletal MR images with different tissue contrasts and spatial resolutions. The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Quantitative and qualitative measure of intralaboratory two-dimensional protein gel reproducibility and the effects of sample preparation, sample load, and image analysis.

PubMed

Choe, Leila H; Lee, Kelvin H

2003-10-01

We investigate one approach to assess the quantitative variability in two-dimensional gel electrophoresis (2-DE) separations based on gel-to-gel variability, sample preparation variability, sample load differences, and the effect of automation on image analysis. We observe that 95% of spots present in three out of four replicate gels exhibit less than a 0.52 coefficient of variation (CV) in fluorescent stain intensity (% volume) for a single sample run on multiple gels. When four parallel sample preparations are performed, this value increases to 0.57. We do not observe any significant change in quantitative value for an increase or decrease in sample load of 30% when using appropriate image analysis variables. Increasing use of automation, while necessary in modern 2-DE experiments, does change the observed level of quantitative and qualitative variability among replicate gels. The number of spots that change qualitatively for a single sample run in parallel varies from a CV = 0.03 for fully manual analysis to CV = 0.20 for a fully automated analysis. We present a systematic method by which a single laboratory can measure gel-to-gel variability using only three gel runs.
Image segmentation evaluation for very-large datasets

NASA Astrophysics Data System (ADS)

Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.
Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging.

PubMed

Pertuz, Said; McDonald, Elizabeth S; Weinstein, Susan P; Conant, Emily F; Kontos, Despina

2016-04-01

To assess a fully automated method for volumetric breast density (VBD) estimation in digital breast tomosynthesis (DBT) and to compare the findings with those of full-field digital mammography (FFDM) and magnetic resonance (MR) imaging. Bilateral DBT images, FFDM images, and sagittal breast MR images were retrospectively collected from 68 women who underwent breast cancer screening from October 2011 to September 2012 with institutional review board-approved, HIPAA-compliant protocols. A fully automated computer algorithm was developed for quantitative estimation of VBD from DBT images. FFDM images were processed with U.S. Food and Drug Administration-cleared software, and the MR images were processed with a previously validated automated algorithm to obtain corresponding VBD estimates. Pearson correlation and analysis of variance with Tukey-Kramer post hoc correction were used to compare the multimodality VBD estimates. Estimates of VBD from DBT were significantly correlated with FFDM-based and MR imaging-based estimates with r = 0.83 (95% confidence interval [CI]: 0.74, 0.90) and r = 0.88 (95% CI: 0.82, 0.93), respectively (P < .001). The corresponding correlation between FFDM and MR imaging was r = 0.84 (95% CI: 0.76, 0.90). However, statistically significant differences after post hoc correction (α = 0.05) were found among VBD estimates from FFDM (mean ± standard deviation, 11.1% ± 7.0) relative to MR imaging (16.6% ± 11.2) and DBT (19.8% ± 16.2). Differences between VDB estimates from DBT and MR imaging were not significant (P = .26). Fully automated VBD estimates from DBT, FFDM, and MR imaging are strongly correlated but show statistically significant differences. Therefore, absolute differences in VBD between FFDM, DBT, and MR imaging should be considered in breast cancer risk assessment.
Automated frame selection process for high-resolution microendoscopy

NASA Astrophysics Data System (ADS)

Ishijima, Ayumu; Schwarz, Richard A.; Shin, Dongsuk; Mondrik, Sharon; Vigneswaran, Nadarajah; Gillenwater, Ann M.; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2015-04-01

We developed an automated frame selection algorithm for high-resolution microendoscopy video sequences. The algorithm rapidly selects a representative frame with minimal motion artifact from a short video sequence, enabling fully automated image analysis at the point-of-care. The algorithm was evaluated by quantitative comparison of diagnostically relevant image features and diagnostic classification results obtained using automated frame selection versus manual frame selection. A data set consisting of video sequences collected in vivo from 100 oral sites and 167 esophageal sites was used in the analysis. The area under the receiver operating characteristic curve was 0.78 (automated selection) versus 0.82 (manual selection) for oral sites, and 0.93 (automated selection) versus 0.92 (manual selection) for esophageal sites. The implementation of fully automated high-resolution microendoscopy at the point-of-care has the potential to reduce the number of biopsies needed for accurate diagnosis of precancer and cancer in low-resource settings where there may be limited infrastructure and personnel for standard histologic analysis.
Fully automated segmentation of callus by micro-CT compared to biomechanics.

PubMed

Bissinger, Oliver; Götz, Carolin; Wolff, Klaus-Dietrich; Hapfelmeier, Alexander; Prodinger, Peter Michael; Tischer, Thomas

2017-07-11

A high percentage of closed femur fractures have slight comminution. Using micro-CT (μCT), multiple fragment segmentation is much more difficult than segmentation of unfractured or osteotomied bone. Manual or semi-automated segmentation has been performed to date. However, such segmentation is extremely laborious, time-consuming and error-prone. Our aim was to therefore apply a fully automated segmentation algorithm to determine μCT parameters and examine their association with biomechanics. The femura of 64 rats taken after randomised inhibitory or neutral medication, in terms of the effect on fracture healing, and controls were closed fractured after a Kirschner wire was inserted. After 21 days, μCT and biomechanical parameters were determined by a fully automated method and correlated (Pearson's correlation). The fully automated segmentation algorithm automatically detected bone and simultaneously separated cortical bone from callus without requiring ROI selection for each single bony structure. We found an association of structural callus parameters obtained by μCT to the biomechanical properties. However, results were only explicable by additionally considering the callus location. A large number of slightly comminuted fractures in combination with therapies that influence the callus qualitatively and/or quantitatively considerably affects the association between μCT and biomechanics. In the future, contrast-enhanced μCT imaging of the callus cartilage might provide more information to improve the non-destructive and non-invasive prediction of callus mechanical properties. As studies evaluating such important drugs increase, fully automated segmentation appears to be clinically important.
Flexible automated approach for quantitative liquid handling of complex biological samples.

PubMed

Palandra, Joe; Weller, David; Hudson, Gary; Li, Jeff; Osgood, Sarah; Hudson, Emily; Zhong, Min; Buchholz, Lisa; Cohen, Lucinda H

2007-11-01

A fully automated protein precipitation technique for biological sample preparation has been developed for the quantitation of drugs in various biological matrixes. All liquid handling during sample preparation was automated using a Hamilton MicroLab Star Robotic workstation, which included the preparation of standards and controls from a Watson laboratory information management system generated work list, shaking of 96-well plates, and vacuum application. Processing time is less than 30 s per sample or approximately 45 min per 96-well plate, which is then immediately ready for injection onto an LC-MS/MS system. An overview of the process workflow is discussed, including the software development. Validation data are also provided, including specific liquid class data as well as comparative data of automated vs manual preparation using both quality controls and actual sample data. The efficiencies gained from this automated approach are described.
Localization-based super-resolution imaging meets high-content screening.

PubMed

Beghin, Anne; Kechkar, Adel; Butler, Corey; Levet, Florian; Cabillic, Marine; Rossier, Olivier; Giannone, Gregory; Galland, Rémi; Choquet, Daniel; Sibarita, Jean-Baptiste

2017-12-01

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.
Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging

PubMed Central

Pertuz, Said; McDonald, Elizabeth S.; Weinstein, Susan P.; Conant, Emily F.

2016-01-01

Purpose To assess a fully automated method for volumetric breast density (VBD) estimation in digital breast tomosynthesis (DBT) and to compare the findings with those of full-field digital mammography (FFDM) and magnetic resonance (MR) imaging. Materials and Methods Bilateral DBT images, FFDM images, and sagittal breast MR images were retrospectively collected from 68 women who underwent breast cancer screening from October 2011 to September 2012 with institutional review board–approved, HIPAA-compliant protocols. A fully automated computer algorithm was developed for quantitative estimation of VBD from DBT images. FFDM images were processed with U.S. Food and Drug Administration–cleared software, and the MR images were processed with a previously validated automated algorithm to obtain corresponding VBD estimates. Pearson correlation and analysis of variance with Tukey-Kramer post hoc correction were used to compare the multimodality VBD estimates. Results Estimates of VBD from DBT were significantly correlated with FFDM-based and MR imaging–based estimates with r = 0.83 (95% confidence interval [CI]: 0.74, 0.90) and r = 0.88 (95% CI: 0.82, 0.93), respectively (P < .001). The corresponding correlation between FFDM and MR imaging was r = 0.84 (95% CI: 0.76, 0.90). However, statistically significant differences after post hoc correction (α = 0.05) were found among VBD estimates from FFDM (mean ± standard deviation, 11.1% ± 7.0) relative to MR imaging (16.6% ± 11.2) and DBT (19.8% ± 16.2). Differences between VDB estimates from DBT and MR imaging were not significant (P = .26). Conclusion Fully automated VBD estimates from DBT, FFDM, and MR imaging are strongly correlated but show statistically significant differences. Therefore, absolute differences in VBD between FFDM, DBT, and MR imaging should be considered in breast cancer risk assessment. © RSNA, 2015 Online supplemental material is available for this article. PMID:26491909
Early detection of glaucoma using fully automated disparity analysis of the optic nerve head (ONH) from stereo fundus images

NASA Astrophysics Data System (ADS)

Sharma, Archie; Corona, Enrique; Mitra, Sunanda; Nutter, Brian S.

2006-03-01

Early detection of structural damage to the optic nerve head (ONH) is critical in diagnosis of glaucoma, because such glaucomatous damage precedes clinically identifiable visual loss. Early detection of glaucoma can prevent progression of the disease and consequent loss of vision. Traditional early detection techniques involve observing changes in the ONH through an ophthalmoscope. Stereo fundus photography is also routinely used to detect subtle changes in the ONH. However, clinical evaluation of stereo fundus photographs suffers from inter- and intra-subject variability. Even the Heidelberg Retina Tomograph (HRT) has not been found to be sufficiently sensitive for early detection. A semi-automated algorithm for quantitative representation of the optic disc and cup contours by computing accumulated disparities in the disc and cup regions from stereo fundus image pairs has already been developed using advanced digital image analysis methodologies. A 3-D visualization of the disc and cup is achieved assuming camera geometry. High correlation among computer-generated and manually segmented cup to disc ratios in a longitudinal study involving 159 stereo fundus image pairs has already been demonstrated. However, clinical usefulness of the proposed technique can only be tested by a fully automated algorithm. In this paper, we present a fully automated algorithm for segmentation of optic cup and disc contours from corresponding stereo disparity information. Because this technique does not involve human intervention, it eliminates subjective variability encountered in currently used clinical methods and provides ophthalmologists with a cost-effective and quantitative method for detection of ONH structural damage for early detection of glaucoma.
Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

PubMed

Pound, Michael P; Atkinson, Jonathan A; Townsend, Alexandra J; Wilson, Michael H; Griffiths, Marcus; Jackson, Aaron S; Bulat, Adrian; Tzimiropoulos, Georgios; Wells, Darren M; Murchie, Erik H; Pridmore, Tony P; French, Andrew P

2017-10-01

In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation for finding a fully automated approach. Deep learning is an emerging field that promises unparalleled results on many data analysis problems. Building on artificial neural networks, deep approaches have many more hidden layers in the network, and hence have greater discriminative and predictive power. We demonstrate the use of such approaches as part of a plant phenotyping pipeline. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping and demonstrate state-of-the-art results (>97% accuracy) for root and shoot feature identification and localization. We use fully automated trait identification using deep learning to identify quantitative trait loci in root architecture datasets. The majority (12 out of 14) of manually identified quantitative trait loci were also discovered using our automated approach based on deep learning detection to locate plant features. We have shown deep learning-based phenotyping to have very good detection and localization accuracy in validation and testing image sets. We have shown that such features can be used to derive meaningful biological traits, which in turn can be used in quantitative trait loci discovery pipelines. This process can be completely automated. We predict a paradigm shift in image-based phenotyping bought about by such deep learning approaches, given sufficient training sets. © The Authors 2017. Published by Oxford University Press.
Towards quantitative imaging: stability of fully automated nodule segmentation across varied dose levels and reconstruction parameters in a low-dose CT screening patient cohort

NASA Astrophysics Data System (ADS)

Wahi-Anwar, M. Wasil; Emaminejad, Nastaran; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael F.

2018-02-01

Quantitative imaging in lung cancer CT seeks to characterize nodules through quantitative features, usually from a region of interest delineating the nodule. The segmentation, however, can vary depending on segmentation approach and image quality, which can affect the extracted feature values. In this study, we utilize a fully-automated nodule segmentation method - to avoid reader-influenced inconsistencies - to explore the effects of varied dose levels and reconstruction parameters on segmentation. Raw projection CT images from a low-dose screening patient cohort (N=59) were reconstructed at multiple dose levels (100%, 50%, 25%, 10%), two slice thicknesses (1.0mm, 0.6mm), and a medium kernel. Fully-automated nodule detection and segmentation was then applied, from which 12 nodules were selected. Dice similarity coefficient (DSC) was used to assess the similarity of the segmentation ROIs of the same nodule across different reconstruction and dose conditions. Nodules at 1.0mm slice thickness and dose levels of 25% and 50% resulted in DSC values greater than 0.85 when compared to 100% dose, with lower dose leading to a lower average and wider spread of DSC values. At 0.6mm, the increased bias and wider spread of DSC values from lowering dose were more pronounced. The effects of dose reduction on DSC for CAD-segmented nodules were similar in magnitude to reducing the slice thickness from 1.0mm to 0.6mm. In conclusion, variation of dose and slice thickness can result in very different segmentations because of noise and image quality. However, there exists some stability in segmentation overlap, as even at 1mm, an image with 25% of the lowdose scan still results in segmentations similar to that seen in a full-dose scan.
Nonlinear optical microscopy: use of second harmonic generation and two-photon microscopy for automated quantitative liver fibrosis studies.

PubMed

Sun, Wanxin; Chang, Shi; Tai, Dean C S; Tan, Nancy; Xiao, Guangfa; Tang, Huihuan; Yu, Hanry

2008-01-01

Liver fibrosis is associated with an abnormal increase in an extracellular matrix in chronic liver diseases. Quantitative characterization of fibrillar collagen in intact tissue is essential for both fibrosis studies and clinical applications. Commonly used methods, histological staining followed by either semiquantitative or computerized image analysis, have limited sensitivity, accuracy, and operator-dependent variations. The fibrillar collagen in sinusoids of normal livers could be observed through second-harmonic generation (SHG) microscopy. The two-photon excited fluorescence (TPEF) images, recorded simultaneously with SHG, clearly revealed the hepatocyte morphology. We have systematically optimized the parameters for the quantitative SHG/TPEF imaging of liver tissue and developed fully automated image analysis algorithms to extract the information of collagen changes and cell necrosis. Subtle changes in the distribution and amount of collagen and cell morphology are quantitatively characterized in SHG/TPEF images. By comparing to traditional staining, such as Masson's trichrome and Sirius red, SHG/TPEF is a sensitive quantitative tool for automated collagen characterization in liver tissue. Our system allows for enhanced detection and quantification of sinusoidal collagen fibers in fibrosis research and clinical diagnostics.
Fully automated, internally controlled quantification of hepatitis B Virus DNA by real-time PCR by use of the MagNA Pure LC and LightCycler instruments.

PubMed

Leb, Victoria; Stöcher, Markus; Valentine-Thon, Elizabeth; Hölzl, Gabriele; Kessler, Harald; Stekel, Herbert; Berg, Jörg

2004-02-01

We report on the development of a fully automated real-time PCR assay for the quantitative detection of hepatitis B virus (HBV) DNA in plasma with EDTA (EDTA plasma). The MagNA Pure LC instrument was used for automated DNA purification and automated preparation of PCR mixtures. Real-time PCR was performed on the LightCycler instrument. An internal amplification control was devised as a PCR competitor and was introduced into the assay at the stage of DNA purification to permit monitoring for sample adequacy. The detection limit of the assay was found to be 200 HBV DNA copies/ml, with a linear dynamic range of 8 orders of magnitude. When samples from the European Union Quality Control Concerted Action HBV Proficiency Panel 1999 were examined, the results were found to be in acceptable agreement with the HBV DNA concentrations of the panel members. In a clinical laboratory evaluation of 123 EDTA plasma samples, a significant correlation was found with the results obtained by the Roche HBV Monitor test on the Cobas Amplicor analyzer within the dynamic range of that system. In conclusion, the newly developed assay has a markedly reduced hands-on time, permits monitoring for sample adequacy, and is suitable for the quantitative detection of HBV DNA in plasma in a routine clinical laboratory.
Automated optimization techniques for aircraft synthesis

NASA Technical Reports Server (NTRS)

Vanderplaats, G. N.

1976-01-01

Application of numerical optimization techniques to automated conceptual aircraft design is examined. These methods are shown to be a general and efficient way to obtain quantitative information for evaluating alternative new vehicle projects. Fully automated design is compared with traditional point design methods and time and resource requirements for automated design are given. The NASA Ames Research Center aircraft synthesis program (ACSYNT) is described with special attention to calculation of the weight of a vehicle to fly a specified mission. The ACSYNT procedures for automatically obtaining sensitivity of the design (aircraft weight, performance and cost) to various vehicle, mission, and material technology parameters are presented. Examples are used to demonstrate the efficient application of these techniques.
Quantitative determination of opioids in whole blood using fully automated dried blood spot desorption coupled to on-line SPE-LC-MS/MS.

PubMed

Verplaetse, Ruth; Henion, Jack

2016-01-01

Opioids are well known, widely used painkillers. Increased stability of opioids in the dried blood spot (DBS) matrix compared to blood/plasma has been described. Other benefits provided by DBS techniques include point-of-care collection, less invasive micro sampling, more economical shipment, and convenient storage. Current methodology for analysis of micro whole blood samples for opioids is limited to the classical DBS workflow, including tedious manual punching of the DBS cards followed by extraction and liquid chromatography-tandem mass spectrometry (LC-MS/MS) bioanalysis. The goal of this study was to develop and validate a fully automated on-line sample preparation procedure for the analysis of DBS micro samples relevant to the detection of opioids in finger prick blood. To this end, automated flow-through elution of DBS cards was followed by on-line solid-phase extraction (SPE) and analysis by LC-MS/MS. Selective, sensitive, accurate, and reproducible quantitation of five representative opioids in human blood at sub-therapeutic, therapeutic, and toxic levels was achieved. The range of reliable response (R(2) ≥0.997) was 1 to 500 ng/mL whole blood for morphine, codeine, oxycodone, hydrocodone; and 0.1 to 50 ng/mL for fentanyl. Inter-day, intra-day, and matrix inter-lot accuracy and precision was less than 15% (even at lower limits of quantitation (LLOQ) level). The method was successfully used to measure hydrocodone and its major metabolite norhydrocodone in incurred human samples. Our data support the enormous potential of DBS sampling and automated analysis for monitoring opioids as well as other pharmaceuticals in both anti-doping and pain management regimens. Copyright © 2015 John Wiley & Sons, Ltd.
Feasibility of simultaneous computed tomographic colonography and fully automated bone mineral densitometry in a single examination.

PubMed

Summers, Ronald M; Baecher, Nicolai; Yao, Jianhua; Liu, Jiamin; Pickhardt, Perry J; Choi, J Richard; Hill, Suvimol

2011-01-01

To show the feasibility of calculating the bone mineral density (BMD) from computed tomographic colonography (CTC) scans using fully automated software. Automated BMD measurement software was developed that measures the BMD of the first and second lumbar vertebrae on computed tomography and calculates the mean of the 2 values to provide a per patient BMD estimate. The software was validated in a reference population of 17 consecutive women who underwent quantitative computed tomography and in a population of 475 women from a consecutive series of asymptomatic patients enrolled in a CTC screening trial conducted at 3 medical centers. The mean (SD) BMD was 133.6 (34.6) mg/mL (95% confidence interval, 130.5-136.7; n = 475). In women aged 42 to 60 years (n = 316) and 61 to 79 years (n = 159), the mean (SD) BMDs were 143.1 (33.5) and 114.7 (28.3) mg/mL, respectively (P < 0.0001). Fully automated BMD measurements were reproducible for a given patient with 95% limits of agreement of -9.79 to 8.46 mg/mL for the mean difference between paired assessments on supine and prone CTC. Osteoporosis screening can be performed simultaneously with screening for colorectal polyps.
Electrochemical Detection in Stacked Paper Networks.

PubMed

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.

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

PubMed

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

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

Wahi-Anwar, M; Lo, P; Kim, H

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 identifiesmore » 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 component to automatically verify image acquisition parameters and automated adherence to specifications. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH Grant support from: U01 CA181156.« less
Automatic detection of cone photoreceptors in split detector adaptive optics scanning light ophthalmoscope images.

PubMed

Cunefare, David; Cooper, Robert F; Higgins, Brian; Katz, David F; Dubra, Alfredo; Carroll, Joseph; Farsiu, Sina

2016-05-01

Quantitative analysis of the cone photoreceptor mosaic in the living retina is potentially useful for early diagnosis and prognosis of many ocular diseases. Non-confocal split detector based adaptive optics scanning light ophthalmoscope (AOSLO) imaging reveals the cone photoreceptor inner segment mosaics often not visualized on confocal AOSLO imaging. Despite recent advances in automated cone segmentation algorithms for confocal AOSLO imagery, quantitative analysis of split detector AOSLO images is currently a time-consuming manual process. In this paper, we present the fully automatic adaptive filtering and local detection (AFLD) method for detecting cones in split detector AOSLO images. We validated our algorithm on 80 images from 10 subjects, showing an overall mean Dice's coefficient of 0.95 (standard deviation 0.03), when comparing our AFLD algorithm to an expert grader. This is comparable to the inter-observer Dice's coefficient of 0.94 (standard deviation 0.04). To the best of our knowledge, this is the first validated, fully-automated segmentation method which has been applied to split detector AOSLO images.
Analysis of HER2 status in breast carcinoma by fully automated HER2 fluorescence in situ hybridization (FISH): comparison of two immunohistochemical tests and manual FISH.

PubMed

Yoon, Nara; Do, In-Gu; Cho, Eun Yoon

2014-09-01

Easy and accurate HER2 testing is essential when considering the prognostic and predictive significance of HER2 in breast cancer. The use of a fully automated, quantitative FISH assay would be helpful to detect HER2 amplification in breast cancer tissue specimens with reduced inter-laboratory variability. We compared the concordance of HER2 status as assessed by an automated FISH staining system to manual FISH testing. Using 60 formalin-fixed paraffin-embedded breast carcinoma specimens, we assessed HER2 immunoexpression with two antibodies (DAKO HercepTest and CB11). In addition, HER2 status was evaluated with automated FISH using the Leica FISH System for BOND and a manual FISH using the Abbott PathVysion DNA Probe Kit. All but one specimen were successfully stained using both FISH methods. When the data were divided into two groups according to HER2/CEP17 ratio, positive and negative, the results from both the automated and manual FISH techniques were identical for all 59 evaluable specimens. The HER2 and CEP17 copy numbers and HER2/CEP17 ratio showed great agreement between both FISH methods. The automated FISH technique was interpretable with signal intensity similar to those of the manual FISH technique. In contrast with manual FISH, the automated FISH technique showed well-preserved architecture due to low membrane digestion. HER2 immunohistochemistry and FISH results showed substantial significant agreement (κ = 1.0, p < 0.001). HER2 status can be reliably determined using a fully automated HER2 FISH system with high concordance to the well-established manual FISH method. Because of stable signal intensity and high staining quality, the automated FISH technique may be more appropriate than manual FISH for routine applications. © 2013 APMIS. Published by John Wiley & Sons Ltd.
In vivo classification of human skin burns using machine learning and quantitative features captured by optical coherence tomography

NASA Astrophysics Data System (ADS)

Singla, Neeru; Srivastava, Vishal; Singh Mehta, Dalip

2018-02-01

We report the first fully automated detection of human skin burn injuries in vivo, with the goal of automatic surgical margin assessment based on optical coherence tomography (OCT) images. Our proposed automated procedure entails building a machine-learning-based classifier by extracting quantitative features from normal and burn tissue images recorded by OCT. In this study, 56 samples (28 normal, 28 burned) were imaged by OCT and eight features were extracted. A linear model classifier was trained using 34 samples and 22 samples were used to test the model. Sensitivity of 91.6% and specificity of 90% were obtained. Our results demonstrate the capability of a computer-aided technique for accurately and automatically identifying burn tissue resection margins during surgical treatment.
Adapting the γ-H2AX assay for automated processing in human lymphocytes. 1. Technological aspects.

PubMed

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

NASA Astrophysics Data System (ADS)

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.
21 CFR 866.1645 - Fully automated short-term incubation cycle antimicrobial susceptibility system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Fully automated short-term incubation cycle... Diagnostic Devices § 866.1645 Fully automated short-term incubation cycle antimicrobial susceptibility system. (a) Identification. A fully automated short-term incubation cycle antimicrobial susceptibility system...
Automated finite element modeling of the lumbar spine: Using a statistical shape model to generate a virtual population of models.

PubMed

Campbell, J Q; Petrella, A J

2016-09-06

Population-based modeling of the lumbar spine has the potential to be a powerful clinical tool. However, developing a fully parameterized model of the lumbar spine with accurate geometry has remained a challenge. The current study used automated methods for landmark identification to create a statistical shape model of the lumbar spine. The shape model was evaluated using compactness, generalization ability, and specificity. The primary shape modes were analyzed visually, quantitatively, and biomechanically. The biomechanical analysis was performed by using the statistical shape model with an automated method for finite element model generation to create a fully parameterized finite element model of the lumbar spine. Functional finite element models of the mean shape and the extreme shapes (±3 standard deviations) of all 17 shape modes were created demonstrating the robust nature of the methods. This study represents an advancement in finite element modeling of the lumbar spine and will allow population-based modeling in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.
The role of 3-D interactive visualization in blind surveys of H I in galaxies

NASA Astrophysics Data System (ADS)

Punzo, D.; van der Hulst, J. M.; Roerdink, J. B. T. M.; Oosterloo, T. A.; Ramatsoku, M.; Verheijen, M. A. W.

2015-09-01

Upcoming H I surveys will deliver large datasets, and automated processing using the full 3-D information (two positional dimensions and one spectral dimension) to find and characterize H I objects is imperative. In this context, visualization is an essential tool for enabling qualitative and quantitative human control on an automated source finding and analysis pipeline. We discuss how Visual Analytics, the combination of automated data processing and human reasoning, creativity and intuition, supported by interactive visualization, enables flexible and fast interaction with the 3-D data, helping the astronomer to deal with the analysis of complex sources. 3-D visualization, coupled to modeling, provides additional capabilities helping the discovery and analysis of subtle structures in the 3-D domain. The requirements for a fully interactive visualization tool are: coupled 1-D/2-D/3-D visualization, quantitative and comparative capabilities, combined with supervised semi-automated analysis. Moreover, the source code must have the following characteristics for enabling collaborative work: open, modular, well documented, and well maintained. We review four state of-the-art, 3-D visualization packages assessing their capabilities and feasibility for use in the case of 3-D astronomical data.
A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology

PubMed Central

Tang, Xiaoying; Luo, Yuan; Chen, Zhibin; Huang, Nianwei; Johnson, Hans J.; Paulsen, Jane S.; Miller, Michael I.

2018-01-01

In this paper, we present a fully-automated subcortical and ventricular shape generation pipeline that acts on structural magnetic resonance images (MRIs) of the human brain. Principally, the proposed pipeline consists of three steps: (1) automated structure segmentation using the diffeomorphic multi-atlas likelihood-fusion algorithm; (2) study-specific shape template creation based on the Delaunay triangulation; (3) deformation-based shape filtering using the large deformation diffeomorphic metric mapping for surfaces. The proposed pipeline is shown to provide high accuracy, sufficient smoothness, and accurate anatomical topology. Two datasets focused upon Huntington's disease (HD) were used for evaluating the performance of the proposed pipeline. The first of these contains a total of 16 MRI scans, each with a gold standard available, on which the proposed pipeline's outputs were observed to be highly accurate and smooth when compared with the gold standard. Visual examinations and outlier analyses on the second dataset, which contains a total of 1,445 MRI scans, revealed 100% success rates for the putamen, the thalamus, the globus pallidus, the amygdala, and the lateral ventricle in both hemispheres and rates no smaller than 97% for the bilateral hippocampus and caudate. Another independent dataset, consisting of 15 atlas images and 20 testing images, was also used to quantitatively evaluate the proposed pipeline, with high accuracy having been obtained. In short, the proposed pipeline is herein demonstrated to be effective, both quantitatively and qualitatively, using a large collection of MRI scans. PMID:29867332
A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology.

PubMed

Tang, Xiaoying; Luo, Yuan; Chen, Zhibin; Huang, Nianwei; Johnson, Hans J; Paulsen, Jane S; Miller, Michael I

2018-01-01

In this paper, we present a fully-automated subcortical and ventricular shape generation pipeline that acts on structural magnetic resonance images (MRIs) of the human brain. Principally, the proposed pipeline consists of three steps: (1) automated structure segmentation using the diffeomorphic multi-atlas likelihood-fusion algorithm; (2) study-specific shape template creation based on the Delaunay triangulation; (3) deformation-based shape filtering using the large deformation diffeomorphic metric mapping for surfaces. The proposed pipeline is shown to provide high accuracy, sufficient smoothness, and accurate anatomical topology. Two datasets focused upon Huntington's disease (HD) were used for evaluating the performance of the proposed pipeline. The first of these contains a total of 16 MRI scans, each with a gold standard available, on which the proposed pipeline's outputs were observed to be highly accurate and smooth when compared with the gold standard. Visual examinations and outlier analyses on the second dataset, which contains a total of 1,445 MRI scans, revealed 100% success rates for the putamen, the thalamus, the globus pallidus, the amygdala, and the lateral ventricle in both hemispheres and rates no smaller than 97% for the bilateral hippocampus and caudate. Another independent dataset, consisting of 15 atlas images and 20 testing images, was also used to quantitatively evaluate the proposed pipeline, with high accuracy having been obtained. In short, the proposed pipeline is herein demonstrated to be effective, both quantitatively and qualitatively, using a large collection of MRI scans.
In vivo automated quantification of quality of apples during storage using optical coherence tomography images

NASA Astrophysics Data System (ADS)

Srivastava, Vishal; Dalal, Devjyoti; Kumar, Anuj; Prakash, Surya; Dalal, Krishna

2018-06-01

Moisture content is an important feature of fruits and vegetables. As 80% of apple content is water, so decreasing the moisture content will degrade the quality of apples (Golden Delicious). The computational and texture features of the apples were extracted from optical coherence tomography (OCT) images. A support vector machine with a Gaussian kernel model was used to perform automated classification. To evaluate the quality of wax coated apples during storage in vivo, our proposed method opens up the possibility of fully automated quantitative analysis based on the morphological features of apples. Our results demonstrate that the analysis of the computational and texture features of OCT images may be a good non-destructive method for the assessment of the quality of apples.
Automated solid-phase extraction of herbicides from water for gas chromatographic-mass spectrometric analysis

USGS Publications Warehouse

Meyer, M.T.; Mills, M.S.; Thurman, E.M.

1993-01-01

An automated solid-phase extraction (SPE) method was developed for the pre-concentration of chloroacetanilide and triazine herbicides, and two triazine metabolites from 100-ml water samples. Breakthrough experiments for the C18 SPE cartridge show that the two triazine metabolites are not fully retained and that increasing flow-rate decreases their retention. Standard curve r2 values of 0.998-1.000 for each compound were consistently obtained and a quantitation level of 0.05 ??g/l was achieved for each compound tested. More than 10,000 surface and ground water samples have been analyzed by this method.
Improved automated lumen contour detection by novel multifrequency processing algorithm with current intravascular ultrasound system.

PubMed

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.
TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

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

Young, S; Lo, P; Hoffman, J

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 modulesmore » 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 of acquisition and reconstruction parameters present in the clinical environment. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.« less
Automated extraction of lysergic acid diethylamide (LSD) and N-demethyl-LSD from blood, serum, plasma, and urine samples using the Zymark RapidTrace with LC/MS/MS confirmation.

PubMed

de Kanel, J; Vickery, W E; Waldner, B; Monahan, R M; Diamond, F X

1998-05-01

A forensic procedure for the quantitative confirmation of lysergic acid diethylamide (LSD) and the qualitative confirmation of its metabolite, N-demethyl-LSD, in blood, serum, plasma, and urine samples is presented. The Zymark RapidTrace was used to perform fully automated solid-phase extractions of all specimen types. After extract evaporation, confirmations were performed using liquid chromatography (LC) followed by positive electrospray ionization (ESI+) mass spectrometry/mass spectrometry (MS/MS) without derivatization. Quantitation of LSD was accomplished using LSD-d3 as an internal standard. The limit of quantitation (LOQ) for LSD was 0.05 ng/mL. The limit of detection (LOD) for both LSD and N-demethyl-LSD was 0.025 ng/mL. The recovery of LSD was greater than 95% at levels of 0.1 ng/mL and 2.0 ng/mL. For LSD at 1.0 ng/mL, the within-run and between-run (different day) relative standard deviation (RSD) was 2.2% and 4.4%, respectively.
A sensitive and rapid assay for 4-aminophenol in paracetamol drug and tablet formulation, by flow injection analysis with spectrophotometric detection.

PubMed

Bloomfield, M S

2002-12-06

4-Aminophenol (4AP) is the primary degradation product of paracetamol which is limited at a low level (50 ppm or 0.005% w/w) in the drug substance by the European, United States, British and German Pharmacopoeias, employing a manual colourimetric limit test. The 4AP limit is widened to 1000 ppm or 0.1% w/w for the tablet product monographs, which quote the use of a less sensitive automated HPLC method. The lower drug substance specification limit is applied to our products, (50 ppm, equivalent to 25 mug 4AP in a tablet containing 500-mg paracetamol) and the pharmacopoeial HPLC assay was not suitable at this low level due to matrix interference. For routine analysis a rapid, automated assay was required. This paper presents a highly sensitive, precise and automated method employing the technique of Flow Injection (FI) analysis to quantitatively assay low levels of this degradant. A solution of the drug substance, or an extract of the tablets, containing 4AP and paracetamol is injected into a solvent carrier stream and merged on-line with alkaline sodium nitroprusside reagent, to form a specific blue derivative which is detected spectrophotometrically at 710 nm. Standard HPLC equipment is used throughout. The procedure is fully quantitative and has been optimised for sensitivity and robustness using a multivariate experimental design (multi-level 'Central Composite' response surface) model. The method has been fully validated and is linear down to 0.01 mug ml(-1). The approach should be applicable to a range of paracetamol products.
Progress in Fully Automated Abdominal CT Interpretation

PubMed Central

Summers, Ronald M.

2016-01-01

OBJECTIVE Automated analysis of abdominal CT has advanced markedly over just the last few years. Fully automated assessment of organs, lymph nodes, adipose tissue, muscle, bowel, spine, and tumors are some examples where tremendous progress has been made. Computer-aided detection of lesions has also improved dramatically. CONCLUSION This article reviews the progress and provides insights into what is in store in the near future for automated analysis for abdominal CT, ultimately leading to fully automated interpretation. PMID:27101207
Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging.

PubMed

Bonekamp, S; Ghosh, P; Crawford, S; Solga, S F; Horska, A; Brancati, F L; Diehl, A M; Smith, S; Clark, J M

2008-01-01

To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results. Feature evaluation and test-retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue. A random sample of 15 obese adults with type 2 diabetes. Axial T1-weighted spin echo images centered at vertebral bodies of L2-L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test-retest reliability. Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test-retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness. Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages.

Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging

PubMed Central

Bonekamp, S; Ghosh, P; Crawford, S; Solga, SF; Horska, A; Brancati, FL; Diehl, AM; Smith, S; Clark, JM

2009-01-01

Objective To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results. Design Feature evaluation and test–retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue. Subjects A random sample of 15 obese adults with type 2 diabetes. Measurements Axial T1-weighted spin echo images centered at vertebral bodies of L2–L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test–retest reliability. Results Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test–retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness. Conclusion Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages. PMID:17700582
Introduction of an automated user-independent quantitative volumetric magnetic resonance imaging breast density measurement system using the Dixon sequence: comparison with mammographic breast density assessment.

PubMed

Wengert, Georg Johannes; Helbich, Thomas H; Vogl, Wolf-Dieter; Baltzer, Pascal; Langs, Georg; Weber, Michael; Bogner, Wolfgang; Gruber, Stephan; Trattnig, Siegfried; Pinker, Katja

2015-02-01

The purposes of this study were to introduce and assess an automated user-independent quantitative volumetric (AUQV) breast density (BD) measurement system on the basis of magnetic resonance imaging (MRI) using the Dixon technique as well as to compare it with qualitative and quantitative mammographic (MG) BD measurements. Forty-three women with normal mammogram results (Breast Imaging Reporting and Data System 1) were included in this institutional review board-approved prospective study. All participants were subjected to BD assessment with MRI using the following sequence with the Dixon technique (echo time/echo time, 6 milliseconds/2.45 milliseconds/2.67 milliseconds; 1-mm isotropic; 3 minutes 38 seconds). To test the reproducibility, a second MRI after patient repositioning was performed. The AUQV magnetic resonance (MR) BD measurement system automatically calculated percentage (%) BD. The qualitative BD assessment was performed using the American College of Radiology Breast Imaging Reporting and Data System BD categories. Quantitative BD was estimated semiautomatically using the thresholding technique Cumulus4. Appropriate statistical tests were used to assess the agreement between the AUQV MR measurements and to compare them with qualitative and quantitative MG BD estimations. The AUQV MR BD measurements were successfully performed in all 43 women. There was a nearly perfect agreement of AUQV MR BD measurements between the 2 MR examinations for % BD (P < 0.001; intraclass correlation coefficient, 0.998) with no significant differences (P = 0.384). The AUQV MR BD measurements were significantly lower than quantitative and qualitative MG BD assessment (P < 0.001). The AUQV MR BD measurement system allows a fully automated, user-independent, robust, reproducible, as well as radiation- and compression-free volumetric quantitative BD assessment through different levels of BD. The AUQV MR BD measurements were significantly lower than the currently used qualitative and quantitative MG-based approaches, implying that the current assessment might overestimate breast density with MG.
Detection of Respiratory Viruses in Sputum from Adults by Use of Automated Multiplex PCR

PubMed Central

Walsh, Edward E.; Formica, Maria A.; Falsey, Ann R.

2014-01-01

Respiratory tract infections (RTI) frequently cause hospital admissions among adults. Diagnostic viral reverse transcriptase PCR (RT-PCR) of nose and throat swabs (NTS) is useful for patient care by informing antiviral use and appropriate isolation. However, automated RT-PCR systems are not amenable to utilizing sputum due to its viscosity. We evaluated a simple method of processing sputum samples in a fully automated respiratory viral panel RT-PCR assay (FilmArray). Archived sputum and NTS samples collected in 2008-2012 from hospitalized adults with RTI were evaluated. A subset of sputum samples positive for 10 common viruses by a uniplex RT-PCR was selected. A sterile cotton-tip swab was dunked in sputum, swirled in 700 μL of sterile water (dunk and swirl method) and tested by the FilmArray assay. Quantitative RT-PCR was performed on “dunked” sputum and NTS samples for influenza A (Flu A), respiratory syncytial virus (RSV), coronavirus OC43 (OC43), and human metapneumovirus (HMPV). Viruses were identified in 31% of 965 illnesses using a uniplex RT-PCR. The sputum sample was the only sample positive for 105 subjects, including 35% (22/64) of influenza cases and significantly increased the diagnostic yield of NTS alone (302/965 [31%] versus 197/965 [20%]; P = 0.0001). Of 108 sputum samples evaluated by the FilmArray assay using the dunk and swirl method, 99 (92%) were positive. Quantitative RT-PCR revealed higher mean viral loads in dunked sputum samples compared to NTS samples for Flu A, RSV, and HMPV (P = 0.0001, P = 0.006, and P = 0.011, respectively). The dunk and swirl method is a simple and practical method for reliably processing sputum samples in a fully automated PCR system. The higher viral loads in sputa may increase detection over NTS testing alone. PMID:25056335
Automated Quantitative Characterization of Retinal Vascular Leakage and Microaneurysms in Ultra-widefield Fluorescein Angiography

PubMed Central

Ehlers, Justis P.; Wang, Kevin; Vasanji, Amit; Hu, Ming; Srivastava, Sunil K.

2017-01-01

Summary Ultra-widefield fluorescein angiography (UWFA) is an emerging imaging modality used to characterize pathology in the retinal vasculature such as microaneurysms (MA) and vascular leakage. Despites its potential value for diagnosis and disease surveillance, objective quantitative assessment of retinal pathology by UWFA is currently limited because it requires laborious manual segmentation by trained human graders. In this report, we describe a novel fully automated software platform, which segments MAs and leakage areas in native and dewarped UWFA images with retinal vascular disease. Comparison of the algorithm to human grader generated gold standards demonstrated significant strong correlations for MA and leakage areas (ICC=0.78-0.87 and ICC=0.70-0.86, respectively, p=2.1×10-7 to 3.5×10-10 and p=7.8×10-6 to 1.3×10-9, respectively). These results suggest the algorithm performs similarly to human graders in MA and leakage segmentation and may be of significant utility in clinical and research settings. PMID:28432113
Data-Driven Surface Traversability Analysis for Mars 2020 Landing Site Selection

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Rothrock, Brandon; Almeida, Eduardo; Ansar, Adnan; Otero, Richard; Huertas, Andres; Heverly, Matthew

2015-01-01

The objective of this paper is three-fold: 1) to describe the engineering challenges in the surface mobility of the Mars 2020 Rover mission that are considered in the landing site selection processs, 2) to introduce new automated traversability analysis capabilities, and 3) to present the preliminary analysis results for top candidate landing sites. The analysis capabilities presented in this paper include automated terrain classification, automated rock detection, digital elevation model (DEM) generation, and multi-ROI (region of interest) route planning. These analysis capabilities enable to fully utilize the vast volume of high-resolution orbiter imagery, quantitatively evaluate surface mobility requirements for each candidate site, and reject subjectivity in the comparison between sites in terms of engineering considerations. The analysis results supported the discussion in the Second Landing Site Workshop held in August 2015, which resulted in selecting eight candidate sites that will be considered in the third workshop.
Automated Quantitative Analysis of Retinal Microvasculature in Normal Eyes on Optical Coherence Tomography Angiography.

PubMed

Lupidi, Marco; Coscas, Florence; Cagini, Carlo; Fiore, Tito; Spaccini, Elisa; Fruttini, Daniela; Coscas, Gabriel

2016-09-01

To describe a new automated quantitative technique for displaying and analyzing macular vascular perfusion using optical coherence tomography angiography (OCT-A) and to determine a normative data set, which might be used as reference in identifying progressive changes due to different retinal vascular diseases. Reliability study. A retrospective review of 47 eyes of 47 consecutive healthy subjects imaged with a spectral-domain OCT-A device was performed in a single institution. Full-spectrum amplitude-decorrelation angiography generated OCT angiograms of the retinal superficial and deep capillary plexuses. A fully automated custom-built software was used to provide quantitative data on the foveal avascular zone (FAZ) features and the total vascular and avascular surfaces. A comparative analysis between central macular thickness (and volume) and FAZ metrics was performed. Repeatability and reproducibility were also assessed in order to establish the feasibility and reliability of the method. The comparative analysis between the superficial capillary plexus and the deep capillary plexus revealed a statistically significant difference (P < .05) in terms of FAZ perimeter, surface, and major axis and a not statistically significant difference (P > .05) when considering total vascular and avascular surfaces. A linear correlation was demonstrated between central macular thickness (and volume) and the FAZ surface. Coefficients of repeatability and reproducibility were less than 0.4, thus demonstrating high intraobserver repeatability and interobserver reproducibility for all the examined data. A quantitative approach on retinal vascular perfusion, which is visible on Spectralis OCT angiography, may offer an objective and reliable method for monitoring disease progression in several retinal vascular diseases. Copyright © 2016 Elsevier Inc. All rights reserved.
Hematocrit-Independent Quantitation of Stimulants in Dried Blood Spots: Pipet versus Microfluidic-Based Volumetric Sampling Coupled with Automated Flow-Through Desorption and Online Solid Phase Extraction-LC-MS/MS Bioanalysis.

PubMed

Verplaetse, Ruth; Henion, Jack

2016-07-05

A workflow overcoming microsample collection issues and hematocrit (HCT)-related bias would facilitate more widespread use of dried blood spots (DBS). This report describes comparative results between the use of a pipet and a microfluidic-based sampling device for the creation of volumetric DBS. Both approaches were successfully coupled to HCT-independent, fully automated sample preparation and online liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis allowing detection of five stimulants in finger prick blood. Reproducible, selective, accurate, and precise responses meeting generally accepted regulated bioanalysis guidelines were observed over the range of 5-1000 ng/mL whole blood. The applied heated flow-through solvent desorption of the entire spot and online solid phase extraction (SPE) procedure were unaffected by the blood's HCT value within the tested range of 28.0-61.5% HCT. Enhanced stability for mephedrone on DBS compared to liquid whole blood was observed. Finger prick blood samples were collected using both volumetric sampling approaches over a time course of 25 h after intake of a single oral dose of phentermine. A pharmacokinetic curve for the incurred phentermine was successfully produced using the described validated method. These results suggest that either volumetric sample collection method may be amenable to field-use followed by fully automated, HCT-independent DBS-SPE-LC-MS/MS bioanalysis for the quantitation of these representative controlled substances. Analytical data from DBS prepared with a pipet and microfluidic-based sampling devices were comparable, but the latter is easier to operate, making this approach more suitable for sample collection by unskilled persons.
Automated biphasic morphological assessment of hepatitis B-related liver fibrosis using second harmonic generation microscopy

NASA Astrophysics Data System (ADS)

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 < 0.001). A biphasic scoring method was applied, combining support vector machine and multivariate generalized linear models to assess the early and late stages of fibrosis, respectively, based on these parameters. The verification cohort was used to verify the scoring method, and the area under the receiver operating characteristic curve was >0.82 for liver cirrhosis detection. Since no subjective gradings are needed, interobserver discrepancies could be avoided using this fully automated method.
Automated biphasic morphological assessment of hepatitis B-related liver fibrosis using second harmonic generation microscopy.

PubMed

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

2015-08-11

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 < 0.001). A biphasic scoring method was applied, combining support vector machine and multivariate generalized linear models to assess the early and late stages of fibrosis, respectively, based on these parameters. The verification cohort was used to verify the scoring method, and the area under the receiver operating characteristic curve was >0.82 for liver cirrhosis detection. Since no subjective gradings are needed, interobserver discrepancies could be avoided using this fully automated method.
A high-throughput screening system for barley/powdery mildew interactions based on automated analysis of light micrographs.

PubMed

Ihlow, Alexander; Schweizer, Patrick; Seiffert, Udo

2008-01-23

To find candidate genes that potentially influence the susceptibility or resistance of crop plants to powdery mildew fungi, an assay system based on transient-induced gene silencing (TIGS) as well as transient over-expression in single epidermal cells of barley has been developed. However, this system relies on quantitative microscopic analysis of the barley/powdery mildew interaction and will only become a high-throughput tool of phenomics upon automation of the most time-consuming steps. We have developed a high-throughput screening system based on a motorized microscope which evaluates the specimens fully automatically. A large-scale double-blind verification of the system showed an excellent agreement of manual and automated analysis and proved the system to work dependably. Furthermore, in a series of bombardment experiments an RNAi construct targeting the Mlo gene was included, which is expected to phenocopy resistance mediated by recessive loss-of-function alleles such as mlo5. In most cases, the automated analysis system recorded a shift towards resistance upon RNAi of Mlo, thus providing proof of concept for its usefulness in detecting gene-target effects. Besides saving labor and enabling a screening of thousands of candidate genes, this system offers continuous operation of expensive laboratory equipment and provides a less subjective analysis as well as a complete and enduring documentation of the experimental raw data in terms of digital images. In general, it proves the concept of enabling available microscope hardware to handle challenging screening tasks fully automatically.
Automated determination of arterial input function for DCE-MRI of the prostate

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Chang, Ming-Ching; Gupta, Sandeep

2011-03-01

Prostate cancer is one of the commonest cancers in the world. Dynamic contrast enhanced MRI (DCE-MRI) provides an opportunity for non-invasive diagnosis, staging, and treatment monitoring. Quantitative analysis of DCE-MRI relies on determination of an accurate arterial input function (AIF). Although several methods for automated AIF detection have been proposed in literature, none are optimized for use in prostate DCE-MRI, which is particularly challenging due to large spatial signal inhomogeneity. In this paper, we propose a fully automated method for determining the AIF from prostate DCE-MRI. Our method is based on modeling pixel uptake curves as gamma variate functions (GVF). First, we analytically compute bounds on GVF parameters for more robust fitting. Next, we approximate a GVF for each pixel based on local time domain information, and eliminate the pixels with false estimated AIFs using the deduced upper and lower bounds. This makes the algorithm robust to signal inhomogeneity. After that, according to spatial information such as similarity and distance between pixels, we formulate the global AIF selection as an energy minimization problem and solve it using a message passing algorithm to further rule out the weak pixels and optimize the detected AIF. Our method is fully automated without training or a priori setting of parameters. Experimental results on clinical data have shown that our method obtained promising detection accuracy (all detected pixels inside major arteries), and a very good match with expert traced manual AIF.
ATALARS Operational Requirements: Automated Tactical Aircraft Launch and Recovery System

DOT National Transportation Integrated Search

1988-04-01

The Automated Tactical Aircraft Launch and Recovery System (ATALARS) is a fully automated air traffic management system intended for the military service but is also fully compatible with civil air traffic control systems. This report documents a fir...
Some selected quantitative methods of thermal image analysis in Matlab.

PubMed

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Fully automated bone mineral density assessment from low-dose chest CT

NASA Astrophysics Data System (ADS)

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 < 0.001) strong 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.
Significantly improved precision of cell migration analysis in time-lapse video microscopy through use of a fully automated tracking system

PubMed Central

2010-01-01

Background Cell motility is a critical parameter in many physiological as well as pathophysiological processes. In time-lapse video microscopy, manual cell tracking remains the most common method of analyzing migratory behavior of cell populations. In addition to being labor-intensive, this method is susceptible to user-dependent errors regarding the selection of "representative" subsets of cells and manual determination of precise cell positions. Results We have quantitatively analyzed these error sources, demonstrating that manual cell tracking of pancreatic cancer cells lead to mis-calculation of migration rates of up to 410%. In order to provide for objective measurements of cell migration rates, we have employed multi-target tracking technologies commonly used in radar applications to develop fully automated cell identification and tracking system suitable for high throughput screening of video sequences of unstained living cells. Conclusion We demonstrate that our automatic multi target tracking system identifies cell objects, follows individual cells and computes migration rates with high precision, clearly outperforming manual procedures. PMID:20377897
Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy.

PubMed

Farid, Nikdokht; Girard, Holly M; Kemmotsu, Nobuko; Smith, Michael E; Magda, Sebastian W; Lim, Wei Y; Lee, Roland R; McDonald, Carrie R

2012-08-01

To determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE). This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated by using U.S. Food and Drug Administration-cleared software for automated quantitative MR imaging analysis (NeuroQuant). Results of quantitative MR imaging were compared with visual detection of atrophy, and, when available, with histologic specimens. Receiver operating characteristic analyses were performed to determine the optimal sensitivity and specificity of quantitative MR imaging for detecting HA and asymmetry. A linear classifier with cross validation was used to estimate the ability of quantitative MR imaging to help lateralize the seizure focus. Quantitative MR imaging-derived hippocampal asymmetries discriminated patients with TLE from control subjects with high sensitivity (86.7%-89.5%) and specificity (92.2%-94.1%). When a linear classifier was used to discriminate left versus right TLE, hippocampal asymmetry achieved 94% classification accuracy. Volumetric asymmetries of other subcortical structures did not improve classification. Compared with invasive video electroencephalographic recordings, lateralization accuracy was 88% with quantitative MR imaging and 85% with visual inspection of volumetric MR imaging studies but only 76% with visual inspection of clinical MR imaging studies. Quantitative MR imaging can depict the presence and laterality of HA in TLE with accuracy rates that may exceed those achieved with visual inspection of clinical MR imaging studies. Thus, quantitative MR imaging may enhance standard visual analysis, providing a useful and viable means for translating volumetric analysis into clinical practice.
Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI*

NASA Astrophysics Data System (ADS)

Ringenberg, Jordan; Deo, Makarand; Devabhaktuni, Vijay; Filgueiras-Rama, David; Pizarro, Gonzalo; Ibañez, Borja; Berenfeld, Omer; Boyers, Pamela; Gold, Jeffrey

2012-12-01

This paper presents an automated method to segment left ventricle (LV) tissues from functional and delayed-enhancement (DE) cardiac magnetic resonance imaging (MRI) scans using a sequential multi-step approach. First, a region of interest (ROI) is computed to create a subvolume around the LV using morphological operations and image arithmetic. From the subvolume, the myocardial contours are automatically delineated using difference of Gaussians (DoG) filters and GSV snakes. These contours are used as a mask to identify pathological tissues, such as fibrosis or scar, within the DE-MRI. The presented automated technique is able to accurately delineate the myocardium and identify the pathological tissue in patient sets. The results were validated by two expert cardiologists, and in one set the automated results are quantitatively and qualitatively compared with expert manual delineation. Furthermore, the method is patient-specific, performed on an entire patient MRI series. Thus, in addition to providing a quick analysis of individual MRI scans, the fully automated segmentation method is used for effectively tagging regions in order to reconstruct computerized patient-specific 3D cardiac models. These models can then be used in electrophysiological studies and surgical strategy planning.
Fully Automated Sunspot Detection and Classification Using SDO HMI Imagery in MATLAB

DTIC Science & Technology

2014-03-27

FULLY AUTOMATED SUNSPOT DETECTION AND CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB THESIS Gordon M. Spahr, Second Lieutenant, USAF AFIT-ENP-14-M-34...CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB THESIS Presented to the Faculty Department of Engineering Physics Graduate School of Engineering and Management Air...DISTRIUBUTION UNLIMITED. AFIT-ENP-14-M-34 FULLY AUTOMATED SUNSPOT DETECTION AND CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB Gordon M. Spahr, BS Second
Use of the MagNA Pure LC Automated Nucleic Acid Extraction System followed by Real-Time Reverse Transcription-PCR for Ultrasensitive Quantitation of Hepatitis C Virus RNA

PubMed Central

Cook, Linda; Ng, Ka-Wing; Bagabag, Arthur; Corey, Lawrence; Jerome, Keith R.

2004-01-01

Hepatitis C virus (HCV) infection is an increasing health problem worldwide. Quantitative assays for HCV viral load are valuable in predicting response to therapy and for following treatment efficacy. Unfortunately, most quantitative tests for HCV RNA are limited by poor sensitivity. We have developed a convenient, highly sensitive real-time reverse transcription-PCR assay for HCV RNA. The assay amplifies a portion of the 5′ untranslated region of HCV, which is then quantitated using the TaqMan 7700 detection system. Extraction of viral RNA for our assay is fully automated with the MagNA Pure LC extraction system (Roche). Our assay has a 100% detection rate for samples containing 50 IU of HCV RNA/ml and is linear up to viral loads of at least 109 IU/ml. The assay detects genotypes 1a, 2a, and 3a with equal efficiency. Quantitative results by our assay correlate well with HCV viral load as determined by the Bayer VERSANT HCV RNA 3.0 bDNA assay. In clinical use, our assay is highly reproducible, with high and low control specimens showing a coefficient of variation for the logarithmic result of 2.8 and 7.0%, respectively. The combination of reproducibility, extreme sensitivity, and ease of performance makes this assay an attractive option for routine HCV viral load testing. PMID:15365000
The future of fully automated vehicles : opportunities for vehicle- and ride-sharing, with cost and emissions savings.

DOT National Transportation Integrated Search

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...

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

PubMed Central

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

2015-01-01

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 < 0.001). A biphasic scoring method was applied, combining support vector machine and multivariate generalized linear models to assess the early and late stages of fibrosis, respectively, based on these parameters. The verification cohort was used to verify the scoring method, and the area under the receiver operating characteristic curve was >0.82 for liver cirrhosis detection. Since no subjective gradings are needed, interobserver discrepancies could be avoided using this fully automated method. PMID:26260921
A quality assurance framework for the fully automated and objective evaluation of image quality in cone-beam computed tomography.

PubMed

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 percentage interscan variation of repeated measurements was less than 4% and 1.7% on average for all investigated quality criteria. The NPS-based image noise differed by less than 5% from the conventional standard deviation approach and spatially selective 10% MTF values were well comparable to subjective results obtained with 3D resolution pattern. Determining only transverse spatial resolution and global noise behavior in the central field of measurement turned out to be insufficient. The proposed framework transfers QA routines employed in conventional CT in an advanced version to CBCT for fully automated and time-efficient evaluation of technical equipment. With the modular phantom design, a routine as well as an expert version for assessing IQ is provided. The QA program can be used for arbitrary CT units to evaluate 3D imaging characteristics automatically.
A quality assurance framework for the fully automated and objective evaluation of image quality in cone-beam computed tomography

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

Steiding, Christian; Kolditz, Daniel; Kalender, Willi A., E-mail: willi.kalender@imp.uni-erlangen.de

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, andmore » 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 verified. The maximum percentage interscan variation of repeated measurements was less than 4% and 1.7% on average for all investigated quality criteria. The NPS-based image noise differed by less than 5% from the conventional standard deviation approach and spatially selective 10% MTF values were well comparable to subjective results obtained with 3D resolution pattern. Determining only transverse spatial resolution and global noise behavior in the central field of measurement turned out to be insufficient. Conclusions: The proposed framework transfers QA routines employed in conventional CT in an advanced version to CBCT for fully automated and time-efficient evaluation of technical equipment. With the modular phantom design, a routine as well as an expert version for assessing IQ is provided. The QA program can be used for arbitrary CT units to evaluate 3D imaging characteristics automatically.« less
Fully automated processing of fMRI data in SPM: from MRI scanner to PACS.

PubMed

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.
Optimization and automation of quantitative NMR data extraction.

PubMed

Bernstein, Michael A; Sýkora, Stan; Peng, Chen; Barba, Agustín; Cobas, Carlos

2013-06-18

NMR is routinely used to quantitate chemical species. The necessary experimental procedures to acquire quantitative data are well-known, but relatively little attention has been applied to data processing and analysis. We describe here a robust expert system that can be used to automatically choose the best signals in a sample for overall concentration determination and determine analyte concentration using all accepted methods. The algorithm is based on the complete deconvolution of the spectrum which makes it tolerant of cases where signals are very close to one another and includes robust methods for the automatic classification of NMR resonances and molecule-to-spectrum multiplets assignments. With the functionality in place and optimized, it is then a relatively simple matter to apply the same workflow to data in a fully automatic way. The procedure is desirable for both its inherent performance and applicability to NMR data acquired for very large sample sets.
Integrated Platform for Expedited Synthesis–Purification–Testing of Small Molecule Libraries

PubMed Central

2017-01-01

The productivity of medicinal chemistry programs can be significantly increased through the introduction of automation, leading to shortened discovery cycle times. Herein, we describe a platform that consolidates synthesis, purification, quantitation, dissolution, and testing of small molecule libraries. The system was validated through the synthesis and testing of two libraries of binders of polycomb protein EED, and excellent correlation of obtained data with results generated through conventional approaches was observed. The fully automated and integrated platform enables batch-supported compound synthesis based on a broad array of chemical transformations with testing in a variety of biochemical assay formats. A library turnaround time of between 24 and 36 h was achieved, and notably, each library synthesis produces sufficient amounts of compounds for further evaluation in secondary assays thereby contributing significantly to the shortening of medicinal chemistry discovery cycles. PMID:28435537
An Automated Solar Synoptic Analysis Software System

NASA Astrophysics Data System (ADS)

Hong, S.; Lee, S.; Oh, S.; Kim, J.; Lee, J.; Kim, Y.; Lee, J.; Moon, Y.; Lee, D.

2012-12-01

We have developed an automated software system of identifying solar active regions, filament channels, and coronal holes, those are three major solar sources causing the space weather. Space weather forecasters of NOAA Space Weather Prediction Center produce the solar synoptic drawings as a daily basis to predict solar activities, i.e., solar flares, filament eruptions, high speed solar wind streams, and co-rotating interaction regions as well as their possible effects to the Earth. As an attempt to emulate this process with a fully automated and consistent way, we developed a software system named ASSA(Automated Solar Synoptic Analysis). When identifying solar active regions, ASSA uses high-resolution SDO HMI intensitygram and magnetogram as inputs and providing McIntosh classification and Mt. Wilson magnetic classification of each active region by applying appropriate image processing techniques such as thresholding, morphology extraction, and region growing. At the same time, it also extracts morphological and physical properties of active regions in a quantitative way for the short-term prediction of flares and CMEs. When identifying filament channels and coronal holes, images of global H-alpha network and SDO AIA 193 are used for morphological identification and also SDO HMI magnetograms for quantitative verification. The output results of ASSA are routinely checked and validated against NOAA's daily SRS(Solar Region Summary) and UCOHO(URSIgram code for coronal hole information). A couple of preliminary scientific results are to be presented using available output results. ASSA will be deployed at the Korean Space Weather Center and serve its customers in an operational status by the end of 2012.
Autoreject: Automated artifact rejection for MEG and EEG data.

PubMed

Jas, Mainak; Engemann, Denis A; Bekhti, Yousra; Raimondo, Federico; Gramfort, Alexandre

2017-10-01

We present an automated algorithm for unified rejection and repair of bad trials in magnetoencephalography (MEG) and electroencephalography (EEG) signals. Our method capitalizes on cross-validation in conjunction with a robust evaluation metric to estimate the optimal peak-to-peak threshold - a quantity commonly used for identifying bad trials in M/EEG. This approach is then extended to a more sophisticated algorithm which estimates this threshold for each sensor yielding trial-wise bad sensors. Depending on the number of bad sensors, the trial is then repaired by interpolation or by excluding it from subsequent analysis. All steps of the algorithm are fully automated thus lending itself to the name Autoreject. In order to assess the practical significance of the algorithm, we conducted extensive validation and comparisons with state-of-the-art methods on four public datasets containing MEG and EEG recordings from more than 200 subjects. The comparisons include purely qualitative efforts as well as quantitatively benchmarking against human supervised and semi-automated preprocessing pipelines. The algorithm allowed us to automate the preprocessing of MEG data from the Human Connectome Project (HCP) going up to the computation of the evoked responses. The automated nature of our method minimizes the burden of human inspection, hence supporting scalability and reliability demanded by data analysis in modern neuroscience. Copyright © 2017 Elsevier Inc. All rights reserved.
Quantitative diagnostic performance of myocardial perfusion SPECT with attenuation correction in women.

PubMed

Wolak, Arik; Slomka, Piotr J; Fish, Mathews B; Lorenzo, Santiago; Berman, Daniel S; Germano, Guido

2008-06-01

Attenuation correction (AC) for myocardial perfusion SPECT (MPS) had not been evaluated separately in women despite specific considerations in this group because of breast photon attenuation. We aimed to evaluate the performance of AC in women by using automated quantitative analysis of MPS to avoid any bias. Consecutive female patients--134 with a low likelihood (LLk) of coronary artery disease (CAD) and 114 with coronary angiography performed within less than 3 mo of MPS--who were referred for rest-stress electrocardiography-gated 99mTc-sestamibi MPS with AC were considered. Imaging data were evaluated for contour quality control. An additional 50 LLk studies in women were used to create equivalent normal limits for studies with AC and with no correction (NC). An experienced technologist unaware of the angiography and other results performed the contour quality control. All other processing was performed in a fully automated manner. Quantitative analysis was performed with the Cedars-Sinai myocardial perfusion analysis package. All automated segmental analyses were performed with the 17-segment, 5-point American Heart Association model. Summed stress scores (SSS) of > or =3 were considered abnormal. CAD (> or =70% stenosis) was present in 69 of 114 patients (60%). The normalcy rates were 93% for both NC and AC studies. The SSS for patients with CAD and without CAD for NC versus AC were 10.0 +/- 9.0 (mean +/- SD) versus 10.2 +/- 8.5 and 1.6 +/- 2.3 versus 1.8 +/- 2.5, respectively; P was not significant (NS) for all comparisons of NC versus AC. The SSS for LLk patients for NC versus AC were 0.51 +/- 1.0 versus 0.6 +/- 1.1, respectively; P was NS. The specificity for both NC and AC was 73%. The sensitivities for NC and AC were 80% and 81%, respectively, and the accuracies for NC and AC were 77% and 78%, respectively; P was NS for both comparisons. There are no significant diagnostic differences between automated quantitative MPS analyses performed in studies processed with and without AC in women.
Quantitative Analysis of Mouse Retinal Layers Using Automated Segmentation of Spectral Domain Optical Coherence Tomography Images

PubMed Central

Dysli, Chantal; Enzmann, Volker; Sznitman, Raphael; Zinkernagel, Martin S.

2015-01-01

Purpose Quantification of retinal layers using automated segmentation of optical coherence tomography (OCT) images allows for longitudinal studies of retinal and neurological disorders in mice. The purpose of this study was to compare the performance of automated retinal layer segmentation algorithms with data from manual segmentation in mice using the Spectralis OCT. Methods Spectral domain OCT images from 55 mice from three different mouse strains were analyzed in total. The OCT scans from 22 C57Bl/6, 22 BALBc, and 11 C3A.Cg-Pde6b+Prph2Rd2/J mice were automatically segmented using three commercially available automated retinal segmentation algorithms and compared to manual segmentation. Results Fully automated segmentation performed well in mice and showed coefficients of variation (CV) of below 5% for the total retinal volume. However, all three automated segmentation algorithms yielded much thicker total retinal thickness values compared to manual segmentation data (P < 0.0001) due to segmentation errors in the basement membrane. Conclusions Whereas the automated retinal segmentation algorithms performed well for the inner layers, the retinal pigmentation epithelium (RPE) was delineated within the sclera, leading to consistently thicker measurements of the photoreceptor layer and the total retina. Translational Relevance The introduction of spectral domain OCT allows for accurate imaging of the mouse retina. Exact quantification of retinal layer thicknesses in mice is important to study layers of interest under various pathological conditions. PMID:26336634
Computer-aided endovascular aortic repair using fully automated two- and three-dimensional fusion imaging.

PubMed

Panuccio, Giuseppe; Torsello, Giovanni Federico; Pfister, Markus; Bisdas, Theodosios; Bosiers, Michel J; Torsello, Giovanni; Austermann, Martin

2016-12-01

To assess the usability of a fully automated fusion imaging engine prototype, matching preinterventional computed tomography with intraoperative fluoroscopic angiography during endovascular aortic repair. From June 2014 to February 2015, all patients treated electively for abdominal and thoracoabdominal aneurysms were enrolled prospectively. Before each procedure, preoperative planning was performed with a fully automated fusion engine prototype based on computed tomography angiography, creating a mesh model of the aorta. In a second step, this three-dimensional dataset was registered with the two-dimensional intraoperative fluoroscopy. The main outcome measure was the applicability of the fully automated fusion engine. Secondary outcomes were freedom from failure of automatic segmentation or of the automatic registration as well as accuracy of the mesh model, measuring deviations from intraoperative angiography in millimeters, if applicable. Twenty-five patients were enrolled in this study. The fusion imaging engine could be used in successfully 92% of the cases (n = 23). Freedom from failure of automatic segmentation was 44% (n = 11). The freedom from failure of the automatic registration was 76% (n = 19), the median error of the automatic registration process was 0 mm (interquartile range, 0-5 mm). The fully automated fusion imaging engine was found to be applicable in most cases, albeit in several cases a fully automated data processing was not possible, requiring manual intervention. The accuracy of the automatic registration yielded excellent results and promises a useful and simple to use technology. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.
Fully-automated segmentation of fluid regions in exudative age-related macular degeneration subjects: Kernel graph cut in neutrosophic domain

PubMed Central

Rashno, Abdolreza; Nazari, Behzad; Koozekanani, Dara D.; Drayna, Paul M.; Sadri, Saeed; Rabbani, Hossein

2017-01-01

A fully-automated method based on graph shortest path, graph cut and neutrosophic (NS) sets is presented for fluid segmentation in OCT volumes for exudative age related macular degeneration (EAMD) subjects. The proposed method includes three main steps: 1) The inner limiting membrane (ILM) and the retinal pigment epithelium (RPE) layers are segmented using proposed methods based on graph shortest path in NS domain. A flattened RPE boundary is calculated such that all three types of fluid regions, intra-retinal, sub-retinal and sub-RPE, are located above it. 2) Seed points for fluid (object) and tissue (background) are initialized for graph cut by the proposed automated method. 3) A new cost function is proposed in kernel space, and is minimized with max-flow/min-cut algorithms, leading to a binary segmentation. Important properties of the proposed steps are proven and quantitative performance of each step is analyzed separately. The proposed method is evaluated using a publicly available dataset referred as Optima and a local dataset from the UMN clinic. For fluid segmentation in 2D individual slices, the proposed method outperforms the previously proposed methods by 18%, 21% with respect to the dice coefficient and sensitivity, respectively, on the Optima dataset, and by 16%, 11% and 12% with respect to the dice coefficient, sensitivity and precision, respectively, on the local UMN dataset. Finally, for 3D fluid volume segmentation, the proposed method achieves true positive rate (TPR) and false positive rate (FPR) of 90% and 0.74%, respectively, with a correlation of 95% between automated and expert manual segmentations using linear regression analysis. PMID:29059257
Temporal Lobe Epilepsy: Quantitative MR Volumetry in Detection of Hippocampal Atrophy

PubMed Central

Farid, Nikdokht; Girard, Holly M.; Kemmotsu, Nobuko; Smith, Michael E.; Magda, Sebastian W.; Lim, Wei Y.; Lee, Roland R.

2012-01-01

Purpose: To determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE). Materials and Methods: This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated by using U.S. Food and Drug Administration–cleared software for automated quantitative MR imaging analysis (NeuroQuant). Results of quantitative MR imaging were compared with visual detection of atrophy, and, when available, with histologic specimens. Receiver operating characteristic analyses were performed to determine the optimal sensitivity and specificity of quantitative MR imaging for detecting HA and asymmetry. A linear classifier with cross validation was used to estimate the ability of quantitative MR imaging to help lateralize the seizure focus. Results: Quantitative MR imaging–derived hippocampal asymmetries discriminated patients with TLE from control subjects with high sensitivity (86.7%–89.5%) and specificity (92.2%–94.1%). When a linear classifier was used to discriminate left versus right TLE, hippocampal asymmetry achieved 94% classification accuracy. Volumetric asymmetries of other subcortical structures did not improve classification. Compared with invasive video electroencephalographic recordings, lateralization accuracy was 88% with quantitative MR imaging and 85% with visual inspection of volumetric MR imaging studies but only 76% with visual inspection of clinical MR imaging studies. Conclusion: Quantitative MR imaging can depict the presence and laterality of HA in TLE with accuracy rates that may exceed those achieved with visual inspection of clinical MR imaging studies. Thus, quantitative MR imaging may enhance standard visual analysis, providing a useful and viable means for translating volumetric analysis into clinical practice. © RSNA, 2012 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12112638/-/DC1 PMID:22723496
Parallel solution-phase synthesis of a 2-aminothiazole library including fully automated work-up.

PubMed

Buchstaller, Hans-Peter; Anlauf, Uwe

2011-02-01

A straightforward and effective procedure for the solution phase preparation of a 2-aminothiazole combinatorial library is described. Reaction, work-up and isolation of the title compounds as free bases was accomplished in a fully automated fashion using the Chemspeed ASW 2000 automated synthesizer. The compounds were obtained in good yields and excellent purities without any further purification procedure.
Does bacteriology laboratory automation reduce time to results and increase quality management?

PubMed

Dauwalder, O; Landrieve, L; Laurent, F; de Montclos, M; Vandenesch, F; Lina, G

2016-03-01

Due to reductions in financial and human resources, many microbiological laboratories have merged to build very large clinical microbiology laboratories, which allow the use of fully automated laboratory instruments. For clinical chemistry and haematology, automation has reduced the time to results and improved the management of laboratory quality. The aim of this review was to examine whether fully automated laboratory instruments for microbiology can reduce time to results and impact quality management. This study focused on solutions that are currently available, including the BD Kiestra™ Work Cell Automation and Total Lab Automation and the Copan WASPLab(®). Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES.

PubMed

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.
What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.

PubMed

Hamzeiy, Hamid; Cox, Jürgen

2017-02-01

Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Automated volumetric evaluation of stereoscopic disc photography

PubMed Central

Xu, Juan; Ishikawa, Hiroshi; Wollstein, Gadi; Bilonick, Richard A; Kagemann, Larry; Craig, Jamie E; Mackey, David A; Hewitt, Alex W; Schuman, Joel S

2010-01-01

PURPOSE: To develop a fully automated algorithm (AP) to perform a volumetric measure of the optic disc using conventional stereoscopic optic nerve head (ONH) photographs, and to compare algorithm-produced parameters with manual photogrammetry (MP), scanning laser ophthalmoscope (SLO) and optical coherence tomography (OCT) measurements. METHODS: One hundred twenty-two stereoscopic optic disc photographs (61 subjects) were analyzed. Disc area, rim area, cup area, cup/disc area ratio, vertical cup/disc ratio, rim volume and cup volume were automatically computed by the algorithm. Latent variable measurement error models were used to assess measurement reproducibility for the four techniques. RESULTS: AP had better reproducibility for disc area and cup volume and worse reproducibility for cup/disc area ratio and vertical cup/disc ratio, when the measurements were compared to the MP, SLO and OCT methods. CONCLUSION: AP provides a useful technique for an objective quantitative assessment of 3D ONH structures. PMID:20588996
An Algorithm to Automate Yeast Segmentation and Tracking

PubMed Central

Doncic, Andreas; Eser, Umut; Atay, Oguzhan; Skotheim, Jan M.

2013-01-01

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation. PMID:23520484
Breast Density Estimation with Fully Automated Volumetric Method: Comparison to Radiologists' Assessment by BI-RADS Categories.

PubMed

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 < 0.001). A significant positive correlation was found between BI-RADS categories and volumetric density grading by fully automated software (ρ = 0.728, P < 0.001 for first radiologist and ρ = 0.725, P < 0.001 for second radiologist). Pairwise estimates of the weighted kappa between Volpara density grade and 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.

A Fully Automated Microfluidic Femtosecond Laser Axotomy Platform for Nerve Regeneration Studies in C. elegans

PubMed Central

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. PMID:25470130
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.

PubMed

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-based volumetry allows detection of regional grey matter volume loss that correlates with neuropsychological performance in patients with amnestic MCI or mild AD. Because of the high level of automation, MRI-based volumetry may easily be integrated into clinical routine to complement the current diagnostic procedure.
Comparison of manual & automated analysis methods for corneal endothelial cell density measurements by specular microscopy.

PubMed

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.
Extended Field Laser Confocal Microscopy (EFLCM): Combining automated Gigapixel image capture with in silico virtual microscopy

PubMed Central

Flaberg, Emilie; Sabelström, Per; Strandh, Christer; Szekely, Laszlo

2008-01-01

Background Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture. Methods Using the combination of microlens enhanced Nipkow spinning disc confocal illumination together with fully automated image capture and large scale in silico image processing we have developed a system allowing the acquisition, presentation and analysis of maximum resolution confocal panorama images of several Gigapixel size. We call the method Extended Field Laser Confocal Microscopy (EFLCM). Results We show using the EFLCM technique that it is possible to create a continuous confocal multi-colour mosaic from thousands of individually captured images. EFLCM can digitize and analyze histological slides, sections of entire rodent organ and full size embryos. It can also record hundreds of thousands cultured cells at multiple wavelength in single event or time-lapse fashion on fixed slides, in live cell imaging chambers or microtiter plates. Conclusion The observer independent image capture of EFLCM allows quantitative measurements of fluorescence intensities and morphological parameters on a large number of cells. EFLCM therefore bridges the gap between the mainly illustrative fluorescence microscopy and purely quantitative flow cytometry. EFLCM can also be used as high content analysis (HCA) instrument for automated screening processes. PMID:18627634
Extended Field Laser Confocal Microscopy (EFLCM): combining automated Gigapixel image capture with in silico virtual microscopy.

PubMed

Flaberg, Emilie; Sabelström, Per; Strandh, Christer; Szekely, Laszlo

2008-07-16

Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture. Using the combination of microlens enhanced Nipkow spinning disc confocal illumination together with fully automated image capture and large scale in silico image processing we have developed a system allowing the acquisition, presentation and analysis of maximum resolution confocal panorama images of several Gigapixel size. We call the method Extended Field Laser Confocal Microscopy (EFLCM). We show using the EFLCM technique that it is possible to create a continuous confocal multi-colour mosaic from thousands of individually captured images. EFLCM can digitize and analyze histological slides, sections of entire rodent organ and full size embryos. It can also record hundreds of thousands cultured cells at multiple wavelength in single event or time-lapse fashion on fixed slides, in live cell imaging chambers or microtiter plates. The observer independent image capture of EFLCM allows quantitative measurements of fluorescence intensities and morphological parameters on a large number of cells. EFLCM therefore bridges the gap between the mainly illustrative fluorescence microscopy and purely quantitative flow cytometry. EFLCM can also be used as high content analysis (HCA) instrument for automated screening processes.
Development of a fully automated software system for rapid analysis/processing of the falling weight deflectometer data.

DOT National Transportation Integrated Search

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...
New fully automated software for assessment of brachial artery flow- mediated dilation with advantages of continuous measurement.

PubMed

Ercan, Ertuğrul; Kırılmaz, Bahadır; Kahraman, İsmail; Bayram, Vildan; Doğan, Hüseyin

2012-11-01

Flow-mediated dilation (FMD) is used to evaluate endothelial functions. Computer-assisted analysis utilizing edge detection permits continuous measurements along the vessel wall. We have developed a new fully automated software program to allow accurate and reproducible measurement. FMD has been measured and analyzed in 18 coronary artery disease (CAD) patients and 17 controls both by manually and by the software developed (computer supported) methods. The agreement between methods was assessed by Bland-Altman analysis. The mean age, body mass index and cardiovascular risk factors were higher in CAD group. Automated FMD% measurement for the control subjects was 18.3±8.5 and 6.8±6.5 for the CAD group (p=0.0001). The intraobserver and interobserver correlation for automated measurement was high (r=0.974, r=0.981, r=0.937, r=0.918, respectively). Manual FMD% at 60th second was correlated with automated FMD % (r=0.471, p=0.004). The new fully automated software© can be used to precise measurement of FMD with low intra- and interobserver variability than manual assessment.
Receiver-operating-characteristic analysis of an automated program for analyzing striatal uptake of 123I-ioflupane SPECT images: calibration using visual reads.

PubMed

Kuo, Phillip Hsin; Avery, Ryan; Krupinski, Elizabeth; Lei, Hong; Bauer, Adam; Sherman, Scott; McMillan, Natalie; Seibyl, John; Zubal, George

2013-03-01

A fully automated objective striatal analysis (OSA) program that quantitates dopamine transporter uptake in subjects with suspected Parkinson's disease was applied to images from clinical (123)I-ioflupane studies. The striatal binding ratios or alternatively the specific binding ratio (SBR) of the lowest putamen uptake was computed, and receiver-operating-characteristic (ROC) analysis was applied to 94 subjects to determine the best discriminator using this quantitative method. Ninety-four (123)I-ioflupane SPECT scans were analyzed from patients referred to our clinical imaging department and were reconstructed using the manufacturer-supplied reconstruction and filtering parameters for the radiotracer. Three trained readers conducted independent visual interpretations and reported each case as either normal or showing dopaminergic deficit (abnormal). The same images were analyzed using the OSA software, which locates the striatal and occipital structures and places regions of interest on the caudate and putamen. Additionally, the OSA places a region of interest on the occipital region that is used to calculate the background-subtracted SBR. The lower SBR of the 2 putamen regions was taken as the quantitative report. The 33 normal (bilateral comma-shaped striata) and 61 abnormal (unilateral or bilateral dopaminergic deficit) studies were analyzed to generate ROC curves. Twenty-nine of the scans were interpreted as normal and 59 as abnormal by all 3 readers. For 12 scans, the 3 readers did not unanimously agree in their interpretations (discordant). The ROC analysis, which used the visual-majority-consensus interpretation from the readers as the gold standard, yielded an area under the curve of 0.958 when using 1.08 as the threshold SBR for the lowest putamen. The sensitivity and specificity of the automated quantitative analysis were 95% and 89%, respectively. The OSA program delivers SBR quantitative values that have a high sensitivity and specificity, compared with visual interpretations by trained nuclear medicine readers. Such a program could be a helpful aid for readers not yet experienced with (123)I-ioflupane SPECT images and if further adapted and validated may be useful to assess disease progression during pharmaceutical testing of therapies.
21 CFR 864.5200 - Automated cell counter.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automated cell counter. 864.5200 Section 864.5200....5200 Automated cell counter. (a) Identification. An automated cell counter is a fully-automated or semi-automated device used to count red blood cells, white blood cells, or blood platelets using a sample of the...
21 CFR 864.5240 - Automated blood cell diluting apparatus.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automated blood cell diluting apparatus. 864.5240... § 864.5240 Automated blood cell diluting apparatus. (a) Identification. An automated blood cell diluting apparatus is a fully automated or semi-automated device used to make appropriate dilutions of a blood sample...
21 CFR 864.5240 - Automated blood cell diluting apparatus.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Automated blood cell diluting apparatus. 864.5240... § 864.5240 Automated blood cell diluting apparatus. (a) Identification. An automated blood cell diluting apparatus is a fully automated or semi-automated device used to make appropriate dilutions of a blood sample...
21 CFR 866.1645 - Fully automated short-term incubation cycle antimicrobial susceptibility system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Fully automated short-term incubation cycle antimicrobial susceptibility system. 866.1645 Section 866.1645 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES IMMUNOLOGY AND MICROBIOLOGY DEVICES...
21 CFR 866.1645 - Fully automated short-term incubation cycle antimicrobial susceptibility system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Fully automated short-term incubation cycle antimicrobial susceptibility system. 866.1645 Section 866.1645 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES IMMUNOLOGY AND MICROBIOLOGY DEVICES...
21 CFR 866.1645 - Fully automated short-term incubation cycle antimicrobial susceptibility system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Fully automated short-term incubation cycle antimicrobial susceptibility system. 866.1645 Section 866.1645 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES IMMUNOLOGY AND MICROBIOLOGY DEVICES...
21 CFR 866.1645 - Fully automated short-term incubation cycle antimicrobial susceptibility system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Fully automated short-term incubation cycle antimicrobial susceptibility system. 866.1645 Section 866.1645 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES IMMUNOLOGY AND MICROBIOLOGY DEVICES...
Confocal nanoscanning, bead picking (CONA): PickoScreen microscopes for automated and quantitative screening of one-bead one-compound libraries.

PubMed

Hintersteiner, Martin; Buehler, Christof; Uhl, Volker; Schmied, Mario; Müller, Jürgen; Kottig, Karsten; Auer, Manfred

2009-01-01

Solid phase combinatorial chemistry provides fast and cost-effective access to large bead based libraries with compound numbers easily exceeding tens of thousands of compounds. Incubating one-bead one-compound library beads with fluorescently labeled target proteins and identifying and isolating the beads which contain a bound target protein, potentially represents one of the most powerful generic primary high throughput screening formats. On-bead screening (OBS) based on this detection principle can be carried out with limited automation. Often hit bead detection, i.e. recognizing beads with a fluorescently labeled protein bound to the compound on the bead, relies on eye-inspection under a wide-field microscope. Using low resolution detection techniques, the identification of hit beads and their ranking is limited by a low fluorescence signal intensity and varying levels of the library beads' autofluorescence. To exploit the full potential of an OBS process, reliable methods for both automated quantitative detection of hit beads and their subsequent isolation are needed. In a joint collaborative effort with Evotec Technologies (now Perkin-Elmer Cellular Technologies Germany GmbH), we have built two confocal bead scanner and picker platforms PS02 and a high-speed variant PS04 dedicated to automated high resolution OBS. The PS0X instruments combine fully automated confocal large area scanning of a bead monolayer at the bottom of standard MTP plates with semiautomated isolation of individual hit beads via hydraulic-driven picker capillaries. The quantification of fluorescence intensities with high spatial resolution in the equatorial plane of each bead allows for a reliable discrimination between entirely bright autofluorescent beads and real hit beads which exhibit an increased fluorescence signal at the outer few micrometers of the bead. The achieved screening speed of up to 200,000 bead assayed in less than 7 h and the picking time of approximately 1 bead/min allow exploitation of one-bead one-compound libraries with high sensitivity, accuracy, and speed.
Automated segmentation of cardiac visceral fat in low-dose non-contrast chest CT images

NASA Astrophysics Data System (ADS)

Xie, Yiting; Liang, Mingzhu; Yankelevitz, David F.; Henschke, Claudia I.; Reeves, Anthony P.

2015-03-01

Cardiac visceral fat was segmented from low-dose non-contrast chest CT images using a fully automated method. Cardiac visceral fat is defined as the fatty tissues surrounding the heart region, enclosed by the lungs and posterior to the sternum. It is measured by constraining the heart region with an Anatomy Label Map that contains robust segmentations of the lungs and other major organs and estimating the fatty tissue within this region. The algorithm was evaluated on 124 low-dose and 223 standard-dose non-contrast chest CT scans from two public datasets. Based on visual inspection, 343 cases had good cardiac visceral fat segmentation. For quantitative evaluation, manual markings of cardiac visceral fat regions were made in 3 image slices for 45 low-dose scans and the Dice similarity coefficient (DSC) was computed. The automated algorithm achieved an average DSC of 0.93. Cardiac visceral fat volume (CVFV), heart region volume (HRV) and their ratio were computed for each case. The correlation between cardiac visceral fat measurement and coronary artery and aortic calcification was also evaluated. Results indicated the automated algorithm for measuring cardiac visceral fat volume may be an alternative method to the traditional manual assessment of thoracic region fat content in the assessment of cardiovascular disease risk.
Fully automated analytical procedure for propofol determination by sequential injection technique with spectrophotometric and fluorimetric detections.

PubMed

Šrámková, Ivana; Amorim, Célia G; Sklenářová, Hana; Montenegro, Maria C B M; Horstkotte, Burkhard; Araújo, Alberto N; Solich, Petr

2014-01-01

In this work, an application of an enzymatic reaction for the determination of the highly hydrophobic drug propofol in emulsion dosage form is presented. Emulsions represent a complex and therefore challenging matrix for analysis. Ethanol was used for breakage of a lipid emulsion, which enabled optical detection. A fully automated method based on Sequential Injection Analysis was developed, allowing propofol determination without the requirement of tedious sample pre-treatment. The method was based on spectrophotometric detection after the enzymatic oxidation catalysed by horseradish peroxidase and subsequent coupling with 4-aminoantipyrine leading to a coloured product with an absorbance maximum at 485 nm. This procedure was compared with a simple fluorimetric method, which was based on the direct selective fluorescence emission of propofol in ethanol at 347 nm. Both methods provide comparable validation parameters with linear working ranges of 0.005-0.100 mg mL(-1) and 0.004-0.243 mg mL(-1) for the spectrophotometric and fluorimetric methods, respectively. The detection and quantitation limits achieved with the spectrophotometric method were 0.0016 and 0.0053 mg mL(-1), respectively. The fluorimetric method provided the detection limit of 0.0013 mg mL(-1) and limit of quantitation of 0.0043 mg mL(-1). The RSD did not exceed 5% and 2% (n=10), correspondingly. A sample throughput of approx. 14 h(-1) for the spectrophotometric and 68 h(-1) for the fluorimetric detection was achieved. Both methods proved to be suitable for the determination of propofol in pharmaceutical formulation with average recovery values of 98.1 and 98.5%. © 2013 Elsevier B.V. All rights reserved.
Anesthesiology, automation, and artificial intelligence.

PubMed

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.
Quantitation of repaglinide and metabolites in mouse whole-body thin tissue sections using droplet-based liquid microjunction surface sampling-high-performance liquid chromatography-electrospray ionization tandem mass spectrometry.

PubMed

Chen, Weiqi; Wang, Lifei; Van Berkel, Gary J; Kertesz, Vilmos; Gan, Jinping

2016-03-25

Herein, quantitation aspects of a fully automated autosampler/HPLC-MS/MS system applied for unattended droplet-based surface sampling of repaglinide dosed thin tissue sections with subsequent HPLC separation and mass spectrometric analysis of parent drug and various drug metabolites were studied. Major organs (brain, lung, liver, kidney and muscle) from whole-body thin tissue sections and corresponding organ homogenates prepared from repaglinide dosed mice were sampled by surface sampling and by bulk extraction, respectively, and analyzed by HPLC-MS/MS. A semi-quantitative agreement between data obtained by surface sampling and that by employing organ homogenate extraction was observed. Drug concentrations obtained by the two methods followed the same patterns for post-dose time points (0.25, 0.5, 1 and 2 h). Drug amounts determined in the specific tissues was typically higher when analyzing extracts from the organ homogenates. In addition, relative comparison of the levels of individual metabolites between the two analytical methods also revealed good semi-quantitative agreement. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitation of repaglinide and metabolites in mouse whole-body thin tissue sections using droplet-based liquid microjunction surface sampling-high-performance liquid chromatography-electrospray ionization tandem mass spectrometry

DOE PAGES

Chen, Weiqi; Wang, Lifei; Van Berkel, Gary J.; ...

2015-11-03

Herein, quantitation aspects of a fully automated autosampler/HPLC-MS/MS system applied for unattended droplet-based surface sampling of repaglinide dosed thin tissue sections with subsequent HPLC separation and mass spectrometric analysis of parent drug and various drug metabolites was studied. Major organs (brain, lung, liver, kidney, muscle) from whole-body thin tissue sections and corresponding organ homogenates prepared from repaglinide dosed mice were sampled by surface sampling and by bulk extraction, respectively, and analyzed by HPLC-MS/MS. A semi-quantitative agreement between data obtained by surface sampling and that by employing organ homogenate extraction was observed. Drug concentrations obtained by the two methods followed themore » same patterns for post-dose time points (0.25, 0.5, 1 and 2 h). Drug amounts determined in the specific tissues was typically higher when analyzing extracts from the organ homogenates. Furthermore, relative comparison of the levels of individual metabolites between the two analytical methods also revealed good semi-quantitative agreement.« less
Quantitation of repaglinide and metabolites in mouse whole-body thin tissue sections using droplet-based liquid microjunction surface sampling-high-performance liquid chromatography-electrospray ionization tandem mass spectrometry

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

Chen, Weiqi; Wang, Lifei; Van Berkel, Gary J.

Herein, quantitation aspects of a fully automated autosampler/HPLC-MS/MS system applied for unattended droplet-based surface sampling of repaglinide dosed thin tissue sections with subsequent HPLC separation and mass spectrometric analysis of parent drug and various drug metabolites was studied. Major organs (brain, lung, liver, kidney, muscle) from whole-body thin tissue sections and corresponding organ homogenates prepared from repaglinide dosed mice were sampled by surface sampling and by bulk extraction, respectively, and analyzed by HPLC-MS/MS. A semi-quantitative agreement between data obtained by surface sampling and that by employing organ homogenate extraction was observed. Drug concentrations obtained by the two methods followed themore » same patterns for post-dose time points (0.25, 0.5, 1 and 2 h). Drug amounts determined in the specific tissues was typically higher when analyzing extracts from the organ homogenates. Furthermore, relative comparison of the levels of individual metabolites between the two analytical methods also revealed good semi-quantitative agreement.« less
21 CFR 864.5200 - Automated cell counter.

Code of Federal Regulations, 2014 CFR

2014-04-01

....5200 Automated cell counter. (a) Identification. An automated cell counter is a fully-automated or semi-automated device used to count red blood cells, white blood cells, or blood platelets using a sample of the patient's peripheral blood (blood circulating in one of the body's extremities, such as the arm). These...
21 CFR 864.5200 - Automated cell counter.

Code of Federal Regulations, 2011 CFR

2011-04-01

....5200 Automated cell counter. (a) Identification. An automated cell counter is a fully-automated or semi-automated device used to count red blood cells, white blood cells, or blood platelets using a sample of the patient's peripheral blood (blood circulating in one of the body's extremities, such as the arm). These...
21 CFR 864.5200 - Automated cell counter.

Code of Federal Regulations, 2012 CFR

2012-04-01

....5200 Automated cell counter. (a) Identification. An automated cell counter is a fully-automated or semi-automated device used to count red blood cells, white blood cells, or blood platelets using a sample of the patient's peripheral blood (blood circulating in one of the body's extremities, such as the arm). These...
21 CFR 864.5200 - Automated cell counter.

Code of Federal Regulations, 2013 CFR

2013-04-01

....5200 Automated cell counter. (a) Identification. An automated cell counter is a fully-automated or semi-automated device used to count red blood cells, white blood cells, or blood platelets using a sample of the patient's peripheral blood (blood circulating in one of the body's extremities, such as the arm). These...
Automated measurement of uptake in cerebellum, liver, and aortic arch in full-body FDG PET/CT scans.

PubMed

Bauer, Christian; Sun, Shanhui; Sun, Wenqing; Otis, Justin; Wallace, Audrey; Smith, Brian J; Sunderland, John J; Graham, Michael M; Sonka, Milan; Buatti, John M; Beichel, Reinhard R

2012-06-01

The purpose of this work was to develop and validate fully automated methods for uptake measurement of cerebellum, liver, and aortic arch in full-body PET/CT scans. Such measurements are of interest in the context of uptake normalization for quantitative assessment of metabolic activity and/or automated image quality control. Cerebellum, liver, and aortic arch regions were segmented with different automated approaches. Cerebella were segmented in PET volumes by means of a robust active shape model (ASM) based method. For liver segmentation, a largest possible hyperellipsoid was fitted to the liver in PET scans. The aortic arch was first segmented in CT images of a PET/CT scan by a tubular structure analysis approach, and the segmented result was then mapped to the corresponding PET scan. For each of the segmented structures, the average standardized uptake value (SUV) was calculated. To generate an independent reference standard for method validation, expert image analysts were asked to segment several cross sections of each of the three structures in 134 F-18 fluorodeoxyglucose (FDG) PET/CT scans. For each case, the true average SUV was estimated by utilizing statistical models and served as the independent reference standard. For automated aorta and liver SUV measurements, no statistically significant scale or shift differences were observed between automated results and the independent standard. In the case of the cerebellum, the scale and shift were not significantly different, if measured in the same cross sections that were utilized for generating the reference. In contrast, automated results were scaled 5% lower on average although not shifted, if FDG uptake was calculated from the whole segmented cerebellum volume. The estimated reduction in total SUV measurement error ranged between 54.7% and 99.2%, and the reduction was found to be statistically significant for cerebellum and aortic arch. With the proposed methods, the authors have demonstrated that automated SUV uptake measurements in cerebellum, liver, and aortic arch agree with expert-defined independent standards. The proposed methods were found to be accurate and showed less intra- and interobserver variability, compared to manual analysis. The approach provides an alternative to manual uptake quantification, which is time-consuming. Such an approach will be important for application of quantitative PET imaging to large scale clinical trials. © 2012 American Association of Physicists in Medicine.
An ODE-Based Wall Model for Turbulent Flow Simulations

NASA Technical Reports Server (NTRS)

Berger, Marsha J.; Aftosmis, Michael J.

2017-01-01

Fully automated meshing for Reynolds-Averaged Navier-Stokes Simulations, Mesh generation for complex geometry continues to be the biggest bottleneck in the RANS simulation process; Fully automated Cartesian methods routinely used for inviscid simulations about arbitrarily complex geometry; These methods lack of an obvious & robust way to achieve near wall anisotropy; Goal: Extend these methods for RANS simulation without sacrificing automation, at an affordable cost; Note: Nothing here is limited to Cartesian methods, and much becomes simpler in a body-fitted setting.
Anesthesiology, automation, and artificial intelligence

PubMed Central

Alexander, John C.; Joshi, Girish P.

2018-01-01

ABSTRACT 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. PMID:29686578
MsViz: A Graphical Software Tool for In-Depth Manual Validation and Quantitation of Post-translational Modifications.

PubMed

Martín-Campos, Trinidad; Mylonas, Roman; Masselot, Alexandre; Waridel, Patrice; Petricevic, Tanja; Xenarios, Ioannis; Quadroni, Manfredo

2017-08-04

Mass spectrometry (MS) has become the tool of choice for the large scale identification and quantitation of proteins and their post-translational modifications (PTMs). This development has been enabled by powerful software packages for the automated analysis of MS data. While data on PTMs of thousands of proteins can nowadays be readily obtained, fully deciphering the complexity and combinatorics of modification patterns even on a single protein often remains challenging. Moreover, functional investigation of PTMs on a protein of interest requires validation of the localization and the accurate quantitation of its changes across several conditions, tasks that often still require human evaluation. Software tools for large scale analyses are highly efficient but are rarely conceived for interactive, in-depth exploration of data on individual proteins. We here describe MsViz, a web-based and interactive software tool that supports manual validation of PTMs and their relative quantitation in small- and medium-size experiments. The tool displays sequence coverage information, peptide-spectrum matches, tandem MS spectra and extracted ion chromatograms through a single, highly intuitive interface. We found that MsViz greatly facilitates manual data inspection to validate PTM location and quantitate modified species across multiple samples.
A quantitative image cytometry technique for time series or population analyses of signaling networks.

PubMed

Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

2010-04-01

Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.
High-throughput, fully-automated volumetry for prediction of MMSE and CDR decline in mild cognitive impairment

PubMed Central

Kovacevic, Sanja; Rafii, Michael S.; Brewer, James B.

2008-01-01

Medial temporal lobe (MTL) atrophy is associated with increased risk for conversion to Alzheimer's disease (AD), but manual tracing techniques and even semi-automated techniques for volumetric assessment are not practical in the clinical setting. In addition, most studies that examined MTL atrophy in AD have focused only on the hippocampus. It is unknown the extent to which volumes of amygdala and temporal horn of the lateral ventricle predict subsequent clinical decline. This study examined whether measures of hippocampus, amygdala, and temporal horn volume predict clinical decline over the following 6-month period in patients with mild cognitive impairment (MCI). Fully-automated volume measurements were performed in 269 MCI patients. Baseline volumes of the hippocampus, amygdala, and temporal horn were evaluated as predictors of change in Mini-mental State Exam (MMSE) and Clinical Dementia Rating Sum of Boxes (CDR SB) over a 6-month interval. Fully-automated measurements of baseline hippocampus and amygdala volumes correlated with baseline delayed recall scores. Patients with smaller baseline volumes of the hippocampus and amygdala or larger baseline volumes of the temporal horn had more rapid subsequent clinical decline on MMSE and CDR SB. Fully-automated and rapid measurement of segmental MTL volumes may help clinicians predict clinical decline in MCI patients. PMID:19474571
Twelve automated thresholding methods for segmentation of PET images: a phantom study.

PubMed

Prieto, Elena; Lecumberri, Pablo; Pagola, Miguel; Gómez, Marisol; Bilbao, Izaskun; Ecay, Margarita; Peñuelas, Iván; Martí-Climent, Josep M

2012-06-21

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.
Twelve automated thresholding methods for segmentation of PET images: a phantom study

NASA Astrophysics Data System (ADS)

Prieto, Elena; Lecumberri, Pablo; Pagola, Miguel; Gómez, Marisol; Bilbao, Izaskun; Ecay, Margarita; Peñuelas, Iván; Martí-Climent, Josep M.

2012-06-01

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 18F-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.
Auto-segmentation of normal and target structures in head and neck CT images: a feature-driven model-based approach.

PubMed

Qazi, Arish A; Pekar, Vladimir; Kim, John; Xie, Jason; Breen, Stephen L; Jaffray, David A

2011-11-01

Intensity modulated radiation therapy (IMRT) allows greater control over dose distribution, which leads to a decrease in radiation related toxicity. IMRT, however, requires precise and accurate delineation of the organs at risk and target volumes. Manual delineation is tedious and suffers from both interobserver and intraobserver variability. State of the art auto-segmentation methods are either atlas-based, model-based or hybrid however, robust fully automated segmentation is often difficult due to the insufficient discriminative information provided by standard medical imaging modalities for certain tissue types. In this paper, the authors present a fully automated hybrid approach which combines deformable registration with the model-based approach to accurately segment normal and target tissues from head and neck CT images. The segmentation process starts by using an average atlas to reliably identify salient landmarks in the patient image. The relationship between these landmarks and the reference dataset serves to guide a deformable registration algorithm, which allows for a close initialization of a set of organ-specific deformable models in the patient image, ensuring their robust adaptation to the boundaries of the structures. Finally, the models are automatically fine adjusted by our boundary refinement approach which attempts to model the uncertainty in model adaptation using a probabilistic mask. This uncertainty is subsequently resolved by voxel classification based on local low-level organ-specific features. To quantitatively evaluate the method, they auto-segment several organs at risk and target tissues from 10 head and neck CT images. They compare the segmentations to the manual delineations outlined by the expert. The evaluation is carried out by estimating two common quantitative measures on 10 datasets: volume overlap fraction or the Dice similarity coefficient (DSC), and a geometrical metric, the median symmetric Hausdorff distance (HD), which is evaluated slice-wise. They achieve an average overlap of 93% for the mandible, 91% for the brainstem, 83% for the parotids, 83% for the submandibular glands, and 74% for the lymph node levels. Our automated segmentation framework is able to segment anatomy in the head and neck region with high accuracy within a clinically-acceptable segmentation time.
Groping for quantitative digital 3-D image analysis: an approach to quantitative fluorescence in situ hybridization in thick tissue sections of prostate carcinoma.

PubMed

Rodenacker, K; Aubele, M; Hutzler, P; Adiga, P S

1997-01-01

In molecular pathology numerical chromosome aberrations have been found to be decisive for the prognosis of malignancy in tumours. The existence of such aberrations can be detected by interphase fluorescence in situ hybridization (FISH). The gain or loss of certain base sequences in the desoxyribonucleic acid (DNA) can be estimated by counting the number of FISH signals per cell nucleus. The quantitative evaluation of such events is a necessary condition for a prospective use in diagnostic pathology. To avoid occlusions of signals, the cell nucleus has to be analyzed in three dimensions. Confocal laser scanning microscopy is the means to obtain series of optical thin sections from fluorescence stained or marked material to fulfill the conditions mentioned above. A graphical user interface (GUI) to a software package for display, inspection, count and (semi-)automatic analysis of 3-D images for pathologists is outlined including the underlying methods of 3-D image interaction and segmentation developed. The preparative methods are briefly described. Main emphasis is given to the methodical questions of computer-aided analysis of large 3-D image data sets for pathologists. Several automated analysis steps can be performed for segmentation and succeeding quantification. However tumour material is in contrast to isolated or cultured cells even for visual inspection, a difficult material. For the present a fully automated digital image analysis of 3-D data is not in sight. A semi-automatic segmentation method is thus presented here.
CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

PubMed Central

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087
CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

PubMed

Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

2013-08-09

: The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.
Automated liver elasticity calculation for 3D MRE

NASA Astrophysics Data System (ADS)

Dzyubak, Bogdan; Glaser, Kevin J.; Manduca, Armando; Ehman, Richard L.

2017-03-01

Magnetic Resonance Elastography (MRE) is a phase-contrast MRI technique which calculates quantitative stiffness images, called elastograms, by imaging the propagation of acoustic waves in tissues. It is used clinically to diagnose liver fibrosis. Automated analysis of MRE is difficult as the corresponding MRI magnitude images (which contain anatomical information) are affected by intensity inhomogeneity, motion artifact, and poor tissue- and edge-contrast. Additionally, areas with low wave amplitude must be excluded. An automated algorithm has already been successfully developed and validated for clinical 2D MRE. 3D MRE acquires substantially more data and, due to accelerated acquisition, has exacerbated image artifacts. Also, the current 3D MRE processing does not yield a confidence map to indicate MRE wave quality and guide ROI selection, as is the case in 2D. In this study, extension of the 2D automated method, with a simple wave-amplitude metric, was developed and validated against an expert reader in a set of 57 patient exams with both 2D and 3D MRE. The stiffness discrepancy with the expert for 3D MRE was -0.8% +/- 9.45% and was better than discrepancy with the same reader for 2D MRE (-3.2% +/- 10.43%), and better than the inter-reader discrepancy observed in previous studies. There were no automated processing failures in this dataset. Thus, the automated liver elasticity calculation (ALEC) algorithm is able to calculate stiffness from 3D MRE data with minimal bias and good precision, while enabling stiffness measurements to be fully reproducible and to be easily performed on the large 3D MRE datasets.
21 CFR 864.5620 - Automated hemoglobin system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Automated hemoglobin system. 864.5620 Section 864....5620 Automated hemoglobin system. (a) Identification. An automated hemoglobin system is a fully... hemoglobin content of human blood. (b) Classification. Class II (performance standards). [45 FR 60601, Sept...

21 CFR 864.5620 - Automated hemoglobin system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Automated hemoglobin system. 864.5620 Section 864....5620 Automated hemoglobin system. (a) Identification. An automated hemoglobin system is a fully... hemoglobin content of human blood. (b) Classification. Class II (performance standards). [45 FR 60601, Sept...
An Automated Method for High-Throughput Screening of Arabidopsis Rosette Growth in Multi-Well Plates and Its Validation in Stress Conditions.

PubMed

De Diego, Nuria; Fürst, Tomáš; Humplík, Jan F; Ugena, Lydia; Podlešáková, Kateřina; Spíchal, Lukáš

2017-01-01

High-throughput plant phenotyping platforms provide new possibilities for automated, fast scoring of several plant growth and development traits, followed over time using non-invasive sensors. Using Arabidops is as a model offers important advantages for high-throughput screening with the opportunity to extrapolate the results obtained to other crops of commercial interest. In this study we describe the development of a highly reproducible high-throughput Arabidopsis in vitro bioassay established using our OloPhen platform, suitable for analysis of rosette growth in multi-well plates. This method was successfully validated on example of multivariate analysis of Arabidopsis rosette growth in different salt concentrations and the interaction with varying nutritional composition of the growth medium. Several traits such as changes in the rosette area, relative growth rate, survival rate and homogeneity of the population are scored using fully automated RGB imaging and subsequent image analysis. The assay can be used for fast screening of the biological activity of chemical libraries, phenotypes of transgenic or recombinant inbred lines, or to search for potential quantitative trait loci. It is especially valuable for selecting genotypes or growth conditions that improve plant stress tolerance.
Automated 3D renal segmentation based on image partitioning

NASA Astrophysics Data System (ADS)

Yeghiazaryan, Varduhi; Voiculescu, Irina D.

2016-03-01

Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.
Automated 3D closed surface segmentation: application to vertebral body segmentation in CT images.

PubMed

Liu, Shuang; Xie, Yiting; Reeves, Anthony P

2016-05-01

A fully automated segmentation algorithm, progressive surface resolution (PSR), is presented in this paper to determine the closed surface of approximately convex blob-like structures that are common in biomedical imaging. The PSR algorithm was applied to the cortical surface segmentation of 460 vertebral bodies on 46 low-dose chest CT images, which can be potentially used for automated bone mineral density measurement and compression fracture detection. The target surface is realized by a closed triangular mesh, which thereby guarantees the enclosure. The surface vertices of the triangular mesh representation are constrained along radial trajectories that are uniformly distributed in 3D angle space. The segmentation is accomplished by determining for each radial trajectory the location of its intersection with the target surface. The surface is first initialized based on an input high confidence boundary image and then resolved progressively based on a dynamic attraction map in an order of decreasing degree of evidence regarding the target surface location. For the visual evaluation, the algorithm achieved acceptable segmentation for 99.35 % vertebral bodies. Quantitative evaluation was performed on 46 vertebral bodies and achieved overall mean Dice coefficient of 0.939 (with max [Formula: see text] 0.957, min [Formula: see text] 0.906 and standard deviation [Formula: see text] 0.011) using manual annotations as the ground truth. Both visual and quantitative evaluations demonstrate encouraging performance of the PSR algorithm. This novel surface resolution strategy provides uniform angular resolution for the segmented surface with computation complexity and runtime that are linearly constrained by the total number of vertices of the triangular mesh representation.
Designing automation for human use: empirical studies and quantitative models.

PubMed

Parasuraman, R

2000-07-01

An emerging knowledge base of human performance research can provide guidelines for designing automation that can be used effectively by human operators of complex systems. Which functions should be automated and to what extent in a given system? A model for types and levels of automation that provides a framework and an objective basis for making such choices is described. The human performance consequences of particular types and levels of automation constitute primary evaluative criteria for automation design when using the model. Four human performance areas are considered--mental workload, situation awareness, complacency and skill degradation. Secondary evaluative criteria include such factors as automation reliability, the risks of decision/action consequences and the ease of systems integration. In addition to this qualitative approach, quantitative models can inform design. Several computational and formal models of human interaction with automation that have been proposed by various researchers are reviewed. An important future research need is the integration of qualitative and quantitative approaches. Application of these models provides an objective basis for designing automation for effective human use.
Towards Automated Screening of Two-dimensional Crystals

PubMed Central

Cheng, Anchi; Leung, Albert; Fellmann, Denis; Quispe, Joel; Suloway, Christian; Pulokas, James; Carragher, Bridget; Potter, Clinton S.

2007-01-01

Screening trials to determine the presence of two-dimensional (2D) protein crystals suitable for three-dimensional structure determination using electron crystallography is a very labor-intensive process. Methods compatible with fully automated screening have been developed for the process of crystal production by dialysis and for producing negatively stained grids of the resulting trials. Further automation via robotic handling of the EM grids, and semi-automated transmission electron microscopic imaging and evaluation of the trial grids is also possible. We, and others, have developed working prototypes for several of these tools and tested and evaluated them in a simple screen of 24 crystallization conditions. While further development of these tools is certainly required for a turn-key system, the goal of fully automated screening appears to be within reach. PMID:17977016
Investigating Factors Affecting the Uptake of Automated Assessment Technology

ERIC Educational Resources Information Center

Dreher, Carl; Reiners, Torsten; Dreher, Heinz

2011-01-01

Automated assessment is an emerging innovation in educational praxis, however its pedagogical potential is not fully utilised in Australia, particularly regarding automated essay grading. The rationale for this research is that the usage of automated assessment currently lags behind the capacity that the technology provides, thus restricting the…
A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology.

PubMed

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 < 0.0001) and a Bland-Altman plot shows that 95% of the data are between the 2SD agreement lines. We demonstrate the effectiveness and robustness of the CEAS 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.
Bioprocess automation on a Mini Pilot Plant enables fast quantitative microbial phenotyping.

PubMed

Unthan, Simon; Radek, Andreas; Wiechert, Wolfgang; Oldiges, Marco; Noack, Stephan

2015-03-11

The throughput of cultivation experiments in bioprocess development has drastically increased in recent years due to the availability of sophisticated microliter scale cultivation devices. However, as these devices still require time-consuming manual work, the bottleneck was merely shifted to media preparation, inoculation and finally the analyses of cultivation samples. A first step towards solving these issues was undertaken in our former study by embedding a BioLector in a robotic workstation. This workstation already allowed for the optimization of heterologous protein production processes, but remained limited when aiming for the characterization of small molecule producer strains. In this work, we extended our workstation to a versatile Mini Pilot Plant (MPP) by integrating further robotic workflows and microtiter plate assays that now enable a fast and accurate phenotyping of a broad range of microbial production hosts. A fully automated harvest procedure was established, which repeatedly samples up to 48 wells from BioLector cultivations in response to individually defined trigger conditions. The samples are automatically clarified by centrifugation and finally frozen for subsequent analyses. Sensitive metabolite assays in 384-well plate scale were integrated on the MPP for the direct determination of substrate uptake (specifically D-glucose and D-xylose) and product formation (specifically amino acids). In a first application, we characterized a set of Corynebacterium glutamicum L-lysine producer strains and could rapidly identify a unique strain showing increased L-lysine titers, which was subsequently confirmed in lab-scale bioreactor experiments. In a second study, we analyzed the substrate uptake kinetics of a previously constructed D-xylose-converting C. glutamicum strain during cultivation on mixed carbon sources in a fully automated experiment. The presented MPP is designed to face the challenges typically encountered during early-stage bioprocess development. Especially the bottleneck of sample analyses from fast and parallelized microtiter plate cultivations can be solved using cutting-edge robotic automation. As robotic workstations become increasingly attractive for biotechnological research, we expect our setup to become a template for future bioprocess development.
Automated meteorological data from commercial aircraft via satellite: Present experience and future implications

NASA Technical Reports Server (NTRS)

Steinberg, R.

1978-01-01

A low-cost communications system to provide meteorological data from commercial aircraft, in neat real-time, on a fully automated basis has been developed. The complete system including the low profile antenna and all installation hardware weighs 34 kg. The prototype system was installed on a B-747 aircraft and provided meteorological data (wind angle and velocity, temperature, altitude and position as a function of time) on a fully automated basis. The results were exceptional. This concept is expected to have important implications for operational meteorology and airline route forecasting.
Automated model-based quantitative analysis of phantoms with spherical inserts in FDG PET scans.

PubMed

Ulrich, Ethan J; Sunderland, John J; Smith, Brian J; Mohiuddin, Imran; Parkhurst, Jessica; Plichta, Kristin A; Buatti, John M; Beichel, Reinhard R

2018-01-01

Quality control plays an increasingly important role in quantitative PET imaging and is typically performed using phantoms. The purpose of this work was to develop and validate a fully automated analysis method for two common PET/CT quality assurance phantoms: the NEMA NU-2 IQ and SNMMI/CTN oncology phantom. The algorithm was designed to only utilize the PET scan to enable the analysis of phantoms with thin-walled inserts. We introduce a model-based method for automated analysis of phantoms with spherical inserts. Models are first constructed for each type of phantom to be analyzed. A robust insert detection algorithm uses the model to locate all inserts inside the phantom. First, candidates for inserts are detected using a scale-space detection approach. Second, candidates are given an initial label using a score-based optimization algorithm. Third, a robust model fitting step aligns the phantom model to the initial labeling and fixes incorrect labels. Finally, the detected insert locations are refined and measurements are taken for each insert and several background regions. In addition, an approach for automated selection of NEMA and CTN phantom models is presented. The method was evaluated on a diverse set of 15 NEMA and 20 CTN phantom PET/CT scans. NEMA phantoms were filled with radioactive tracer solution at 9.7:1 activity ratio over background, and CTN phantoms were filled with 4:1 and 2:1 activity ratio over background. For quantitative evaluation, an independent reference standard was generated by two experts using PET/CT scans of the phantoms. In addition, the automated approach was compared against manual analysis, which represents the current clinical standard approach, of the PET phantom scans by four experts. The automated analysis method successfully detected and measured all inserts in all test phantom scans. It is a deterministic algorithm (zero variability), and the insert detection RMS error (i.e., bias) was 0.97, 1.12, and 1.48 mm for phantom activity ratios 9.7:1, 4:1, and 2:1, respectively. For all phantoms and at all contrast ratios, the average RMS error was found to be significantly lower for the proposed automated method compared to the manual analysis of the phantom scans. The uptake measurements produced by the automated method showed high correlation with the independent reference standard (R 2 ≥ 0.9987). In addition, the average computing time for the automated method was 30.6 s and was found to be significantly lower (P ≪ 0.001) compared to manual analysis (mean: 247.8 s). The proposed automated approach was found to have less error when measured against the independent reference than the manual approach. It can be easily adapted to other phantoms with spherical inserts. In addition, it eliminates inter- and intraoperator variability in PET phantom analysis and is significantly more time efficient, and therefore, represents a promising approach to facilitate and simplify PET standardization and harmonization efforts. © 2017 American Association of Physicists in Medicine.
Automated localisation of Mars rovers using co-registered HiRISE-CTX-HRSC orthorectified images and wide baseline Navcam orthorectified mosaics

NASA Astrophysics Data System (ADS)

Tao, Yu; Muller, Jan-Peter; Poole, William

2016-12-01

We present a wide range of research results in the area of orbit-to-orbit and orbit-to-ground data fusion, achieved within the EU-FP7 PRoVisG project and EU-FP7 PRoViDE project. We focus on examples from three Mars rover missions, i.e. MER-A/B and MSL, to provide examples of a new fully automated offline method for rover localisation. We start by introducing the mis-registration discovered between the current HRSC and HiRISE datasets. Then we introduce the HRSC to CTX and CTX to HiRISE co-registration workflow. Finally, we demonstrate results of wide baseline stereo reconstruction with fixed mast position rover stereo imagery and its application to ground-to-orbit co-registration with HiRISE orthorectified image. We show examples of the quantitative assessment of recomputed rover traverses, and extensional exploitation of the co-registered datasets in visualisation and within an interactive web-GIS.
Automated tracking of whiskers in videos of head fixed rodents.

PubMed

Clack, Nathan G; O'Connor, Daniel H; Huber, Daniel; Petreanu, Leopoldo; Hires, Andrew; Peron, Simon; Svoboda, Karel; Myers, Eugene W

2012-01-01

We have developed software for fully automated tracking of vibrissae (whiskers) in high-speed videos (>500 Hz) of head-fixed, behaving rodents trimmed to a single row of whiskers. Performance was assessed against a manually curated dataset consisting of 1.32 million video frames comprising 4.5 million whisker traces. The current implementation detects whiskers with a recall of 99.998% and identifies individual whiskers with 99.997% accuracy. The average processing rate for these images was 8 Mpx/s/cpu (2.6 GHz Intel Core2, 2 GB RAM). This translates to 35 processed frames per second for a 640 px×352 px video of 4 whiskers. The speed and accuracy achieved enables quantitative behavioral studies where the analysis of millions of video frames is required. We used the software to analyze the evolving whisking strategies as mice learned a whisker-based detection task over the course of 6 days (8148 trials, 25 million frames) and measure the forces at the sensory follicle that most underlie haptic perception.
Automated Tracking of Whiskers in Videos of Head Fixed Rodents

PubMed Central

Clack, Nathan G.; O'Connor, Daniel H.; Huber, Daniel; Petreanu, Leopoldo; Hires, Andrew; Peron, Simon; Svoboda, Karel; Myers, Eugene W.

2012-01-01

We have developed software for fully automated tracking of vibrissae (whiskers) in high-speed videos (>500 Hz) of head-fixed, behaving rodents trimmed to a single row of whiskers. Performance was assessed against a manually curated dataset consisting of 1.32 million video frames comprising 4.5 million whisker traces. The current implementation detects whiskers with a recall of 99.998% and identifies individual whiskers with 99.997% accuracy. The average processing rate for these images was 8 Mpx/s/cpu (2.6 GHz Intel Core2, 2 GB RAM). This translates to 35 processed frames per second for a 640 px×352 px video of 4 whiskers. The speed and accuracy achieved enables quantitative behavioral studies where the analysis of millions of video frames is required. We used the software to analyze the evolving whisking strategies as mice learned a whisker-based detection task over the course of 6 days (8148 trials, 25 million frames) and measure the forces at the sensory follicle that most underlie haptic perception. PMID:22792058
Automated Axon Counting in Rodent Optic Nerve Sections with AxonJ.

PubMed

Zarei, Kasra; Scheetz, Todd E; Christopher, Mark; Miller, Kathy; Hedberg-Buenz, Adam; Tandon, Anamika; Anderson, Michael G; Fingert, John H; Abràmoff, Michael David

2016-05-26

We have developed a publicly available tool, AxonJ, which quantifies the axons in optic nerve sections of rodents stained with paraphenylenediamine (PPD). In this study, we compare AxonJ's performance to human experts on 100x and 40x images of optic nerve sections obtained from multiple strains of mice, including mice with defects relevant to glaucoma. AxonJ produced reliable axon counts with high sensitivity of 0.959 and high precision of 0.907, high repeatability of 0.95 when compared to a gold-standard of manual assessments and high correlation of 0.882 to the glaucoma damage staging of a previously published dataset. AxonJ allows analyses that are quantitative, consistent, fully-automated, parameter-free, and rapid on whole optic nerve sections at 40x. As a freely available ImageJ plugin that requires no highly specialized equipment to utilize, AxonJ represents a powerful new community resource augmenting studies of the optic nerve using mice.
Automated Axon Counting in Rodent Optic Nerve Sections with AxonJ

NASA Astrophysics Data System (ADS)

Zarei, Kasra; Scheetz, Todd E.; Christopher, Mark; Miller, Kathy; Hedberg-Buenz, Adam; Tandon, Anamika; Anderson, Michael G.; Fingert, John H.; Abràmoff, Michael David

2016-05-01

We have developed a publicly available tool, AxonJ, which quantifies the axons in optic nerve sections of rodents stained with paraphenylenediamine (PPD). In this study, we compare AxonJ’s performance to human experts on 100x and 40x images of optic nerve sections obtained from multiple strains of mice, including mice with defects relevant to glaucoma. AxonJ produced reliable axon counts with high sensitivity of 0.959 and high precision of 0.907, high repeatability of 0.95 when compared to a gold-standard of manual assessments and high correlation of 0.882 to the glaucoma damage staging of a previously published dataset. AxonJ allows analyses that are quantitative, consistent, fully-automated, parameter-free, and rapid on whole optic nerve sections at 40x. As a freely available ImageJ plugin that requires no highly specialized equipment to utilize, AxonJ represents a powerful new community resource augmenting studies of the optic nerve using mice.
Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed that the device identified influenza A hemagglutinin and neuraminidase subtypes and sequenced portions of both genes, demonstrating the potential of integrated microfluidic and microarray technology for multiple virus detection. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluidic handling steps and allows microarray-based DNA analysis in a rapid and automated fashion.
Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery.

PubMed

Boitor, Radu; Kong, Kenny; Shipp, Dustin; Varma, Sandeep; Koloydenko, Alexey; Kulkarni, Kusum; Elsheikh, Somaia; Schut, Tom Bakker; Caspers, Peter; Puppels, Gerwin; van der Wolf, Martin; Sokolova, Elena; Nijsten, T E C; Salence, Brogan; Williams, Hywel; Notingher, Ioan

2017-12-01

Multimodal spectral histopathology (MSH), an optical technique combining tissue auto-fluorescence (AF) imaging and Raman micro-spectroscopy (RMS), was previously proposed for detection of residual basal cell carcinoma (BCC) at the surface of surgically-resected skin tissue. Here we report the development of a fully-automated prototype instrument based on MSH designed to be used in the clinic and operated by a non-specialist spectroscopy user. The algorithms for the AF image processing and Raman spectroscopy classification had been first optimised on a manually-operated laboratory instrument and then validated on the automated prototype using skin samples from independent patients. We present results on a range of skin samples excised during Mohs micrographic surgery, and demonstrate consistent diagnosis obtained in repeat test measurement, in agreement with the reference histopathology diagnosis. We also show that the prototype instrument can be operated by clinical users (a skin surgeon and a core medical trainee, after only 1-8 hours of training) to obtain consistent results in agreement with histopathology. The development of the new automated prototype and demonstration of inter-instrument transferability of the diagnosis models are important steps on the clinical translation path: it allows the testing of the MSH technology in a relevant clinical environment in order to evaluate its performance on a sufficiently large number of patients.
An automated gas chromatography time-of-flight mass spectrometry instrument for the quantitative analysis of halocarbons in air

NASA Astrophysics Data System (ADS)

Obersteiner, F.; Bönisch, H.; Engel, A.

2016-01-01

We present the characterization and application of a new gas chromatography time-of-flight mass spectrometry instrument (GC-TOFMS) for the quantitative analysis of halocarbons in air samples. The setup comprises three fundamental enhancements compared to our earlier work (Hoker et al., 2015): (1) full automation, (2) a mass resolving power R = m/Δm of the TOFMS (Tofwerk AG, Switzerland) increased up to 4000 and (3) a fully accessible data format of the mass spectrometric data. Automation in combination with the accessible data allowed an in-depth characterization of the instrument. Mass accuracy was found to be approximately 5 ppm in mean after automatic recalibration of the mass axis in each measurement. A TOFMS configuration giving R = 3500 was chosen to provide an R-to-sensitivity ratio suitable for our purpose. Calculated detection limits are as low as a few femtograms by means of the accurate mass information. The precision for substance quantification was 0.15 % at the best for an individual measurement and in general mainly determined by the signal-to-noise ratio of the chromatographic peak. Detector non-linearity was found to be insignificant up to a mixing ratio of roughly 150 ppt at 0.5 L sampled volume. At higher concentrations, non-linearities of a few percent were observed (precision level: 0.2 %) but could be attributed to a potential source within the detection system. A straightforward correction for those non-linearities was applied in data processing, again by exploiting the accurate mass information. Based on the overall characterization results, the GC-TOFMS instrument was found to be very well suited for the task of quantitative halocarbon trace gas observation and a big step forward compared to scanning, quadrupole MS with low mass resolving power and a TOFMS technique reported to be non-linear and restricted by a small dynamical range.
Toward fully automated processing of dynamic susceptibility contrast perfusion MRI for acute ischemic cerebral stroke.

PubMed

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 quality assessment by two observers revealed that the MTT maps exhibited superior quality over the TTP maps (88% good rating of MTT as compared to 68% of TTP). Our software allowed fully automated deconvolution analysis of DSC PWI using proven efficient algorithms that can be applied to acute stroke treatment decisions. Our streamlined method also offers promise for further development of automated quantitative analysis of the ischemic penumbra. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Fully automated method for the liquid chromatographic determination of cyproterone acetate in plasma using restricted access material for sample pre-treatment.

PubMed

Christiaens, B; Chiap, P; Rbeida, O; Cello, D; Crommen, J; Hubert, Ph

2003-09-25

A new fully automated method for the quantitative analysis of an antiandrogenic substance, cyproterone acetate (CPA), in plasma samples has been developed using on-line solid-phase extraction (SPE) prior to the determination by reversed-phase liquid chromatography (LC). The automated method was based on the use of a precolumn packed with an internal-surface reversed-phase packing material (LiChrospher RP-4 ADS) for sample clean-up coupled to LC analysis on an octadecyl stationary phase using a column-switching system. A 200-microL volume of plasma sample was injected directly on the precolumn packed with restricted access material using a mixture of water-acetonitrile (90:10, v/v) as washing liquid. The analyte was then eluted in the back-flush mode with the LC mobile phase which consisted of a mixture of phosphate buffer, pH 7.0-acetonitrile (54:46, v/v). The elution profiles of CPA and blank plasma samples on the precolumn and the time needed for analyte transfer from the precolumn to the analytical column were determined. Different compositions of washing liquid and mobile phase were tested to reduce the interference of plasma endogenous components. UV detection was achieved at 280 nm. Finally, the developed method was validated using a new approach, namely the application of the accuracy profile based on the interval confidence at 90% of the total measurement error (bias+standard deviation). The limit of quantification of cyproterone acetate in plasma was determined at 15 ng mL(-1). The validated method should be applicable to the determination of CPA in patients treated by at least 50 mg day(-1).
Left ventricle: fully automated segmentation based on spatiotemporal continuity and myocardium information in cine cardiac magnetic resonance imaging (LV-FAST).

PubMed

Wang, Lijia; Pei, Mengchao; Codella, Noel C F; Kochar, Minisha; Weinsaft, Jonathan W; Li, Jianqi; Prince, Martin R; Wang, Yi

2015-01-01

CMR quantification of LV chamber volumes typically and manually defines the basal-most LV, which adds processing time and user-dependence. This study developed an LV segmentation method that is fully automated based on the spatiotemporal continuity of the LV (LV-FAST). An iteratively decreasing threshold region growing approach was used first from the midventricle to the apex, until the LV area and shape discontinued, and then from midventricle to the base, until less than 50% of the myocardium circumference was observable. Region growth was constrained by LV spatiotemporal continuity to improve robustness of apical and basal segmentations. The LV-FAST method was compared with manual tracing on cardiac cine MRI data of 45 consecutive patients. Of the 45 patients, LV-FAST and manual selection identified the same apical slices at both ED and ES and the same basal slices at both ED and ES in 38, 38, 38, and 41 cases, respectively, and their measurements agreed within -1.6 ± 8.7 mL, -1.4 ± 7.8 mL, and 1.0 ± 5.8% for EDV, ESV, and EF, respectively. LV-FAST allowed LV volume-time course quantitatively measured within 3 seconds on a standard desktop computer, which is fast and accurate for processing the cine volumetric cardiac MRI data, and enables LV filling course quantification over the cardiac cycle.
Fully automated corneal endothelial morphometry of images captured by clinical specular microscopy

NASA Astrophysics Data System (ADS)

Bucht, Curry; Söderberg, Per; Manneberg, Göran

2009-02-01

The corneal endothelium serves as the posterior barrier of the cornea. Factors such as clarity and refractive properties of the cornea are in direct relationship to the quality of the endothelium. The endothelial cell density is considered the most important morphological factor. Morphometry of the corneal endothelium is presently done by semi-automated analysis of pictures captured by a Clinical Specular Microscope (CSM). Because of the occasional need of operator involvement, this process can be tedious, having a negative impact on sampling size. This study was dedicated to the development of fully automated analysis of images of the corneal endothelium, captured by CSM, using Fourier analysis. Software was developed in the mathematical programming language Matlab. Pictures of the corneal endothelium, captured by CSM, were read into the analysis software. The software automatically performed digital enhancement of the images. The digitally enhanced images of the corneal endothelium were transformed, using the fast Fourier transform (FFT). Tools were developed and applied for identification and analysis of relevant characteristics of the Fourier transformed images. The data obtained from each Fourier transformed image was used to calculate the mean cell density of its corresponding corneal endothelium. The calculation was based on well known diffraction theory. Results in form of estimated cell density of the corneal endothelium were obtained, using fully automated analysis software on images captured by CSM. The cell density obtained by the fully automated analysis was compared to the cell density obtained from classical, semi-automated analysis and a relatively large correlation was found.
Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification.

PubMed

Vrooman, Henri A; Cocosco, Chris A; van der Lijn, Fedde; Stokking, Rik; Ikram, M Arfan; Vernooij, Meike W; Breteler, Monique M B; Niessen, Wiro J

2007-08-01

Conventional k-Nearest-Neighbor (kNN) classification, which has been successfully applied to classify brain tissue in MR data, requires training on manually labeled subjects. This manual labeling is a laborious and time-consuming procedure. In this work, a new fully automated brain tissue classification procedure is presented, in which kNN training is automated. This is achieved by non-rigidly registering the MR data with a tissue probability atlas to automatically select training samples, followed by a post-processing step to keep the most reliable samples. The accuracy of the new method was compared to rigid registration-based training and to conventional kNN-based segmentation using training on manually labeled subjects for segmenting gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) in 12 data sets. Furthermore, for all classification methods, the performance was assessed when varying the free parameters. Finally, the robustness of the fully automated procedure was evaluated on 59 subjects. The automated training method using non-rigid registration with a tissue probability atlas was significantly more accurate than rigid registration. For both automated training using non-rigid registration and for the manually trained kNN classifier, the difference with the manual labeling by observers was not significantly larger than inter-observer variability for all tissue types. From the robustness study, it was clear that, given an appropriate brain atlas and optimal parameters, our new fully automated, non-rigid registration-based method gives accurate and robust segmentation results. A similarity index was used for comparison with manually trained kNN. The similarity indices were 0.93, 0.92 and 0.92, for CSF, GM and WM, respectively. It can be concluded that our fully automated method using non-rigid registration may replace manual segmentation, and thus that automated brain tissue segmentation without laborious manual training is feasible.
Investigating the Effects of Motion Streaks on pQCT-Derived Leg Muscle Density and Its Association With Fractures.

PubMed

Chan, Adrian C H; Adachi, Jonathan D; Papaioannou, Alexandra; Wong, Andy Kin On

Lower peripheral quantitative computed tomography (pQCT)-derived leg muscle density has been associated with fragility fractures in postmenopausal women. Limb movement during image acquisition may result in motion streaks in muscle that could dilute this relationship. This cross-sectional study examined a subset of women from the Canadian Multicentre Osteoporosis Study. pQCT leg scans were qualitatively graded (1-5) for motion severity. Muscle and motion streak were segmented using semi-automated (watershed) and fully automated (threshold-based) methods, computing area, and density. Binary logistic regression evaluated odds ratios (ORs) for fragility or all-cause fractures related to each of these measures with covariate adjustment. Among the 223 women examined (mean age: 72.7 ± 7.1 years, body mass index: 26.30 ± 4.97 kg/m 2 ), muscle density was significantly lower after removing motion (p < 0.001) for both methods. Motion streak areas segmented using the semi-automated method correlated better with visual motion grades (rho = 0.90, p < 0.01) compared to the fully automated method (rho = 0.65, p < 0.01). Although the analysis-reanalysis precision of motion streak area segmentation using the semi-automated method is above 5% error (6.44%), motion-corrected muscle density measures remained well within 2% analytical error. The effect of motion-correction on strengthening the association between muscle density and fragility fractures was significant when motion grade was ≥3 (p interaction <0.05). This observation was most dramatic for the semi-automated algorithm (OR: 1.62 [0.82,3.17] before to 2.19 [1.05,4.59] after correction). Although muscle density showed an overall association with all-cause fractures (OR: 1.49 [1.05,2.12]), the effect of motion-correction was again, most impactful within individuals with scans showing grade 3 or above motion. Correcting for motion in pQCT leg scans strengthened the relationship between muscle density and fragility fractures, particularly in scans with motion grades of 3 or above. Motion streaks are not confounders to the relationship between pQCT-derived leg muscle density and fractures, but may introduce heterogeneity in muscle density measurements, rendering associations with fractures to be weaker. Copyright © 2016. Published by Elsevier Inc.
A Fully Automated High-Throughput Zebrafish Behavioral Ototoxicity Assay.

PubMed

Todd, Douglas W; Philip, Rohit C; Niihori, Maki; Ringle, Ryan A; Coyle, Kelsey R; Zehri, Sobia F; Zabala, Leanne; Mudery, Jordan A; Francis, Ross H; Rodriguez, Jeffrey J; Jacob, Abraham

2017-08-01

Zebrafish animal models lend themselves to behavioral assays that can facilitate rapid screening of ototoxic, otoprotective, and otoregenerative drugs. Structurally similar to human inner ear hair cells, the mechanosensory hair cells on their lateral line allow the zebrafish to sense water flow and orient head-to-current in a behavior called rheotaxis. This rheotaxis behavior deteriorates in a dose-dependent manner with increased exposure to the ototoxin cisplatin, thereby establishing itself as an excellent biomarker for anatomic damage to lateral line hair cells. Building on work by our group and others, we have built a new, fully automated high-throughput behavioral assay system that uses automated image analysis techniques to quantify rheotaxis behavior. This novel system consists of a custom-designed swimming apparatus and imaging system consisting of network-controlled Raspberry Pi microcomputers capturing infrared video. Automated analysis techniques detect individual zebrafish, compute their orientation, and quantify the rheotaxis behavior of a zebrafish test population, producing a powerful, high-throughput behavioral assay. Using our fully automated biological assay to test a standardized ototoxic dose of cisplatin against varying doses of compounds that protect or regenerate hair cells may facilitate rapid translation of candidate drugs into preclinical mammalian models of hearing loss.
Validation of automated white matter hyperintensity segmentation.

PubMed

Smart, Sean D; Firbank, Michael J; O'Brien, John T

2011-01-01

Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scans were also segmented in a fully automated fashion by three different programmes. The voxel overlap between manual and automated segmentation was compared. Results. Between observer overlap ratio was 63%. Using our previously described in-house software, we had overlap of 62.2%. We investigated the use of a modified version of SPM segmentation; however, this was not successful, with only 14% overlap. Discussion. Using our previously reported software, we demonstrated good segmentation of WMHs in a fully automated fashion.
How a Fully Automated eHealth Program Simulates Three Therapeutic Processes: A Case Study.

PubMed

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

PubMed Central

Johansen, Ayna; Brendryen, Håvar

2016-01-01

Background 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. Objective 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. Methods 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. Results 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. Conclusions 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. PMID:27354373
Automated MRI segmentation for individualized modeling of current flow in the human head.

PubMed

Huang, Yu; Dmochowski, Jacek P; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C

2013-12-01

High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.
Automated Liver Elasticity Calculation for 3D MRE

PubMed Central

Dzyubak, Bogdan; Glaser, Kevin J.; Manduca, Armando; Ehman, Richard L.

2017-01-01

Magnetic Resonance Elastography (MRE) is a phase-contrast MRI technique which calculates quantitative stiffness images, called elastograms, by imaging the propagation of acoustic waves in tissues. It is used clinically to diagnose liver fibrosis. Automated analysis of MRE is difficult as the corresponding MRI magnitude images (which contain anatomical information) are affected by intensity inhomogeneity, motion artifact, and poor tissue- and edge-contrast. Additionally, areas with low wave amplitude must be excluded. An automated algorithm has already been successfully developed and validated for clinical 2D MRE. 3D MRE acquires substantially more data and, due to accelerated acquisition, has exacerbated image artifacts. Also, the current 3D MRE processing does not yield a confidence map to indicate MRE wave quality and guide ROI selection, as is the case in 2D. In this study, extension of the 2D automated method, with a simple wave-amplitude metric, was developed and validated against an expert reader in a set of 57 patient exams with both 2D and 3D MRE. The stiffness discrepancy with the expert for 3D MRE was −0.8% ± 9.45% and was better than discrepancy with the same reader for 2D MRE (−3.2% ± 10.43%), and better than the inter-reader discrepancy observed in previous studies. There were no automated processing failures in this dataset. Thus, the automated liver elasticity calculation (ALEC) algorithm is able to calculate stiffness from 3D MRE data with minimal bias and good precision, while enabling stiffness measurements to be fully reproducible and to be easily performed on the large 3D MRE datasets. PMID:29033488
Fully automated registration of first-pass myocardial perfusion MRI using independent component analysis.

PubMed

Milles, J; van der Geest, R J; Jerosch-Herold, M; Reiber, J H C; Lelieveldt, B P F

2007-01-01

This paper presents a novel method for registration of cardiac perfusion MRI. The presented method successfully corrects for breathing motion without any manual interaction using Independent Component Analysis to extract physiologically relevant features together with their time-intensity behavior. A time-varying reference image mimicking intensity changes in the data of interest is computed based on the results of ICA, and used to compute the displacement caused by breathing for each frame. Qualitative and quantitative validation of the method is carried out using 46 clinical quality, short-axis, perfusion MR datasets comprising 100 images each. Validation experiments showed a reduction of the average LV motion from 1.26+/-0.87 to 0.64+/-0.46 pixels. Time-intensity curves are also improved after registration with an average error reduced from 2.65+/-7.89% to 0.87+/-3.88% between registered data and manual gold standard. We conclude that this fully automatic ICA-based method shows an excellent accuracy, robustness and computation speed, adequate for use in a clinical environment.
Medical ADP Systems: Automated Medical Records Hold Promise to Improve Patient Care

DTIC Science & Technology

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
Instrumentation Automation for Concrete Structures: Report 2, Automation Hardware and Retrofitting Techniques, and Report 3, Available Data Collection and Reduction Software

DTIC Science & Technology

1987-06-01

commercial products. · OP -- Typical cutout at a plumbiinc location where an automated monitoring system has bv :• installed. The sensor used with the...This report provides a description of commercially available sensors , instruments, and ADP equipment that may be selected to fully automate...automated. The automated plumbline monitoring system includes up to twelve sensors , repeaters, a system controller, and a printer. The system may
Automation and Preclinical Evaluation of a Dedicated Emission Mammotomography System for Fully 3-D Molecular Breast Imaging

DTIC Science & Technology

2009-10-01

molecular breast imaging, with the ability to dynamically contour any sized breast, will improve detection and potentially in vivo characterization of...Having flexible 3D positioning about the breast yielded minimal RMSD differences, which is important for high resolution molecular emission imaging. This...TITLE: Automation and Preclinical Evaluation of a Dedicated Emission Mammotomography System for Fully 3-D Molecular Breast Imaging PRINCIPAL
Automated Quantitative Rare Earth Elements Mineralogy by Scanning Electron Microscopy

NASA Astrophysics Data System (ADS)

Sindern, Sven; Meyer, F. Michael

2016-09-01

Increasing industrial demand of rare earth elements (REEs) stems from the central role they play for advanced technologies and the accelerating move away from carbon-based fuels. However, REE production is often hampered by the chemical, mineralogical as well as textural complexity of the ores with a need for better understanding of their salient properties. This is not only essential for in-depth genetic interpretations but also for a robust assessment of ore quality and economic viability. The design of energy and cost-efficient processing of REE ores depends heavily on information about REE element deportment that can be made available employing automated quantitative process mineralogy. Quantitative mineralogy assigns numeric values to compositional and textural properties of mineral matter. Scanning electron microscopy (SEM) combined with a suitable software package for acquisition of backscatter electron and X-ray signals, phase assignment and image analysis is one of the most efficient tools for quantitative mineralogy. The four different SEM-based automated quantitative mineralogy systems, i.e. FEI QEMSCAN and MLA, Tescan TIMA and Zeiss Mineralogic Mining, which are commercially available, are briefly characterized. Using examples of quantitative REE mineralogy, this chapter illustrates capabilities and limitations of automated SEM-based systems. Chemical variability of REE minerals and analytical uncertainty can reduce performance of phase assignment. This is shown for the REE phases parisite and synchysite. In another example from a monazite REE deposit, the quantitative mineralogical parameters surface roughness and mineral association derived from image analysis are applied for automated discrimination of apatite formed in a breakdown reaction of monazite and apatite formed by metamorphism prior to monazite breakdown. SEM-based automated mineralogy fulfils all requirements for characterization of complex unconventional REE ores that will become increasingly important for supply of REEs in the future.
Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment.

PubMed

Wengert, G J; Helbich, T H; Woitek, R; Kapetas, P; Clauser, P; Baltzer, P A; Vogl, W-D; Weber, M; Meyer-Baese, A; Pinker, Katja

2016-11-01

To evaluate the inter-/intra-observer agreement of BI-RADS-based subjective visual estimation of the amount of fibroglandular tissue (FGT) with magnetic resonance imaging (MRI), and to investigate whether FGT assessment benefits from an automated, observer-independent, quantitative MRI measurement by comparing both approaches. Eighty women with no imaging abnormalities (BI-RADS 1 and 2) were included in this institutional review board (IRB)-approved prospective study. All women underwent un-enhanced breast MRI. Four radiologists independently assessed FGT with MRI by subjective visual estimation according to BI-RADS. Automated observer-independent quantitative measurement of FGT with MRI was performed using a previously described measurement system. Inter-/intra-observer agreements of qualitative and quantitative FGT measurements were assessed using Cohen's kappa (k). Inexperienced readers achieved moderate inter-/intra-observer agreement and experienced readers a substantial inter- and perfect intra-observer agreement for subjective visual estimation of FGT. Practice and experience reduced observer-dependency. Automated observer-independent quantitative measurement of FGT was successfully performed and revealed only fair to moderate agreement (k = 0.209-0.497) with subjective visual estimations of FGT. Subjective visual estimation of FGT with MRI shows moderate intra-/inter-observer agreement, which can be improved by practice and experience. Automated observer-independent quantitative measurements of FGT are necessary to allow a standardized risk evaluation. • Subjective FGT estimation with MRI shows moderate intra-/inter-observer agreement in inexperienced readers. • Inter-observer agreement can be improved by practice and experience. • Automated observer-independent quantitative measurements can provide reliable and standardized assessment of FGT with MRI.
Automated detection and quantitation of bacterial RNA by using electrical microarrays.

PubMed

Elsholz, B; Wörl, R; Blohm, L; Albers, J; Feucht, H; Grunwald, T; Jürgen, B; Schweder, T; Hintsche, Rainer

2006-07-15

Low-density electrical 16S rRNA specific oligonucleotide microarrays and an automated analysis system have been developed for the identification and quantitation of pathogens. The pathogens are Escherichia coli, Pseudomonas aeruginosa, Enterococcus faecalis, Staphylococcus aureus, and Staphylococcus epidermidis, which are typically involved in urinary tract infections. Interdigitated gold array electrodes (IDA-electrodes), which have structures in the nanometer range, have been used for very sensitive analysis. Thiol-modified oligonucleotides are immobilized on the gold IDA as capture probes. They mediate the specific recognition of the target 16S rRNA by hybridization. Additionally three unlabeled oligonucleotides are hybridized in close proximity to the capturing site. They are supporting molecules, because they improve the RNA hybridization at the capturing site. A biotin labeled detector oligonucleotide is also allowed to hybridize to the captured RNA sequence. The biotin labels enable the binding of avidin alkaline phophatase conjugates. The phosphatase liberates the electrochemical mediator p-aminophenol from its electrically inactive phosphate derivative. The electrical signals were generated by amperometric redox cycling and detected by a unique multipotentiostat. The read out signals of the microarray are position specific current and change over time in proportion to the analyte concentration. If two additional biotins are introduced into the affinity binding complex via the supporting oligonucleotides, the sensitivity of the assays increase more than 60%. The limit of detection of Escherichia coli total RNA has been determined to be 0.5 ng/microL. The control of fluidics for variable assay formats as well as the multichannel electrical read out and data handling have all been fully automated. The fast and easy procedure does not require any amplification of the targeted nucleic acids by PCR.
Fully-automated, high-throughput micro-computed tomography analysis of body composition enables therapeutic efficacy monitoring in preclinical models.

PubMed

Wyatt, S K; Barck, K H; Kates, L; Zavala-Solorio, J; Ross, J; Kolumam, G; Sonoda, J; Carano, R A D

2015-11-01

The ability to non-invasively measure body composition in mouse models of obesity and obesity-related disorders is essential for elucidating mechanisms of metabolic regulation and monitoring the effects of novel treatments. These studies aimed to develop a fully automated, high-throughput micro-computed tomography (micro-CT)-based image analysis technique for longitudinal quantitation of adipose, non-adipose and lean tissue as well as bone and demonstrate utility for assessing the effects of two distinct treatments. An initial validation study was performed in diet-induced obesity (DIO) and control mice on a vivaCT 75 micro-CT system. Subsequently, four groups of DIO mice were imaged pre- and post-treatment with an experimental agonistic antibody specific for anti-fibroblast growth factor receptor 1 (anti-FGFR1, R1MAb1), control immunoglobulin G antibody, a known anorectic antiobesity drug (rimonabant, SR141716), or solvent control. The body composition analysis technique was then ported to a faster micro-CT system (CT120) to markedly increase throughput as well as to evaluate the use of micro-CT image intensity for hepatic lipid content in DIO and control mice. Ex vivo chemical analysis and colorimetric analysis of the liver triglycerides were performed as the standard metrics for correlation with body composition and hepatic lipid status, respectively. Micro-CT-based body composition measures correlate with ex vivo chemical analysis metrics and enable distinction between DIO and control mice. R1MAb1 and rimonabant have differing effects on body composition as assessed by micro-CT. High-throughput body composition imaging is possible using a modified CT120 system. Micro-CT also provides a non-invasive assessment of hepatic lipid content. This work describes, validates and demonstrates utility of a fully automated image analysis technique to quantify in vivo micro-CT-derived measures of adipose, non-adipose and lean tissue, as well as bone. These body composition metrics highly correlate with standard ex vivo chemical analysis and enable longitudinal evaluation of body composition and therapeutic efficacy monitoring.
Automated transit networks (ATN) : a review of the state of the industry and prospects for the future.

DOT National Transportation Integrated Search

2014-09-01

The concept of Automated Transit Networks (ATN) - in which fully automated vehicles on exclusive, grade-separated guideways : provide on-demand, primarily non-stop, origin-to-destination service over an area network has been around since the 1950...

Validation of Automated White Matter Hyperintensity Segmentation

PubMed Central

Smart, Sean D.; Firbank, Michael J.; O'Brien, John T.

2011-01-01

Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scans were also segmented in a fully automated fashion by three different programmes. The voxel overlap between manual and automated segmentation was compared. Results. Between observer overlap ratio was 63%. Using our previously described in-house software, we had overlap of 62.2%. We investigated the use of a modified version of SPM segmentation; however, this was not successful, with only 14% overlap. Discussion. Using our previously reported software, we demonstrated good segmentation of WMHs in a fully automated fashion. PMID:21904678
Glaciated valleys in Europe and western Asia

PubMed Central

Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar

2015-01-01

In recent years, remote sensing, morphometric analysis, and other computational concepts and tools have invigorated the field of geomorphological mapping. Automated interpretation of digital terrain data based on impartial rules holds substantial promise for large dataset processing and objective landscape classification. However, the geomorphological realm presents tremendous complexity and challenges in the translation of qualitative descriptions into geomorphometric semantics. Here, the simple, conventional distinction of V-shaped fluvial and U-shaped glacial valleys was analyzed quantitatively using multi-scale curvature and a novel morphometric variable termed Difference of Minimum Curvature (DMC). We used this automated terrain analysis approach to produce a raster map at a scale of 1:6,000,000 showing the distribution of glaciated valleys across Europe and western Asia. The data set has a cell size of 3 arc seconds and consists of more than 40 billion grid cells. Glaciated U-shaped valleys commonly associated with erosion by warm-based glaciers are abundant in the alpine regions of mid Europe and western Asia but also occur at the margins of mountain ice sheets in Scandinavia. The high-level correspondence with field mapping and the fully transferable semantics validate this approach for automated analysis of yet unexplored terrain around the globe and qualify for potential applications on other planetary bodies like Mars. PMID:27019665
Reading the leaves: A comparison of leaf rank and automated areole measurement for quantifying aspects of leaf venation1

PubMed Central

Green, Walton A.; Little, Stefan A.; Price, Charles A.; Wing, Scott L.; Smith, Selena Y.; Kotrc, Benjamin; Doria, Gabriela

2014-01-01

The reticulate venation that is characteristic of a dicot leaf has excited interest from systematists for more than a century, and from physiological and developmental botanists for decades. The tools of digital image acquisition and computer image analysis, however, are only now approaching the sophistication needed to quantify aspects of the venation network found in real leaves quickly, easily, accurately, and reliably enough to produce biologically meaningful data. In this paper, we examine 120 leaves distributed across vascular plants (representing 118 genera and 80 families) using two approaches: a semiquantitative scoring system called “leaf ranking,” devised by the late Leo Hickey, and an automated image-analysis protocol. In the process of comparing these approaches, we review some methodological issues that arise in trying to quantify a vein network, and discuss the strengths and weaknesses of automatic data collection and human pattern recognition. We conclude that subjective leaf rank provides a relatively consistent, semiquantitative measure of areole size among other variables; that modal areole size is generally consistent across large sections of a leaf lamina; and that both approaches—semiquantitative, subjective scoring; and fully quantitative, automated measurement—have appropriate places in the study of leaf venation. PMID:25202646
A two-dimensionally coincident second difference cosmic ray spike removal method for the fully automated processing of Raman spectra.

PubMed

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.
Automated meteorological data from commercial aircraft via satellite - Present experience and future implications

NASA Technical Reports Server (NTRS)

Steinberg, R.

1978-01-01

The National Aeronautics and Space Administration has developed a low-cost communications system to provide meteorological data from commercial aircraft, in near real-time, on a fully automated basis. The complete system including the low profile antenna and all installation hardware weighs 34 kg. The prototype system has been installed on a Pan American B-747 aircraft and has been providing meteorological data (wind angle and velocity, temperature, altitude and position as a function of time) on a fully automated basis for the past several months. The results have been exceptional. This concept is expected to have important implications for operational meteorology and airline route forecasting.
A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

NASA Astrophysics Data System (ADS)

Barat, Christian; Phlypo, Ronald

2010-12-01

We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.
Computer-aided liver volumetry: performance of a fully-automated, prototype post-processing solution for whole-organ and lobar segmentation based on MDCT imaging.

PubMed

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 volume and greater variability in edge detection for the left hepatic lobe compared to manual segmentation.
Advantages and challenges in automated apatite fission track counting

NASA Astrophysics Data System (ADS)

Enkelmann, E.; Ehlers, T. A.

2012-04-01

Fission track thermochronometer data are often a core element of modern tectonic and denudation studies. Soon after the development of the fission track methods interest emerged for the developed an automated counting procedure to replace the time consuming labor of counting fission tracks under the microscope. Automated track counting became feasible in recent years with increasing improvements in computer software and hardware. One such example used in this study is the commercial automated fission track counting procedure from Autoscan Systems Pty that has been highlighted through several venues. We conducted experiments that are designed to reliably and consistently test the ability of this fully automated counting system to recognize fission tracks in apatite and a muscovite external detector. Fission tracks were analyzed in samples with a step-wise increase in sample complexity. The first set of experiments used a large (mm-size) slice of Durango apatite cut parallel to the prism plane. Second, samples with 80-200 μm large apatite grains of Fish Canyon Tuff were analyzed. This second sample set is characterized by complexities often found in apatites in different rock types. In addition to the automated counting procedure, the same samples were also analyzed using conventional counting procedures. We found for all samples that the fully automated fission track counting procedure using the Autoscan System yields a larger scatter in the fission track densities measured compared to conventional (manual) track counting. This scatter typically resulted from the false identification of tracks due surface and mineralogical defects, regardless of the image filtering procedure used. Large differences between track densities analyzed with the automated counting persisted between different grains analyzed in one sample as well as between different samples. As a result of these differences a manual correction of the fully automated fission track counts is necessary for each individual surface area and grain counted. This manual correction procedure significantly increases (up to four times) the time required to analyze a sample with the automated counting procedure compared to the conventional approach.
Crossword: A Fully Automated Algorithm for the Segmentation and Quality Control of Protein Microarray Images

PubMed Central

2015-01-01

Biological assays formatted as microarrays have become a critical tool for the generation of the comprehensive data sets required for systems-level understanding of biological processes. Manual annotation of data extracted from images of microarrays, however, remains a significant bottleneck, particularly for protein microarrays due to the sensitivity of this technology to weak artifact signal. In order to automate the extraction and curation of data from protein microarrays, we describe an algorithm called Crossword that logically combines information from multiple approaches to fully automate microarray segmentation. Automated artifact removal is also accomplished by segregating structured pixels from the background noise using iterative clustering and pixel connectivity. Correlation of the location of structured pixels across image channels is used to identify and remove artifact pixels from the image prior to data extraction. This component improves the accuracy of data sets while reducing the requirement for time-consuming visual inspection of the data. Crossword enables a fully automated protocol that is robust to significant spatial and intensity aberrations. Overall, the average amount of user intervention is reduced by an order of magnitude and the data quality is increased through artifact removal and reduced user variability. The increase in throughput should aid the further implementation of microarray technologies in clinical studies. PMID:24417579
Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

NASA Astrophysics Data System (ADS)

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 system for the quantification of human osteoarthritic knee joint effusion volume using magnetic resonance imaging.

PubMed

Li, Wei; Abram, François; Pelletier, Jean-Pierre; Raynauld, Jean-Pierre; Dorais, Marc; d'Anjou, Marc-André; Martel-Pelletier, Johanne

2010-01-01

Joint effusion is frequently associated with osteoarthritis (OA) flare-up and is an important marker of therapeutic response. This study aimed at developing and validating a fully automated system based on magnetic resonance imaging (MRI) for the quantification of joint effusion volume in knee OA patients. MRI examinations consisted of two axial sequences: a T2-weighted true fast imaging with steady-state precession and a T1-weighted gradient echo. An automated joint effusion volume quantification system using MRI was developed and validated (a) with calibrated phantoms (cylinder and sphere) and effusion from knee OA patients; (b) with assessment by manual quantification; and (c) by direct aspiration. Twenty-five knee OA patients with joint effusion were included in the study. The automated joint effusion volume quantification was developed as a four stage sequencing process: bone segmentation, filtering of unrelated structures, segmentation of joint effusion, and subvoxel volume calculation. Validation experiments revealed excellent coefficients of variation with the calibrated cylinder (1.4%) and sphere (0.8%) phantoms. Comparison of the OA knee joint effusion volume assessed by the developed automated system and by manual quantification was also excellent (r = 0.98; P < 0.0001), as was the comparison with direct aspiration (r = 0.88; P = 0.0008). The newly developed fully automated MRI-based system provided precise quantification of OA knee joint effusion volume with excellent correlation with data from phantoms, a manual system, and joint aspiration. Such an automated system will be instrumental in improving the reproducibility/reliability of the evaluation of this marker in clinical application.
Quantitative microstructural imaging by scanning Laue x-ray micro- and nanodiffraction

DOE PAGES

Chen, Xian; Dejoie, Catherine; Jiang, Tengfei; ...

2016-06-08

We present that local crystal structure, crystal orientation, and crystal deformation can all be probed by Laue diffraction using a submicron x-ray beam. This technique, employed at a synchrotron facility, is particularly suitable for fast mapping the mechanical and microstructural properties of inhomogeneous multiphase polycrystalline samples, as well as imperfect epitaxial films or crystals. As synchrotron Laue x-ray microdiffraction enters its 20th year of existence and new synchrotron nanoprobe facilities are being built and commissioned around the world, we take the opportunity to overview current capabilities as well as the latest technical developments. Fast data collection provided by state-of-the-art areamore » detectors and fully automated pattern indexing algorithms optimized for speed make it possible to map large portions of a sample with fine step size and obtain quantitative images of its microstructure in near real time. Lastly, we extrapolate how the technique is anticipated to evolve in the near future and its potential emerging applications at a free-electron laser facility.« less
PaCER - A fully automated method for electrode trajectory and contact reconstruction in deep brain stimulation.

PubMed

Husch, Andreas; V Petersen, Mikkel; Gemmar, Peter; Goncalves, Jorge; Hertel, Frank

2018-01-01

Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N = 44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 μm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care.
A discriminative model-constrained graph cuts approach to fully automated pediatric brain tumor segmentation in 3-D MRI.

PubMed

Wels, Michael; Carneiro, Gustavo; Aplas, Alexander; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2008-01-01

In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation approach based on a Markov random field (MRF) model that combines probabilistic boosting trees (PBT) and lower-level segmentation via graph cuts. The PBT algorithm provides a strong discriminative observation model that classifies tumor appearance while a spatial prior takes into account the pair-wise homogeneity in terms of classification labels and multi-spectral voxel intensities. The discriminative model relies not only on observed local intensities but also on surrounding context for detecting candidate regions for pathology. A mathematically sound formulation for integrating the two approaches into a unified statistical framework is given. The proposed method is applied to the challenging task of detection and delineation of pediatric brain tumors. This segmentation task is characterized by a high non-uniformity of both the pathology and the surrounding non-pathologic brain tissue. A quantitative evaluation illustrates the robustness of the proposed method. Despite dealing with more complicated cases of pediatric brain tumors the results obtained are mostly better than those reported for current state-of-the-art approaches to 3-D MR brain tumor segmentation in adult patients. The entire processing of one multi-spectral data set does not require any user interaction, and takes less time than previously proposed methods.
ROBOCAL: An automated NDA (nondestructive analysis) calorimetry and gamma isotopic system

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

Hurd, J.R.; Powell, W.D.; Ostenak, C.A.

1989-11-01

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 acquisitionmore » and to perform state-of-the-art analyses on both homogeneous and heterogeneous distributions of nuclear materials in a wide variety of matrices.« less
Fully automated urban traffic system

NASA Technical Reports Server (NTRS)

Dobrotin, B. M.; Hansen, G. R.; Peng, T. K. C.; Rennels, D. A.

1977-01-01

The replacement of the driver with an automatic system which could perform the functions of guiding and routing a vehicle with a human's capability of responding to changing traffic demands was discussed. The problem was divided into four technological areas; guidance, routing, computing, and communications. It was determined that the latter three areas being developed independent of any need for fully automated urban traffic. A guidance system that would meet system requirements was not being developed but was technically feasible.
A fully automated digitally controlled 30-inch telescope

NASA Technical Reports Server (NTRS)

Colgate, S. A.; Moore, E. P.; Carlson, R.

1975-01-01

A fully automated 30-inch (75-cm) telescope has been successfully designed and constructed from a military surplus Nike-Ajax radar mount. Novel features include: closed-loop operation between mountain telescope and campus computer 30 km apart via microwave link, a TV-type sensor which is photon shot-noise limited, a special lightweight primary mirror, and a stepping motor drive capable of slewing and settling one degree in one second or a radian in fifteen seconds.
Preprocessing film-copied MRI for studying morphological brain changes.

PubMed

Pham, Tuan D; Eisenblätter, Uwe; Baune, Bernhard T; Berger, Klaus

2009-06-15

The magnetic resonance imaging (MRI) of the brain is one of the important data items for studying memory and morbidity in elderly as these images can provide useful information through the quantitative measures of various regions of interest of the brain. As an effort to fully automate the biomedical analysis of the brain that can be combined with the genetic data of the same human population and where the records of the original MRI data are missing, this paper presents two effective methods for addressing this imaging problem. The first method handles the restoration of the film-copied MRI. The second method involves the segmentation of the image data. Experimental results and comparisons with other methods suggest the usefulness of the proposed image analysis methodology.
What is in a contour map? A region-based logical formalization of contour semantics

USGS Publications Warehouse

Usery, E. Lynn; Hahmann, Torsten

2015-01-01

This paper analyses and formalizes contour semantics in a first-order logic ontology that forms the basis for enabling computational common sense reasoning about contour information. The elicited contour semantics comprises four key concepts – contour regions, contour lines, contour values, and contour sets – and their subclasses and associated relations, which are grounded in an existing qualitative spatial ontology. All concepts and relations are illustrated and motivated by physical-geographic features identifiable on topographic contour maps. The encoding of the semantics of contour concepts in first-order logic and a derived conceptual model as basis for an OWL ontology lay the foundation for fully automated, semantically-aware qualitative and quantitative reasoning about contours.
Universal microfluidic automaton for autonomous sample processing: application to the Mars Organic Analyzer.

PubMed

Kim, Jungkyu; Jensen, Erik C; Stockton, Amanda M; Mathies, Richard A

2013-08-20

A fully integrated multilayer microfluidic chemical analyzer for automated sample processing and labeling, as well as analysis using capillary zone electrophoresis is developed and characterized. Using lifting gate microfluidic control valve technology, a microfluidic automaton consisting of a two-dimensional microvalve cellular array is fabricated with soft lithography in a format that enables facile integration with a microfluidic capillary electrophoresis device. The programmable sample processor performs precise mixing, metering, and routing operations that can be combined to achieve automation of complex and diverse assay protocols. Sample labeling protocols for amino acid, aldehyde/ketone and carboxylic acid analysis are performed automatically followed by automated transfer and analysis by the integrated microfluidic capillary electrophoresis chip. Equivalent performance to off-chip sample processing is demonstrated for each compound class; the automated analysis resulted in a limit of detection of ~16 nM for amino acids. Our microfluidic automaton provides a fully automated, portable microfluidic analysis system capable of autonomous analysis of diverse compound classes in challenging environments.

Automated MRI Segmentation for Individualized Modeling of Current Flow in the Human Head

PubMed Central

Huang, Yu; Dmochowski, Jacek P.; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C.

2013-01-01

Objective High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography (HD-EEG) require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images (MRI) requires labor-intensive manual segmentation, even when leveraging available automated segmentation tools. Also, accurate placement of many high-density electrodes on individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. Approach A fully automated segmentation technique based on Statical Parametric Mapping 8 (SPM8), including an improved tissue probability map (TPM) and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on 4 healthy subjects and 7 stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. Main results The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view (FOV) extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Significance Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials. PMID:24099977
Automated MRI segmentation for individualized modeling of current flow in the human head

NASA Astrophysics Data System (ADS)

Huang, Yu; Dmochowski, Jacek P.; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C.

2013-12-01

Objective. High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. Approach. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets.Main results. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly.Significance. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.
Maximizing Your Investment in Building Automation System Technology.

ERIC Educational Resources Information Center

Darnell, Charles

2001-01-01

Discusses how organizational issues and system standardization can be important factors that determine an institution's ability to fully exploit contemporary building automation systems (BAS). Further presented is management strategy for maximizing BAS investments. (GR)
Numerical and experimental analysis of a ducted propeller designed by a fully automated optimization process under open water condition

NASA Astrophysics Data System (ADS)

Yu, Long; Druckenbrod, Markus; Greve, Martin; Wang, Ke-qi; Abdel-Maksoud, Moustafa

2015-10-01

A fully automated optimization process is provided for the design of ducted propellers under open water conditions, including 3D geometry modeling, meshing, optimization algorithm and CFD analysis techniques. The developed process allows the direct integration of a RANSE solver in the design stage. A practical ducted propeller design case study is carried out for validation. Numerical simulations and open water tests are fulfilled and proved that the optimum ducted propeller improves hydrodynamic performance as predicted.
Evaluation of an automated microplate technique in the Galileo system for ABO and Rh(D) blood grouping.

PubMed

Xu, Weiyi; Wan, Feng; Lou, Yufeng; Jin, Jiali; Mao, Weilin

2014-01-01

A number of automated devices for pretransfusion testing have recently become available. This study evaluated the Immucor Galileo System, a fully automated device based on the microplate hemagglutination technique for ABO/Rh (D) determinations. Routine ABO/Rh typing tests were performed on 13,045 samples using the Immucor automated instruments. Manual tube method was used to resolve ABO forward and reverse grouping discrepancies. D-negative test results were investigated and confirmed manually by the indirect antiglobulin test (IAT). The system rejected 70 tests for sample inadequacy. 87 samples were read as "No-type-determined" due to forward and reverse grouping discrepancies. 25 tests gave these results because of sample hemolysis. After further tests, we found 34 tests were caused by weakened RBC antibodies, 5 tests were attributable to weak A and/or B antigens, 4 tests were due to mixed-field reactions, and 8 tests had high titer cold agglutinin with blood qualifications which react only at temperatures below 34 degrees C. In the remaining 11 cases, irregular RBC antibodies were identified in 9 samples (seven anti-M and two anti-P) and two subgroups were identified in 2 samples (one A1 and one A2) by a reference laboratory. As for D typing, 2 weak D+ samples missed by automated systems gave negative results, but weak-positive reactions were observed in the IAT. The Immucor Galileo System is reliable and suited for ABO and D blood groups, some reasons may cause a discrepancy in ABO/D typing using a fully automated system. It is suggested that standardization of sample collection may improve the performance of the fully automated system.
Fully automated system for the quantification of human osteoarthritic knee joint effusion volume using magnetic resonance imaging

PubMed Central

2010-01-01

Introduction Joint effusion is frequently associated with osteoarthritis (OA) flare-up and is an important marker of therapeutic response. This study aimed at developing and validating a fully automated system based on magnetic resonance imaging (MRI) for the quantification of joint effusion volume in knee OA patients. Methods MRI examinations consisted of two axial sequences: a T2-weighted true fast imaging with steady-state precession and a T1-weighted gradient echo. An automated joint effusion volume quantification system using MRI was developed and validated (a) with calibrated phantoms (cylinder and sphere) and effusion from knee OA patients; (b) with assessment by manual quantification; and (c) by direct aspiration. Twenty-five knee OA patients with joint effusion were included in the study. Results The automated joint effusion volume quantification was developed as a four stage sequencing process: bone segmentation, filtering of unrelated structures, segmentation of joint effusion, and subvoxel volume calculation. Validation experiments revealed excellent coefficients of variation with the calibrated cylinder (1.4%) and sphere (0.8%) phantoms. Comparison of the OA knee joint effusion volume assessed by the developed automated system and by manual quantification was also excellent (r = 0.98; P < 0.0001), as was the comparison with direct aspiration (r = 0.88; P = 0.0008). Conclusions The newly developed fully automated MRI-based system provided precise quantification of OA knee joint effusion volume with excellent correlation with data from phantoms, a manual system, and joint aspiration. Such an automated system will be instrumental in improving the reproducibility/reliability of the evaluation of this marker in clinical application. PMID:20846392
The Impact of Acquisition Dose on Quantitative Breast Density Estimation with Digital Mammography: Results from ACRIN PA 4006.

PubMed

Chen, Lin; Ray, Shonket; Keller, Brad M; Pertuz, Said; McDonald, Elizabeth S; Conant, Emily F; Kontos, Despina

2016-09-01

Purpose To investigate the impact of radiation dose on breast density estimation in digital mammography. Materials and Methods With institutional review board approval and Health Insurance Portability and Accountability Act compliance under waiver of consent, a cohort of women from the American College of Radiology Imaging Network Pennsylvania 4006 trial was retrospectively analyzed. All patients underwent breast screening with a combination of dose protocols, including standard full-field digital mammography, low-dose digital mammography, and digital breast tomosynthesis. A total of 5832 images from 486 women were analyzed with previously validated, fully automated software for quantitative estimation of density. Clinical Breast Imaging Reporting and Data System (BI-RADS) density assessment results were also available from the trial reports. The influence of image acquisition radiation dose on quantitative breast density estimation was investigated with analysis of variance and linear regression. Pairwise comparisons of density estimations at different dose levels were performed with Student t test. Agreement of estimation was evaluated with quartile-weighted Cohen kappa values and Bland-Altman limits of agreement. Results Radiation dose of image acquisition did not significantly affect quantitative density measurements (analysis of variance, P = .37 to P = .75), with percent density demonstrating a high overall correlation between protocols (r = 0.88-0.95; weighted κ = 0.83-0.90). However, differences in breast percent density (1.04% and 3.84%, P < .05) were observed within high BI-RADS density categories, although they were significantly correlated across the different acquisition dose levels (r = 0.76-0.92, P < .05). Conclusion Precision and reproducibility of automated breast density measurements with digital mammography are not substantially affected by variations in radiation dose; thus, the use of low-dose techniques for the purpose of density estimation may be feasible. (©) RSNA, 2016 Online supplemental material is available for this article.
The Impact of Acquisition Dose on Quantitative Breast Density Estimation with Digital Mammography: Results from ACRIN PA 4006

PubMed Central

Chen, Lin; Ray, Shonket; Keller, Brad M.; Pertuz, Said; McDonald, Elizabeth S.; Conant, Emily F.

2016-01-01

Purpose To investigate the impact of radiation dose on breast density estimation in digital mammography. Materials and Methods With institutional review board approval and Health Insurance Portability and Accountability Act compliance under waiver of consent, a cohort of women from the American College of Radiology Imaging Network Pennsylvania 4006 trial was retrospectively analyzed. All patients underwent breast screening with a combination of dose protocols, including standard full-field digital mammography, low-dose digital mammography, and digital breast tomosynthesis. A total of 5832 images from 486 women were analyzed with previously validated, fully automated software for quantitative estimation of density. Clinical Breast Imaging Reporting and Data System (BI-RADS) density assessment results were also available from the trial reports. The influence of image acquisition radiation dose on quantitative breast density estimation was investigated with analysis of variance and linear regression. Pairwise comparisons of density estimations at different dose levels were performed with Student t test. Agreement of estimation was evaluated with quartile-weighted Cohen kappa values and Bland-Altman limits of agreement. Results Radiation dose of image acquisition did not significantly affect quantitative density measurements (analysis of variance, P = .37 to P = .75), with percent density demonstrating a high overall correlation between protocols (r = 0.88–0.95; weighted κ = 0.83–0.90). However, differences in breast percent density (1.04% and 3.84%, P < .05) were observed within high BI-RADS density categories, although they were significantly correlated across the different acquisition dose levels (r = 0.76–0.92, P < .05). Conclusion Precision and reproducibility of automated breast density measurements with digital mammography are not substantially affected by variations in radiation dose; thus, the use of low-dose techniques for the purpose of density estimation may be feasible. © RSNA, 2016 Online supplemental material is available for this article. PMID:27002418
Integrating Test-Form Formatting into Automated Test Assembly

ERIC Educational Resources Information Center

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…
Wire-Guide Manipulator For Automated Welding

NASA Technical Reports Server (NTRS)

Morris, Tim; White, Kevin; Gordon, Steve; Emerich, Dave; Richardson, Dave; Faulkner, Mike; Stafford, Dave; Mccutcheon, Kim; Neal, Ken; Milly, Pete

1994-01-01

Compact motor drive positions guide for welding filler wire. Drive part of automated wire feeder in partly or fully automated welding system. Drive unit contains three parallel subunits. Rotations of lead screws in three subunits coordinated to obtain desired motions in three degrees of freedom. Suitable for both variable-polarity plasma arc welding and gas/tungsten arc welding.
Fully automated corneal endothelial morphometry of images captured by clinical specular microscopy

NASA Astrophysics Data System (ADS)

Bucht, Curry; Söderberg, Per; Manneberg, Göran

2010-02-01

The corneal endothelium serves as the posterior barrier of the cornea. Factors such as clarity and refractive properties of the cornea are in direct relationship to the quality of the endothelium. The endothelial cell density is considered the most important morphological factor of the corneal endothelium. Pathological conditions and physical trauma may threaten the endothelial cell density to such an extent that the optical property of the cornea and thus clear eyesight is threatened. Diagnosis of the corneal endothelium through morphometry is an important part of several clinical applications. Morphometry of the corneal endothelium is presently carried out by semi automated analysis of pictures captured by a Clinical Specular Microscope (CSM). Because of the occasional need of operator involvement, this process can be tedious, having a negative impact on sampling size. This study was dedicated to the development and use of fully automated analysis of a very large range of images of the corneal endothelium, captured by CSM, using Fourier analysis. Software was developed in the mathematical programming language Matlab. Pictures of the corneal endothelium, captured by CSM, were read into the analysis software. The software automatically performed digital enhancement of the images, normalizing lights and contrasts. The digitally enhanced images of the corneal endothelium were Fourier transformed, using the fast Fourier transform (FFT) and stored as new images. Tools were developed and applied for identification and analysis of relevant characteristics of the Fourier transformed images. The data obtained from each Fourier transformed image was used to calculate the mean cell density of its corresponding corneal endothelium. The calculation was based on well known diffraction theory. Results in form of estimated cell density of the corneal endothelium were obtained, using fully automated analysis software on 292 images captured by CSM. The cell density obtained by the fully automated analysis was compared to the cell density obtained from classical, semi-automated analysis and a relatively large correlation was found.
Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

PubMed

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.
Quantitative Indicators for Behaviour Drift Detection from Home Automation Data.

PubMed

Veronese, Fabio; Masciadri, Andrea; Comai, Sara; Matteucci, Matteo; Salice, Fabio

2017-01-01

Smart Homes diffusion provides an opportunity to implement elderly monitoring, extending seniors' independence and avoiding unnecessary assistance costs. Information concerning the inhabitant behaviour is contained in home automation data, and can be extracted by means of quantitative indicators. The application of such approach proves it can evidence behaviour changes.
Alternative Fuels Data Center

Science.gov Websites

Autonomous Vehicle Operation A person can operate a fully autonomous vehicle with the automated federal motor vehicle safety standards and is registered as a fully autonomous vehicle. Other conditions
Xenon International Automated Control

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

2016-08-05

The Xenon International Automated Control software monitors, displays status, and allows for manual operator control as well as fully automatic control of multiple commercial and PNNL designed hardware components to generate and transmit atmospheric radioxenon concentration measurements every six hours.
Development of Fully Automated Low-Cost Immunoassay System for Research Applications.

PubMed

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.
REBOCOL (Robotic Calorimetry): An automated NDA (Nondestructive assay) calorimetry and gamma isotopic system

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

Hurd, J.R.; Bonner, C.A.; Ostenak, C.A.

1989-01-01

ROBOCAL, which is presently being developed and tested at Los Alamos National Laboratory, is a full-scale, prototypical robotic system, for remote calorimetric and gamma-ray analysis of special nuclear materials. It integrates a fully automated, multi-drawer, 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 and data-base system are provided to interact with the automated mechanical and assay systems. The assay system is designed to completely integrate calorimetric andmore » 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. 10 refs., 10 figs., 4 tabs.« less
ProDeGe: A computational protocol for fully automated decontamination of genomes

DOE PAGES

Tennessen, Kristin; Andersen, Evan; Clingenpeel, Scott; ...

2015-06-09

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies.more » On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). Lastly, the procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.« less
ProDeGe: A computational protocol for fully automated decontamination of genomes

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

Tennessen, Kristin; Andersen, Evan; Clingenpeel, Scott

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies.more » On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). Lastly, the procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.« less
The iFly Tracking System for an Automated Locomotor and Behavioural Analysis of Drosophila melanogaster

PubMed Central

Kohlhoff, Kai J.; Jahn, Thomas R.; Lomas, David A.; Dobson, Christopher M.; Crowther, Damian C.; Vendruscolo, Michele

2016-01-01

The use of animal models in medical research provides insights into molecular and cellular mechanisms of human disease, and helps identify and test novel therapeutic strategies. Drosophila melanogaster – the common fruit fly – is one of the most established model organisms, as its study can be performed more readily and with far less expense than for other model animal systems, such as mice, fish, or indeed primates. In the case of fruit flies, standard assays are based on the analysis of longevity and basic locomotor functions. Here we present the iFly tracking system, which enables to increase the amount of quantitative information that can be extracted from these studies, and to reduce significantly the duration and costs associated with them. The iFly system uses a single camera to simultaneously track the trajectories of up to 20 individual flies with about 100μm spatial and 33ms temporal resolution. The statistical analysis of fly movements recorded with such accuracy makes it possible to perform a rapid and fully automated quantitative analysis of locomotor changes in response to a range of different stimuli. We anticipate that the iFly method will reduce very considerably the costs and the duration of the testing of genetic and pharmacological interventions in Drosophila models, including an earlier detection of behavioural changes and a large increase in throughput compared to current longevity and locomotor assays. PMID:21698336

A Robotic Platform for Quantitative High-Throughput Screening

PubMed Central

Michael, Sam; Auld, Douglas; Klumpp, Carleen; Jadhav, Ajit; Zheng, Wei; Thorne, Natasha; Austin, Christopher P.; Inglese, James

2008-01-01

Abstract High-throughput screening (HTS) is increasingly being adopted in academic institutions, where the decoupling of screening and drug development has led to unique challenges, as well as novel uses of instrumentation, assay formulations, and software tools. Advances in technology have made automated unattended screening in the 1,536-well plate format broadly accessible and have further facilitated the exploration of new technologies and approaches to screening. A case in point is our recently developed quantitative HTS (qHTS) paradigm, which tests each library compound at multiple concentrations to construct concentration-response curves (CRCs) generating a comprehensive data set for each assay. The practical implementation of qHTS for cell-based and biochemical assays across libraries of > 100,000 compounds (e.g., between 700,000 and 2,000,000 sample wells tested) requires maximal efficiency and miniaturization and the ability to easily accommodate many different assay formats and screening protocols. Here, we describe the design and utilization of a fully integrated and automated screening system for qHTS at the National Institutes of Health's Chemical Genomics Center. We report system productivity, reliability, and flexibility, as well as modifications made to increase throughput, add additional capabilities, and address limitations. The combination of this system and qHTS has led to the generation of over 6 million CRCs from > 120 assays in the last 3 years and is a technology that can be widely implemented to increase efficiency of screening and lead generation. PMID:19035846
Retinal health information and notification system (RHINO)

NASA Astrophysics Data System (ADS)

Dashtbozorg, Behdad; Zhang, Jiong; Abbasi-Sureshjani, Samaneh; Huang, Fan; ter Haar Romeny, Bart M.

2017-03-01

The retinal vasculature is the only part of the blood circulation system that can be observed non-invasively using fundus cameras. Changes in the dynamic properties of retinal blood vessels are associated with many systemic and vascular diseases, such as hypertension, coronary heart disease and diabetes. The assessment of the characteristics of the retinal vascular network provides important information for an early diagnosis and prognosis of many systemic and vascular diseases. The manual analysis of the retinal vessels and measurement of quantitative biomarkers in large-scale screening programs is a tedious task, time-consuming and costly. This paper describes a reliable, automated, and efficient retinal health information and notification system (acronym RHINO) which can extract a wealth of geometric biomarkers in large volumes of fundus images. The fully automated software presented in this paper includes vessel enhancement and segmentation, artery/vein classification, optic disc, fovea, and vessel junction detection, and bifurcation/crossing discrimination. Pipelining these tools allows the assessment of several quantitative vascular biomarkers: width, curvature, bifurcation geometry features and fractal dimension. The brain-inspired algorithms outperform most of the state-of-the-art techniques. Moreover, several annotation tools are implemented in RHINO for the manual labeling of arteries and veins, marking optic disc and fovea, and delineating vessel centerlines. The validation phase is ongoing and the software is currently being used for the analysis of retinal images from the Maastricht study (the Netherlands) which includes over 10,000 subjects (healthy and diabetic) with a broad spectrum of clinical measurements
The impact of injector-based contrast agent administration in time-resolved MRA.

PubMed

Budjan, Johannes; Attenberger, Ulrike I; Schoenberg, Stefan O; Pietsch, Hubertus; Jost, Gregor

2018-05-01

Time-resolved contrast-enhanced MR angiography (4D-MRA), which allows the simultaneous visualization of the vasculature and blood-flow dynamics, is widely used in clinical routine. In this study, the impact of two different contrast agent injection methods on 4D-MRA was examined in a controlled, standardized setting in an animal model. Six anesthetized Goettingen minipigs underwent two identical 4D-MRA examinations at 1.5 T in a single session. The contrast agent (0.1 mmol/kg body weight gadobutrol, followed by 20 ml saline) was injected using either manual injection or an automated injection system. A quantitative comparison of vascular signal enhancement and quantitative renal perfusion analyses were performed. Analysis of signal enhancement revealed higher peak enhancements and shorter time to peak intervals for the automated injection. Significantly different bolus shapes were found: automated injection resulted in a compact first-pass bolus shape clearly separated from the recirculation while manual injection resulted in a disrupted first-pass bolus with two peaks. In the quantitative perfusion analyses, statistically significant differences in plasma flow values were found between the injection methods. The results of both qualitative and quantitative 4D-MRA depend on the contrast agent injection method, with automated injection providing more defined bolus shapes and more standardized examination protocols. • Automated and manual contrast agent injection result in different bolus shapes in 4D-MRA. • Manual injection results in an undefined and interrupted bolus with two peaks. • Automated injection provides more defined bolus shapes. • Automated injection can lead to more standardized examination protocols.
Automation in Clinical Microbiology

PubMed Central

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
Interim Assessment of the VAL Automated Guideway Transit System.

DOT National Transportation Integrated Search

1981-11-01

This report describes an interim assessment of the VAL (Vehicules Automatiques Legers or Light Automated Vehicle) AGT system which is currently under construction in Lille, France, and which is to become fully operational in December 1983. This repor...
Extraction efficiency and implications for absolute quantitation of propranolol in mouse brain, liver and kidney thin tissue sections using droplet-based liquid microjunction surface sampling-HPLC ESI-MS/MS

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

Kertesz, Vilmos; Weiskittel, Taylor M.; Vavek, Marissa

Currently, absolute quantitation aspects of droplet-based surface sampling for thin tissue analysis using a fully automated autosampler/HPLC-ESI-MS/MS system are not fully evaluated. Knowledge of extraction efficiency and its reproducibility is required to judge the potential of the method for absolute quantitation of analytes from thin tissue sections. Methods: Adjacent thin tissue sections of propranolol dosed mouse brain (10- μm-thick), kidney (10- μm-thick) and liver (8-, 10-, 16- and 24- μm-thick) were obtained. Absolute concentration of propranolol was determined in tissue punches from serial sections using standard bulk tissue extraction protocols and subsequent HPLC separations and tandem mass spectrometric analysis. Thesemore » values were used to determine propranolol extraction efficiency from the tissues with the droplet-based surface sampling approach. Results: Extraction efficiency of propranolol using 10- μm-thick brain, kidney and liver thin tissues using droplet-based surface sampling varied between ~45-63%. Extraction efficiency decreased from ~65% to ~36% with liver thickness increasing from 8 μm to 24 μm. Randomly selecting half of the samples as standards, precision and accuracy of propranolol concentrations obtained for the other half of samples as quality control metrics were determined. Resulting precision ( ±15%) and accuracy ( ±3%) values, respectively, were within acceptable limits. In conclusion, comparative quantitation of adjacent mouse thin tissue sections of different organs and of various thicknesses by droplet-based surface sampling and by bulk extraction of tissue punches showed that extraction efficiency was incomplete using the former method, and that it depended on the organ and tissue thickness. However, once extraction efficiency was determined and applied, the droplet-based approach provided the required quantitation accuracy and precision for assay validations. Furthermore, this means that once the extraction efficiency was calibrated for a given tissue type and drug, the droplet-based approach provides a non-labor intensive and high-throughput means to acquire spatially resolved quantitative analysis of multiple samples of the same type.« less
Extraction efficiency and implications for absolute quantitation of propranolol in mouse brain, liver and kidney thin tissue sections using droplet-based liquid microjunction surface sampling-HPLC ESI-MS/MS

DOE PAGES

Kertesz, Vilmos; Weiskittel, Taylor M.; Vavek, Marissa; ...

2016-06-22

Currently, absolute quantitation aspects of droplet-based surface sampling for thin tissue analysis using a fully automated autosampler/HPLC-ESI-MS/MS system are not fully evaluated. Knowledge of extraction efficiency and its reproducibility is required to judge the potential of the method for absolute quantitation of analytes from thin tissue sections. Methods: Adjacent thin tissue sections of propranolol dosed mouse brain (10- μm-thick), kidney (10- μm-thick) and liver (8-, 10-, 16- and 24- μm-thick) were obtained. Absolute concentration of propranolol was determined in tissue punches from serial sections using standard bulk tissue extraction protocols and subsequent HPLC separations and tandem mass spectrometric analysis. Thesemore » values were used to determine propranolol extraction efficiency from the tissues with the droplet-based surface sampling approach. Results: Extraction efficiency of propranolol using 10- μm-thick brain, kidney and liver thin tissues using droplet-based surface sampling varied between ~45-63%. Extraction efficiency decreased from ~65% to ~36% with liver thickness increasing from 8 μm to 24 μm. Randomly selecting half of the samples as standards, precision and accuracy of propranolol concentrations obtained for the other half of samples as quality control metrics were determined. Resulting precision ( ±15%) and accuracy ( ±3%) values, respectively, were within acceptable limits. In conclusion, comparative quantitation of adjacent mouse thin tissue sections of different organs and of various thicknesses by droplet-based surface sampling and by bulk extraction of tissue punches showed that extraction efficiency was incomplete using the former method, and that it depended on the organ and tissue thickness. However, once extraction efficiency was determined and applied, the droplet-based approach provided the required quantitation accuracy and precision for assay validations. Furthermore, this means that once the extraction efficiency was calibrated for a given tissue type and drug, the droplet-based approach provides a non-labor intensive and high-throughput means to acquire spatially resolved quantitative analysis of multiple samples of the same type.« less
A population-based tissue probability map-driven level set method for fully automated mammographic density estimations.

PubMed

Kim, Youngwoo; Hong, Byung Woo; Kim, Seung Ja; Kim, Jong Hyo

2014-07-01

A major challenge when distinguishing glandular tissues on mammograms, especially for area-based estimations, lies in determining a boundary on a hazy transition zone from adipose to glandular tissues. This stems from the nature of mammography, which is a projection of superimposed tissues consisting of different structures. In this paper, the authors present a novel segmentation scheme which incorporates the learned prior knowledge of experts into a level set framework for fully automated mammographic density estimations. The authors modeled the learned knowledge as a population-based tissue probability map (PTPM) that was designed to capture the classification of experts' visual systems. The PTPM was constructed using an image database of a selected population consisting of 297 cases. Three mammogram experts extracted regions for dense and fatty tissues on digital mammograms, which was an independent subset used to create a tissue probability map for each ROI based on its local statistics. This tissue class probability was taken as a prior in the Bayesian formulation and was incorporated into a level set framework as an additional term to control the evolution and followed the energy surface designed to reflect experts' knowledge as well as the regional statistics inside and outside of the evolving contour. A subset of 100 digital mammograms, which was not used in constructing the PTPM, was used to validate the performance. The energy was minimized when the initial contour reached the boundary of the dense and fatty tissues, as defined by experts. The correlation coefficient between mammographic density measurements made by experts and measurements by the proposed method was 0.93, while that with the conventional level set was 0.47. The proposed method showed a marked improvement over the conventional level set method in terms of accuracy and reliability. This result suggests that the proposed method successfully incorporated the learned knowledge of the experts' visual systems and has potential to be used as an automated and quantitative tool for estimations of mammographic breast density levels.
ASPECTS: an automation-assisted SPE method development system.

PubMed

Li, Ming; Chou, Judy; King, Kristopher W; Yang, Liyu

2013-07-01

A typical conventional SPE method development (MD) process usually involves deciding the chemistry of the sorbent and eluent based on information about the analyte; experimentally preparing and trying out various combinations of adsorption chemistry and elution conditions; quantitatively evaluating the various conditions; and comparing quantitative results from all combination of conditions to select the best condition for method qualification. The second and fourth steps have mostly been performed manually until now. We developed an automation-assisted system that expedites the conventional SPE MD process by automating 99% of the second step, and expedites the fourth step by automatically processing the results data and presenting it to the analyst in a user-friendly format. The automation-assisted SPE MD system greatly saves the manual labor in SPE MD work, prevents analyst errors from causing misinterpretation of quantitative results, and shortens data analysis and interpretation time.
Semi-automated 96-well liquid-liquid extraction for quantitation of drugs in biological fluids.

PubMed

Zhang, N; Hoffman, K L; Li, W; Rossi, D T

2000-02-01

A semi-automated liquid-liquid extraction (LLE) technique for biological fluid sample preparation was introduced for the quantitation of four drugs in rat plasma. All liquid transferring during the sample preparation was automated using a Tomtec Quadra 96 Model 320 liquid handling robot, which processed up to 96 samples in parallel. The samples were either in 96-deep-well plate or tube-rack format. One plate of samples can be prepared in approximately 1.5 h, and the 96-well plate is directly compatible with the autosampler of an LC/MS system. Selection of organic solvents and recoveries are discussed. Also, precision, relative error, linearity and quantitation of the semi automated LLE method are estimated for four example drugs using LC/MS/MS with a multiple reaction monitoring (MRM) approach. The applicability of this method and future directions are evaluated.
Recent development in software and automation tools for high-throughput discovery bioanalysis.

PubMed

Shou, Wilson Z; Zhang, Jun

2012-05-01

Bioanalysis with LC-MS/MS has been established as the method of choice for quantitative determination of drug candidates in biological matrices in drug discovery and development. The LC-MS/MS bioanalytical support for drug discovery, especially for early discovery, often requires high-throughput (HT) analysis of large numbers of samples (hundreds to thousands per day) generated from many structurally diverse compounds (tens to hundreds per day) with a very quick turnaround time, in order to provide important activity and liability data to move discovery projects forward. Another important consideration for discovery bioanalysis is its fit-for-purpose quality requirement depending on the particular experiments being conducted at this stage, and it is usually not as stringent as those required in bioanalysis supporting drug development. These aforementioned attributes of HT discovery bioanalysis made it an ideal candidate for using software and automation tools to eliminate manual steps, remove bottlenecks, improve efficiency and reduce turnaround time while maintaining adequate quality. In this article we will review various recent developments that facilitate automation of individual bioanalytical procedures, such as sample preparation, MS/MS method development, sample analysis and data review, as well as fully integrated software tools that manage the entire bioanalytical workflow in HT discovery bioanalysis. In addition, software tools supporting the emerging high-resolution accurate MS bioanalytical approach are also discussed.
Automatic cerebrospinal fluid segmentation in non-contrast CT images using a 3D convolutional network

NASA Astrophysics Data System (ADS)

Patel, Ajay; van de Leemput, Sil C.; Prokop, Mathias; van Ginneken, Bram; Manniesing, Rashindra

2017-03-01

Segmentation of anatomical structures is fundamental in the development of computer aided diagnosis systems for cerebral pathologies. Manual annotations are laborious, time consuming and subject to human error and observer variability. Accurate quantification of cerebrospinal fluid (CSF) can be employed as a morphometric measure for diagnosis and patient outcome prediction. However, segmenting CSF in non-contrast CT images is complicated by low soft tissue contrast and image noise. In this paper we propose a state-of-the-art method using a multi-scale three-dimensional (3D) fully convolutional neural network (CNN) to automatically segment all CSF within the cranial cavity. The method is trained on a small dataset comprised of four manually annotated cerebral CT images. Quantitative evaluation of a separate test dataset of four images shows a mean Dice similarity coefficient of 0.87 +/- 0.01 and mean absolute volume difference of 4.77 +/- 2.70 %. The average prediction time was 68 seconds. Our method allows for fast and fully automated 3D segmentation of cerebral CSF in non-contrast CT, and shows promising results despite a limited amount of training data.
Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation

PubMed Central

Beijbom, Oscar; Edmunds, Peter J.; Roelfsema, Chris; Smith, Jennifer; Kline, David I.; Neal, Benjamin P.; Dunlap, Matthew J.; Moriarty, Vincent; Fan, Tung-Yung; Tan, Chih-Jui; Chan, Stephen; Treibitz, Tali; Gamst, Anthony; Mitchell, B. Greg; Kriegman, David

2015-01-01

Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys. PMID:26154157
Assessing Library Automation and Virtual Library Development in Four Academic Libraries in Oyo, Oyo State, Nigeria

ERIC Educational Resources Information Center

Gbadamosi, Belau Olatunde

2011-01-01

The paper examines the level of library automation and virtual library development in four academic libraries. A validated questionnaire was used to capture the responses from academic librarians of the libraries under study. The paper discovers that none of the four academic libraries is fully automated. The libraries make use of librarians with…
A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

PubMed

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.
C-reactive protein and interleukin 6 microfluidic immunoassays with on-chip pre-stored reagents and centrifugo-pneumatic liquid control.

PubMed

Zhao, Y; Czilwik, G; Klein, V; Mitsakakis, K; Zengerle, R; Paust, N

2017-05-02

We present a fully automated centrifugal microfluidic method for particle based protein immunoassays. Stick-pack technology is employed for pre-storage and release of liquid reagents. Quantitative layout of centrifugo-pneumatic particle handling, including timed valving, switching and pumping is assisted by network simulations. The automation is exclusively controlled by the spinning frequency and does not require any additional means. New centrifugal microfluidic process chains are developed in order to sequentially supply wash buffer based on frequency dependent stick-pack opening and pneumatic pumping to perform two washing steps from one stored wash buffer; pre-store and re-suspend functionalized microparticles on a disk; and switch between the path of the waste fluid and the path of the substrate reaction product with 100% efficiency. The automated immunoassay concept is composed of on demand ligand binding, two washing steps, the substrate reaction, timed separation of the reaction products, and termination of the substrate reaction. We demonstrated separation of particles from three different liquids with particle loss below 4% and residual liquid remaining within particles below 3%. The automated immunoassay concept was demonstrated by means of detecting C-reactive protein (CRP) in the range of 1-81 ng ml -1 and interleukin 6 (IL-6) in the range of 64-13 500 pg ml -1 . The limit of detection and quantification were 1.0 ng ml -1 and 2.1 ng ml -1 for CRP and 64 pg ml -1 and 205 pg ml -1 for IL-6, respectively.
Automated tetraploid genotype calling by hierarchical clustering

USDA-ARS?s Scientific Manuscript database

SNP arrays are transforming breeding and genetics research for autotetraploids. To fully utilize these arrays, however, the relationship between signal intensity and allele dosage must be inferred independently for each marker. We developed an improved computational method to automate this process, ...
Development of a Novel and Rapid Fully Automated Genetic Testing System.

PubMed

Uehara, Masayuki

2016-01-01

We have developed a rapid genetic testing system integrating nucleic acid extraction, purification, amplification, and detection in a single cartridge. The system performs real-time polymerase chain reaction (PCR) after nucleic acid purification in a fully automated manner. RNase P, a housekeeping gene, was purified from human nasal epithelial cells using silica-coated magnetic beads and subjected to real-time PCR using a novel droplet-real-time-PCR machine. The process was completed within 13 min. This system will be widely applicable for research and diagnostic uses.
An iterative method for airway segmentation using multiscale leakage detection

NASA Astrophysics Data System (ADS)

Nadeem, Syed Ahmed; Jin, Dakai; Hoffman, Eric A.; Saha, Punam K.

2017-02-01

There are growing applications of quantitative computed tomography for assessment of pulmonary diseases by characterizing lung parenchyma as well as the bronchial tree. Many large multi-center studies incorporating lung imaging as a study component are interested in phenotypes relating airway branching patterns, wall-thickness, and other morphological measures. To our knowledge, there are no fully automated airway tree segmentation methods, free of the need for user review. Even when there are failures in a small fraction of segmentation results, the airway tree masks must be manually reviewed for all results which is laborious considering that several thousands of image data sets are evaluated in large studies. In this paper, we present a CT-based novel airway tree segmentation algorithm using iterative multi-scale leakage detection, freezing, and active seed detection. The method is fully automated requiring no manual inputs or post-segmentation editing. It uses simple intensity based connectivity and a new leakage detection algorithm to iteratively grow an airway tree starting from an initial seed inside the trachea. It begins with a conservative threshold and then, iteratively shifts toward generous values. The method was applied on chest CT scans of ten non-smoking subjects at total lung capacity and ten at functional residual capacity. Airway segmentation results were compared to an expert's manually edited segmentations. Branch level accuracy of the new segmentation method was examined along five standardized segmental airway paths (RB1, RB4, RB10, LB1, LB10) and two generations beyond these branches. The method successfully detected all branches up to two generations beyond these segmental bronchi with no visual leakages.
Manual, semiautomated, and fully automated measurement of the aortic annulus for planning of transcatheter aortic valve replacement (TAVR/TAVI): analysis of interchangeability.

PubMed

Lou, Junyang; Obuchowski, Nancy A; Krishnaswamy, Amar; Popovic, Zoran; Flamm, Scott D; Kapadia, Samir R; Svensson, Lars G; Bolen, Michael A; Desai, Milind Y; Halliburton, Sandra S; Tuzcu, E Murat; Schoenhagen, Paul

2015-01-01

Preprocedural 3-dimensional CT imaging of the aortic annular plane plays a critical role for transcatheter aortic valve replacement (TAVR) planning; however, manual reconstructions are complex. Automated analysis software may improve reproducibility and agreement between readers but is incompletely validated. In 110 TAVR patients (mean age, 81 years; 37% female) undergoing preprocedural multidetector CT, automated reconstruction of the aortic annular plane and planimetry of the annulus was performed with a prototype of now commercially available software (syngo.CT Cardiac Function-Valve Pilot; Siemens Healthcare, Erlangen, Germany). Fully automated, semiautomated, and manual annulus measurements were compared. Intrareader and inter-reader agreement, intermodality agreement, and interchangeability were analyzed. Finally, the impact of these measurements on recommended valve size was evaluated. Semiautomated analysis required major correction in 5 patients (4.5%). In the remaining 95.5%, only minor correction was performed. Mean manual annulus area was significantly smaller than fully automated results (P < .001 for both readers) but similar to semiautomated measurements (5.0 vs 5.4 vs 4.9 cm(2), respectively). The frequency of concordant recommendations for valve size increased if manual analysis was replaced with the semiautomated method (60% agreement was improved to 82.4%; 95% confidence interval for the difference [69.1%-83.4%]). Semiautomated aortic annulus analysis, with minor correction by the user, provides reliable results in the context of TAVR annulus evaluation. Copyright © 2015 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Space science experimentation automation and support

NASA Technical Reports Server (NTRS)

Frainier, Richard J.; Groleau, Nicolas; Shapiro, Jeff C.

1994-01-01

This paper outlines recent work done at the NASA Ames Artificial Intelligence Research Laboratory on automation and support of science experiments on the US Space Shuttle in low earth orbit. Three approaches to increasing the science return of these experiments using emerging automation technologies are described: remote control (telescience), science advisors for astronaut operators, and fully autonomous experiments. The capabilities and limitations of these approaches are reviewed.
Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease

PubMed Central

Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B.; Torres, Vicente E.; Yu, Alan S.L.; Mrug, Michal; Bennett, William M.; Flessner, Michael F.; Landsittel, Doug P.

2016-01-01

Background and objectives Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Design, setting, participants, & measurements Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2–weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Results Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable. Conclusions We have developed a fully automated method for segmentation of kidneys from abdominal magnetic resonance images in patients with autosomal dominant polycystic kidney disease with varying kidney volumes. The performance of the automated method was in good agreement with that of manual method. PMID:26797708
Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease.

PubMed

Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B; Torres, Vicente E; Yu, Alan S L; Mrug, Michal; Bennett, William M; Flessner, Michael F; Landsittel, Doug P; Bae, Kyongtae T

2016-04-07

Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2-weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable. We have developed a fully automated method for segmentation of kidneys from abdominal magnetic resonance images in patients with autosomal dominant polycystic kidney disease with varying kidney volumes. The performance of the automated method was in good agreement with that of manual method. Copyright © 2016 by the American Society of Nephrology.
Automated acquisition system for routine, noninvasive monitoring of physiological data.

PubMed

Ogawa, M; Tamura, T; Togawa, T

1998-01-01

A fully automated, noninvasive data-acquisition system was developed to permit long-term measurement of physiological functions at home, without disturbing subjects' normal routines. The system consists of unconstrained monitors built into furnishings and structures in a home environment. An electrocardiographic (ECG) monitor in the bathtub measures heart function during bathing, a temperature monitor in the bed measures body temperature, and a weight monitor built into the toilet serves as a scale to record weight. All three monitors are connected to one computer and function with data-acquisition programs and a data format rule. The unconstrained physiological parameter monitors and fully automated measurement procedures collect data noninvasively without the subject's awareness. The system was tested for 1 week by a healthy male subject, aged 28, in laboratory-based facilities.
A Fully Automated Drosophila Olfactory Classical Conditioning and Testing System for Behavioral Learning and Memory Assessment

PubMed Central

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

2016-01-01

Background 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. New Method 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. Results The approach allows accurate learning/memory determinations with operational fail-safes. Automated learning indices (immediately post-training) and memory indices (after 24 hours) are comparable to traditional manual experiments, while minimizing experimenter involvement. Comparison with Existing Methods 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. Conclusions 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. PMID:26703418
A fully automated Drosophila olfactory classical conditioning and testing system for behavioral learning and memory assessment.

PubMed

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.
Fully automated, real-time 3D ultrasound segmentation to estimate first trimester placental volume using deep learning.

PubMed

Looney, Pádraig; Stevenson, Gordon N; Nicolaides, Kypros H; Plasencia, Walter; Molloholli, Malid; Natsis, Stavros; Collins, Sally L

2018-06-07

We present a new technique to fully automate the segmentation of an organ from 3D ultrasound (3D-US) volumes, using the placenta as the target organ. Image analysis tools to estimate organ volume do exist but are too time consuming and operator dependant. Fully automating the segmentation process would potentially allow the use of placental volume to screen for increased risk of pregnancy complications. The placenta was segmented from 2,393 first trimester 3D-US volumes using a semiautomated technique. This was quality controlled by three operators to produce the "ground-truth" data set. A fully convolutional neural network (OxNNet) was trained using this ground-truth data set to automatically segment the placenta. OxNNet delivered state-of-the-art automatic segmentation. The effect of training set size on the performance of OxNNet demonstrated the need for large data sets. The clinical utility of placental volume was tested by looking at predictions of small-for-gestational-age babies at term. The receiver-operating characteristics curves demonstrated almost identical results between OxNNet and the ground-truth). Our results demonstrated good similarity to the ground-truth and almost identical clinical results for the prediction of SGA.
Fully automated atlas-based hippocampal volumetry for detection of Alzheimer's disease in a memory clinic setting.

PubMed

Suppa, Per; Anker, Ulrich; Spies, Lothar; Bopp, Irene; Rüegger-Frey, Brigitte; Klaghofer, Richard; Gocke, Carola; Hampel, Harald; Beck, Sacha; Buchert, Ralph

2015-01-01

Hippocampal volume is a promising biomarker to enhance the accuracy of the diagnosis of dementia due to Alzheimer's disease (AD). However, whereas hippocampal volume is well studied in patient samples from clinical trials, its value in clinical routine patient care is still rather unclear. The aim of the present study, therefore, was to evaluate fully automated atlas-based hippocampal volumetry for detection of AD in the setting of a secondary care expert memory clinic for outpatients. One-hundred consecutive patients with memory complaints were clinically evaluated and categorized into three diagnostic groups: AD, intermediate AD, and non-AD. A software tool based on open source software (Statistical Parametric Mapping SPM8) was employed for fully automated tissue segmentation and stereotactical normalization of high-resolution three-dimensional T1-weighted magnetic resonance images. Predefined standard masks were used for computation of grey matter volume of the left and right hippocampus which then was scaled to the patient's total grey matter volume. The right hippocampal volume provided an area under the receiver operating characteristic curve of 84% for detection of AD patients in the whole sample. This indicates that fully automated MR-based hippocampal volumetry fulfills the requirements for a relevant core feasible biomarker for detection of AD in everyday patient care in a secondary care memory clinic for outpatients. The software used in the present study has been made freely available as an SPM8 toolbox. It is robust and fast so that it is easily integrated into routine workflow.
Evaluation of Automated and Semi-Automated Scoring of Polysomnographic Recordings from a Clinical Trial Using Zolpidem in the Treatment of Insomnia

PubMed Central

Svetnik, Vladimir; Ma, Junshui; Soper, Keith A.; Doran, Scott; Renger, John J.; Deacon, Steve; Koblan, Ken S.

2007-01-01

Objective: To evaluate the performance of 2 automated systems, Morpheus and Somnolyzer24X7, with various levels of human review/editing, in scoring polysomnographic (PSG) recordings from a clinical trial using zolpidem in a model of transient insomnia. Methods: 164 all-night PSG recordings from 82 subjects collected during 2 nights of sleep, one under placebo and one under zolpidem (10 mg) treatment were used. For each recording, 6 different methods were used to provide sleep stage scores based on Rechtschaffen & Kales criteria: 1) full manual scoring, 2) automated scoring by Morpheus 3) automated scoring by Somnolyzer24X7, 4) automated scoring by Morpheus with full manual review, 5) automated scoring by Morpheus with partial manual review, 6) automated scoring by Somnolyzer24X7 with partial manual review. Ten traditional clinical efficacy measures of sleep initiation, maintenance, and architecture were calculated. Results: Pair-wise epoch-by-epoch agreements between fully automated and manual scores were in the range of intersite manual scoring agreements reported in the literature (70%-72%). Pair-wise epoch-by-epoch agreements between automated scores manually reviewed were higher (73%-76%). The direction and statistical significance of treatment effect sizes using traditional efficacy endpoints were essentially the same whichever method was used. As the degree of manual review increased, the magnitude of the effect size approached those estimated with fully manual scoring. Conclusion: Automated or semi-automated sleep PSG scoring offers valuable alternatives to costly, time consuming, and intrasite and intersite variable manual scoring, especially in large multicenter clinical trials. Reduction in scoring variability may also reduce the sample size of a clinical trial. Citation: Svetnik V; Ma J; Soper KA; Doran S; Renger JJ; Deacon S; Koblan KS. Evaluation of automated and semi-automated scoring of polysomnographic recordings from a clinical trial using zolpidem in the treatment of insomnia. SLEEP 2007;30(11):1562-1574. PMID:18041489
Automated quantitative cytological analysis using portable microfluidic microscopy.

PubMed

Jagannadh, Veerendra Kalyan; Murthy, Rashmi Sreeramachandra; Srinivasan, Rajesh; Gorthi, Sai Siva

2016-06-01

In this article, a portable microfluidic microscopy based approach for automated cytological investigations is presented. Inexpensive optical and electronic components have been used to construct a simple microfluidic microscopy system. In contrast to the conventional slide-based methods, the presented method employs microfluidics to enable automated sample handling and image acquisition. The approach involves the use of simple in-suspension staining and automated image acquisition to enable quantitative cytological analysis of samples. The applicability of the presented approach to research in cellular biology is shown by performing an automated cell viability assessment on a given population of yeast cells. Further, the relevance of the presented approach to clinical diagnosis and prognosis has been demonstrated by performing detection and differential assessment of malaria infection in a given sample. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
An improved level set method for brain MR images segmentation and bias correction.

PubMed

Chen, Yunjie; Zhang, Jianwei; Macione, Jim

2009-10-01

Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.
Multi-atlas propagation based left atrium segmentation coupled with super-voxel based pulmonary veins delineation in late gadolinium-enhanced cardiac MRI

NASA Astrophysics Data System (ADS)

Yang, Guang; Zhuang, Xiahai; Khan, Habib; Haldar, Shouvik; Nyktari, Eva; Li, Lei; Ye, Xujiong; Slabaugh, Greg; Wong, Tom; Mohiaddin, Raad; Keegan, Jennifer; Firmin, David

2017-02-01

Late Gadolinium-Enhanced Cardiac MRI (LGE CMRI) is a non-invasive technique, which has shown promise in detecting native and post-ablation atrial scarring. To visualize the scarring, a precise segmentation of the left atrium (LA) and pulmonary veins (PVs) anatomy is performed as a first step—usually from an ECG gated CMRI roadmap acquisition—and the enhanced scar regions from the LGE CMRI images are superimposed. The anatomy of the LA and PVs in particular is highly variable and manual segmentation is labor intensive and highly subjective. In this paper, we developed a multi-atlas propagation based whole heart segmentation (WHS) to delineate the LA and PVs from ECG gated CMRI roadmap scans. While this captures the anatomy of the atrium well, the PVs anatomy is less easily visualized. The process is therefore augmented by semi-automated manual strokes for PVs identification in the registered LGE CMRI data. This allows us to extract more accurate anatomy than the fully automated WHS. Both qualitative visualization and quantitative assessment with respect to manual segmented ground truth showed that our method is efficient and effective with an overall mean Dice score of 0.91.
Pulmonary Lobe Segmentation with Probabilistic Segmentation of the Fissures and a Groupwise Fissure Prior

PubMed Central

Bragman, Felix J.S.; McClelland, Jamie R.; Jacob, Joseph; Hurst, John R.; Hawkes, David J.

2017-01-01

A fully automated, unsupervised lobe segmentation algorithm is presented based on a probabilistic segmentation of the fissures and the simultaneous construction of a population model of the fissures. A two-class probabilistic segmentation segments the lung into candidate fissure voxels and the surrounding parenchyma. This was combined with anatomical information and a groupwise fissure prior to drive non-parametric surface fitting to obtain the final segmentation. The performance of our fissure segmentation was validated on 30 patients from the COPDGene cohort, achieving a high median F1-score of 0.90 and showed general insensitivity to filter parameters. We evaluated our lobe segmentation algorithm on the LOLA11 dataset, which contains 55 cases at varying levels of pathology. We achieved the highest score of 0.884 of the automated algorithms. Our method was further tested quantitatively and qualitatively on 80 patients from the COPDGene study at varying levels of functional impairment. Accurate segmentation of the lobes is shown at various degrees of fissure incompleteness for 96% of all cases. We also show the utility of including a groupwise prior in segmenting the lobes in regions of grossly incomplete fissures. PMID:28436850
ConfocalCheck - A Software Tool for the Automated Monitoring of Confocal Microscope Performance

PubMed Central

Hng, Keng Imm; Dormann, Dirk

2013-01-01

Laser scanning confocal microscopy has become an invaluable tool in biomedical research but regular quality testing is vital to maintain the system’s performance for diagnostic and research purposes. Although many methods have been devised over the years to characterise specific aspects of a confocal microscope like measuring the optical point spread function or the field illumination, only very few analysis tools are available. Our aim was to develop a comprehensive quality assurance framework ranging from image acquisition to automated analysis and documentation. We created standardised test data to assess the performance of the lasers, the objective lenses and other key components required for optimum confocal operation. The ConfocalCheck software presented here analyses the data fully automatically. It creates numerous visual outputs indicating potential issues requiring further investigation. By storing results in a web browser compatible file format the software greatly simplifies record keeping allowing the operator to quickly compare old and new data and to spot developing trends. We demonstrate that the systematic monitoring of confocal performance is essential in a core facility environment and how the quantitative measurements obtained can be used for the detailed characterisation of system components as well as for comparisons across multiple instruments. PMID:24224017
Fully automated synthesis of [(18) F]fluoro-dihydrotestosterone ([(18) F]FDHT) using the FlexLab module.

PubMed

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.
Automated estimation of image quality for coronary computed tomographic angiography using machine learning.

PubMed

Nakanishi, Rine; Sankaran, Sethuraman; Grady, Leo; Malpeso, Jenifer; Yousfi, Razik; Osawa, Kazuhiro; Ceponiene, Indre; Nazarat, Negin; Rahmani, Sina; Kissel, Kendall; Jayawardena, Eranthi; Dailing, Christopher; Zarins, Christopher; Koo, Bon-Kwon; Min, James K; Taylor, Charles A; Budoff, Matthew J

2018-03-23

Our goal was to evaluate the efficacy of a fully automated method for assessing the image quality (IQ) of coronary computed tomography angiography (CCTA). The machine learning method was trained using 75 CCTA studies by mapping features (noise, contrast, misregistration scores, and un-interpretability index) to an IQ score based on manual ground truth data. The automated method was validated on a set of 50 CCTA studies and subsequently tested on a new set of 172 CCTA studies against visual IQ scores on a 5-point Likert scale. The area under the curve in the validation set was 0.96. In the 172 CCTA studies, our method yielded a Cohen's kappa statistic for the agreement between automated and visual IQ assessment of 0.67 (p < 0.01). In the group where good to excellent (n = 163), fair (n = 6), and poor visual IQ scores (n = 3) were graded, 155, 5, and 2 of the patients received an automated IQ score > 50 %, respectively. Fully automated assessment of the IQ of CCTA data sets by machine learning was reproducible and provided similar results compared with visual analysis within the limits of inter-operator variability. • The proposed method enables automated and reproducible image quality assessment. • Machine learning and visual assessments yielded comparable estimates of image quality. • Automated assessment potentially allows for more standardised image quality. • Image quality assessment enables standardization of clinical trial results across different datasets.
Three-Dimensional Echocardiographic Assessment of Left Heart Chamber Size and Function with Fully Automated Quantification Software in Patients with Atrial Fibrillation.

PubMed

Otani, Kyoko; Nakazono, Akemi; Salgo, Ivan S; Lang, Roberto M; Takeuchi, Masaaki

2016-10-01

Echocardiographic determination of left heart chamber volumetric parameters by using manual tracings during multiple beats is tedious in atrial fibrillation (AF). The aim of this study was to determine the usefulness of fully automated left chamber quantification software with single-beat three-dimensional transthoracic echocardiographic data sets in patients with AF. Single-beat full-volume three-dimensional transthoracic echocardiographic data sets were prospectively acquired during consecutive multiple cardiac beats (≥10 beats) in 88 patients with AF. In protocol 1, left ventricular volumes, left ventricular ejection fraction, and maximal left atrial volume were validated using automated quantification against the manual tracing method in identical beats in 10 patients. In protocol 2, automated quantification-derived averaged values from multiple beats were compared with the corresponding values obtained from the indexed beat in all patients. Excellent correlations of left chamber parameters between automated quantification and the manual method were observed (r = 0.88-0.98) in protocol 1. The time required for the analysis with the automated quantification method (5 min) was significantly less compared with the manual method (27 min) (P < .0001). In protocol 2, there were excellent linear correlations between the averaged left chamber parameters and the corresponding values obtained from the indexed beat (r = 0.94-0.99), and test-retest variability of left chamber parameters was low (3.5%-4.8%). Three-dimensional transthoracic echocardiography with fully automated quantification software is a rapid and reliable way to measure averaged values of left heart chamber parameters during multiple consecutive beats. Thus, it is a potential new approach for left chamber quantification in patients with AF in daily routine practice. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.
An approach to standardization of urine sediment analysis via suggestion of a common manual protocol.

PubMed

Ko, Dae-Hyun; Ji, Misuk; Kim, Sollip; Cho, Eun-Jung; Lee, Woochang; Yun, Yeo-Min; Chun, Sail; Min, Won-Ki

2016-01-01

The results of urine sediment analysis have been reported semiquantitatively. However, as recent guidelines recommend quantitative reporting of urine sediment, and with the development of automated urine sediment analyzers, there is an increasing need for quantitative analysis of urine sediment. Here, we developed a protocol for urine sediment analysis and quantified the results. Based on questionnaires, various reports, guidelines, and experimental results, we developed a protocol for urine sediment analysis. The results of this new protocol were compared with those obtained with a standardized chamber and an automated sediment analyzer. Reference intervals were also estimated using new protocol. We developed a protocol with centrifugation at 400 g for 5 min, with the average concentration factor of 30. The correlation between quantitative results of urine sediment analysis, the standardized chamber, and the automated sediment analyzer were generally good. The conversion factor derived from the new protocol showed a better fit with the results of manual count than the default conversion factor in the automated sediment analyzer. We developed a protocol for manual urine sediment analysis to quantitatively report the results. This protocol may provide a mean for standardization of urine sediment analysis.
Visual Versus Fully Automated Analyses of 18F-FDG and Amyloid PET for Prediction of Dementia Due to Alzheimer Disease in Mild Cognitive Impairment.

PubMed

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 rule out underlying AD. The findings of the present study favor a fully automated method of analysis for (11)C-PiB assessments and a visual analysis by experts for (18)F-FDG assessments. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.
Fully automated MR liver volumetry using watershed segmentation coupled with active contouring.

PubMed

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.

CANEapp: a user-friendly application for automated next generation transcriptomic data analysis.

PubMed

Velmeshev, Dmitry; Lally, Patrick; Magistri, Marco; Faghihi, Mohammad Ali

2016-01-13

Next generation sequencing (NGS) technologies are indispensable for molecular biology research, but data analysis represents the bottleneck in their application. Users need to be familiar with computer terminal commands, the Linux environment, and various software tools and scripts. Analysis workflows have to be optimized and experimentally validated to extract biologically meaningful data. Moreover, as larger datasets are being generated, their analysis requires use of high-performance servers. To address these needs, we developed CANEapp (application for Comprehensive automated Analysis of Next-generation sequencing Experiments), a unique suite that combines a Graphical User Interface (GUI) and an automated server-side analysis pipeline that is platform-independent, making it suitable for any server architecture. The GUI runs on a PC or Mac and seamlessly connects to the server to provide full GUI control of RNA-sequencing (RNA-seq) project analysis. The server-side analysis pipeline contains a framework that is implemented on a Linux server through completely automated installation of software components and reference files. Analysis with CANEapp is also fully automated and performs differential gene expression analysis and novel noncoding RNA discovery through alternative workflows (Cuffdiff and R packages edgeR and DESeq2). We compared CANEapp to other similar tools, and it significantly improves on previous developments. We experimentally validated CANEapp's performance by applying it to data derived from different experimental paradigms and confirming the results with quantitative real-time PCR (qRT-PCR). CANEapp adapts to any server architecture by effectively using available resources and thus handles large amounts of data efficiently. CANEapp performance has been experimentally validated on various biological datasets. CANEapp is available free of charge at http://psychiatry.med.miami.edu/research/laboratory-of-translational-rna-genomics/CANE-app . We believe that CANEapp will serve both biologists with no computational experience and bioinformaticians as a simple, timesaving but accurate and powerful tool to analyze large RNA-seq datasets and will provide foundations for future development of integrated and automated high-throughput genomics data analysis tools. Due to its inherently standardized pipeline and combination of automated analysis and platform-independence, CANEapp is an ideal for large-scale collaborative RNA-seq projects between different institutions and research groups.
Peak picking multidimensional NMR spectra with the contour geometry based algorithm CYPICK.

PubMed

Würz, Julia M; Güntert, Peter

2017-01-01

The automated identification of signals in multidimensional NMR spectra is a challenging task, complicated by signal overlap, noise, and spectral artifacts, for which no universally accepted method is available. Here, we present a new peak picking algorithm, CYPICK, that follows, as far as possible, the manual approach taken by a spectroscopist who analyzes peak patterns in contour plots of the spectrum, but is fully automated. Human visual inspection is replaced by the evaluation of geometric criteria applied to contour lines, such as local extremality, approximate circularity (after appropriate scaling of the spectrum axes), and convexity. The performance of CYPICK was evaluated for a variety of spectra from different proteins by systematic comparison with peak lists obtained by other, manual or automated, peak picking methods, as well as by analyzing the results of automated chemical shift assignment and structure calculation based on input peak lists from CYPICK. The results show that CYPICK yielded peak lists that compare in most cases favorably to those obtained by other automated peak pickers with respect to the criteria of finding a maximal number of real signals, a minimal number of artifact peaks, and maximal correctness of the chemical shift assignments and the three-dimensional structure obtained by fully automated assignment and structure calculation.
Comparison of semi-automated center-dot and fully automated endothelial cell analyses from specular microscopy images.

PubMed

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.
GiA Roots: software for the high throughput analysis of plant root system architecture.

PubMed

Galkovskyi, Taras; Mileyko, Yuriy; Bucksch, Alexander; Moore, Brad; Symonova, Olga; Price, Charles A; Topp, Christopher N; Iyer-Pascuzzi, Anjali S; Zurek, Paul R; Fang, Suqin; Harer, John; Benfey, Philip N; Weitz, Joshua S

2012-07-26

Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks. We have developed GiA Roots (General Image Analysis of Roots), a semi-automated software tool designed specifically for the high-throughput analysis of root system images. GiA Roots includes user-assisted algorithms to distinguish root from background and a fully automated pipeline that extracts dozens of root system phenotypes. Quantitative information on each phenotype, along with intermediate steps for full reproducibility, is returned to the end-user for downstream analysis. GiA Roots has a GUI front end and a command-line interface for interweaving the software into large-scale workflows. GiA Roots can also be extended to estimate novel phenotypes specified by the end-user. We demonstrate the use of GiA Roots on a set of 2393 images of rice roots representing 12 genotypes from the species Oryza sativa. We validate trait measurements against prior analyses of this image set that demonstrated that RSA traits are likely heritable and associated with genotypic differences. Moreover, we demonstrate that GiA Roots is extensible and an end-user can add functionality so that GiA Roots can estimate novel RSA traits. In summary, we show that the software can function as an efficient tool as part of a workflow to move from large numbers of root images to downstream analysis.
Textural Maturity Analysis and Sedimentary Environment Discrimination Based on Grain Shape Data

NASA Astrophysics Data System (ADS)

Tunwal, M.; Mulchrone, K. F.; Meere, P. A.

2017-12-01

Morphological analysis of clastic sedimentary grains is an important source of information regarding the processes involved in their formation, transportation and deposition. However, a standardised approach for quantitative grain shape analysis is generally lacking. In this contribution we report on a study where fully automated image analysis techniques were applied to loose sediment samples collected from glacial, aeolian, beach and fluvial environments. A range of shape parameters are evaluated for their usefulness in textural characterisation of populations of grains. The utility of grain shape data in ranking textural maturity of samples within a given sedimentary environment is evaluated. Furthermore, discrimination of sedimentary environment on the basis of grain shape information is explored. The data gathered demonstrates a clear progression in textural maturity in terms of roundness, angularity, irregularity, fractal dimension, convexity, solidity and rectangularity. Textural maturity can be readily categorised using automated grain shape parameter analysis. However, absolute discrimination between different depositional environments on the basis of shape parameters alone is less certain. For example, the aeolian environment is quite distinct whereas fluvial, glacial and beach samples are inherently variable and tend to overlap each other in terms of textural maturity. This is most likely due to a collection of similar processes and sources operating within these environments. This study strongly demonstrates the merit of quantitative population-based shape parameter analysis of texture and indicates that it can play a key role in characterising both loose and consolidated sediments. This project is funded by the Irish Petroleum Infrastructure Programme (www.pip.ie)
Designing Domain-Specific HUMS Architectures: An Automated Approach

NASA Technical Reports Server (NTRS)

Mukkamala, Ravi; Agarwal, Neha; Kumar, Pramod; Sundaram, Parthiban

2004-01-01

The HUMS automation system automates the design of HUMS architectures. The automated design process involves selection of solutions from a large space of designs as well as pure synthesis of designs. Hence the whole objective is to efficiently search for or synthesize designs or parts of designs in the database and to integrate them to form the entire system design. The automation system adopts two approaches in order to produce the designs: (a) Bottom-up approach and (b) Top down approach. Both the approaches are endowed with a Suite of quantitative and quantitative techniques that enable a) the selection of matching component instances, b) the determination of design parameters, c) the evaluation of candidate designs at component-level and at system-level, d) the performance of cost-benefit analyses, e) the performance of trade-off analyses, etc. In short, the automation system attempts to capitalize on the knowledge developed from years of experience in engineering, system design and operation of the HUMS systems in order to economically produce the most optimal and domain-specific designs.
TreeRipper web application: towards a fully automated optical tree recognition software.

PubMed

Hughes, Joseph

2011-05-20

Relationships between species, genes and genomes have been printed as trees for over a century. Whilst this may have been the best format for exchanging and sharing phylogenetic hypotheses during the 20th century, the worldwide web now provides faster and automated ways of transferring and sharing phylogenetic knowledge. However, novel software is needed to defrost these published phylogenies for the 21st century. TreeRipper is a simple website for the fully-automated recognition of multifurcating phylogenetic trees (http://linnaeus.zoology.gla.ac.uk/~jhughes/treeripper/). The program accepts a range of input image formats (PNG, JPG/JPEG or GIF). The underlying command line c++ program follows a number of cleaning steps to detect lines, remove node labels, patch-up broken lines and corners and detect line edges. The edge contour is then determined to detect the branch length, tip label positions and the topology of the tree. Optical Character Recognition (OCR) is used to convert the tip labels into text with the freely available tesseract-ocr software. 32% of images meeting the prerequisites for TreeRipper were successfully recognised, the largest tree had 115 leaves. Despite the diversity of ways phylogenies have been illustrated making the design of a fully automated tree recognition software difficult, TreeRipper is a step towards automating the digitization of past phylogenies. We also provide a dataset of 100 tree images and associated tree files for training and/or benchmarking future software. TreeRipper is an open source project licensed under the GNU General Public Licence v3.
Fully automated contour detection of the ascending aorta in cardiac 2D phase-contrast MRI.

PubMed

Codari, Marina; Scarabello, Marco; Secchi, Francesco; Sforza, Chiarella; Baselli, Giuseppe; Sardanelli, Francesco

2018-04-01

In this study we proposed a fully automated method for localizing and segmenting the ascending aortic lumen with phase-contrast magnetic resonance imaging (PC-MRI). Twenty-five phase-contrast series were randomly selected out of a large population dataset of patients whose cardiac MRI examination, performed from September 2008 to October 2013, was unremarkable. The local Ethical Committee approved this retrospective study. The ascending aorta was automatically identified on each phase of the cardiac cycle using a priori knowledge of aortic geometry. The frame that maximized the area, eccentricity, and solidity parameters was chosen for unsupervised initialization. Aortic segmentation was performed on each frame using active contouring without edges techniques. The entire algorithm was developed using Matlab R2016b. To validate the proposed method, the manual segmentation performed by a highly experienced operator was used. Dice similarity coefficient, Bland-Altman analysis, and Pearson's correlation coefficient were used as performance metrics. Comparing automated and manual segmentation of the aortic lumen on 714 images, Bland-Altman analysis showed a bias of -6.68mm 2 , a coefficient of repeatability of 91.22mm 2 , a mean area measurement of 581.40mm 2 , and a reproducibility of 85%. Automated and manual segmentation were highly correlated (R=0.98). The Dice similarity coefficient versus the manual reference standard was 94.6±2.1% (mean±standard deviation). A fully automated and robust method for identification and segmentation of ascending aorta on PC-MRI was developed. Its application on patients with a variety of pathologic conditions is advisable. Copyright © 2017 Elsevier Inc. All rights reserved.
ATLAS from Data Research Associates: A Fully Integrated Automation System.

ERIC Educational Resources Information Center

Mellinger, Michael J.

1987-01-01

This detailed description of a fully integrated, turnkey library system includes a complete profile of the system (functions, operational characteristics, hardware, operating system, minimum memory and pricing); history of the technologies involved; and descriptions of customer services and availability. (CLB)
Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

PubMed

Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

2008-04-01

The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.
EasyLCMS: an asynchronous web application for the automated quantification of LC-MS data

PubMed Central

2012-01-01

Background Downstream applications in metabolomics, as well as mathematical modelling, require data in a quantitative format, which may also necessitate the automated and simultaneous quantification of numerous metabolites. Although numerous applications have been previously developed for metabolomics data handling, automated calibration and calculation of the concentrations in terms of μmol have not been carried out. Moreover, most of the metabolomics applications are designed for GC-MS, and would not be suitable for LC-MS, since in LC, the deviation in the retention time is not linear, which is not taken into account in these applications. Moreover, only a few are web-based applications, which could improve stand-alone software in terms of compatibility, sharing capabilities and hardware requirements, even though a strong bandwidth is required. Furthermore, none of these incorporate asynchronous communication to allow real-time interaction with pre-processed results. Findings Here, we present EasyLCMS (http://www.easylcms.es/), a new application for automated quantification which was validated using more than 1000 concentration comparisons in real samples with manual operation. The results showed that only 1% of the quantifications presented a relative error higher than 15%. Using clustering analysis, the metabolites with the highest relative error distributions were identified and studied to solve recurrent mistakes. Conclusions EasyLCMS is a new web application designed to quantify numerous metabolites, simultaneously integrating LC distortions and asynchronous web technology to present a visual interface with dynamic interaction which allows checking and correction of LC-MS raw data pre-processing results. Moreover, quantified data obtained with EasyLCMS are fully compatible with numerous downstream applications, as well as for mathematical modelling in the systems biology field. PMID:22884039
ROBOCAL: Gamma-ray isotopic hardware/software interface

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

Hurd, J.R.; Bonner, C.A.; Ostenak, C.A.

1989-01-01

ROBOCAL, presently being developed at the Los Alamos National Laboratory, is a full-scale prototypical robotic system for remotely performing calorimetric and gamma-ray isotopics measurements of nuclear materials. It features a fully automated vertical stacker-retriever for storing and retrieving packaged nuclear materials from a multi-drawer system, and a fully automated, uniquely integrated gantry robot for programmable selection and transfer of nuclear materials to calorimetric and gamma-ray isotopic measurement stations. Since ROBOCAL is to require almost no operator intervention, a mechanical control system is required in addition to a totally automated assay system. The assay system must be a completely integrated datamore » acquisition and isotopic analysis package fully capable of performing state-of-the-art homogeneous and heterogeneous analyses on many varied matrices. The TRIFID assay system being discussed at this conference by J. G. Fleissner of the Rocky Flats Plant has been adopted because of its many automated features. These include: MCA/ADC setup and acquisition; spectral storage and analysis utilizing an expert system formalism; report generation with internal measurement control printout; user friendly screens and menus. The mechanical control portion consists primarily of two detector platforms and a sample platform, each with independent movement. Some minor modifications and additions are needed with TRIFID to interface the assay and mechanical portions with the CimRoc 4000 software controlling the robot. 6 refs., 5 figs., 3 tabs.« less
Fully automated analysis of multi-resolution four-channel micro-array genotyping data

NASA Astrophysics Data System (ADS)

Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.

2006-03-01

We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.
FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping.

PubMed

Khan, Ali R; Wang, Lei; Beg, Mirza Faisal

2008-07-01

Fully-automated brain segmentation methods have not been widely adopted for clinical use because of issues related to reliability, accuracy, and limitations of delineation protocol. By combining the probabilistic-based FreeSurfer (FS) method with the Large Deformation Diffeomorphic Metric Mapping (LDDMM)-based label-propagation method, we are able to increase reliability and accuracy, and allow for flexibility in template choice. Our method uses the automated FreeSurfer subcortical labeling to provide a coarse-to-fine introduction of information in the LDDMM template-based segmentation resulting in a fully-automated subcortical brain segmentation method (FS+LDDMM). One major advantage of the FS+LDDMM-based approach is that the automatically generated segmentations generated are inherently smooth, thus subsequent steps in shape analysis can directly follow without manual post-processing or loss of detail. We have evaluated our new FS+LDDMM method on several databases containing a total of 50 subjects with different pathologies, scan sequences and manual delineation protocols for labeling the basal ganglia, thalamus, and hippocampus. In healthy controls we report Dice overlap measures of 0.81, 0.83, 0.74, 0.86 and 0.75 for the right caudate nucleus, putamen, pallidum, thalamus and hippocampus respectively. We also find statistically significant improvement of accuracy in FS+LDDMM over FreeSurfer for the caudate nucleus and putamen of Huntington's disease and Tourette's syndrome subjects, and the right hippocampus of Schizophrenia subjects.
Utility of an automated thermal-based approach for monitoring evapotranspiration

USDA-ARS?s Scientific Manuscript database

A very simple remote sensing-based model for water use monitoring is presented. The model acronym DATTUTDUT, (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature) is a Dutch word which loosely translates as “It’s unbelievable that it works”. DATTUTDUT is fully automated and o...
e-Measures: insight into the challenges and opportunities of automating publicly reported quality measures

PubMed Central

Garrido, Terhilda; Kumar, Sudheen; Lekas, John; Lindberg, Mark; Kadiyala, Dhanyaja; Whippy, Alan; Crawford, Barbara; Weissberg, Jed

2014-01-01

Using electronic health records (EHR) to automate publicly reported quality measures is receiving increasing attention and is one of the promises of EHR implementation. Kaiser Permanente has fully or partly automated six of 13 the joint commission measure sets. We describe our experience with automation and the resulting time savings: a reduction by approximately 50% of abstractor time required for one measure set alone (surgical care improvement project). However, our experience illustrates the gap between the current and desired states of automated public quality reporting, which has important implications for measure developers, accrediting entities, EHR vendors, public/private payers, and government. PMID:23831833
Fully-automated identification of fish species based on otolith contour: using short-time Fourier transform and discriminant analysis (STFT-DA).

PubMed

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.
An automated workflow for enhancing microbial bioprocess optimization on a novel microbioreactor platform

PubMed Central

2012-01-01

Background High-throughput methods are widely-used for strain screening effectively resulting in binary information regarding high or low productivity. Nevertheless achieving quantitative and scalable parameters for fast bioprocess development is much more challenging, especially for heterologous protein production. Here, the nature of the foreign protein makes it impossible to predict the, e.g. best expression construct, secretion signal peptide, inductor concentration, induction time, temperature and substrate feed rate in fed-batch operation to name only a few. Therefore, a high number of systematic experiments are necessary to elucidate the best conditions for heterologous expression of each new protein of interest. Results To increase the throughput in bioprocess development, we used a microtiter plate based cultivation system (Biolector) which was fully integrated into a liquid-handling platform enclosed in laminar airflow housing. This automated cultivation platform was used for optimization of the secretory production of a cutinase from Fusarium solani pisi with Corynebacterium glutamicum. The online monitoring of biomass, dissolved oxygen and pH in each of the microtiter plate wells enables to trigger sampling or dosing events with the pipetting robot used for a reliable selection of best performing cutinase producers. In addition to this, further automated methods like media optimization and induction profiling were developed and validated. All biological and bioprocess parameters were exclusively optimized at microtiter plate scale and showed perfect scalable results to 1 L and 20 L stirred tank bioreactor scale. Conclusions The optimization of heterologous protein expression in microbial systems currently requires extensive testing of biological and bioprocess engineering parameters. This can be efficiently boosted by using a microtiter plate cultivation setup embedded into a liquid-handling system, providing more throughput by parallelization and automation. Due to improved statistics by replicate cultivations, automated downstream analysis, and scalable process information, this setup has superior performance compared to standard microtiter plate cultivation. PMID:23113930
Automated PCR setup for forensic casework samples using the Normalization Wizard and PCR Setup robotic methods.

PubMed

Greenspoon, S A; Sykes, K L V; Ban, J D; Pollard, A; Baisden, M; Farr, M; Graham, N; Collins, B L; Green, M M; Christenson, C C

2006-12-20

Human genome, pharmaceutical and research laboratories have long enjoyed the application of robotics to performing repetitive laboratory tasks. However, the utilization of robotics in forensic laboratories for processing casework samples is relatively new and poses particular challenges. Since the quantity and quality (a mixture versus a single source sample, the level of degradation, the presence of PCR inhibitors) of the DNA contained within a casework sample is unknown, particular attention must be paid to procedural susceptibility to contamination, as well as DNA yield, especially as it pertains to samples with little biological material. The Virginia Department of Forensic Science (VDFS) has successfully automated forensic casework DNA extraction utilizing the DNA IQ(trade mark) System in conjunction with the Biomek 2000 Automation Workstation. Human DNA quantitation is also performed in a near complete automated fashion utilizing the AluQuant Human DNA Quantitation System and the Biomek 2000 Automation Workstation. Recently, the PCR setup for casework samples has been automated, employing the Biomek 2000 Automation Workstation and Normalization Wizard, Genetic Identity version, which utilizes the quantitation data, imported into the software, to create a customized automated method for DNA dilution, unique to that plate of DNA samples. The PCR Setup software method, used in conjunction with the Normalization Wizard method and written for the Biomek 2000, functions to mix the diluted DNA samples, transfer the PCR master mix, and transfer the diluted DNA samples to PCR amplification tubes. Once the process is complete, the DNA extracts, still on the deck of the robot in PCR amplification strip tubes, are transferred to pre-labeled 1.5 mL tubes for long-term storage using an automated method. The automation of these steps in the process of forensic DNA casework analysis has been accomplished by performing extensive optimization, validation and testing of the software methods.
Reproducibility of myelin content-based human habenula segmentation at 3 Tesla.

PubMed

Kim, Joo-Won; Naidich, Thomas P; Joseph, Joshmi; Nair, Divya; Glasser, Matthew F; O'halloran, Rafael; Doucet, Gaelle E; Lee, Won Hee; Krinsky, Hannah; Paulino, Alejandro; Glahn, David C; Anticevic, Alan; Frangou, Sophia; Xu, Junqian

2018-03-26

In vivo morphological study of the human habenula, a pair of small epithalamic nuclei adjacent to the dorsomedial thalamus, has recently gained significant interest for its role in reward and aversion processing. However, segmenting the habenula from in vivo magnetic resonance imaging (MRI) is challenging due to the habenula's small size and low anatomical contrast. Although manual and semi-automated habenula segmentation methods have been reported, the test-retest reproducibility of the segmented habenula volume and the consistency of the boundaries of habenula segmentation have not been investigated. In this study, we evaluated the intra- and inter-site reproducibility of in vivo human habenula segmentation from 3T MRI (0.7-0.8 mm isotropic resolution) using our previously proposed semi-automated myelin contrast-based method and its fully-automated version, as well as a previously published manual geometry-based method. The habenula segmentation using our semi-automated method showed consistent boundary definition (high Dice coefficient, low mean distance, and moderate Hausdorff distance) and reproducible volume measurement (low coefficient of variation). Furthermore, the habenula boundary in our semi-automated segmentation from 3T MRI agreed well with that in the manual segmentation from 7T MRI (0.5 mm isotropic resolution) of the same subjects. Overall, our proposed semi-automated habenula segmentation showed reliable and reproducible habenula localization, while its fully-automated version offers an efficient way for large sample analysis. © 2018 Wiley Periodicals, Inc.

Automation of [(18) F]fluoroacetaldehyde synthesis: application to a recombinant human interleukin-1 receptor antagonist (rhIL-1RA).

PubMed

Morris, Olivia; McMahon, Adam; Boutin, Herve; Grigg, Julian; Prenant, Christian

2016-06-15

[(18) F]Fluoroacetaldehyde is a biocompatible prosthetic group that has been implemented pre-clinically using a semi-automated remotely controlled system. Automation of radiosyntheses permits use of higher levels of [(18) F]fluoride whilst minimising radiochemist exposure and enhancing reproducibility. In order to achieve full-automation of [(18) F]fluoroacetaldehyde peptide radiolabelling, a customised GE Tracerlab FX-FN with fully programmed automated synthesis was developed. The automated synthesis of [(18) F]fluoroacetaldehyde is carried out using a commercially available precursor, with reproducible yields of 26% ± 3 (decay-corrected, n = 10) within 45 min. Fully automated radiolabelling of a protein, recombinant human interleukin-1 receptor antagonist (rhIL-1RA), with [(18) F]fluoroacetaldehyde was achieved within 2 h. Radiolabelling efficiency of rhIL-1RA with [(18) F]fluoroacetaldehyde was confirmed using HPLC and reached 20% ± 10 (n = 5). Overall RCY of [(18) F]rhIL-1RA was 5% ± 2 (decay-corrected, n = 5) within 2 h starting from 35 to 40 GBq of [(18) F]fluoride. Specific activity measurements of 8.11-13.5 GBq/µmol were attained (n = 5), a near three-fold improvement of those achieved using the semi-automated approach. The strategy can be applied to radiolabelling a range of peptides and proteins with [(18) F]fluoroacetaldehyde analogous to other aldehyde-bearing prosthetic groups, yet automation of the method provides reproducibility thereby aiding translation to Good Manufacturing Practice manufacture and the transformation from pre-clinical to clinical production. Copyright © 2016 The Authors. Journal of Labelled Compounds and Radiopharmaceuticals published by John Wiley & Sons, Ltd.
ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping.

PubMed

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren; Nielsen, Morten

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.
Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

DOE PAGES

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R.; ...

2015-06-18

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland.more » AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.« less
Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC-ESI-MS-MS.

PubMed

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R; Changelian, Armen; Laws, Edward R; Santagata, Sandro; Agar, Nathalie Y R; Van Berkel, Gary J

2015-08-01

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections, using a fully automated droplet-based liquid-microjunction surface-sampling-HPLC-ESI-MS-MS system for spatially resolved sampling, HPLC separation, and mass spectrometric detection. Excellent correlation was found between the protein distribution data obtained with this method and data obtained with matrix-assisted laser desorption/ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland. AVP was most abundant in the posterior pituitary gland region (neurohypophysis), and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH-secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH-secreting adenomas and in normal anterior adenohypophysis compared with non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis, as expected. This work reveals that a fully automated droplet-based liquid-microjunction surface-sampling system coupled to HPLC-ESI-MS-MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, including AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity, and specificity of this method support the potential of this basic technology, with further advancement, for assisting surgical decision-making. Graphical Abstract Mass spectrometry based profiling of hormones in human pituitary gland and tumor thin tissue sections.
Rapid, Fully Automated Digital Immunoassay for p24 Protein with the Sensitivity of Nucleic Acid Amplification for Detecting Acute HIV Infection.

PubMed

Cabrera, Carlos; Chang, Lei; Stone, Mars; Busch, Michael; Wilson, David H

2015-11-01

Nucleic acid testing (NAT) has become the standard for high sensitivity in detecting low levels of virus. However, adoption of NAT can be cost prohibitive in low-resource settings where access to extreme sensitivity could be clinically advantageous for early detection of infection. We report development and preliminary validation of a simple, low-cost, fully automated digital p24 antigen immunoassay with the sensitivity of quantitative NAT viral load (NAT-VL) methods for detection of acute HIV infection. We developed an investigational 69-min immunoassay for p24 capsid protein for use on a novel digital analyzer on the basis of single-molecule-array technology. We evaluated the assay for sensitivity by dilution of standardized preparations of p24, cultured HIV, and preseroconversion samples. We characterized analytical performance and concordance with 2 NAT-VL methods and 2 contemporary p24 Ag/Ab combination immunoassays with dilutions of viral isolates and samples from the earliest stages of HIV infection. Analytical sensitivity was 0.0025 ng/L p24, equivalent to 60 HIV RNA copies/mL. The limit of quantification was 0.0076 ng/L, and imprecision across 10 runs was <10% for samples as low as 0.09 ng/L. Clinical specificity was 95.1%. Sensitivity concordance vs NAT-VL on dilutions of preseroconversion samples and Group M viral isolates was 100%. The digital immunoassay exhibited >4000-fold greater sensitivity than contemporary immunoassays for p24 and sensitivity equivalent to that of NAT methods for early detection of HIV. The data indicate that NAT-level sensitivity for acute HIV infection is possible with a simple, low-cost digital immunoassay. © 2015 American Association for Clinical Chemistry.
Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

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

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R.

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland.more » AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.« less
ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

PubMed Central

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope. PMID:28095436
Application of Artificial Intelligence to Improve Aircraft Survivability.

DTIC Science & Technology

1985-12-01

may be as smooth and effective as possible. 3. Fully Automatic Digital Engine Control ( FADEC ) Under development at the Naval Weapons Center, a major...goal of the FADEC program is to significantly reduce engine vulnerability by fully automating the regulation of engine controls. Given a thrust
Neurodegenerative changes in Alzheimer's disease: a comparative study of manual, semi-automated, and fully automated assessment using MRI

NASA Astrophysics Data System (ADS)

Fritzsche, Klaus H.; Giesel, Frederik L.; Heimann, Tobias; Thomann, Philipp A.; Hahn, Horst K.; Pantel, Johannes; Schröder, Johannes; Essig, Marco; Meinzer, Hans-Peter

2008-03-01

Objective quantification of disease specific neurodegenerative changes can facilitate diagnosis and therapeutic monitoring in several neuropsychiatric disorders. Reproducibility and easy-to-perform assessment are essential to ensure applicability in clinical environments. Aim of this comparative study is the evaluation of a fully automated approach that assesses atrophic changes in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). 21 healthy volunteers (mean age 66.2), 21 patients with MCI (66.6), and 10 patients with AD (65.1) were enrolled. Subjects underwent extensive neuropsychological testing and MRI was conducted on a 1.5 Tesla clinical scanner. Atrophic changes were measured automatically by a series of image processing steps including state of the art brain mapping techniques. Results were compared with two reference approaches: a manual segmentation of the hippocampal formation and a semi-automated estimation of temporal horn volume, which is based upon interactive selection of two to six landmarks in the ventricular system. All approaches separated controls and AD patients significantly (10 -5 < p < 10 -4) and showed a slight but not significant increase of neurodegeneration for subjects with MCI compared to volunteers. The automated approach correlated significantly with the manual (r = -0.65, p < 10 -6) and semi automated (r = -0.83, p < 10 -13) measurements. It proved high accuracy and at the same time maximized observer independency, time reduction and thus usefulness for clinical routine.
Understanding attrition from international Internet health interventions: a step towards global eHealth.

PubMed

Geraghty, Adam W A; Torres, Leandro D; Leykin, Yan; Pérez-Stable, Eliseo J; Muñoz, Ricardo F

2013-09-01

Worldwide automated Internet health interventions have the potential to greatly reduce health disparities. High attrition from automated Internet interventions is ubiquitous, and presents a challenge in the evaluation of their effectiveness. Our objective was to evaluate variables hypothesized to be related to attrition, by modeling predictors of attrition in a secondary data analysis of two cohorts of an international, dual language (English and Spanish) Internet smoking cessation intervention. The two cohorts were identical except for the approach to follow-up (FU): one cohort employed only fully automated FU (n = 16 430), while the other cohort also used 'live' contact conditional upon initial non-response (n = 1000). Attrition rates were 48.1 and 10.8% for the automated FU and live FU cohorts, respectively. Significant attrition predictors in the automated FU cohort included higher levels of nicotine dependency, lower education, lower quitting confidence and receiving more contact emails. Participants' younger age was the sole predictor of attrition in the live FU cohort. While research on large-scale deployment of Internet interventions is at an early stage, this study demonstrates that differences in attrition from trials on this scale are (i) systematic and predictable and (ii) can largely be eliminated by live FU efforts. In fully automated trials, targeting the predictors we identify may reduce attrition, a necessary precursor to effective behavioral Internet interventions that can be accessed globally.
Man-Robot Symbiosis: A Framework For Cooperative Intelligence And Control

NASA Astrophysics Data System (ADS)

Parker, Lynne E.; Pin, Francois G.

1988-10-01

The man-robot symbiosis concept has the fundamental objective of bridging the gap between fully human-controlled and fully autonomous systems to achieve true man-robot cooperative control and intelligence. Such a system would allow improved speed, accuracy, and efficiency of task execution, while retaining the man in the loop for innovative reasoning and decision-making. The symbiont would have capabilities for supervised and unsupervised learning, allowing an increase of expertise in a wide task domain. This paper describes a robotic system architecture facilitating the symbiotic integration of teleoperative and automated modes of task execution. The architecture reflects a unique blend of many disciplines of artificial intelligence into a working system, including job or mission planning, dynamic task allocation, man-robot communication, automated monitoring, and machine learning. These disciplines are embodied in five major components of the symbiotic framework: the Job Planner, the Dynamic Task Allocator, the Presenter/Interpreter, the Automated Monitor, and the Learning System.
Rapid access to compound libraries through flow technology: fully automated synthesis of a 3-aminoindolizine library via orthogonal diversification.

PubMed

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.
Cost-Effectiveness Analysis of the Automation of a Circulation System.

ERIC Educational Resources Information Center

Mosley, Isobel

A general methodology for cost effectiveness analysis was developed and applied to the Colorado State University library loan desk. The cost effectiveness of the existing semi-automated circulation system was compared with that of a fully manual one, based on the existing manual subsystem. Faculty users' time and computer operating costs were…
Automated Semantic Indices Related to Cognitive Function and Rate of Cognitive Decline

ERIC Educational Resources Information Center

Pakhomov, Serguei V. S.; Hemmy, Laura S.; Lim, Kelvin O.

2012-01-01

The objective of our study is to introduce a fully automated, computational linguistic technique to quantify semantic relations between words generated on a standard semantic verbal fluency test and to determine its cognitive and clinical correlates. Cognitive differences between patients with Alzheimer's disease and mild cognitive impairment are…
Bibliographic Networks and Microcomputer Applications for Aerospace and Defense Scientific and Technical Information.

ERIC Educational Resources Information Center

Hartt, Richard W.

This report discusses the characteristics, operations, and automation requirements of technical libraries providing services to organizations involved in aerospace and defense scientific and technical work, and describes the Local Automation Model project. This on-going project is designed to demonstrate the concept of a fully integrated library…
Robotic implementation of assays: tissue-nonspecific alkaline phosphatase (TNAP) case study.

PubMed

Chung, Thomas D Y

2013-01-01

Laboratory automation and robotics have "industrialized" the execution and completion of large-scale, enabling high-capacity and high-throughput (100 K-1 MM/day) screening (HTS) campaigns of large "libraries" of compounds (>200 K-2 MM) to complete in a few days or weeks. Critical to the success these HTS campaigns is the ability of a competent assay development team to convert a validated research-grade laboratory "benchtop" assay suitable for manual or semi-automated operations on a few hundreds of compounds into a robust miniaturized (384- or 1,536-well format), well-engineered, scalable, industrialized assay that can be seamlessly implemented on a fully automated, fully integrated robotic screening platform for cost-effective screening of hundreds of thousands of compounds. Here, we provide a review of the theoretical guiding principles and practical considerations necessary to reduce often complex research biology into a "lean manufacturing" engineering endeavor comprising adaption, automation, and implementation of HTS. Furthermore we provide a detailed example specifically for a cell-free in vitro biochemical, enzymatic phosphatase assay for tissue-nonspecific alkaline phosphatase that illustrates these principles and considerations.
Centrifugal LabTube platform for fully automated DNA purification and LAMP amplification based on an integrated, low-cost heating system.

PubMed

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

PubMed

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.
Fully automated, deep learning segmentation of oxygen-induced retinopathy images

PubMed Central

Xiao, Sa; Bucher, Felicitas; Wu, Yue; Rokem, Ariel; Lee, Cecilia S.; Marra, Kyle V.; Fallon, Regis; Diaz-Aguilar, Sophia; Aguilar, Edith; Friedlander, Martin; Lee, Aaron Y.

2017-01-01

Oxygen-induced retinopathy (OIR) is a widely used model to study ischemia-driven neovascularization (NV) in the retina and to serve in proof-of-concept studies in evaluating antiangiogenic drugs for ocular, as well as nonocular, diseases. The primary parameters that are analyzed in this mouse model include the percentage of retina with vaso-obliteration (VO) and NV areas. However, quantification of these two key variables comes with a great challenge due to the requirement of human experts to read the images. Human readers are costly, time-consuming, and subject to bias. Using recent advances in machine learning and computer vision, we trained deep learning neural networks using over a thousand segmentations to fully automate segmentation in OIR images. While determining the percentage area of VO, our algorithm achieved a similar range of correlation coefficients to that of expert inter-human correlation coefficients. In addition, our algorithm achieved a higher range of correlation coefficients compared with inter-expert correlation coefficients for quantification of the percentage area of neovascular tufts. In summary, we have created an open-source, fully automated pipeline for the quantification of key values of OIR images using deep learning neural networks. PMID:29263301
Designs and concept reliance of a fully automated high-content screening platform.

PubMed

Radu, Constantin; Adrar, Hosna Sana; Alamir, Ab; Hatherley, Ian; Trinh, Trung; Djaballah, Hakim

2012-10-01

High-content screening (HCS) is becoming an accepted platform in academic and industry screening labs and does require slightly different logistics for execution. To automate our stand-alone HCS microscopes, namely, an alpha IN Cell Analyzer 3000 (INCA3000), originally a Praelux unit hooked to a Hudson Plate Crane with a maximum capacity of 50 plates per run, and the IN Cell Analyzer 2000 (INCA2000), in which up to 320 plates could be fed per run using the Thermo Fisher Scientific Orbitor, we opted for a 4 m linear track system harboring both microscopes, plate washer, bulk dispensers, and a high-capacity incubator allowing us to perform both live and fixed cell-based assays while accessing both microscopes on deck. Considerations in design were given to the integration of the alpha INCA3000, a new gripper concept to access the onboard nest, and peripheral locations on deck to ensure a self-reliant system capable of achieving higher throughput. The resulting system, referred to as Hestia, has been fully operational since the new year, has an onboard capacity of 504 plates, and harbors the only fully automated alpha INCA3000 unit in the world.

Designs and Concept-Reliance of a Fully Automated High Content Screening Platform

PubMed Central

Radu, Constantin; Adrar, Hosna Sana; Alamir, Ab; Hatherley, Ian; Trinh, Trung; Djaballah, Hakim

2013-01-01

High content screening (HCS) is becoming an accepted platform in academic and industry screening labs and does require slightly different logistics for execution. To automate our stand alone HCS microscopes, namely an alpha IN Cell Analyzer 3000 (INCA3000) originally a Praelux unit hooked to a Hudson Plate Crane with a maximum capacity of 50 plates per run; and the IN Cell Analyzer 2000 (INCA2000) where up to 320 plates could be fed per run using the Thermo Fisher Scientific Orbitor, we opted for a 4 meter linear track system harboring both microscopes, plate washer, bulk dispensers, and a high capacity incubator allowing us to perform both live and fixed cell based assays while accessing both microscopes on deck. Considerations in design were given to the integration of the alpha INCA3000, a new gripper concept to access the onboard nest, and peripheral locations on deck to ensure a self reliant system capable of achieving higher throughput. The resulting system, referred to as Hestia, has been fully operational since the New Year, has an onboard capacity of 504 plates, and harbors the only fully automated alpha INCA3000 unit in the World. PMID:22797489
Fully automated two-step assay for detection of metallothionein through magnetic isolation using functionalized γ-Fe2O3 particles.

PubMed

Merlos Rodrigo, Miguel Angel; Krejcova, Ludmila; Kudr, Jiri; Cernei, Natalia; Kopel, Pavel; Richtera, Lukas; Moulick, Amitava; Hynek, David; Adam, Vojtech; Stiborova, Marie; Eckschlager, Tomas; Heger, Zbynek; Zitka, Ondrej

2016-12-15

Metallothioneins (MTs) are involved in heavy metal detoxification in a wide range of living organisms. Currently, it is well known that MTs play substantial role in many pathophysiological processes, including carcinogenesis, and they can serve as diagnostic biomarkers. In order to increase the applicability of MT in cancer diagnostics, an easy-to-use and rapid method for its detection is required. Hence, the aim of this study was to develop a fully automated and high-throughput assay for the estimation of MT levels. Here, we report the optimal conditions for the isolation of MTs from rabbit liver and their characterization using MALDI-TOF MS. In addition, we described a two-step assay, which started with an isolation of the protein using functionalized paramagnetic particles and finished with their electrochemical analysis. The designed easy-to-use, cost-effective, error-free and fully automated procedure for the isolation of MT coupled with a simple analytical detection method can provide a prototype for the construction of a diagnostic instrument, which would be appropriate for the monitoring of carcinogenesis or MT-related chemoresistance of tumors. Copyright © 2016 Elsevier B.V. All rights reserved.
Automated Selection of Hotspots (ASH): enhanced automated segmentation and adaptive step finding for Ki67 hotspot detection in adrenal cortical cancer.

PubMed

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

PubMed

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 analysis may still aid and improve the pathologists' detection of mitoses in melanoma and possibly other malignancies.
Automated System for Early Breast Cancer Detection in Mammograms

NASA Technical Reports Server (NTRS)

Bankman, Isaac N.; Kim, Dong W.; Christens-Barry, William A.; Weinberg, Irving N.; Gatewood, Olga B.; Brody, William R.

1993-01-01

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.
Results from the first fully automated PBS-mask process and pelliclization

NASA Astrophysics Data System (ADS)

Oelmann, Andreas B.; Unger, Gerd M.

1994-02-01

Automation is widely discussed in IC- and mask-manufacturing and partially realized everywhere. The idea for the automation goes back to 1978, when it turned out that the operators for the then newly installed PBS-process-line (the first in Europe) should be trained to behave like robots for particle reduction gaining lower defect densities on the masks. More than this goal has been achieved. It turned out recently, that the automation with its dedicated work routes and detailed documentation of every lot (individual mask or reticle) made it easy to obtain the CEEC certificate which includes ISO 9001.
Automated classification of cell morphology by coherence-controlled holographic microscopy

NASA Astrophysics Data System (ADS)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.
An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

PubMed

Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

2016-07-01

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.
Automated classification of cell morphology by coherence-controlled holographic microscopy.

PubMed

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
[Establishment of Automation System for Detection of Alcohol in Blood].

PubMed

Tian, L L; Shen, Lei; Xue, J F; Liu, M M; Liang, L J

2017-02-01

To establish an automation system for detection of alcohol content in blood. The determination was performed by automated workstation of extraction-headspace gas chromatography （HS-GC）. The blood collection with negative pressure, sealing time of headspace bottle and sample needle were checked and optimized in the abstraction of automation system. The automatic sampling was compared with the manual sampling. The quantitative data obtained by the automated workstation of extraction-HS-GC for alcohol was stable. The relative differences of two parallel samples were less than 5%. The automated extraction was superior to the manual extraction. A good linear relationship was obtained at the alcohol concentration range of 0.1-3.0 mg/mL （ r ≥0.999） with good repeatability. The method is simple and quick, with more standard experiment process and accurate experimental data. It eliminates the error from the experimenter and has good repeatability, which can be applied to the qualitative and quantitative detections of alcohol in blood. Copyright© by the Editorial Department of Journal of Forensic Medicine
Anxiety Online—A Virtual Clinic: Preliminary Outcomes Following Completion of Five Fully Automated Treatment Programs for Anxiety Disorders and Symptoms

PubMed Central

Meyer, Denny; Austin, David William; Kyrios, Michael

2011-01-01

Background The development of e-mental health interventions to treat or prevent mental illness and to enhance wellbeing has risen rapidly over the past decade. This development assists the public in sidestepping some of the obstacles that are often encountered when trying to access traditional face-to-face mental health care services. Objective The objective of our study was to investigate the posttreatment effectiveness of five fully automated self-help cognitive behavior e-therapy programs for generalized anxiety disorder (GAD), panic disorder with or without agoraphobia (PD/A), obsessive–compulsive disorder (OCD), posttraumatic stress disorder (PTSD), and social anxiety disorder (SAD) offered to the international public via Anxiety Online, an open-access full-service virtual psychology clinic for anxiety disorders. Methods We used a naturalistic participant choice, quasi-experimental design to evaluate each of the five Anxiety Online fully automated self-help e-therapy programs. Participants were required to have at least subclinical levels of one of the anxiety disorders to be offered the associated disorder-specific fully automated self-help e-therapy program. These programs are offered free of charge via Anxiety Online. Results A total of 225 people self-selected one of the five e-therapy programs (GAD, n = 88; SAD, n = 50; PD/A, n = 40; PTSD, n = 30; OCD, n = 17) and completed their 12-week posttreatment assessment. Significant improvements were found on 21/25 measures across the five fully automated self-help programs. At postassessment we observed significant reductions on all five anxiety disorder clinical disorder severity ratings (Cohen d range 0.72–1.22), increased confidence in managing one’s own mental health care (Cohen d range 0.70–1.17), and decreases in the total number of clinical diagnoses (except for the PD/A program, where a positive trend was found) (Cohen d range 0.45–1.08). In addition, we found significant improvements in quality of life for the GAD, OCD, PTSD, and SAD e-therapy programs (Cohen d range 0.11–0.96) and significant reductions relating to general psychological distress levels for the GAD, PD/A, and PTSD e-therapy programs (Cohen d range 0.23–1.16). Overall, treatment satisfaction was good across all five e-therapy programs, and posttreatment assessment completers reported using their e-therapy program an average of 395.60 (SD 272.2) minutes over the 12-week treatment period. Conclusions Overall, all five fully automated self-help e-therapy programs appear to be delivering promising high-quality outcomes; however, the results require replication. Trial Registration Australian and New Zealand Clinical Trials Registry ACTRN121611000704998; http://www.anzctr.org.au/trial_view.aspx?ID=336143 (Archived by WebCite at http://www.webcitation.org/618r3wvOG) PMID:22057287
Fully automated gynecomastia quantification from low-dose chest CT

NASA Astrophysics Data System (ADS)

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 < 0.001) with the reference categorical grades. The encouraging results demonstrate the feasibility of fully automated gynecomastia quantification from LDCT, which may aid the early detection as well as the treatment of both gynecomastia and the underlying medical problems, if any, that cause gynecomastia.
Fully Automated Driving: Impact of Trust and Practice on Manual Control Recovery.

PubMed

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.
Automated condition-invariable neurite segmentation and synapse classification using textural analysis-based machine-learning algorithms

PubMed Central

Kandaswamy, Umasankar; Rotman, Ziv; Watt, Dana; Schillebeeckx, Ian; Cavalli, Valeria; Klyachko, Vitaly

2013-01-01

High-resolution live-cell imaging studies of neuronal structure and function are characterized by large variability in image acquisition conditions due to background and sample variations as well as low signal-to-noise ratio. The lack of automated image analysis tools that can be generalized for varying image acquisition conditions represents one of the main challenges in the field of biomedical image analysis. Specifically, segmentation of the axonal/dendritic arborizations in brightfield or fluorescence imaging studies is extremely labor-intensive and still performed mostly manually. Here we describe a fully automated machine-learning approach based on textural analysis algorithms for segmenting neuronal arborizations in high-resolution brightfield images of live cultured neurons. We compare performance of our algorithm to manual segmentation and show that it combines 90% accuracy, with similarly high levels of specificity and sensitivity. Moreover, the algorithm maintains high performance levels under a wide range of image acquisition conditions indicating that it is largely condition-invariable. We further describe an application of this algorithm to fully automated synapse localization and classification in fluorescence imaging studies based on synaptic activity. Textural analysis-based machine-learning approach thus offers a high performance condition-invariable tool for automated neurite segmentation. PMID:23261652
Building Flexible User Interfaces for Solving PDEs

NASA Astrophysics Data System (ADS)

Logg, Anders; Wells, Garth N.

2010-09-01

FEniCS is a collection of software tools for the automated solution of differential equations by finite element methods. In this note, we describe how FEniCS can be used to solve a simple nonlinear model problem with varying levels of automation. At one extreme, FEniCS provides tools for the fully automated and adaptive solution of nonlinear partial differential equations. At the other extreme, FEniCS provides a range of tools that allow the computational scientist to experiment with novel solution algorithms.
Effects of Automation Types on Air Traffic Controller Situation Awareness and Performance

NASA Technical Reports Server (NTRS)

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.
JPLEX: Java Simplex Implementation with Branch-and-Bound Search for Automated Test Assembly

ERIC Educational Resources Information Center

Park, Ryoungsun; Kim, Jiseon; Dodd, Barbara G.; Chung, Hyewon

2011-01-01

JPLEX, short for Java simPLEX, is an automated test assembly (ATA) program. It is a mixed integer linear programming (MILP) solver written in Java. It reads in a configuration file, solves the minimization problem, and produces an output file for postprocessing. It implements the simplex algorithm to create a fully relaxed solution and…
ECMS--Educational Contest Management System for Selecting Elite Students

ERIC Educational Resources Information Center

Schneider, Thorsten

2004-01-01

Selecting elite students out of a huge collective is a difficult task. The main problem is to provide automated processes to reduce human work. ECMS (Educational Contest Management System) is an online tool approach to help--fully or partly automated--with the task of selecting such elite students out of a mass of candidates. International tests…
An Automated Distillation Column for the Unit Operations Laboratory

ERIC Educational Resources Information Center

Perkins, Douglas M.; Bruce, David A.; Gooding, Charles H.; Butler, Justin T.

2005-01-01

A batch distillation apparatus has been designed and built for use in the undergraduate unit operations laboratory course. The column is fully automated and is accompanied by data acquisition and control software. A mixture of 1-propanol and 2-propanol is separated in the column, using either a constant distillate rate or constant composition…
An automated system for global atmospheric sampling using B-747 airliners

NASA Technical Reports Server (NTRS)

Lew, K. Q.; Gustafsson, U. R. C.; Johnson, R. E.

1981-01-01

The global air sampling program utilizes commercial aircrafts in scheduled service to measure atmospheric constituents. A fully automated system designed for the 747 aircraft is described. Airline operational constraints and data and control subsystems are treated. The overall program management, system monitoring, and data retrieval from four aircraft in global service is described.

Facility monitoring of chemical warfare agent simulants in air using an automated, field-deployable, miniature mass spectrometer.

PubMed

Smith, Jonell N; Noll, Robert J; Cooks, R Graham

2011-05-30

Vapors of four chemical warfare agent (CWA) stimulants, 2-chloroethyl ethyl sulfide (CEES), diethyl malonate (DEM), dimethyl methylphosphonate (DMMP), and methyl salicylate (MeS), were detected, identified, and quantitated using a fully automated, field-deployable, miniature mass spectrometer. Samples were ionized using a glow discharge electron ionization (GDEI) source, and ions were mass analyzed with a cylindrical ion trap (CIT) mass analyzer. A dual-tube thermal desorption system was used to trap compounds on 50:50 Tenax TA/Carboxen 569 sorbent before their thermal release. The sample concentrations ranged from low parts per billion [ppb] to two parts per million [ppm]. Limits of detection (LODs) ranged from 0.26 to 5.0 ppb. Receiver operating characteristic (ROC) curves are presented for each analyte. A sample of CEES at low ppb concentration was combined separately with two interferents, bleach (saturated vapor) and diesel fuel exhaust (1%), as a way to explore the capability of detecting the simulant in an environmental matrix. Also investigated was a mixture of the four CWA simulants (at concentrations in air ranging from 270 to 380 ppb). Tandem mass (MS/MS) spectral data were used to identify and quantify the individual components. Copyright © 2011 John Wiley & Sons, Ltd.
A machine learning approach for automated assessment of retinal vasculature in the oxygen induced retinopathy model.

PubMed

Mazzaferri, Javier; Larrivée, Bruno; Cakir, Bertan; Sapieha, Przemyslaw; Costantino, Santiago

2018-03-02

Preclinical studies of vascular retinal diseases rely on the assessment of developmental dystrophies in the oxygen induced retinopathy rodent model. The quantification of vessel tufts and avascular regions is typically computed manually from flat mounted retinas imaged using fluorescent probes that highlight the vascular network. Such manual measurements are time-consuming and hampered by user variability and bias, thus a rapid and objective method is needed. Here, we introduce a machine learning approach to segment and characterize vascular tufts, delineate the whole vasculature network, and identify and analyze avascular regions. Our quantitative retinal vascular assessment (QuRVA) technique uses a simple machine learning method and morphological analysis to provide reliable computations of vascular density and pathological vascular tuft regions, devoid of user intervention within seconds. We demonstrate the high degree of error and variability of manual segmentations, and designed, coded, and implemented a set of algorithms to perform this task in a fully automated manner. We benchmark and validate the results of our analysis pipeline using the consensus of several manually curated segmentations using commonly used computer tools. The source code of our implementation is released under version 3 of the GNU General Public License ( https://www.mathworks.com/matlabcentral/fileexchange/65699-javimazzaf-qurva ).
Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment.

PubMed

Besmer, Michael D; Epting, Jannis; Page, Rebecca M; Sigrist, Jürg A; Huggenberger, Peter; Hammes, Frederik

2016-12-07

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality - particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL -1 . The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.
Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

PubMed Central

Besmer, Michael D.; Epting, Jannis; Page, Rebecca M.; Sigrist, Jürg A.; Huggenberger, Peter; Hammes, Frederik

2016-01-01

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality – particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL−1. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems. PMID:27924920
Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures.

PubMed

Lim, Issel Anne L; Faria, Andreia V; Li, Xu; Hsu, Johnny T C; Airan, Raag D; Mori, Susumu; van Zijl, Peter C M

2013-11-15

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a "deep gray matter parcellation map" (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established "white matter parcellation map" (WMPM) from the same subject's T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the "Everything Parcellation Map in Eve Space," also known as the "EvePM." It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting "almost perfect" agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray matter structures measured by Hallgren and Sourander (1958) allowed interpolation of the average iron concentration of several deep gray matter regions delineated in the EvePM. Copyright © 2013 Elsevier Inc. All rights reserved.
Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures

PubMed Central

Lim, Issel Anne L.; Faria, Andreia V.; Li, Xu; Hsu, Johnny T.C.; Airan, Raag D.; Mori, Susumu; van Zijl, Peter C. M.

2013-01-01

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a “deep gray matter parcellation map” (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established “white matter parcellation map” (WMPM) from the same subject’s T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the “Everything Parcellation Map in Eve Space,” also known as the “EvePM.” It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting “almost perfect” agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray matter structures measured by Hallgren and Sourander (1958) allowed interpolation of the average iron concentration of several deep gray matter regions delineated in the EvePM. PMID:23769915
Preliminary evaluation of a fully automated quantitative framework for characterizing general breast tissue histology via color histogram and color texture analysis

NASA Astrophysics Data System (ADS)

Keller, Brad M.; Gastounioti, Aimilia; Batiste, Rebecca C.; Kontos, Despina; Feldman, Michael D.

2016-03-01

Visual characterization of histologic specimens is known to suffer from intra- and inter-observer variability. To help address this, we developed an automated framework for characterizing digitized histology specimens based on a novel application of color histogram and color texture analysis. We perform a preliminary evaluation of this framework using a set of 73 trichrome-stained, digitized slides of normal breast tissue which were visually assessed by an expert pathologist in terms of the percentage of collagenous stroma, stromal collagen density, duct-lobular unit density and the presence of elastosis. For each slide, our algorithm automatically segments the tissue region based on the lightness channel in CIELAB colorspace. Within each tissue region, a color histogram feature vector is extracted using a common color palette for trichrome images generated with a previously described method. Then, using a whole-slide, lattice-based methodology, color texture maps are generated using a set of color co-occurrence matrix statistics: contrast, correlation, energy and homogeneity. The extracted features sets are compared to the visually assessed tissue characteristics. Overall, the extracted texture features have high correlations to both the percentage of collagenous stroma (r=0.95, p<0.001) and duct-lobular unit density (r=0.71, p<0.001) seen in the tissue samples, and several individual features were associated with either collagen density and/or the presence of elastosis (p<=0.05). This suggests that the proposed framework has promise as a means to quantitatively extract descriptors reflecting tissue-level characteristics and thus could be useful in detecting and characterizing histological processes in digitized histology specimens.
Quantitative Neuroimaging Software for Clinical Assessment of Hippocampal Volumes on MR Imaging

PubMed Central

Ahdidan, Jamila; Raji, Cyrus A.; DeYoe, Edgar A.; Mathis, Jedidiah; Noe, Karsten Ø.; Rimestad, Jens; Kjeldsen, Thomas K.; Mosegaard, Jesper; Becker, James T.; Lopez, Oscar

2015-01-01

Background: Multiple neurological disorders including Alzheimer’s disease (AD), mesial temporal sclerosis, and mild traumatic brain injury manifest with volume loss on brain MRI. Subtle volume loss is particularly seen early in AD. While prior research has demonstrated the value of this additional information from quantitative neuroimaging, very few applications have been approved for clinical use. Here we describe a US FDA cleared software program, NeuroreaderTM, for assessment of clinical hippocampal volume on brain MRI. Objective: To present the validation of hippocampal volumetrics on a clinical software program. Method: Subjects were drawn (n = 99) from the Alzheimer Disease Neuroimaging Initiative study. Volumetric brain MR imaging was acquired in both 1.5 T (n = 59) and 3.0 T (n = 40) scanners in participants with manual hippocampal segmentation. Fully automated hippocampal segmentation and measurement was done using a multiple atlas approach. The Dice Similarity Coefficient (DSC) measured the level of spatial overlap between NeuroreaderTM and gold standard manual segmentation from 0 to 1 with 0 denoting no overlap and 1 representing complete agreement. DSC comparisons between 1.5 T and 3.0 T scanners were done using standard independent samples T-tests. Results: In the bilateral hippocampus, mean DSC was 0.87 with a range of 0.78–0.91 (right hippocampus) and 0.76–0.91 (left hippocampus). Automated segmentation agreement with manual segmentation was essentially equivalent at 1.5 T (DSC = 0.879) versus 3.0 T (DSC = 0.872). Conclusion: This work provides a description and validation of a software program that can be applied in measuring hippocampal volume, a biomarker that is frequently abnormal in AD and other neurological disorders. PMID:26484924
Sci-Thur AM: YIS – 08: Automated Imaging Quality Assurance for Image-Guided Small Animal Irradiators

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

Johnstone, Chris; Bazalova-Carter, Magdalena

Purpose: To develop quality assurance (QA) standards and tolerance levels for image quality of small animal irradiators. Methods: A fully automated in-house QA software for image analysis of a commercial microCT phantom was created. Quantitative analyses of CT linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, modulation transfer function (MTF), and CT number evaluation was performed. Phantom microCT scans from seven institutions acquired with varying parameters (kVp, mA, time, voxel size, and frame rate) and five irradiator units (Xstrahl SARRP, PXI X-RAD 225Cx, PXI X-RAD SmART, GE explore CT/RT 140, and GE Explore CT 120) were analyzed. Multi-institutional datamore » sets were compared using our in-house software to establish pass/fail criteria for each QA test. Results: CT linearity (R2>0.996) was excellent at all but Institution 2. Acceptable SNR (>35) and noise levels (<55HU) were obtained at four of the seven institutions, where failing scans were acquired with less than 120mAs. Acceptable MTF (>1.5 lp/mm for MTF=0.2) was obtained at all but Institution 6 due to the largest scan voxel size (0.35mm). The geometric accuracy passed (<1.5%) at five of the seven institutions. Conclusion: Our QA software can be used to rapidly perform quantitative imaging QA for small animal irradiators, accumulate results over time, and display possible changes in imaging functionality from its original performance and/or from the recommended tolerance levels. This tool will aid researchers in maintaining high image quality, enabling precise conformal dose delivery to small animals.« less
Tissue slide-based microRNA characterization of tumors: how detailed could diagnosis become for cancer medicine?

PubMed Central

Sempere, Lorenzo F

2014-01-01

miRNAs are short, non-coding, regulatory RNAs that exert cell type-dependent, context-dependent, transcriptome-wide gene expression control under physiological and pathological conditions. Tissue slide-based assays provide qualitative (tumor compartment) and semi-quantitative (expression levels) information about altered miRNA expression at single-cell resolution in clinical tumor specimens. Reviewed here are key technological advances in the last 5 years that have led to implementation of fully automated, robust and reproducible tissue slide-based assays for in situ miRNA detection on US FDA-approved instruments; recent tissue slide-based discovery studies that suggest potential clinical applications of specific miRNAs in cancer medicine are highlighted; and the challenges in bringing tissue slide-based miRNA assays into the clinic are discussed, including clinical validation, biomarker performance, biomarker space and integration with other biomarkers. PMID:25090088
Identification and Quantitative Measurements of Chemical Species by Mass Spectrometry

NASA Technical Reports Server (NTRS)

Zondlo, Mark A.; Bomse, David S.

2005-01-01

The development of a miniature gas chromatograph/mass spectrometer system for the measurement of chemical species of interest to combustion is described. The completed system is a fully-contained, automated instrument consisting of a sampling inlet, a small-scale gas chromatograph, a miniature, quadrupole mass spectrometer, vacuum pumps, and software. A pair of computer-driven valves controls the gas sampling and introduction to the chromatographic column. The column has a stainless steel exterior and a silica interior, and contains an adsorbent of that is used to separate organic species. The detection system is based on a quadrupole mass spectrometer consisting of a micropole array, electrometer, and a computer interface. The vacuum system has two miniature pumps to maintain the low pressure needed for the mass spectrometer. A laptop computer uses custom software to control the entire system and collect the data. In a laboratory demonstration, the system separated calibration mixtures containing 1000 ppm of alkanes and alkenes.
Combined In Situ Illumination-NMR-UV/Vis Spectroscopy: A New Mechanistic Tool in Photochemistry.

PubMed

Seegerer, Andreas; Nitschke, Philipp; Gschwind, Ruth M

2018-06-18

Synthetic applications in photochemistry are booming. Despite great progress in the development of new reactions, mechanistic investigations are still challenging. Therefore, we present a fully automated in situ combination of NMR spectroscopy, UV/Vis spectroscopy, and illumination to allow simultaneous and time-resolved detection of paramagnetic and diamagnetic species. This optical fiber-based setup enables the first acquisition of combined UV/Vis and NMR spectra in photocatalysis, as demonstrated on a conPET process. Furthermore, the broad applicability of combined UVNMR spectroscopy for light-induced processes is demonstrated on a structural and quantitative analysis of a photoswitch, including rate modulation and stabilization of transient species by temperature variation. Owing to the flexibility regarding the NMR hardware, temperature, and light sources, we expect wide-ranging applications of this setup in various research fields. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.
Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography

NASA Astrophysics Data System (ADS)

Yong, Yan Ling; Tan, Li Kuo; McLaughlin, Robert A.; Chee, Kok Han; Liew, Yih Miin

2017-12-01

Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.
Preliminary results of real-time in-vitro electronic speckle pattern interferometry (ESPI) measurements in otolaryngology

NASA Astrophysics Data System (ADS)

Conerty, Michelle D.; Castracane, James; Cacace, Anthony T.; Parnes, Steven M.; Gardner, Glendon M.; Miller, Mitchell B.

1995-05-01

Electronic Speckle Pattern Interferometry (ESPI) is a nondestructive optical evaluation technique that is capable of determining surface and subsurface integrity through the quantitative evaluation of static or vibratory motion. By utilizing state of the art developments in the areas of lasers, fiber optics and solid state detector technology, this technique has become applicable in medical research and diagnostics. Based on initial support from NIDCD and continued support from InterScience, Inc., we have been developing a range of instruments for improved diagnostic evaluation in otolaryngological applications based on the technique of ESPI. These compact fiber optic instruments are capable of making real time interferometric measurements of the target tissue. Ongoing development of image post- processing software is currently capable of extracting the desired quantitative results from the acquired interferometric images. The goal of the research is to develop a fully automated system in which the image processing and quantification will be performed in hardware in near real-time. Subsurface details of both the tympanic membrane and vocal cord dynamics could speed the diagnosis of otosclerosis, laryngeal tumors, and aid in the evaluation of surgical procedures.
Experiments on waves under impulsive wind forcing in view of the Phillips (1957) theory

NASA Astrophysics Data System (ADS)

Shemer, Lev; Zavadsky, Andrey

2016-11-01

Only limited information is currently available on the initial stages of wind-waves growth from rest under sudden wind forcing; the mechanisms leading to the appearance of waves are still not well understood. In the present work, waves emerging in a small-scale laboratory facility under the action of step-like turbulent wind forcing are studied using capacitance and laser slope gauges. Measurements are performed at a number of fetches and for a range of wind velocities. Taking advantage of the fully automated experimental procedure, at least 100 independent realizations are recorded for each wind velocity at every fetch. The accumulated data sets allow calculating ensemble-averaged values of the measured parameters as a function of time elapsed from the blower activation. The accumulated results on the temporal variation of wind-wave field initially at rest allow quantitative comparison with the theory of Phillips (1957). Following Phillips, appearance of the initial detectable ripples was considered first, while the growth of short gravity waves at later times was analyzed separately. Good qualitative and partial quantitative agreement between the Phillips predictions and the measurements was obtained for both those stages of the initial wind-wave field evolution.
Effects of imperfect automation on decision making in a simulated command and control task.

PubMed

Rovira, Ericka; McGarry, Kathleen; Parasuraman, Raja

2007-02-01

Effects of four types of automation support and two levels of automation reliability were examined. The objective was to examine the differential impact of information and decision automation and to investigate the costs of automation unreliability. Research has shown that imperfect automation can lead to differential effects of stages and levels of automation on human performance. Eighteen participants performed a "sensor to shooter" targeting simulation of command and control. Dependent variables included accuracy and response time of target engagement decisions, secondary task performance, and subjective ratings of mental work-load, trust, and self-confidence. Compared with manual performance, reliable automation significantly reduced decision times. Unreliable automation led to greater cost in decision-making accuracy under the higher automation reliability condition for three different forms of decision automation relative to information automation. At low automation reliability, however, there was a cost in performance for both information and decision automation. The results are consistent with a model of human-automation interaction that requires evaluation of the different stages of information processing to which automation support can be applied. If fully reliable decision automation cannot be guaranteed, designers should provide users with information automation support or other tools that allow for inspection and analysis of raw data.
Laboratory Testing Protocols for Heparin-Induced Thrombocytopenia (HIT) Testing.

PubMed

Lau, Kun Kan Edwin; Mohammed, Soma; Pasalic, Leonardo; Favaloro, Emmanuel J

2017-01-01

Heparin-induced thrombocytopenia (HIT) represents a significant high morbidity complication of heparin therapy. The clinicopathological diagnosis of HIT remains challenging for many reasons; thus, laboratory testing represents an important component of an accurate diagnosis. Although there are many assays available to assess HIT, these essentially fall into two categories-(a) immunological assays, and (b) functional assays. The current chapter presents protocols for several HIT assays, being those that are most commonly performed in laboratory practice and have the widest geographic distribution. These comprise a manual lateral flow-based system (STiC), a fully automated latex immunoturbidimetric assay, a fully automated chemiluminescent assay (CLIA), light transmission aggregation (LTA), and whole blood aggregation (Multiplate).
An Open-Source Automated Peptide Synthesizer Based on Arduino and Python.

PubMed

Gali, Hariprasad

2017-10-01

The development of the first open-source automated peptide synthesizer, PepSy, using Arduino UNO and readily available components is reported. PepSy was primarily designed to synthesize small peptides in a relatively small scale (<100 µmol). Scripts to operate PepSy in a fully automatic or manual mode were written in Python. Fully automatic script includes functions to carry out resin swelling, resin washing, single coupling, double coupling, Fmoc deprotection, ivDde deprotection, on-resin oxidation, end capping, and amino acid/reagent line cleaning. Several small peptides and peptide conjugates were successfully synthesized on PepSy with reasonably good yields and purity depending on the complexity of the peptide.
On the Agreement between Manual and Automated Methods for Single-Trial Detection and Estimation of Features from Event-Related Potentials

PubMed Central

Biurrun Manresa, José A.; Arguissain, Federico G.; Medina Redondo, David E.; Mørch, Carsten D.; Andersen, Ole K.

2015-01-01

The agreement between humans and algorithms on whether an event-related potential (ERP) is present or not and the level of variation in the estimated values of its relevant features are largely unknown. Thus, the aim of this study was to determine the categorical and quantitative agreement between manual and automated methods for single-trial detection and estimation of ERP features. To this end, ERPs were elicited in sixteen healthy volunteers using electrical stimulation at graded intensities below and above the nociceptive withdrawal reflex threshold. Presence/absence of an ERP peak (categorical outcome) and its amplitude and latency (quantitative outcome) in each single-trial were evaluated independently by two human observers and two automated algorithms taken from existing literature. Categorical agreement was assessed using percentage positive and negative agreement and Cohen’s κ, whereas quantitative agreement was evaluated using Bland-Altman analysis and the coefficient of variation. Typical values for the categorical agreement between manual and automated methods were derived, as well as reference values for the average and maximum differences that can be expected if one method is used instead of the others. Results showed that the human observers presented the highest categorical and quantitative agreement, and there were significantly large differences between detection and estimation of quantitative features among methods. In conclusion, substantial care should be taken in the selection of the detection/estimation approach, since factors like stimulation intensity and expected number of trials with/without response can play a significant role in the outcome of a study. PMID:26258532
Automation study for space station subsystems and mission ground support

NASA Technical Reports Server (NTRS)

1985-01-01

An automation concept for the autonomous operation of space station subsystems, i.e., electric power, thermal control, and communications and tracking are discussed. To assure that functions essential for autonomous operations are not neglected, an operations function (systems monitoring and control) is included in the discussion. It is recommended that automated speech recognition and synthesis be considered a basic mode of man/machine interaction for space station command and control, and that the data management system (DMS) and other systems on the space station be designed to accommodate fully automated fault detection, isolation, and recovery within the system monitoring function of the DMS.

Diagnostic accuracy of stress perfusion CMR in comparison with quantitative coronary angiography: fully quantitative, semiquantitative, and qualitative assessment.

PubMed

Mordini, Federico E; Haddad, Tariq; Hsu, Li-Yueh; Kellman, Peter; Lowrey, Tracy B; Aletras, Anthony H; Bandettini, W Patricia; Arai, Andrew E

2014-01-01

This study's primary objective was to determine the sensitivity, specificity, and accuracy of fully quantitative stress perfusion cardiac magnetic resonance (CMR) versus a reference standard of quantitative coronary angiography. We hypothesized that fully quantitative analysis of stress perfusion CMR would have high diagnostic accuracy for identifying significant coronary artery stenosis and exceed the accuracy of semiquantitative measures of perfusion and qualitative interpretation. Relatively few studies apply fully quantitative CMR perfusion measures to patients with coronary disease and comparisons to semiquantitative and qualitative methods are limited. Dual bolus dipyridamole stress perfusion CMR exams were performed in 67 patients with clinical indications for assessment of myocardial ischemia. Stress perfusion images alone were analyzed with a fully quantitative perfusion (QP) method and 3 semiquantitative methods including contrast enhancement ratio, upslope index, and upslope integral. Comprehensive exams (cine imaging, stress/rest perfusion, late gadolinium enhancement) were analyzed qualitatively with 2 methods including the Duke algorithm and standard clinical interpretation. A 70% or greater stenosis by quantitative coronary angiography was considered abnormal. The optimum diagnostic threshold for QP determined by receiver-operating characteristic curve occurred when endocardial flow decreased to <50% of mean epicardial flow, which yielded a sensitivity of 87% and specificity of 93%. The area under the curve for QP was 92%, which was superior to semiquantitative methods: contrast enhancement ratio: 78%; upslope index: 82%; and upslope integral: 75% (p = 0.011, p = 0.019, p = 0.004 vs. QP, respectively). Area under the curve for QP was also superior to qualitative methods: Duke algorithm: 70%; and clinical interpretation: 78% (p < 0.001 and p < 0.001 vs. QP, respectively). Fully quantitative stress perfusion CMR has high diagnostic accuracy for detecting obstructive coronary artery disease. QP outperforms semiquantitative measures of perfusion and qualitative methods that incorporate a combination of cine, perfusion, and late gadolinium enhancement imaging. These findings suggest a potential clinical role for quantitative stress perfusion CMR. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Automated Welding System

NASA Technical Reports Server (NTRS)

Bayless, E. O.; Lawless, K. G.; Kurgan, C.; Nunes, A. C.; Graham, B. F.; Hoffman, D.; Jones, C. S.; Shepard, R.

1993-01-01

Fully automated variable-polarity plasma arc VPPA welding system developed at Marshall Space Flight Center. System eliminates defects caused by human error. Integrates many sensors with mathematical model of the weld and computer-controlled welding equipment. Sensors provide real-time information on geometry of weld bead, location of weld joint, and wire-feed entry. Mathematical model relates geometry of weld to critical parameters of welding process.
Fully Automated Deep Learning System for Bone Age Assessment.

PubMed

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

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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.
Automated Quantitative Nuclear Cardiology Methods

PubMed Central

Motwani, Manish; Berman, Daniel S.; Germano, Guido; Slomka, Piotr J.

2016-01-01

Quantitative analysis of SPECT and PET has become a major part of nuclear cardiology practice. Current software tools can automatically segment the left ventricle, quantify function, establish myocardial perfusion maps and estimate global and local measures of stress/rest perfusion – all with minimal user input. State-of-the-art automated techniques have been shown to offer high diagnostic accuracy for detecting coronary artery disease, as well as predict prognostic outcomes. This chapter briefly reviews these techniques, highlights several challenges and discusses the latest developments. PMID:26590779
ATLAS, an integrated structural analysis and design system. Volume 6: Design module theory

NASA Technical Reports Server (NTRS)

Backman, B. F.

1979-01-01

The automated design theory underlying the operation of the ATLAS Design Module is decribed. The methods, applications and limitations associated with the fully stressed design, the thermal fully stressed design and a regional optimization algorithm are presented. A discussion of the convergence characteristics of the fully stressed design is also included. Derivations and concepts specific to the ATLAS design theory are shown, while conventional terminology and established methods are identified by references.
Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method

NASA Astrophysics Data System (ADS)

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 planning and can be readily applied to different treatment sites and modalities.
Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method.

PubMed

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

2017-07-06

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 planning and can be readily applied to different treatment sites and modalities.
Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning

NASA Astrophysics Data System (ADS)

Brown, James M.; Campbell, J. Peter; Beers, Andrew; Chang, Ken; Donohue, Kyra; Ostmo, Susan; Chan, R. V. Paul; Dy, Jennifer; Erdogmus, Deniz; Ioannidis, Stratis; Chiang, Michael F.; Kalpathy-Cramer, Jayashree

2018-03-01

Retinopathy of prematurity (ROP) is a disease that affects premature infants, where abnormal growth of the retinal blood vessels can lead to blindness unless treated accordingly. Infants considered at risk of severe ROP are monitored for symptoms of plus disease, characterized by arterial tortuosity and venous dilation at the posterior pole, with a standard photographic definition. Disagreement among ROP experts in diagnosing plus disease has driven the development of computer-based methods that classify images based on hand-crafted features extracted from the vasculature. However, most of these approaches are semi-automated, which are time-consuming and subject to variability. In contrast, deep learning is a fully automated approach that has shown great promise in a wide variety of domains, including medical genetics, informatics and imaging. Convolutional neural networks (CNNs) are deep networks which learn rich representations of disease features that are highly robust to variations in acquisition and image quality. In this study, we utilized a U-Net architecture to perform vessel segmentation and then a GoogLeNet to perform disease classification. The classifier was trained on 3,000 retinal images and validated on an independent test set of patients with different observed progressions and treatments. We show that our fully automated algorithm can be used to monitor the progression of plus disease over multiple patient visits with results that are consistent with the experts' consensus diagnosis. Future work will aim to further validate the method on larger cohorts of patients to assess its applicability within the clinic as a treatment monitoring tool.
Field performance of a low-cost and fully-automated blood counting system operated by trained and untrained users (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xie, Dengling; Xie, Yanjun; Liu, Peng; Tong, Lieshu; Chu, Kaiqin; Smith, Zachary J.

2017-02-01

Current flow-based blood counting devices require expensive and centralized medical infrastructure and are not appropriate for field use. In this paper we report a method to count red blood cells, white blood cells as well as platelets through a low-cost and fully-automated blood counting system. The approach consists of using a compact, custom-built microscope with large field-of-view to record bright-field and fluorescence images of samples that are diluted with a single, stable reagent mixture and counted using automatic algorithms. Sample collection is performed manually using a spring loaded lancet, and volume-metering capillary tubes. The capillaries are then dropped into a tube of pre-measured reagents and gently shaken for 10-30 seconds. The sample is loaded into a measurement chamber and placed on a custom 3D printed platform. Sample translation and focusing is fully automated, and a user has only to press a button for the measurement and analysis to commence. Cost of the system is minimized through the use of custom-designed motorized components. We performed a series of comparative experiments by trained and untrained users on blood from adults and children. We compare the performance of our system, as operated by trained and untrained users, to the clinical gold standard using a Bland-Altman analysis, demonstrating good agreement of our system to the clinical standard. The system's low cost, complete automation, and good field performance indicate that it can be successfully translated for use in low-resource settings where central hematology laboratories are not accessible.
Automated structure determination of proteins with the SAIL-FLYA NMR method.

PubMed

Takeda, Mitsuhiro; Ikeya, Teppei; Güntert, Peter; Kainosho, Masatsune

2007-01-01

The labeling of proteins with stable isotopes enhances the NMR method for the determination of 3D protein structures in solution. Stereo-array isotope labeling (SAIL) provides an optimal stereospecific and regiospecific pattern of stable isotopes that yields sharpened lines, spectral simplification without loss of information, and the ability to collect rapidly and evaluate fully automatically the structural restraints required to solve a high-quality solution structure for proteins up to twice as large as those that can be analyzed using conventional methods. Here, we describe a protocol for the preparation of SAIL proteins by cell-free methods, including the preparation of S30 extract and their automated structure analysis using the FLYA algorithm and the program CYANA. Once efficient cell-free expression of the unlabeled or uniformly labeled target protein has been achieved, the NMR sample preparation of a SAIL protein can be accomplished in 3 d. A fully automated FLYA structure calculation can be completed in 1 d on a powerful computer system.
Fully automated spectrometric protocols for determination of antioxidant activity: advantages and disadvantages.

PubMed

Sochor, Jiri; Ryvolova, Marketa; Krystofova, Olga; Salas, Petr; Hubalek, Jaromir; Adam, Vojtech; Trnkova, Libuse; Havel, Ladislav; Beklova, Miroslava; Zehnalek, Josef; Provaznik, Ivo; Kizek, Rene

2010-11-29

The aim of this study was to describe behaviour, kinetics, time courses and limitations of the six different fully automated spectrometric methods--DPPH, TEAC, FRAP, DMPD, Free Radicals and Blue CrO5. Absorption curves were measured and absorbance maxima were found. All methods were calibrated using the standard compounds Trolox® and/or gallic acid. Calibration curves were determined (relative standard deviation was within the range from 1.5 to 2.5%). The obtained characteristics were compared and discussed. Moreover, the data obtained were applied to optimize and to automate all mentioned protocols. Automatic analyzer allowed us to analyse simultaneously larger set of samples, to decrease the measurement time, to eliminate the errors and to provide data of higher quality in comparison to manual analysis. The total time of analysis for one sample was decreased to 10 min for all six methods. In contrary, the total time of manual spectrometric determination was approximately 120 min. The obtained data provided good correlations between studied methods (R=0.97-0.99).
A fully automated FTIR system for remote sensing of greenhouse gases in the tropics

NASA Astrophysics Data System (ADS)

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

PubMed

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.
Automation of surface observations program

NASA Technical Reports Server (NTRS)

Short, Steve E.

1988-01-01

At present, surface weather observing methods are still largely manual and labor intensive. Through the nationwide implementation of Automated Surface Observing Systems (ASOS), this situation can be improved. Two ASOS capability levels are planned. The first is a basic-level system which will automatically observe the weather parameters essential for aviation operations and will operate either with or without supplemental contributions by an observer. The second is a more fully automated, stand-alone system which will observe and report the full range of weather parameters and will operate primarily in the unattended mode. Approximately 250 systems are planned by the end of the decade. When deployed, these systems will generate the standard hourly and special long-line transmitted weather observations, as well as provide continuous weather information direct to airport users. Specific ASOS configurations will vary depending upon whether the operation is unattended, minimally attended, or fully attended. The major functions of ASOS are data collection, data processing, product distribution, and system control. The program phases of development, demonstration, production system acquisition, and operational implementation are described.
Automated production at the curie level of no-carrier-added 6-[(18)F]fluoro-L-dopa and 2-[(18)F]fluoro-L-tyrosine on a FASTlab synthesizer.

PubMed

Lemaire, C; Libert, L; Franci, X; Genon, J-L; Kuci, S; Giacomelli, F; Luxen, A

2015-06-15

An efficient, fully automated, enantioselective multi-step synthesis of no-carrier-added (nca) 6-[(18)F]fluoro-L-dopa ([(18)F]FDOPA) and 2-[(18)F]fluoro-L-tyrosine ([(18)F]FTYR) on a GE FASTlab synthesizer in conjunction with an additional high- performance liquid chromatography (HPLC) purification has been developed. A PTC (phase-transfer catalyst) strategy was used to synthesize these two important radiopharmaceuticals. According to recent chemistry improvements, automation of the whole process was implemented in a commercially available GE FASTlab module, with slight hardware modification using single use cassettes and stand-alone HPLC. [(18)F]FDOPA and [(18)F]FTYR were produced in 36.3 ± 3.0% (n = 8) and 50.5 ± 2.7% (n = 10) FASTlab radiochemical yield (decay corrected). The automated radiosynthesis on the FASTlab module requires about 52 min. Total synthesis time including HPLC purification and formulation was about 62 min. Enantiomeric excesses for these two aromatic amino acids were always >95%, and the specific activity of was >740 GBq/µmol. This automated synthesis provides high amount of [(18)F]FDOPA and [(18)F]FTYR (>37 GBq end of synthesis (EOS)). The process, fully adaptable for reliable production across multiple PET sites, could be readily implemented into a clinical good manufacturing process (GMP) environment. Copyright © 2015 John Wiley & Sons, Ltd.
Fully Automated Anesthesia, Analgesia and Fluid Management

ClinicalTrials.gov

2017-01-03

General Anesthetic Drug Overdose; Adverse Effect of Intravenous Anesthetics, Sequela; Complication of Anesthesia; Drug Delivery System Malfunction; Hemodynamic Instability; Underdosing of Other General Anesthetics
Pilot opinions on high level flight deck automation issues: Toward the development of a design philosophy

NASA Technical Reports Server (NTRS)

Tenney, Yvette J.; Rogers, William H.; Pew, Richard W.

1995-01-01

There has been much concern in recent years about the rapid increase in automation on commercial flight decks. The survey was composed of three major sections. The first section asked pilots to rate different automation components that exist on the latest commercial aircraft regarding their obtrusiveness and the attention and effort required in using them. The second section addressed general 'automation philosophy' issues. The third section focused on issues related to levels and amount of automation. The results indicate that pilots of advanced aircraft like their automation, use it, and would welcome more automation. However, they also believe that automation has many disadvantages, especially fully autonomous automation. They want their automation to be simple and reliable and to produce predictable results. The biggest needs for higher levels of automation were in pre-flight, communication, systems management, and task management functions, planning as well as response tasks, and high workload situations. There is an irony and a challenge in the implications of these findings. On the one hand pilots would like new automation to be simple and reliable, but they need it to support the most complex part of the job--managing and planning tasks in high workload situations.
Accuracy of patient specific organ-dose estimates obtained using an automated image segmentation algorithm

NASA Astrophysics Data System (ADS)

Gilat-Schmidt, Taly; Wang, Adam; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-03-01

The overall goal of this work is to develop a rapid, accurate and fully automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using a deterministic Boltzmann Transport Equation solver and automated CT segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. The investigated algorithm uses a combination of feature-based and atlas-based methods. A multiatlas approach was also investigated. We hypothesize that the auto-segmentation algorithm is sufficiently accurate to provide organ dose estimates since random errors at the organ boundaries will average out when computing the total organ dose. To test this hypothesis, twenty head-neck CT scans were expertly segmented into nine regions. A leave-one-out validation study was performed, where every case was automatically segmented with each of the remaining cases used as the expert atlas, resulting in nineteen automated segmentations for each of the twenty datasets. The segmented regions were applied to gold-standard Monte Carlo dose maps to estimate mean and peak organ doses. The results demonstrated that the fully automated segmentation algorithm estimated the mean organ dose to within 10% of the expert segmentation for regions other than the spinal canal, with median error for each organ region below 2%. In the spinal canal region, the median error was 7% across all data sets and atlases, with a maximum error of 20%. The error in peak organ dose was below 10% for all regions, with a median error below 4% for all organ regions. The multiple-case atlas reduced the variation in the dose estimates and additional improvements may be possible with more robust multi-atlas approaches. Overall, the results support potential feasibility of an automated segmentation algorithm to provide accurate organ dose estimates.

Gas pressure assisted microliquid-liquid extraction coupled online to direct infusion mass spectrometry: a new automated screening platform for bioanalysis.

PubMed

Raterink, Robert-Jan; Witkam, Yoeri; Vreeken, Rob J; Ramautar, Rawi; Hankemeier, Thomas

2014-10-21

In the field of bioanalysis, there is an increasing demand for miniaturized, automated, robust sample pretreatment procedures that can be easily connected to direct-infusion mass spectrometry (DI-MS) in order to allow the high-throughput screening of drugs and/or their metabolites in complex body fluids like plasma. Liquid-Liquid extraction (LLE) is a common sample pretreatment technique often used for complex aqueous samples in bioanalysis. Despite significant developments that have been made in automated and miniaturized LLE procedures, fully automated LLE techniques allowing high-throughput bioanalytical studies on small-volume samples using direct infusion mass spectrometry, have not been matured yet. Here, we introduce a new fully automated micro-LLE technique based on gas-pressure assisted mixing followed by passive phase separation, coupled online to nanoelectrospray-DI-MS. Our method was characterized by varying the gas flow and its duration through the solvent mixture. For evaluation of the analytical performance, four drugs were spiked to human plasma, resulting in highly acceptable precision (RSD down to 9%) and linearity (R(2) ranging from 0.990 to 0.998). We demonstrate that our new method does not only allow the reliable extraction of analytes from small sample volumes of a few microliters in an automated and high-throughput manner, but also performs comparable or better than conventional offline LLE, in which the handling of small volumes remains challenging. Finally, we demonstrate the applicability of our method for drug screening on dried blood spots showing excellent linearity (R(2) of 0.998) and precision (RSD of 9%). In conclusion, we present the proof of principe of a new high-throughput screening platform for bioanalysis based on a new automated microLLE method, coupled online to a commercially available nano-ESI-DI-MS.
Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

NASA Astrophysics Data System (ADS)

Polan, Daniel F.; Brady, Samuel L.; Kaufman, Robert A.

2016-09-01

There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 n , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21 patient image sections, were analyzed. The automated algorithm produced segmentation of seven material classes with a median DSC of 0.86 ± 0.03 for pediatric patient protocols, and 0.85 ± 0.04 for adult patient protocols. Additionally, 100 randomly selected patient examinations were segmented and analyzed, and a mean sensitivity of 0.91 (range: 0.82-0.98), specificity of 0.89 (range: 0.70-0.98), and accuracy of 0.90 (range: 0.76-0.98) were demonstrated. In this study, we demonstrate that this fully automated segmentation tool was able to produce fast and accurate segmentation of the neck and trunk of the body over a wide range of patient habitus and scan parameters.
Long-term maintenance of human induced pluripotent stem cells by automated cell culture system.

PubMed

Konagaya, Shuhei; Ando, Takeshi; Yamauchi, Toshiaki; Suemori, Hirofumi; Iwata, Hiroo

2015-11-17

Pluripotent stem cells, such as embryonic stem cells and induced pluripotent stem (iPS) cells, are regarded as new sources for cell replacement therapy. These cells can unlimitedly expand under undifferentiated conditions and be differentiated into multiple cell types. Automated culture systems enable the large-scale production of cells. In addition to reducing the time and effort of researchers, an automated culture system improves the reproducibility of cell cultures. In the present study, we newly designed a fully automated cell culture system for human iPS maintenance. Using an automated culture system, hiPS cells maintained their undifferentiated state for 60 days. Automatically prepared hiPS cells had a potency of differentiation into three germ layer cells including dopaminergic neurons and pancreatic cells.
Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis.

PubMed

Lee, Hyunkwang; Troschel, Fabian M; Tajmir, Shahein; Fuchs, Georg; Mario, Julia; Fintelmann, Florian J; Do, Synho

2017-08-01

Pretreatment risk stratification is key for personalized medicine. While many physicians rely on an "eyeball test" to assess whether patients will tolerate major surgery or chemotherapy, "eyeballing" is inherently subjective and difficult to quantify. The concept of morphometric age derived from cross-sectional imaging has been found to correlate well with outcomes such as length of stay, morbidity, and mortality. However, the determination of the morphometric age is time intensive and requires highly trained experts. In this study, we propose a fully automated deep learning system for the segmentation of skeletal muscle cross-sectional area (CSA) on an axial computed tomography image taken at the third lumbar vertebra. We utilized a fully automated deep segmentation model derived from an extended implementation of a fully convolutional network with weight initialization of an ImageNet pre-trained model, followed by post processing to eliminate intramuscular fat for a more accurate analysis. This experiment was conducted by varying window level (WL), window width (WW), and bit resolutions in order to better understand the effects of the parameters on the model performance. Our best model, fine-tuned on 250 training images and ground truth labels, achieves 0.93 ± 0.02 Dice similarity coefficient (DSC) and 3.68 ± 2.29% difference between predicted and ground truth muscle CSA on 150 held-out test cases. Ultimately, the fully automated segmentation system can be embedded into the clinical environment to accelerate the quantification of muscle and expanded to volume analysis of 3D datasets.
Fully automated adipose tissue measurement on abdominal CT

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Sussman, Daniel L.; Summers, Ronald M.

2011-03-01

Obesity has become widespread in America and has been associated as a risk factor for many illnesses. Adipose tissue (AT) content, especially visceral AT (VAT), is an important indicator for risks of many disorders, including heart disease and diabetes. Measuring adipose tissue (AT) with traditional means is often unreliable and inaccurate. CT provides a means to measure AT accurately and consistently. We present a fully automated method to segment and measure abdominal AT in CT. Our method integrates image preprocessing which attempts to correct for image artifacts and inhomogeneities. We use fuzzy cmeans to cluster AT regions and active contour models to separate subcutaneous and visceral AT. We tested our method on 50 abdominal CT scans and evaluated the correlations between several measurements.
Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images

PubMed Central

Srinivasan, Pratul P.; Kim, Leo A.; Mettu, Priyatham S.; Cousins, Scott W.; Comer, Grant M.; Izatt, Joseph A.; Farsiu, Sina

2014-01-01

We present a novel fully automated algorithm for the detection of retinal diseases via optical coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of oriented gradient descriptors as feature vectors of a support vector machine based classifier. The spectral domain OCT data sets used for cross-validation consisted of volumetric scans acquired from 45 subjects: 15 normal subjects, 15 patients with dry age-related macular degeneration (AMD), and 15 patients with diabetic macular edema (DME). Our classifier correctly identified 100% of cases with AMD, 100% cases with DME, and 86.67% cases of normal subjects. This algorithm is a potentially impactful tool for the remote diagnosis of ophthalmic diseases. PMID:25360373
Space applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 4: Application of ARAMIS capabilities to space project functional elements

NASA Technical Reports Server (NTRS)

Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

1982-01-01

Applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities and their related ground support functions are studied, so that informed decisions can be made on which aspects of ARAMIS to develop. The specific tasks which will be required by future space project tasks are identified and the relative merits of these options are evaluated. The ARAMIS options defined and researched span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.
Evaluation of the Aptima HIV-1 Quant Dx Assay for HIV-1 RNA Quantitation in Different Biological Specimen Types.

PubMed

Yek, Christina; Massanella, Marta; Peling, Tashi; Lednovich, Kristen; Nair, Sangeetha V; Worlock, Andrew; Vargas, Milenka; Gianella, Sara; Ellis, Ronald J; Strain, Matthew C; Busch, Michael P; Nugent, C Thomas; Richman, Douglas D

2017-08-01

The search for a cure for HIV infection has highlighted the need for increasingly sensitive and precise assays to measure viral burden in various tissues and body fluids. We describe the application of a standardized assay for HIV-1 RNA in multiple specimen types. The fully automated Aptima HIV-1 Quant Dx assay (Aptima assay) is FDA cleared for blood plasma HIV-1 RNA quantitation. In this study, the Aptima assay was applied for the quantitation of HIV RNA in peripheral blood mononuclear cells (PBMCs; n = 72), seminal plasma ( n = 20), cerebrospinal fluid (CSF; n = 36), dried blood spots (DBS; n = 104), and dried plasma spots (DPS; n = 104). The Aptima assay was equivalent to or better than commercial assays or validated in-house assays for the quantitation of HIV RNA in CSF and seminal plasma. For PBMC specimens, the sensitivity of the Aptima assay in the detection of HIV RNA decayed as background uninfected PBMC counts increased; proteinase K treatment demonstrated some benefit in restoring signal at higher levels of background PBMCs. Finally, the Aptima assay yielded 100% detection rates of DBS in participants with plasma HIV RNA levels of ≥35 copies/ml and 100% detection rates of DPS in participants with plasma HIV RNA levels of ≥394 copies/ml. The Aptima assay can be applied to a variety of specimens from HIV-infected subjects to measure HIV RNA for studies of viral persistence and cure strategies. It can also detect HIV in dried blood and plasma specimens, which may be of benefit in resource-limited settings.
Toward standardized quantitative image quality (IQ) assessment in computed tomography (CT): A comprehensive framework for automated and comparative IQ analysis based on ICRU Report 87.

PubMed

Pahn, Gregor; Skornitzke, Stephan; Schlemmer, Hans-Peter; Kauczor, Hans-Ulrich; Stiller, Wolfram

2016-01-01

Based on the guidelines from "Report 87: Radiation Dose and Image-quality Assessment in Computed Tomography" of the International Commission on Radiation Units and Measurements (ICRU), a software framework for automated quantitative image quality analysis was developed and its usability for a variety of scientific questions demonstrated. The extendable framework currently implements the calculation of the recommended Fourier image quality (IQ) metrics modulation transfer function (MTF) and noise-power spectrum (NPS), and additional IQ quantities such as noise magnitude, CT number accuracy, uniformity across the field-of-view, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated lesions for a commercially available cone-beam phantom. Sample image data were acquired with different scan and reconstruction settings on CT systems from different manufacturers. Spatial resolution is analyzed in terms of edge-spread function, line-spread-function, and MTF. 3D NPS is calculated according to ICRU Report 87, and condensed to 2D and radially averaged 1D representations. Noise magnitude, CT numbers, and uniformity of these quantities are assessed on large samples of ROIs. Low-contrast resolution (CNR, SNR) is quantitatively evaluated as a function of lesion contrast and diameter. Simultaneous automated processing of several image datasets allows for straightforward comparative assessment. The presented framework enables systematic, reproducible, automated and time-efficient quantitative IQ analysis. Consistent application of the ICRU guidelines facilitates standardization of quantitative assessment not only for routine quality assurance, but for a number of research questions, e.g. the comparison of different scanner models or acquisition protocols, and the evaluation of new technology or reconstruction methods. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Automated Medical Supply Chain Management: A Remedy for Logistical Shortcomings

DTIC Science & Technology

2016-08-01

Regional case study where the hospital compared its utilization of automated inventory management technologies (Pyxis) to previous SCM practice in the... management practices within the 96 Medical Group (MDG), Eglin Hospital . It was known that the Defense Medical Logistics Standard was used at Eglin... Hospital but was not fully integrated down to the unit level. Casual manual inventory management practices were used explicitly resulting in
Shape indexes for semi-automated detection of windbreaks in thematic tree cover maps from the central United States

Treesearch

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...
Lab-on-a-Chip Proteomic Assays for Psychiatric Disorders.

PubMed

Peter, Harald; Wienke, Julia; Guest, Paul C; Bistolas, Nikitas; Bier, Frank F

2017-01-01

Lab-on-a-chip assays allow rapid identification of multiple parameters on an automated user-friendly platform. Here we describe a fully automated multiplex immunoassay and readout in less than 15 min using the Fraunhofer in vitro diagnostics (ivD) platform to enable inexpensive point-of-care profiling of sera or a single drop of blood from patients with various diseases such as psychiatric disorders.
The automation of an inlet mass flow control system

NASA Technical Reports Server (NTRS)

Supplee, Frank; Tcheng, Ping; Weisenborn, Michael

1989-01-01

The automation of a closed-loop computer controlled system for the inlet mass flow system (IMFS) developed for a wind tunnel facility at Langley Research Center is presented. This new PC based control system is intended to replace the manual control system presently in use in order to fully automate the plug positioning of the IMFS during wind tunnel testing. Provision is also made for communication between the PC and a host-computer in order to allow total animation of the plug positioning and data acquisition during the complete sequence of predetermined plug locations. As extensive running time is programmed for the IMFS, this new automated system will save both manpower and tunnel running time.
NMR-based automated protein structure determination.

PubMed

Würz, Julia M; Kazemi, Sina; Schmidt, Elena; Bagaria, Anurag; Güntert, Peter

2017-08-15

NMR spectra analysis for protein structure determination can now in many cases be performed by automated computational methods. This overview of the computational methods for NMR protein structure analysis presents recent automated methods for signal identification in multidimensional NMR spectra, sequence-specific resonance assignment, collection of conformational restraints, and structure calculation, as implemented in the CYANA software package. These algorithms are sufficiently reliable and integrated into one software package to enable the fully automated structure determination of proteins starting from NMR spectra without manual interventions or corrections at intermediate steps, with an accuracy of 1-2 Å backbone RMSD in comparison with manually solved reference structures. Copyright © 2017 Elsevier Inc. All rights reserved.
3D Slicer as an Image Computing Platform for the Quantitative Imaging Network

PubMed Central

Fedorov, Andriy; Beichel, Reinhard; Kalpathy-Cramer, Jayashree; Finet, Julien; Fillion-Robin, Jean-Christophe; Pujol, Sonia; Bauer, Christian; Jennings, Dominique; Fennessy, Fiona; Sonka, Milan; Buatti, John; Aylward, Stephen; Miller, James V.; Pieper, Steve; Kikinis, Ron

2012-01-01

Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer. PMID:22770690
Automated identification of Monogeneans using digital image processing and K-nearest neighbour approaches.

PubMed

Yousef Kalafi, Elham; Tan, Wooi Boon; Town, Christopher; Dhillon, Sarinder Kaur

2016-12-22

Monogeneans are flatworms (Platyhelminthes) that are primarily found on gills and skin of fishes. Monogenean parasites have attachment appendages at their haptoral regions that help them to move about the body surface and feed on skin and gill debris. Haptoral attachment organs consist of sclerotized hard parts such as hooks, anchors and marginal hooks. Monogenean species are differentiated based on their haptoral bars, anchors, marginal hooks, reproductive parts' (male and female copulatory organs) morphological characters and soft anatomical parts. The complex structure of these diagnostic organs and also their overlapping in microscopic digital images are impediments for developing fully automated identification system for monogeneans (LNCS 7666:256-263, 2012), (ISDA; 457-462, 2011), (J Zoolog Syst Evol Res 52(2): 95-99. 2013;). In this study images of hard parts of the haptoral organs such as bars and anchors are used to develop a fully automated identification technique for monogenean species identification by implementing image processing techniques and machine learning methods. Images of four monogenean species namely Sinodiplectanotrema malayanus, Trianchoratus pahangensis, Metahaliotrema mizellei and Metahaliotrema sp. (undescribed) were used to develop an automated technique for identification. K-nearest neighbour (KNN) was applied to classify the monogenean specimens based on the extracted features. 50% of the dataset was used for training and the other 50% was used as testing for system evaluation. Our approach demonstrated overall classification accuracy of 90%. In this study Leave One Out (LOO) cross validation is used for validation of our system and the accuracy is 91.25%. The methods presented in this study facilitate fast and accurate fully automated classification of monogeneans at the species level. In future studies more classes will be included in the model, the time to capture the monogenean images will be reduced and improvements in extraction and selection of features will be implemented.
Qualitative and quantitative analysis of mixtures of compounds containing both hydrogen and deuterium

NASA Technical Reports Server (NTRS)

Crespi, H. L.; Harkness, L.; Katz, J. J.; Norman, G.; Saur, W.

1969-01-01

Method allows qualitative and quantitative analysis of mixtures of partially deuterated compounds. Nuclear magnetic resonance spectroscopy determines location and amount of deuterium in organic compounds but not fully deuterated compounds. Mass spectroscopy can detect fully deuterated species but not the location.
Automated road network extraction from high spatial resolution multi-spectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a road network. The extracted road network is evaluated against a reference dataset using a line segment matching algorithm. The entire process is unsupervised and fully automated. Based on extensive experimentation on a variety of remotely-sensed multi-spectral images, the proposed methodology achieves a moderate success in automating road network extraction from high spatial resolution multi-spectral imagery.
Industrializing electrophysiology: HT automated patch clamp on SyncroPatch® 96 using instant frozen cells.

PubMed

Polonchuk, Liudmila

2014-01-01

Patch-clamping is a powerful technique for investigating the ion channel function and regulation. However, its low throughput hampered profiling of large compound series in early drug development. Fortunately, automation has revolutionized the area of experimental electrophysiology over the past decade. Whereas the first automated patch-clamp instruments using the planar patch-clamp technology demonstrated rather a moderate throughput, few second-generation automated platforms recently launched by various companies have significantly increased ability to form a high number of high-resistance seals. Among them is SyncroPatch(®) 96 (Nanion Technologies GmbH, Munich, Germany), a fully automated giga-seal patch-clamp system with the highest throughput on the market. By recording from up to 96 cells simultaneously, the SyncroPatch(®) 96 allows to substantially increase throughput without compromising data quality. This chapter describes features of the innovative automated electrophysiology system and protocols used for a successful transfer of the established hERG assay to this high-throughput automated platform.
AutoQSAR: an automated machine learning tool for best-practice quantitative structure-activity relationship modeling.

PubMed

Dixon, Steven L; Duan, Jianxin; Smith, Ethan; Von Bargen, Christopher D; Sherman, Woody; Repasky, Matthew P

2016-10-01

We introduce AutoQSAR, an automated machine-learning application to build, validate and deploy quantitative structure-activity relationship (QSAR) models. The process of descriptor generation, feature selection and the creation of a large number of QSAR models has been automated into a single workflow within AutoQSAR. The models are built using a variety of machine-learning methods, and each model is scored using a novel approach. Effectiveness of the method is demonstrated through comparison with literature QSAR models using identical datasets for six end points: protein-ligand binding affinity, solubility, blood-brain barrier permeability, carcinogenicity, mutagenicity and bioaccumulation in fish. AutoQSAR demonstrates similar or better predictive performance as compared with published results for four of the six endpoints while requiring minimal human time and expertise.

Complex Genetics of Behavior: BXDs in the Automated Home-Cage.

PubMed

Loos, Maarten; Verhage, Matthijs; Spijker, Sabine; Smit, August B

2017-01-01

This chapter describes a use case for the genetic dissection and automated analysis of complex behavioral traits using the genetically diverse panel of BXD mouse recombinant inbred strains. Strains of the BXD resource differ widely in terms of gene and protein expression in the brain, as well as in their behavioral repertoire. A large mouse resource opens the possibility for gene finding studies underlying distinct behavioral phenotypes, however, such a resource poses a challenge in behavioral phenotyping. To address the specifics of large-scale screening we describe how to investigate: (1) how to assess mouse behavior systematically in addressing a large genetic cohort, (2) how to dissect automation-derived longitudinal mouse behavior into quantitative parameters, and (3) how to map these quantitative traits to the genome, deriving loci underlying aspects of behavior.
Ultramap v3 - a Revolution in Aerial Photogrammetry

NASA Astrophysics Data System (ADS)

Reitinger, B.; Sormann, M.; Zebedin, L.; Schachinger, B.; Hoefler, M.; Tomasi, R.; Lamperter, M.; Gruber, B.; Schiester, G.; Kobald, M.; Unger, M.; Klaus, A.; Bernoegger, S.; Karner, K.; Wiechert, A.; Ponticelli, M.; Gruber, M.

2012-07-01

In the last years, Microsoft has driven innovation in the aerial photogrammetry community. Besides the market leading camera technology, UltraMap has grown to an outstanding photogrammetric workflow system which enables users to effectively work with large digital aerial image blocks in a highly automated way. Best example is the project-based color balancing approach which automatically balances images to a homogeneous block. UltraMap V3 continues innovation, and offers a revolution in terms of ortho processing. A fully automated dense matching module strives for high precision digital surface models (DSMs) which are calculated either on CPUs or on GPUs using a distributed processing framework. By applying constrained filtering algorithms, a digital terrain model can be derived which in turn can be used for fully automated traditional ortho texturing. By having the knowledge about the underlying geometry, seamlines can be generated automatically by applying cost functions in order to minimize visual disturbing artifacts. By exploiting the generated DSM information, a DSMOrtho is created using the balanced input images. Again, seamlines are detected automatically resulting in an automatically balanced ortho mosaic. Interactive block-based radiometric adjustments lead to a high quality ortho product based on UltraCam imagery. UltraMap v3 is the first fully integrated and interactive solution for supporting UltraCam images at best in order to deliver DSM and ortho imagery.
Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

PubMed

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 < 0.001). The AUCs were 0.84 (95% CI 0.78-0.89) for 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.
Fully Automated Atlas-Based Hippocampus Volumetry for Clinical Routine: Validation in Subjects with Mild Cognitive Impairment from the ADNI Cohort.

PubMed

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

PubMed Central

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

PubMed

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

2014-03-01

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

PubMed

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 < 0.001) and 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.
Two techniques for mapping and area estimation of small grains in California using Landsat digital data

NASA Technical Reports Server (NTRS)

Sheffner, E. J.; Hlavka, C. A.; Bauer, E. M.

1984-01-01

Two techniques have been developed for the mapping and area estimation of small grains in California from Landsat digital data. The two techniques are Band Ratio Thresholding, a semi-automated version of a manual procedure, and LCLS, a layered classification technique which can be fully automated and is based on established clustering and classification technology. Preliminary evaluation results indicate that the two techniques have potential for providing map products which can be incorporated into existing inventory procedures and automated alternatives to traditional inventory techniques and those which currently employ Landsat imagery.
Note: Automated electrochemical etching and polishing of silver scanning tunneling microscope tips.

PubMed

Sasaki, Stephen S; Perdue, Shawn M; Rodriguez Perez, Alejandro; Tallarida, Nicholas; Majors, Julia H; Apkarian, V Ara; Lee, Joonhee

2013-09-01

Fabrication of sharp and smooth Ag tips is crucial in optical scanning probe microscope experiments. To ensure reproducible tip profiles, the polishing process is fully automated using a closed-loop laminar flow system to deliver the electrolytic solution to moving electrodes mounted on a motorized translational stage. The repetitive translational motion is controlled precisely on the μm scale with a stepper motor and screw-thread mechanism. The automated setup allows reproducible control over the tip profile and improves smoothness and sharpness of tips (radius 27 ± 18 nm), as measured by ultrafast field emission.
Exploring the Use of a Test Automation Framework

NASA Technical Reports Server (NTRS)

Cervantes, Alex

2009-01-01

It is known that software testers, more often than not, lack the time needed to fully test the delivered software product within the time period allotted to them. When problems in the implementation phase of a development project occur, it normally causes the software delivery date to slide. As a result, testers either need to work longer hours, or supplementary resources need to be added to the test team in order to meet aggressive test deadlines. One solution to this problem is to provide testers with a test automation framework to facilitate the development of automated test solutions.
Fully automated laboratory and field-portable goniometer used for performing accurate and precise multiangular reflectance measurements

NASA Astrophysics Data System (ADS)

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.
High-Content Screening for Quantitative Cell Biology.

PubMed

Mattiazzi Usaj, Mojca; Styles, Erin B; Verster, Adrian J; Friesen, Helena; Boone, Charles; Andrews, Brenda J

2016-08-01

High-content screening (HCS), which combines automated fluorescence microscopy with quantitative image analysis, allows the acquisition of unbiased multiparametric data at the single cell level. This approach has been used to address diverse biological questions and identify a plethora of quantitative phenotypes of varying complexity in numerous different model systems. Here, we describe some recent applications of HCS, ranging from the identification of genes required for specific biological processes to the characterization of genetic interactions. We review the steps involved in the design of useful biological assays and automated image analysis, and describe major challenges associated with each. Additionally, we highlight emerging technologies and future challenges, and discuss how the field of HCS might be enhanced in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.
Automated Detection and Analysis of Interplanetary Shocks with Real-Time Application

NASA Astrophysics Data System (ADS)

Vorotnikov, V.; Smith, C. W.; Hu, Q.; Szabo, A.; Skoug, R. M.; Cohen, C. M.

2006-12-01

The ACE real-time data stream provides web-based now-casting capabilities for solar wind conditions upstream of Earth. Our goal is to provide an automated code that finds and analyzes interplanetary shocks as they occur for possible real-time application to space weather nowcasting. Shock analysis algorithms based on the Rankine-Hugoniot jump conditions exist and are in wide-spread use today for the interactive analysis of interplanetary shocks yielding parameters such as shock speed and propagation direction and shock strength in the form of compression ratios. Although these codes can be automated in a reasonable manner to yield solutions not far from those obtained by user-directed interactive analysis, event detection presents an added obstacle and the first step in a fully automated analysis. We present a fully automated Rankine-Hugoniot analysis code that can scan the ACE science data, find shock candidates, analyze the events, obtain solutions in good agreement with those derived from interactive applications, and dismiss false positive shock candidates on the basis of the conservation equations. The intent is to make this code available to NOAA for use in real-time space weather applications. The code has the added advantage of being able to scan spacecraft data sets to provide shock solutions for use outside real-time applications and can easily be applied to science-quality data sets from other missions. Use of the code for this purpose will also be explored.
Automated Robust Image Segmentation: Level Set Method Using Nonnegative Matrix Factorization with Application to Brain MRI.

PubMed

Dera, Dimah; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

2016-07-01

We address the problem of fully automated region discovery and robust image segmentation by devising a new deformable model based on the level set method (LSM) and the probabilistic nonnegative matrix factorization (NMF). We describe the use of NMF to calculate the number of distinct regions in the image and to derive the local distribution of the regions, which is incorporated into the energy functional of the LSM. The results demonstrate that our NMF-LSM method is superior to other approaches when applied to synthetic binary and gray-scale images and to clinical magnetic resonance images (MRI) of the human brain with and without a malignant brain tumor, glioblastoma multiforme. In particular, the NMF-LSM method is fully automated, highly accurate, less sensitive to the initial selection of the contour(s) or initial conditions, more robust to noise and model parameters, and able to detect as small distinct regions as desired. These advantages stem from the fact that the proposed method relies on histogram information instead of intensity values and does not introduce nuisance model parameters. These properties provide a general approach for automated robust region discovery and segmentation in heterogeneous images. Compared with the retrospective radiological diagnoses of two patients with non-enhancing grade 2 and 3 oligodendroglioma, the NMF-LSM detects earlier progression times and appears suitable for monitoring tumor response. The NMF-LSM method fills an important need of automated segmentation of clinical MRI.
High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles.

PubMed

Li, Fuhai; Zhou, Xiaobo; Zhu, Jinmin; Ma, Jinwen; Huang, Xudong; Wong, Stephen T C

2007-10-09

High content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study. The cellular images of H4 neuroglioma cells exposed to different concentrations of CuO nanoparticles were sampled using IN Cell Analyzer 1000. A fully automated cellular image analysis system has been developed to perform the image analysis for cell viability. A multiple adaptive thresholding method was used to classify the pixels of the nuclei image into three classes: bright nuclei, dark nuclei, and background. During the development of our image analysis methodology, we have achieved the followings: (1) The Gaussian filtering with proper scale has been applied to the cellular images for generation of a local intensity maximum inside each nucleus; (2) a novel local intensity maxima detection method based on the gradient vector field has been established; and (3) a statistical model based splitting method was proposed to overcome the under segmentation problem. Computational results indicate that 95.9% nuclei can be detected and segmented correctly by the proposed image analysis system. The proposed automated image analysis system can effectively segment the images of human H4 neuroglioma cells exposed to CuO nanoparticles. The computational results confirmed our biological finding that human H4 neuroglioma cells had a dose-dependent toxic response to the insult of CuO nanoparticles.
A rapid, automated approach for quantitation of rotavirus and reovirus infectivity.

PubMed

Iskarpatyoti, Jason A; Willis, Janet Z; Guan, John; Morse, E Ashley; Ikizler, Miné; Wetzel, J Denise; Dermody, Terence S; Contractor, Nikhat

2012-09-01

Current microscopy-based approaches for immunofluorescence detection of viral infectivity are time consuming and labor intensive and can yield variable results subject to observer bias. To circumvent these problems, we developed a rapid and automated infrared immunofluorescence imager-based infectivity assay for both rotavirus and reovirus that can be used to quantify viral infectivity and infectivity inhibition. For rotavirus, monolayers of MA104 cells were infected with simian strain SA-11 or SA-11 preincubated with rotavirus-specific human IgA. For reovirus, monolayers of either HeLa S3 cells or L929 cells were infected with strains type 1 Lang (T1L), type 3 Dearing (T3D), or either virus preincubated with a serotype-specific neutralizing monoclonal antibody (mAb). Infected cells were fixed and incubated with virus-specific polyclonal antiserum, followed by an infrared fluorescence-conjugated secondary antibody. Well-to-well variation in cell number was normalized using fluorescent reagents that stain fixed cells. Virus-infected cells were detected by scanning plates using an infrared imager, and results were obtained as a percent response of fluorescence intensity relative to a virus-specific standard. An expected dose-dependent inhibition of both SA-11 infectivity with rotavirus-specific human IgA and reovirus infectivity with T1L-specific mAb 5C6 and T3D-specific mAb 9BG5 was observed, confirming the utility of this assay for quantification of viral infectivity and infectivity blockade. The imager-based viral infectivity assay fully automates data collection and provides an important advance in technology for applications such as screening for novel modulators of viral infectivity. This basic platform can be adapted for use with multiple viruses and cell types. Copyright © 2012 Elsevier B.V. All rights reserved.
High-throughput analysis of sulfatides in cerebrospinal fluid using automated extraction and UPLC-MS/MS.

PubMed

Blomqvist, Maria; Borén, Jan; Zetterberg, Henrik; Blennow, Kaj; Månsson, Jan-Eric; Ståhlman, Marcus

2017-07-01

Sulfatides (STs) are a group of glycosphingolipids that are highly expressed in brain. Due to their importance for normal brain function and their potential involvement in neurological diseases, development of accurate and sensitive methods for their determination is needed. Here we describe a high-throughput oriented and quantitative method for the determination of STs in cerebrospinal fluid (CSF). The STs were extracted using a fully automated liquid/liquid extraction method and quantified using ultra-performance liquid chromatography coupled to tandem mass spectrometry. With the high sensitivity of the developed method, quantification of 20 ST species from only 100 μl of CSF was performed. Validation of the method showed that the STs were extracted with high recovery (90%) and could be determined with low inter- and intra-day variation. Our method was applied to a patient cohort of subjects with an Alzheimer's disease biomarker profile. Although the total ST levels were unaltered compared with an age-matched control group, we show that the ratio of hydroxylated/nonhydroxylated STs was increased in the patient cohort. In conclusion, we believe that the fast, sensitive, and accurate method described in this study is a powerful new tool for the determination of STs in clinical as well as preclinical settings. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.
Model-Independent Phenotyping of C. elegans Locomotion Using Scale-Invariant Feature Transform

PubMed Central

Koren, Yelena; Sznitman, Raphael; Arratia, Paulo E.; Carls, Christopher; Krajacic, Predrag; Brown, André E. X.; Sznitman, Josué

2015-01-01

To uncover the genetic basis of behavioral traits in the model organism C. elegans, a common strategy is to study locomotion defects in mutants. Despite efforts to introduce (semi-)automated phenotyping strategies, current methods overwhelmingly depend on worm-specific features that must be hand-crafted and as such are not generalizable for phenotyping motility in other animal models. Hence, there is an ongoing need for robust algorithms that can automatically analyze and classify motility phenotypes quantitatively. To this end, we have developed a fully-automated approach to characterize C. elegans’ phenotypes that does not require the definition of nematode-specific features. Rather, we make use of the popular computer vision Scale-Invariant Feature Transform (SIFT) from which we construct histograms of commonly-observed SIFT features to represent nematode motility. We first evaluated our method on a synthetic dataset simulating a range of nematode crawling gaits. Next, we evaluated our algorithm on two distinct datasets of crawling C. elegans with mutants affecting neuromuscular structure and function. Not only is our algorithm able to detect differences between strains, results capture similarities in locomotory phenotypes that lead to clustering that is consistent with expectations based on genetic relationships. Our proposed approach generalizes directly and should be applicable to other animal models. Such applicability holds promise for computational ethology as more groups collect high-resolution image data of animal behavior. PMID:25816290
Automated analysis of art object surfaces using time-averaged digital speckle pattern interferometry

NASA Astrophysics Data System (ADS)

Lukomski, Michal; Krzemien, Leszek

2013-05-01

Technical development and practical evaluation of a laboratory built, out-of-plane digital speckle pattern interferometer (DSPI) are reported. The instrument was used for non-invasive, non-contact detection and characterization of early-stage damage, like fracturing and layer separation, of painted objects of art. A fully automated algorithm was developed for recording and analysis of vibrating objects utilizing continuous-wave laser light. The algorithm uses direct, numerical fitting or Hilbert transformation for an independent, quantitative evaluation of the Bessel function at every point of the investigated surface. The procedure does not require phase modulation and thus can be implemented within any, even the simplest, DSPI apparatus. The proposed deformation analysis is fast and computationally inexpensive. Diagnosis of physical state of the surface of a panel painting attributed to Nicolaus Haberschrack (a late-mediaeval painter active in Krakow) from the collection of the National Museum in Krakow is presented as an example of an in situ application of the developed methodology. It has allowed the effectiveness of the deformation analysis to be evaluated for the surface of a real painting (heterogeneous colour and texture) in a conservation studio where vibration level was considerably higher than in the laboratory. It has been established that the methodology, which offers automatic analysis of the interferometric fringe patterns, has a considerable potential to facilitate and render more precise the condition surveys of works of art.
Fast targeted analysis of 132 acidic and neutral drugs and poisons in whole blood using LC-MS/MS.

PubMed

Di Rago, Matthew; Saar, Eva; Rodda, Luke N; Turfus, Sophie; Kotsos, Alex; Gerostamoulos, Dimitri; Drummer, Olaf H

2014-10-01

The aim of this study was to develop an LC-MS/MS based screening technique that covers a broad range of acidic and neutral drugs and poisons by combining a small sample volume and efficient extraction technique with simple automated data processing. After protein precipitation of 100μL of whole blood, 132 common acidic and neutral drugs and poisons including non-steroidal anti-inflammatory drugs, barbiturates, anticonvulsants, antidiabetics, muscle relaxants, diuretics and superwarfarin rodenticides (47 quantitated, 85 reported as detected) were separated using a Shimadzu Prominence HPLC system with a C18 separation column (Kinetex XB-C18, 4.6mm×150mm, 5μm), using gradient elution with a mobile phase of 25mM ammonium acetate buffer (pH 7.5)/acetonitrile. The drugs were detected using an ABSciex(®) API 2000 LC-MS/MS system (ESI+ and -, MRM mode, two transitions per analyte). The method was fully validated in accordance with international guidelines. Quantification data obtained using one-point calibration compared favorably to that using multiple calibrants. The presented LC-MS/MS assay has proven to be applicable for determination of the analytes in blood. The fast and reliable extraction method combined with automated processing gives the opportunity for high throughput and fast turnaround times for forensic and clinical toxicology. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Breast density characterization using texton distributions.

PubMed

Petroudi, Styliani; Brady, Michael

2011-01-01

Breast density has been shown to be one of the most significant risks for developing breast cancer, with women with dense breasts at four to six times higher risk. The Breast Imaging Reporting and Data System (BI-RADS) has a four class classification scheme that describes the different breast densities. However, there is great inter and intra observer variability among clinicians in reporting a mammogram's density class. This work presents a novel texture classification method and its application for the development of a completely automated breast density classification system. The new method represents the mammogram using textons, which can be thought of as the building blocks of texture under the operational definition of Leung and Malik as clustered filter responses. The new proposed method characterizes the mammographic appearance of the different density patterns by evaluating the texton spatial dependence matrix (TDSM) in the breast region's corresponding texton map. The TSDM is a texture model that captures both statistical and structural texture characteristics. The normalized TSDM matrices are evaluated for mammograms from the different density classes and corresponding texture models are established. Classification is achieved using a chi-square distance measure. The fully automated TSDM breast density classification method is quantitatively evaluated on mammograms from all density classes from the Oxford Mammogram Database. The incorporation of texton spatial dependencies allows for classification accuracy reaching over 82%. The breast density classification accuracy is better using texton TSDM compared to simple texton histograms.
Systems Operations Studies for Automated Guideway Transit Systems : Quantitative Analysis of Alternative AGT Operational Control Strategies

DOT National Transportation Integrated Search

1981-10-01

The objectives of the Systems Operation Studies (SOS) for automated guideway transit (AGT) systems are to develop models for the analysis of system operations, to evaluate performance and cost, and to establish guidelines for the design and operation...
Clinical evaluation of the COBAS Ampliprep/COBAS TaqMan for HCV RNA quantitation in comparison with the branched-DNA assay.

PubMed

Pittaluga, Fabrizia; Allice, Tiziano; Abate, Maria Lorena; Ciancio, Alessia; Cerutti, Francesco; Varetto, Silvia; Colucci, Giuseppe; Smedile, Antonina; Ghisetti, Valeria

2008-02-01

Diagnosis and monitoring of HCV infection relies on sensitive and accurate HCV RNA detection and quantitation. The performance of the COBAS AmpliPrep/COBAS TaqMan 48 (CAP/CTM) (Roche, Branchburg, NJ), a fully automated, real-time PCR HCV RNA quantitative test was assessed and compared with the branched-DNA (bDNA) assay. Clinical evaluation on 576 specimens obtained from patients with chronic hepatitis C showed a good correlation (r = 0.893) between the two test, but the CAP/CTM scored higher HCV RNA titers than the bDNA across all viral genotypes. The mean bDNA versus CAP/CTM log10 IU/ml differences were -0.49, -0.4, -0.54, -0.26 for genotype 1a, 1b, 2a/2c, 3a, and 4, respectively. These differences reached statistical significance for genotypes 1b, 2a/c, and 3a. The ability of the CAP/CTM to monitor patients undergoing antiviral therapy and correctly identify the weeks 4 and 12 rapid and early virological responses was confirmed. The broader dynamic range of the CAP/CTM compared with the bDNA allowed for a better definition of viral kinetics. In conclusion, the CAP/CTM appears as a reliable and user-friendly assay to monitor HCV viremia during treatment of patients with chronic hepatitis. Its high sensitivity and wide dynamic range may help a better definition of viral load changes during antiviral therapy. (Copyright) 2007 Wiley-Liss, Inc.
A method for normalizing pathology images to improve feature extraction for quantitative pathology.

PubMed

Tam, Allison; Barker, Jocelyn; Rubin, Daniel

2016-01-01

With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology images by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. ICHE may be a useful preprocessing step a digital pathology image processing pipeline.
Ten years of R&D and full automation in molecular diagnosis.

PubMed

Greub, Gilbert; Sahli, Roland; Brouillet, René; Jaton, Katia

2016-01-01

A 10-year experience of our automated molecular diagnostic platform that carries out 91 different real-time PCR is described. Progresses and future perspectives in molecular diagnostic microbiology are reviewed: why automation is important; how our platform was implemented; how homemade PCRs were developed; the advantages/disadvantages of homemade PCRs, including the critical aspects of troubleshooting and the need to further reduce the turnaround time for specific samples, at least for defined clinical settings such as emergencies. The future of molecular diagnosis depends on automation, and in a novel perspective, it is time now to fully acknowledge the true contribution of molecular diagnostic and to reconsider the indication for PCR, by also using these tests as first-line assays.
Automated homogeneous liposome immunoassay systems for anticonvulsant drugs.

PubMed

Kubotsu, K; Goto, S; Fujita, M; Tuchiya, H; Kida, M; Takano, S; Matsuura, S; Sakurabayashi, I

1992-06-01

We developed automated homogeneous immunoassays, based on immunolysis of liposomes, for measuring phenytoin, phenobarbital, and carbamazepine from serum. Liposome lysis was detected spectrophotometrically from entrapped glucose-6-phosphate dehydrogenase activity. The procedure was fully automated on a routine automated clinical analyzer. Within-run, between-run, dilution, and recovery tests showed good accuracies and reproducibilities. Bilirubin, hemoglobin, triglycerides, and Intrafat did not affect assay results. The results obtained by liposome immunoassays for phenytoin, phenobarbital, and carbamazepine correlated well with those obtained by enzyme-multiplied immunoassay (Syva EMIT) kits (r = 0.995, 0.986, and 0.988, respectively) and fluorescence polarization immunoassay (Abbott TDx) kits (r = 0.990, 0.991, and 0.975, respectively). The proposed method should be useful for monitoring anticonvulsant drug concentrations in blood.
Fully automated multifunctional ultrahigh pressure liquid chromatography system for advanced proteome analyses

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

Lee, Jung Hwa; Hyung, Seok-Won; Mun, Dong-Gi

2012-08-03

A multi-functional liquid chromatography system that performs 1-dimensional, 2-dimensional (strong cation exchange/reverse phase liquid chromatography, or SCX/RPLC) separations, and online phosphopeptides enrichment using a single binary nano-flow pump has been developed. With a simple operation of a function selection valve, which is equipped with a SCX column and a TiO2 (titanium dioxide) column, a fully automated selection of three different experiment modes was achieved. Because the current system uses essentially the same solvent flow paths, the same trap column, and the same separation column for reverse-phase separation of 1D, 2D, and online phosphopeptides enrichment experiments, the elution time information obtainedmore » from these experiments is in excellent agreement, which facilitates correlating peptide information from different experiments.« less
3D model assisted fully automated scanning laser Doppler vibrometer measurements

NASA Astrophysics Data System (ADS)

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
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.

PubMed

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.
Space Applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 1: Executive Summary

NASA Technical Reports Server (NTRS)

Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

1982-01-01

Potential applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities, and to their related ground support functions are explored. The specific tasks which will be required by future space projects are identified. ARAMIS options which are candidates for those space project tasks and the relative merits of these options are defined and evaluated. Promising applications of ARAMIS and specific areas for further research are identified. The ARAMIS options defined and researched by the study group span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.
A Novel ImageJ Macro for Automated Cell Death Quantitation in the Retina

PubMed Central

Maidana, Daniel E.; Tsoka, Pavlina; Tian, Bo; Dib, Bernard; Matsumoto, Hidetaka; Kataoka, Keiko; Lin, Haijiang; Miller, Joan W.; Vavvas, Demetrios G.

2015-01-01

Purpose TUNEL assay is widely used to evaluate cell death. Quantification of TUNEL-positive (TUNEL+) cells in tissue sections is usually performed manually, ideally by two masked observers. This process is time consuming, prone to measurement errors, and not entirely reproducible. In this paper, we describe an automated quantification approach to address these difficulties. Methods We developed an ImageJ macro to quantitate cell death by TUNEL assay in retinal cross-section images. The script was coded using IJ1 programming language. To validate this tool, we selected a dataset of TUNEL assay digital images, calculated layer area and cell count manually (done by two observers), and compared measurements between observers and macro results. Results The automated macro segmented outer nuclear layer (ONL) and inner nuclear layer (INL) successfully. Automated TUNEL+ cell counts were in-between counts of inexperienced and experienced observers. The intraobserver coefficient of variation (COV) ranged from 13.09% to 25.20%. The COV between both observers was 51.11 ± 25.83% for the ONL and 56.07 ± 24.03% for the INL. Comparing observers' results with macro results, COV was 23.37 ± 15.97% for the ONL and 23.44 ± 18.56% for the INL. Conclusions We developed and validated an ImageJ macro that can be used as an accurate and precise quantitative tool for retina researchers to achieve repeatable, unbiased, fast, and accurate cell death quantitation. We believe that this standardized measurement tool could be advantageous to compare results across different research groups, as it is freely available as open source. PMID:26469755
Automated tumor analysis for molecular profiling in lung cancer

PubMed Central

Boyd, Clinton; James, Jacqueline A.; Loughrey, Maurice B.; Hougton, Joseph P.; Boyle, David P.; Kelly, Paul; Maxwell, Perry; McCleary, David; Diamond, James; McArt, Darragh G.; Tunstall, Jonathon; Bankhead, Peter; Salto-Tellez, Manuel

2015-01-01

The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics. PMID:26317646
Quantitative analysis of cardiovascular MR images.

PubMed

van der Geest, R J; de Roos, A; van der Wall, E E; Reiber, J H

1997-06-01

The diagnosis of cardiovascular disease requires the precise assessment of both morphology and function. Nearly all aspects of cardiovascular function and flow can be quantified nowadays with fast magnetic resonance (MR) imaging techniques. Conventional and breath-hold cine MR imaging allow the precise and highly reproducible assessment of global and regional left ventricular function. During the same examination, velocity encoded cine (VEC) MR imaging provides measurements of blood flow in the heart and great vessels. Quantitative image analysis often still relies on manual tracing of contours in the images. Reliable automated or semi-automated image analysis software would be very helpful to overcome the limitations associated with the manual and tedious processing of the images. Recent progress in MR imaging of the coronary arteries and myocardial perfusion imaging with contrast media, along with the further development of faster imaging sequences, suggest that MR imaging could evolve into a single technique ('one stop shop') for the evaluation of many aspects of heart disease. As a result, it is very likely that the need for automated image segmentation and analysis software algorithms will further increase. In this paper the developments directed towards the automated image analysis and semi-automated contour detection for cardiovascular MR imaging are presented.
Automation of laboratory testing for infectious diseases using the polymerase chain reaction-- our past, our present, our future.

PubMed

Jungkind, D

2001-01-01

While it is an extremely powerful and versatile assay method, polymerase chain reaction (PCR) can be a labor-intensive process. Since the advent of commercial test kits from Roche and the semi-automated microwell Amplicor system, PCR has become an increasingly useful and widespread clinical tool. However, more widespread acceptance of molecular testing will depend upon automation that allows molecular assays to enter the routine clinical laboratory. The forces driving the need for automated PCR are the requirements for diagnosis and treatment of chronic viral diseases, economic pressures to develop more automated and less expensive test procedures similar to those in the clinical chemistry laboratories, and a shortage in many areas of qualified laboratory personnel trained in the types of manual procedures used in past decades. The automated Roche COBAS AMPLICOR system has automated the amplification and detection process. Specimen preparation remains the most labor-intensive part of the PCR testing process, accounting for the majority of the hands-on-time in most of the assays. A new automated specimen preparation system, the COBAS AmpliPrep, was evaluated. The system automatically releases the target nucleic acid, captures the target with specific oligonucleotide probes, which become attached to magnetic beads via a biotin-streptavidin binding reaction. Once attached to the beads, the target is purified and concentrated automatically. Results of 298 qualitative and 57 quantitative samples representing a wide range of virus concentrations analyzed after the COBAS AmpliPrep and manual specimen preparation methods, showed that there was no significant difference in qualitative or quantitative hepatitis C virus (HCV) assay performance, respectively. The AmpliPrep instrument decreased the time required to prepare serum or plasma samples for HCV PCR to under 1 min per sample. This was a decrease of 76% compared to the manual specimen preparation method. Systems that can analyze more samples with higher throughput and that can answer more questions about the nature of the microbes that we can presently only detect and quantitate will be needed in the future.
Rapid Protein Global Fold Determination Using Ultrasparse Sampling, High-Dynamic Range Artifact Suppression, and Time-Shared NOESY

PubMed Central

Coggins, Brian E.; Werner-Allen, Jonathan W.; Yan, Anthony; Zhou, Pei

2012-01-01

In structural studies of large proteins by NMR, global fold determination plays an increasingly important role in providing a first look at a target’s topology and reducing assignment ambiguity in NOESY spectra of fully-protonated samples. In this work, we demonstrate the use of ultrasparse sampling, a new data processing algorithm, and a 4-D time-shared NOESY experiment (1) to collect all NOEs in 2H/13C/15N-labeled protein samples with selectively-protonated amide and ILV methyl groups at high resolution in only four days, and (2) to calculate global folds from this data using fully automated resonance assignment. The new algorithm, SCRUB, incorporates the CLEAN method for iterative artifact removal, but applies an additional level of iteration, permitting real signals to be distinguished from noise and allowing nearly all artifacts generated by real signals to be eliminated. In simulations with 1.2% of the data required by Nyquist sampling, SCRUB achieves a dynamic range over 10000:1 (250× better artifact suppression than CLEAN) and completely quantitative reproduction of signal intensities, volumes, and lineshapes. Applied to 4-D time-shared NOESY data, SCRUB processing dramatically reduces aliasing noise from strong diagonal signals, enabling the identification of weak NOE crosspeaks with intensities 100× less than diagonal signals. Nearly all of the expected peaks for interproton distances under 5 Å were observed. The practical benefit of this method is demonstrated with structure calculations for 23 kDa and 29 kDa test proteins using the automated assignment protocol of CYANA, in which unassigned 4-D time-shared NOESY peak lists produce accurate and well-converged global fold ensembles, whereas 3-D peak lists either fail to converge or produce significantly less accurate folds. The approach presented here succeeds with an order of magnitude less sampling than required by alternative methods for processing sparse 4-D data. PMID:22946863
Slide Set: Reproducible image analysis and batch processing with ImageJ.

PubMed

Nanes, Benjamin A

2015-11-01

Most imaging studies in the biological sciences rely on analyses that are relatively simple. However, manual repetition of analysis tasks across multiple regions in many images can complicate even the simplest analysis, making record keeping difficult, increasing the potential for error, and limiting reproducibility. While fully automated solutions are necessary for very large data sets, they are sometimes impractical for the small- and medium-sized data sets common in biology. Here we present the Slide Set plugin for ImageJ, which provides a framework for reproducible image analysis and batch processing. Slide Set organizes data into tables, associating image files with regions of interest and other relevant information. Analysis commands are automatically repeated over each image in the data set, and multiple commands can be chained together for more complex analysis tasks. All analysis parameters are saved, ensuring transparency and reproducibility. Slide Set includes a variety of built-in analysis commands and can be easily extended to automate other ImageJ plugins, reducing the manual repetition of image analysis without the set-up effort or programming expertise required for a fully automated solution.
In-Line Detection and Measurement of Molecular Contamination in Semiconductor Process Solutions

NASA Astrophysics Data System (ADS)

Wang, Jason; West, Michael; Han, Ye; McDonald, Robert C.; Yang, Wenjing; Ormond, Bob; Saini, Harmesh

2005-09-01

This paper discusses a fully automated metrology tool for detection and quantitative measurement of contamination, including cationic, anionic, metallic, organic, and molecular species present in semiconductor process solutions. The instrument is based on an electrospray ionization time-of-flight mass spectrometer (ESI-TOF/MS) platform. The tool can be used in diagnostic or analytical modes to understand process problems in addition to enabling routine metrology functions. Metrology functions include in-line contamination measurement with near real-time trend analysis. This paper discusses representative organic and molecular contamination measurement results in production process problem solving efforts. The examples include the analysis and identification of organic compounds in SC-1 pre-gate clean solution; urea, NMP (N-Methyl-2-pyrrolidone) and phosphoric acid contamination in UPW; and plasticizer and an organic sulfur-containing compound found in isopropyl alcohol (IPA). It is expected that these unique analytical and metrology capabilities will improve the understanding of the effect of organic and molecular contamination on device performance and yield. This will permit the development of quantitative correlations between contamination levels and process degradation. It is also expected that the ability to perform routine process chemistry metrology will lead to corresponding improvements in manufacturing process control and yield, the ability to avoid excursions and will improve the overall cost effectiveness of the semiconductor manufacturing process.
Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour.

PubMed

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E; Kayser, Manfred

2017-02-27

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing.
Determination of caffeine, theobromine and theophylline in Mate beer and Mate soft drinks by high-performance thin-layer chromatography.

PubMed

Oellig, Claudia; Schunck, Jacob; Schwack, Wolfgang

2018-01-19

Mate beer and Mate soft drinks are beverages produced from the dried leaves of Ilex paraguariensis (Yerba Mate). In Yerba Mate, the xanthine derivatives caffeine, theobromine and theophylline, also known as methylxanthines, are important active components. The presented method for the determination of caffeine, theobromine and theophylline in Mate beer and Mate soft drinks by high-performance thin-layer chromatography with ultraviolet detection (HPTLC-UV) offers a fully automated and sensitive determination of the three methylxanthines. Filtration of the samples was followed by degassing, dilution with acetonitrile in the case of Mate beers for protein precipitation, and centrifugation before the extracts were analyzed by HPTLC-UV on LiChrospher silica gel plates with fluorescence indicator and acetone/toluene/chloroform (4:3:3, v/v/v) as the mobile phase. For quantitation, the absorbance was scanned at 274nm. Limits of detection and quantitation were 1 and 4ng/zone, respectively, for caffeine, theobromine and theophylline. With recoveries close to 100% and low standard deviations reliable results were guaranteed. Experimental Mate beers as well as Mate beers and Mate soft drinks from the market were analyzed for their concentrations of methylxanthines. Copyright © 2017 Elsevier B.V. All rights reserved.
Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour

PubMed Central

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H.; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R.; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E.; Kayser, Manfred

2017-01-01

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing. PMID:28240252

Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

PubMed

Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

2014-01-01

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.
Automated Test Requirement Document Generation

DTIC Science & Technology

1987-11-01

DIAGNOSTICS BASED ON THE PRINCIPLES OF ARTIFICIAL INTELIGENCE ", 1984 International Test Conference, 01Oct84, (A3, 3, Cs D3, E2, G2, H2, 13, J6, K) 425...j0O GLOSSARY OF ACRONYMS 0 ABBREVIATION DEFINITION AFSATCOM Air Force Satellite Communication Al Artificial Intelligence ASIC Application Specific...In-Test Equipment (BITE) and AI ( Artificial Intelligence) - Expert Systems - need to be fully applied before a completely automated process can be
An Intelligent Automation Platform for Rapid Bioprocess Design.

PubMed

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

PubMed

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

PubMed

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 (p<0.01), and BMD from 0.583 (±0.068) g/cm 2 to 0.566 (±0.074) g/cm 2 (p<0.01). A significant positive association was observed between ΔJSW and ΔBMD over 1 year (p<0.0001). On an individual joint level, JSWs of undamaged (JSN=0) joints were wider than damaged (JSN>0) 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.
ICSH recommendations for assessing automated high-performance liquid chromatography and capillary electrophoresis equipment for the quantitation of HbA2.

PubMed

Stephens, A D; Colah, R; Fucharoen, S; Hoyer, J; Keren, D; McFarlane, A; Perrett, D; Wild, B J

2015-10-01

Automated high performance liquid chromatography and Capillary electrophoresis are used to quantitate the proportion of Hemoglobin A2 (HbA2 ) in blood samples order to enable screening and diagnosis of carriers of β-thalassemia. Since there is only a very small difference in HbA2 levels between people who are carriers and people who are not carriers such analyses need to be both precise and accurate. This paper examines the different parameters of such equipment and discusses how they should be assessed. © 2015 John Wiley & Sons Ltd.
Automation of dimethylation after guanidination labeling chemistry and its compatibility with common buffers and surfactants for mass spectrometry-based shotgun quantitative proteome analysis.

PubMed

Lo, Andy; Tang, Yanan; Chen, Lu; Li, Liang

2013-07-25

Isotope labeling liquid chromatography-mass spectrometry (LC-MS) is a major analytical platform for quantitative proteome analysis. Incorporation of isotopes used to distinguish samples plays a critical role in the success of this strategy. In this work, we optimized and automated a chemical derivatization protocol (dimethylation after guanidination, 2MEGA) to increase the labeling reproducibility and reduce human intervention. We also evaluated the reagent compatibility of this protocol to handle biological samples in different types of buffers and surfactants. A commercially available liquid handler was used for reagent dispensation to minimize analyst intervention and at least twenty protein digest samples could be prepared in a single run. Different front-end sample preparation methods for protein solubilization (SDS, urea, Rapigest™, and ProteaseMAX™) and two commercially available cell lysis buffers were evaluated for compatibility with the automated protocol. It was found that better than 94% desired labeling could be obtained in all conditions studied except urea, where the rate was reduced to about 92% due to carbamylation on the peptide amines. This work illustrates the automated 2MEGA labeling process can be used to handle a wide range of protein samples containing various reagents that are often encountered in protein sample preparation for quantitative proteome analysis. Copyright © 2013 Elsevier B.V. All rights reserved.
The effect of JPEG compression on automated detection of microaneurysms in retinal images

NASA Astrophysics Data System (ADS)

Cree, M. J.; Jelinek, H. F.

2008-02-01

As JPEG compression at source is ubiquitous in retinal imaging, and the block artefacts introduced are known to be of similar size to microaneurysms (an important indicator of diabetic retinopathy) it is prudent to evaluate the effect of JPEG compression on automated detection of retinal pathology. Retinal images were acquired at high quality and then compressed to various lower qualities. An automated microaneurysm detector was run on the retinal images of various qualities of JPEG compression and the ability to predict the presence of diabetic retinopathy based on the detected presence of microaneurysms was evaluated with receiver operating characteristic (ROC) methodology. The negative effect of JPEG compression on automated detection was observed even at levels of compression sometimes used in retinal eye-screening programmes and these may have important clinical implications for deciding on acceptable levels of compression for a fully automated eye-screening programme.
Immunochemical faecal occult blood test for colorectal cancer screening: a systematic review.

PubMed

Syful Azlie, M F; Hassan, M R; Junainah, S; Rugayah, B

2015-02-01

A systematic review on the effectiveness and costeffectiveness of Immunochemical faecal occult IFOBT for CRC screening was carried out. A total of 450 relevant titles were identified, 41 abstracts were screened and 18 articles were included in the results. There was fair level of retrievable evidence to suggest that the sensitivity and specificity of IFOBT varies with the cut-off point of haemoglobin, whereas the diagnostic accuracy performance was influenced by high temperature and haemoglobin stability. A screening programme using IFOBT can be effective for prevention of advanced CRC and reduced mortality. There was also evidence to suggest that IFOBT is cost-effective in comparison with no screening, whereby a two-day faecal collection method was found to be costeffective as a means of screening for CRC. Based on the review, quantitative IFOBT method can be used in Malaysia as a screening test for CRC. The use of fully automated IFOBT assay would be highly desirable.
White matter lesion extension to automatic brain tissue segmentation on MRI.

PubMed

de Boer, Renske; Vrooman, Henri A; van der Lijn, Fedde; Vernooij, Meike W; Ikram, M Arfan; van der Lugt, Aad; Breteler, Monique M B; Niessen, Wiro J

2009-05-01

A fully automated brain tissue segmentation method is optimized and extended with white matter lesion segmentation. Cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM) are segmented by an atlas-based k-nearest neighbor classifier on multi-modal magnetic resonance imaging data. This classifier is trained by registering brain atlases to the subject. The resulting GM segmentation is used to automatically find a white matter lesion (WML) threshold in a fluid-attenuated inversion recovery scan. False positive lesions are removed by ensuring that the lesions are within the white matter. The method was visually validated on a set of 209 subjects. No segmentation errors were found in 98% of the brain tissue segmentations and 97% of the WML segmentations. A quantitative evaluation using manual segmentations was performed on a subset of 6 subjects for CSF, GM and WM segmentation and an additional 14 for the WML segmentations. The results indicated that the automatic segmentation accuracy is close to the interobserver variability of manual segmentations.
Addressing multi-label imbalance problem of surgical tool detection using CNN.

PubMed

Sahu, Manish; Mukhopadhyay, Anirban; Szengel, Angelika; Zachow, Stefan

2017-06-01

A fully automated surgical tool detection framework is proposed for endoscopic video streams. State-of-the-art surgical tool detection methods rely on supervised one-vs-all or multi-class classification techniques, completely ignoring the co-occurrence relationship of the tools and the associated class imbalance. In this paper, we formulate tool detection as a multi-label classification task where tool co-occurrences are treated as separate classes. In addition, imbalance on tool co-occurrences is analyzed and stratification techniques are employed to address the imbalance during convolutional neural network (CNN) training. Moreover, temporal smoothing is introduced as an online post-processing step to enhance runtime prediction. Quantitative analysis is performed on the M2CAI16 tool detection dataset to highlight the importance of stratification, temporal smoothing and the overall framework for tool detection. The analysis on tool imbalance, backed by the empirical results, indicates the need and superiority of the proposed framework over state-of-the-art techniques.
Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography.

PubMed

Yong, Yan Ling; Tan, Li Kuo; McLaughlin, Robert A; Chee, Kok Han; Liew, Yih Miin

2017-12-01

Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
Evaluation of the Aptima HIV-1 Quant Dx Assay for HIV-1 RNA Quantitation in Different Biological Specimen Types

PubMed Central

Yek, Christina; Massanella, Marta; Peling, Tashi; Lednovich, Kristen; Nair, Sangeetha V.; Worlock, Andrew; Vargas, Milenka; Gianella, Sara; Ellis, Ronald J.; Strain, Matthew C.; Busch, Michael P.; Nugent, C. Thomas

2017-01-01

ABSTRACT The search for a cure for HIV infection has highlighted the need for increasingly sensitive and precise assays to measure viral burden in various tissues and body fluids. We describe the application of a standardized assay for HIV-1 RNA in multiple specimen types. The fully automated Aptima HIV-1 Quant Dx assay (Aptima assay) is FDA cleared for blood plasma HIV-1 RNA quantitation. In this study, the Aptima assay was applied for the quantitation of HIV RNA in peripheral blood mononuclear cells (PBMCs; n = 72), seminal plasma (n = 20), cerebrospinal fluid (CSF; n = 36), dried blood spots (DBS; n = 104), and dried plasma spots (DPS; n = 104). The Aptima assay was equivalent to or better than commercial assays or validated in-house assays for the quantitation of HIV RNA in CSF and seminal plasma. For PBMC specimens, the sensitivity of the Aptima assay in the detection of HIV RNA decayed as background uninfected PBMC counts increased; proteinase K treatment demonstrated some benefit in restoring signal at higher levels of background PBMCs. Finally, the Aptima assay yielded 100% detection rates of DBS in participants with plasma HIV RNA levels of ≥35 copies/ml and 100% detection rates of DPS in participants with plasma HIV RNA levels of ≥394 copies/ml. The Aptima assay can be applied to a variety of specimens from HIV-infected subjects to measure HIV RNA for studies of viral persistence and cure strategies. It can also detect HIV in dried blood and plasma specimens, which may be of benefit in resource-limited settings. PMID:28592548
Quantitative Imaging with a Mobile Phone Microscope

PubMed Central

Skandarajah, Arunan; Reber, Clay D.; Switz, Neil A.; Fletcher, Daniel A.

2014-01-01

Use of optical imaging for medical and scientific applications requires accurate quantification of features such as object size, color, and brightness. High pixel density cameras available on modern mobile phones have made photography simple and convenient for consumer applications; however, the camera hardware and software that enables this simplicity can present a barrier to accurate quantification of image data. This issue is exacerbated by automated settings, proprietary image processing algorithms, rapid phone evolution, and the diversity of manufacturers. If mobile phone cameras are to live up to their potential to increase access to healthcare in low-resource settings, limitations of mobile phone–based imaging must be fully understood and addressed with procedures that minimize their effects on image quantification. Here we focus on microscopic optical imaging using a custom mobile phone microscope that is compatible with phones from multiple manufacturers. We demonstrate that quantitative microscopy with micron-scale spatial resolution can be carried out with multiple phones and that image linearity, distortion, and color can be corrected as needed. Using all versions of the iPhone and a selection of Android phones released between 2007 and 2012, we show that phones with greater than 5 MP are capable of nearly diffraction-limited resolution over a broad range of magnifications, including those relevant for single cell imaging. We find that automatic focus, exposure, and color gain standard on mobile phones can degrade image resolution and reduce accuracy of color capture if uncorrected, and we devise procedures to avoid these barriers to quantitative imaging. By accommodating the differences between mobile phone cameras and the scientific cameras, mobile phone microscopes can be reliably used to increase access to quantitative imaging for a variety of medical and scientific applications. PMID:24824072
The NIST Quantitative Infrared Database

PubMed Central

Chu, P. M.; Guenther, F. R.; Rhoderick, G. C.; Lafferty, W. J.

1999-01-01

With the recent developments in Fourier transform infrared (FTIR) spectrometers it is becoming more feasible to place these instruments in field environments. As a result, there has been enormous increase in the use of FTIR techniques for a variety of qualitative and quantitative chemical measurements. These methods offer the possibility of fully automated real-time quantitation of many analytes; therefore FTIR has great potential as an analytical tool. Recently, the U.S. Environmental Protection Agency (U.S.EPA) has developed protocol methods for emissions monitoring using both extractive and open-path FTIR measurements. Depending upon the analyte, the experimental conditions and the analyte matrix, approximately 100 of the hazardous air pollutants (HAPs) listed in the 1990 U.S.EPA Clean Air Act amendment (CAAA) can be measured. The National Institute of Standards and Technology (NIST) has initiated a program to provide quality-assured infrared absorption coefficient data based on NIST prepared primary gas standards. Currently, absorption coefficient data has been acquired for approximately 20 of the HAPs. For each compound, the absorption coefficient spectrum was calculated using nine transmittance spectra at 0.12 cm−1 resolution and the Beer’s law relationship. The uncertainties in the absorption coefficient data were estimated from the linear regressions of the transmittance data and considerations of other error sources such as the nonlinear detector response. For absorption coefficient values greater than 1 × 10−4 μmol/mol)−1 m−1 the average relative expanded uncertainty is 2.2 %. This quantitative infrared database is currently an ongoing project at NIST. Additional spectra will be added to the database as they are acquired. Our current plans include continued data acquisition of the compounds listed in the CAAA, as well as the compounds that contribute to global warming and ozone depletion.
Varying Levels of Automation on UAS Operator Responses to Traffic Resolution Advisories in Civil Airspace

NASA Technical Reports Server (NTRS)

Kenny, Caitlin; Fern, Lisa

2012-01-01

Continuing demand for the use of Unmanned Aircraft Systems (UAS) has put increasing pressure on operations in civil airspace. The need to fly UAS in the National Airspace System (NAS) in order to perform missions vital to national security and defense, emergency management, and science is increasing at a rapid pace. In order to ensure safe operations in the NAS, operators of unmanned aircraft, like those of manned aircraft, may be required to maintain separation assurance and avoid loss of separation with other aircraft while performing their mission tasks. This experiment investigated the effects of varying levels of automation on UAS operator performance and workload while responding to conflict resolution instructions provided by the Tactical Collision Avoidance System II (TCAS II) during a UAS mission in high-density airspace. The purpose of this study was not to investigate the safety of using TCAS II on UAS, but rather to examine the effect of automation on the ability of operators to respond to traffic collision alerts. Six licensed pilots were recruited to act as UAS operators for this study. Operators were instructed to follow a specified mission flight path, while maintaining radio contact with Air Traffic Control and responding to TCAS II resolution advisories. Operators flew four, 45 minute, experimental missions with four different levels of automation: Manual, Knobs, Management by Exception, and Fully Automated. All missions included TCAS II Resolution Advisories (RAs) that required operator attention and rerouting. Operator compliance and reaction time to RAs was measured, and post-run NASA-TLX ratings were collected to measure workload. Results showed significantly higher compliance rates, faster responses to TCAS II alerts, as well as less preemptive operator actions when higher levels of automation are implemented. Physical and Temporal ratings of workload were significantly higher in the Manual condition than in the Management by Exception and Fully Automated conditions.
Using integrated environmental modeling to automate a process-based Quantitative Microbial Risk Assessment

EPA Science Inventory

Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, an...
Using Integrated Environmental Modeling to Automate a Process-Based Quantitative Microbial Risk Assessment (presentation)

EPA Science Inventory

Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, and...
Design and Prototype of an Automated Column-Switching HPLC System for Radiometabolite Analysis.

PubMed

Vasdev, Neil; Collier, Thomas Lee

2016-08-17

Column-switching high performance liquid chromatography (HPLC) is extensively used for the critical analysis of radiolabeled ligands and their metabolites in plasma. However, the lack of streamlined apparatus and consequently varying protocols remain as a challenge among positron emission tomography laboratories. We report here the prototype apparatus and implementation of a fully automated and simplified column-switching procedure to allow for the easy and automated determination of radioligands and their metabolites in up to 5 mL of plasma. The system has been used with conventional UV and coincidence radiation detectors, as well as with a single quadrupole mass spectrometer.
Performance of the New Aptima HCV Quant Dx Assay in Comparison to the Cobas TaqMan HCV2 Test for Use with the High Pure System in Detection and Quantification of Hepatitis C Virus RNA in Plasma or Serum.

PubMed

Schalasta, Gunnar; Speicher, Andrea; Börner, Anna; Enders, Martin

2016-04-01

Quantitating the level of hepatitis C virus (HCV) RNA is the standard of care for monitoring HCV-infected patients during treatment. The performances of commercially available assays differ for precision, limit of detection, and limit of quantitation (LOQ). Here, we compare the performance of the Hologic Aptima HCV Quant Dx assay (Aptima) to that of the Roche Cobas TaqMan HCV test, version 2.0, using the High Pure system (HPS/CTM), considered a reference assay since it has been used in trials defining clinical decision points in patient care. The assays' performance characteristics were assessed using HCV RNA reference panels and plasma/serum from chronically HCV-infected patients. The agreement between the assays for the 3 reference panels was good, with a difference in quantitation values of <0.5 log. High concordance was demonstrated between the assays for 245 clinical samples (kappa = 0.80; 95% confidence interval [CI], 0.720 to 0.881); however, Aptima detected and/or quantitated 20 samples that HPS/CTM did not detect, while Aptima did not detect 1 sample that was quantitated by HPS/CTM. For the 165 samples quantitated by both assays, the values were highly correlated (R= 0.98;P< 0.0001). The linearity of quantitation from concentrations of 1.4 to 6 log was excellent for both assays for all HCV genotypes (GT) tested (GT 1a, 1b, 2b, and 3a) (R(2)> 0.99). The assays had similar levels of total and intra-assay variability across all genotypes at concentrations from 1,000 to 25 IU/ml. Aptima had a greater analytical sensitivity, quantitating more than 50% of replicates at 25-IU/ml target. Aptima showed performance characteristics comparable to those of HPS/CTM and increased sensitivity, making it suitable for use as a clinical diagnostic tool on the fully automated Panther platform. Copyright © 2016 Schalasta et al.

Automation or De-automation

NASA Astrophysics Data System (ADS)

Gorlach, Igor; Wessel, Oliver

2008-09-01

In the global automotive industry, for decades, vehicle manufacturers have continually increased the level of automation of production systems in order to be competitive. However, there is a new trend to decrease the level of automation, especially in final car assembly, for reasons of economy and flexibility. In this research, the final car assembly lines at three production sites of Volkswagen are analysed in order to determine the best level of automation for each, in terms of manufacturing costs, productivity, quality and flexibility. The case study is based on the methodology proposed by the Fraunhofer Institute. The results of the analysis indicate that fully automated assembly systems are not necessarily the best option in terms of cost, productivity and quality combined, which is attributed to high complexity of final car assembly systems; some de-automation is therefore recommended. On the other hand, the analysis shows that low automation can result in poor product quality due to reasons related to plant location, such as inadequate workers' skills, motivation, etc. Hence, the automation strategy should be formulated on the basis of analysis of all relevant aspects of the manufacturing process, such as costs, quality, productivity and flexibility in relation to the local context. A more balanced combination of automated and manual assembly operations provides better utilisation of equipment, reduces production costs and improves throughput.
Automated Transition State Theory Calculations for High-Throughput Kinetics.

PubMed

Bhoorasingh, Pierre L; Slakman, Belinda L; Seyedzadeh Khanshan, Fariba; Cain, Jason Y; West, Richard H

2017-09-21

A scarcity of known chemical kinetic parameters leads to the use of many reaction rate estimates, which are not always sufficiently accurate, in the construction of detailed kinetic models. To reduce the reliance on these estimates and improve the accuracy of predictive kinetic models, we have developed a high-throughput, fully automated, reaction rate calculation method, AutoTST. The algorithm integrates automated saddle-point geometry search methods and a canonical transition state theory kinetics calculator. The automatically calculated reaction rates compare favorably to existing estimated rates. Comparison against high level theoretical calculations show the new automated method performs better than rate estimates when the estimate is made by a poor analogy. The method will improve by accounting for internal rotor contributions and by improving methods to determine molecular symmetry.
Retina Image Analysis and Ocular Telehealth: The Oak Ridge National Laboratory-Hamilton Eye Institute Case Study

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

Karnowski, Thomas Paul; Giancardo, Luca; Li, Yaquin

2013-01-01

Automated retina image analysis has reached a high level of maturity in recent years, and thus the question of how validation is performed in these systems is beginning to grow in importance. One application of retina image analysis is in telemedicine, where an automated system could enable the automated detection of diabetic retinopathy and other eye diseases as a low-cost method for broad-based screening. In this work we discuss our experiences in developing a telemedical network for retina image analysis, including our progression from a manual diagnosis network to a more fully automated one. We pay special attention to howmore » validations of our algorithm steps are performed, both using data from the telemedicine network and other public databases.« less
Direct to Public Peer Support and e-Therapy Program Versus Information to Aid Self-Management of Depression and Anxiety: Protocol for a Randomized Controlled Trial

PubMed Central

2017-01-01

Background Regardless of geography or income, effective help for depression and anxiety only reaches a small proportion of those who might benefit from it. The scale of the problem suggests a role for effective, safe, anonymized public health–driven Web-based services such as Big White Wall (BWW), which offer immediate peer support at low cost. Objective Using Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) methodology, the aim of this study was to determine the population reach, effectiveness, cost-effectiveness, and barriers and drivers to implementation of BWW compared with Web-based information compiled by UK’s National Health Service (NHS, NHS Choices Moodzone) in people with probable mild to moderate depression and anxiety disorder. Methods A pragmatic, parallel-group, single-blind randomized controlled trial (RCT) is being conducted using a fully automated trial website in which eligible participants are randomized to receive either 6 months access to BWW or signposted to the NHS Moodzone site. The recruitment of 2200 people to the study will be facilitated by a public health engagement campaign involving general marketing and social media, primary care clinical champions, health care staff, large employers, and third sector groups. People will refer themselves to the study and will be eligible if they are older than 16 years, have probable mild to moderate depression or anxiety disorders, and have access to the Internet. Results The primary outcome will be the Warwick-Edinburgh Mental Well-Being Scale at 6 weeks. We will also explore the reach, maintenance, cost-effectiveness, and barriers and drivers to implementation and possible mechanisms of actions using a range of qualitative and quantitative methods. Conclusions This will be the first fully digital trial of a direct to public online peer support program for common mental disorders. The potential advantages of adding this to current NHS mental health services and the challenges of designing a public health campaign and RCT of two digital interventions using a fully automated digital enrollment and data collection process are considered for people with depression and anxiety. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): 12673428; http://www.controlled-trials.com/ISRCTN12673428/12673428 (Archived by WebCite at http://www.webcitation.org/6uw6ZJk5a) PMID:29254909
Analysis of postural load during tasks related to milking cows-a case study.

PubMed

Groborz, Anna; Tokarski, Tomasz; Roman-Liu, Danuta

2011-01-01

The aim of this study was to analyse postural load during tasks related to milking cows of 2 farmers on 2 different farms (one with a manual milk transport system, the other with a fully automated milk transport system) as a case study. The participants were full-time farmers, they were both healthy and experienced in their job. The Ovako Working Posture Analyzing System (OWAS) was used to evaluate postural load and postural risk. Postural load was medium for the farmer on the farm with a manual milk transport system and high for the farmer working on the farm with a fully automated milk transport system. Thus, it can be concluded that a higher level of farm mechanization not always mean that the farmer's postural load is lower, but limitation of OWAS should be considered.
Fully automated laser ray tracing system to measure changes in the crystalline lens GRIN profile.

PubMed

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

PubMed Central

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

2017-01-01

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. PMID:29188093
A fully-automated neural network analysis of AFM force-distance curves for cancer tissue diagnosis

NASA Astrophysics Data System (ADS)

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.
Improved synthesis of [(18)F]FLETT via a fully automated vacuum distillation method for [(18)F]2-fluoroethyl azide purification.

PubMed

Ackermann, Uwe; Plougastel, Lucie; Goh, Yit Wooi; Yeoh, Shinn Dee; Scott, Andrew M

2014-12-01

The synthesis of [(18)F]2-fluoroethyl azide and its subsequent click reaction with 5-ethynyl-2'-deoxyuridine (EDU) to form [(18)F]FLETT was performed using an iPhase FlexLab module. The implementation of a vacuum distillation method afforded [(18)F]2-fluoroethyl azide in 87±5.3% radiochemical yield. The use of Cu(CH3CN)4PF6 and TBTA as catalyst enabled us to fully automate the [(18)F]FLETT synthesis without the need for the operator to enter the radiation field. [(18)F]FLETT was produced in higher overall yield (41.3±6.5%) and shorter synthesis time (67min) than with our previously reported manual method (32.5±2.5% in 130min). Copyright © 2014 Elsevier Ltd. All rights reserved.
A remote-controlled adaptive medchem lab: an innovative approach to enable drug discovery in the 21st Century.

PubMed

Godfrey, Alexander G; Masquelin, Thierry; Hemmerle, Horst

2013-09-01

This article describes our experiences in creating a fully integrated, globally accessible, automated chemical synthesis laboratory. The goal of the project was to establish a fully integrated automated synthesis solution that was initially focused on minimizing the burden of repetitive, routine, rules-based operations that characterize more established chemistry workflows. The architecture was crafted to allow for the expansion of synthetic capabilities while also providing for a flexible interface that permits the synthesis objective to be introduced and manipulated as needed under the judicious direction of a remote user in real-time. This innovative central synthesis suite is herein described along with some case studies to illustrate the impact such a system is having in expanding drug discovery capabilities. Copyright © 2013 Elsevier Ltd. All rights reserved.
Designing a fully automated multi-bioreactor plant for fast DoE optimization of pharmaceutical protein production.

PubMed

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

PubMed

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.
"BRAIN": Baruch Retrieval of Automated Information for Negotiations.

ERIC Educational Resources Information Center

Levenstein, Aaron, Ed.

1981-01-01

A data processing program that can be used as a research and collective bargaining aid for colleges is briefly described and the fields of the system are outlined. The system, known as BRAIN (Baruch Retrieval of Automated Information for Negotiations), is designed primarily as an instrument for quantitative and qualitative analysis. BRAIN consists…
Quantitative semi-automated analysis of morphogenesis with single-cell resolution in complex embryos.

PubMed

Giurumescu, Claudiu A; Kang, Sukryool; Planchon, Thomas A; Betzig, Eric; Bloomekatz, Joshua; Yelon, Deborah; Cosman, Pamela; Chisholm, Andrew D

2012-11-01

A quantitative understanding of tissue morphogenesis requires description of the movements of individual cells in space and over time. In transparent embryos, such as C. elegans, fluorescently labeled nuclei can be imaged in three-dimensional time-lapse (4D) movies and automatically tracked through early cleavage divisions up to ~350 nuclei. A similar analysis of later stages of C. elegans development has been challenging owing to the increased error rates of automated tracking of large numbers of densely packed nuclei. We present Nucleitracker4D, a freely available software solution for tracking nuclei in complex embryos that integrates automated tracking of nuclei in local searches with manual curation. Using these methods, we have been able to track >99% of all nuclei generated in the C. elegans embryo. Our analysis reveals that ventral enclosure of the epidermis is accompanied by complex coordinated migration of the neuronal substrate. We can efficiently track large numbers of migrating nuclei in 4D movies of zebrafish cardiac morphogenesis, suggesting that this approach is generally useful in situations in which the number, packing or dynamics of nuclei present challenges for automated tracking.
Three-dimensional morphological analysis of intracranial aneurysms: a fully automated method for aneurysm sac isolation and quantification.

PubMed

Larrabide, Ignacio; Cruz Villa-Uriol, Maria; Cárdenes, Rubén; Pozo, Jose Maria; Macho, Juan; San Roman, Luis; Blasco, Jordi; Vivas, Elio; Marzo, Alberto; Hose, D Rod; Frangi, Alejandro F

2011-05-01

Morphological descriptors are practical and essential biomarkers for diagnosis and treatment selection for intracranial aneurysm management according to the current guidelines in use. Nevertheless, relatively little work has been dedicated to improve the three-dimensional quantification of aneurysmal morphology, to automate the analysis, and hence to reduce the inherent intra and interobserver variability of manual analysis. In this paper we propose a methodology for the automated isolation and morphological quantification of saccular intracranial aneurysms based on a 3D representation of the vascular anatomy. This methodology is based on the analysis of the vasculature skeleton's topology and the subsequent application of concepts from deformable cylinders. These are expanded inside the parent vessel to identify different regions and discriminate the aneurysm sac from the parent vessel wall. The method renders as output the surface representation of the isolated aneurysm sac, which can then be quantified automatically. The proposed method provides the means for identifying the aneurysm neck in a deterministic way. The results obtained by the method were assessed in two ways: they were compared to manual measurements obtained by three independent clinicians as normally done during diagnosis and to automated measurements from manually isolated aneurysms by three independent operators, nonclinicians, experts in vascular image analysis. All the measurements were obtained using in-house tools. The results were qualitatively and quantitatively compared for a set of the saccular intracranial aneurysms (n = 26). Measurements performed on a synthetic phantom showed that the automated measurements obtained from manually isolated aneurysms where the most accurate. The differences between the measurements obtained by the clinicians and the manually isolated sacs were statistically significant (neck width: p <0.001, sac height: p = 0.002). When comparing clinicians' measurements to automatically isolated sacs, only the differences for the neck width were significant (neck width: p <0.001, sac height: p = 0.95). However, the correlation and agreement between the measurements obtained from manually and automatically isolated aneurysms for the neck width: p = 0.43 and sac height: p = 0.95 where found. The proposed method allows the automated isolation of intracranial aneurysms, eliminating the interobserver variability. In average, the computational cost of the automated method (2 min 36 s) was similar to the time required by a manual operator (measurement by clinicians: 2 min 51 s, manual isolation: 2 min 21 s) but eliminating human interaction. The automated measurements are irrespective of the viewing angle, eliminating any bias or difference between the observer criteria. Finally, the qualitative assessment of the results showed acceptable agreement between manually and automatically isolated aneurysms.
Fully Automated Fluorescent in situ Hybridization (FISH) Staining and Digital Analysis of HER2 in Breast Cancer: A Validation Study

PubMed Central

van der Logt, Elise M. J.; Kuperus, Deborah A. J.; van Setten, Jan W.; van den Heuvel, Marius C.; Boers, James. E.; Schuuring, Ed; Kibbelaar, Robby E.

2015-01-01

HER2 assessment is routinely used to select patients with invasive breast cancer that might benefit from HER2-targeted therapy. The aim of this study was to validate a fully automated in situ hybridization (ISH) procedure that combines the automated Leica HER2 fluorescent ISH system for Bond with supervised automated analysis with the Visia imaging D-Sight digital imaging platform. HER2 assessment was performed on 328 formalin-fixed/paraffin-embedded invasive breast cancer tumors on tissue microarrays (TMA) and 100 (50 selected IHC 2+ and 50 random IHC scores) full-sized slides of resections/biopsies obtained for diagnostic purposes previously. For digital analysis slides were pre-screened at 20x and 100x magnification for all fluorescent signals and supervised-automated scoring was performed on at least two pictures (in total at least 20 nuclei were counted) with the D-Sight HER2 FISH analysis module by two observers independently. Results were compared to data obtained previously with the manual Abbott FISH test. The overall agreement with Abbott FISH data among TMA samples and 50 selected IHC 2+ cases was 98.8% (κ = 0.94) and 93.8% (κ = 0.88), respectively. The results of 50 additionally tested unselected IHC cases were concordant with previously obtained IHC and/or FISH data. The combination of the Leica FISH system with the D-Sight digital imaging platform is a feasible method for HER2 assessment in routine clinical practice for patients with invasive breast cancer. PMID:25844540
Automated sizing of large structures by mixed optimization methods

NASA Technical Reports Server (NTRS)

Sobieszczanski, J.; Loendorf, D.

1973-01-01

A procedure for automating the sizing of wing-fuselage airframes was developed and implemented in the form of an operational program. The program combines fully stressed design to determine an overall material distribution with mass-strength and mathematical programming methods to design structural details accounting for realistic design constraints. The practicality and efficiency of the procedure is demonstrated for transport aircraft configurations. The methodology is sufficiently general to be applicable to other large and complex structures.
Automated ILA design for synchronous sequential circuits

NASA Technical Reports Server (NTRS)

Liu, M. N.; Liu, K. Z.; Maki, G. K.; Whitaker, S. R.

1991-01-01

An iterative logic array (ILA) architecture for synchronous sequential circuits is presented. This technique utilizes linear algebra to produce the design equations. The ILA realization of synchronous sequential logic can be fully automated with a computer program. A programmable design procedure is proposed to fullfill the design task and layout generation. A software algorithm in the C language has been developed and tested to generate 1 micron CMOS layouts using the Hewlett-Packard FUNGEN module generator shell.
Automated position control of a surface array relative to a liquid microjunction surface sampler

DOEpatents

Van Berkel, Gary J.; Kertesz, Vilmos; Ford, Michael James

2007-11-13

A system and method utilizes an image analysis approach for controlling the probe-to-surface distance of a liquid junction-based surface sampling system for use with mass spectrometric detection. Such an approach enables a hands-free formation of the liquid microjunction used to sample solution composition from the surface and for re-optimization, as necessary, of the microjunction thickness during a surface scan to achieve a fully automated surface sampling system.
Using integrated environmental modeling to automate a process-based Quantitative Microbial Risk Assessment

USDA-ARS?s Scientific Manuscript database

Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, and human health effect...

Semi-automated identification of cones in the human retina using circle Hough transform

PubMed Central

Bukowska, Danuta M.; Chew, Avenell L.; Huynh, Emily; Kashani, Irwin; Wan, Sue Ling; Wan, Pak Ming; Chen, Fred K

2015-01-01

A large number of human retinal diseases are characterized by a progressive loss of cones, the photoreceptors critical for visual acuity and color perception. Adaptive Optics (AO) imaging presents a potential method to study these cells in vivo. However, AO imaging in ophthalmology is a relatively new phenomenon and quantitative analysis of these images remains difficult and tedious using manual methods. This paper illustrates a novel semi-automated quantitative technique enabling registration of AO images to macular landmarks, cone counting and its radius quantification at specified distances from the foveal center. The new cone counting approach employs the circle Hough transform (cHT) and is compared to automated counting methods, as well as arbitrated manual cone identification. We explore the impact of varying the circle detection parameter on the validity of cHT cone counting and discuss the potential role of using this algorithm in detecting both cones and rods separately. PMID:26713186
General Staining and Segmentation Procedures for High Content Imaging and Analysis.

PubMed

Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

2018-01-01

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.
Improving Grid Resilience through Informed Decision-making (IGRID)

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

Burnham, Laurie; Stamber, Kevin L.; Jeffers, Robert Fredric

The transformation of the distribution grid from a centralized to decentralized architecture, with bi-directional power and data flows, is made possible by a surge in network intelligence and grid automation. While changes are largely beneficial, the interface between grid operator and automated technologies is not well understood, nor are the benefits and risks of automation. Quantifying and understanding the latter is an important facet of grid resilience that needs to be fully investigated. The work described in this document represents the first empirical study aimed at identifying and mitigating the vulnerabilities posed by automation for a grid that for themore » foreseeable future will remain a human-in-the-loop critical infrastructure. Our scenario-based methodology enabled us to conduct a series of experimental studies to identify causal relationships between grid-operator performance and automated technologies and to collect measurements of human performance as a function of automation. Our findings, though preliminary, suggest there are predictive patterns in the interplay between human operators and automation, patterns that can inform the rollout of distribution automation and the hiring and training of operators, and contribute in multiple and significant ways to the field of grid resilience.« less
An Intelligent Automation Platform for Rapid Bioprocess Design

PubMed Central

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
Advanced automation for in-space vehicle processing

NASA Technical Reports Server (NTRS)

Sklar, Michael; Wegerif, D.

1990-01-01

The primary objective of this 3-year planned study is to assure that the fully evolved Space Station Freedom (SSF) can support automated processing of exploratory mission vehicles. Current study assessments show that required extravehicular activity (EVA) and to some extent intravehicular activity (IVA) manpower requirements for required processing tasks far exceeds the available manpower. Furthermore, many processing tasks are either hazardous operations or they exceed EVA capability. Thus, automation is essential for SSF transportation node functionality. Here, advanced automation represents the replacement of human performed tasks beyond the planned baseline automated tasks. Both physical tasks such as manipulation, assembly and actuation, and cognitive tasks such as visual inspection, monitoring and diagnosis, and task planning are considered. During this first year of activity both the Phobos/Gateway Mars Expedition and Lunar Evolution missions proposed by the Office of Exploration have been evaluated. A methodology for choosing optimal tasks to be automated has been developed. Processing tasks for both missions have been ranked on the basis of automation potential. The underlying concept in evaluating and describing processing tasks has been the use of a common set of 'Primitive' task descriptions. Primitive or standard tasks have been developed both for manual or crew processing and automated machine processing.
Fully automated motion correction in first-pass myocardial perfusion MR image sequences.

PubMed

Milles, Julien; van der Geest, Rob J; Jerosch-Herold, Michael; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2008-11-01

This paper presents a novel method for registration of cardiac perfusion magnetic resonance imaging (MRI). The presented method is capable of automatically registering perfusion data, using independent component analysis (ICA) to extract physiologically relevant features together with their time-intensity behavior. A time-varying reference image mimicking intensity changes in the data of interest is computed based on the results of that ICA. This reference image is used in a two-pass registration framework. Qualitative and quantitative validation of the method is carried out using 46 clinical quality, short-axis, perfusion MR datasets comprising 100 images each. Despite varying image quality and motion patterns in the evaluation set, validation of the method showed a reduction of the average right ventricle (LV) motion from 1.26+/-0.87 to 0.64+/-0.46 pixels. Time-intensity curves are also improved after registration with an average error reduced from 2.65+/-7.89% to 0.87+/-3.88% between registered data and manual gold standard. Comparison of clinically relevant parameters computed using registered data and the manual gold standard show a good agreement. Additional tests with a simulated free-breathing protocol showed robustness against considerable deviations from a standard breathing protocol. We conclude that this fully automatic ICA-based method shows an accuracy, a robustness and a computation speed adequate for use in a clinical environment.
Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry

NASA Astrophysics Data System (ADS)

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-03-01

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.
Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.

PubMed

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-03-22

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.
Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry

PubMed Central

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-01-01

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83–0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments. PMID:27001047
A new fast and fully automated software based algorithm for extracting respiratory signal from raw PET data and its comparison to other methods.

PubMed

Kesner, Adam Leon; Kuntner, Claudia

2010-10-01

Respiratory gating in PET is an approach used to minimize the negative effects of respiratory motion on spatial resolution. It is based on an initial determination of a patient's respiratory movements during a scan, typically using hardware based systems. In recent years, several fully automated databased algorithms have been presented for extracting a respiratory signal directly from PET data, providing a very practical strategy for implementing gating in the clinic. In this work, a new method is presented for extracting a respiratory signal from raw PET sinogram data and compared to previously presented automated techniques. The acquisition of respiratory signal from PET data in the newly proposed method is based on rebinning the sinogram data into smaller data structures and then analyzing the time activity behavior in the elements of these structures. From this analysis, a 1D respiratory trace is produced, analogous to a hardware derived respiratory trace. To assess the accuracy of this fully automated method, respiratory signal was extracted from a collection of 22 clinical FDG-PET scans using this method, and compared to signal derived from several other software based methods as well as a signal derived from a hardware system. The method presented required approximately 9 min of processing time for each 10 min scan (using a single 2.67 GHz processor), which in theory can be accomplished while the scan is being acquired and therefore allowing a real-time respiratory signal acquisition. Using the mean correlation between the software based and hardware based respiratory traces, the optimal parameters were determined for the presented algorithm. The mean/median/range of correlations for the set of scans when using the optimal parameters was found to be 0.58/0.68/0.07-0.86. The speed of this method was within the range of real-time while the accuracy surpassed the most accurate of the previously presented algorithms. PET data inherently contains information about patient motion; information that is not currently being utilized. We have shown that a respiratory signal can be extracted from raw PET data in potentially real-time and in a fully automated manner. This signal correlates well with hardware based signal for a large percentage of scans, and avoids the efforts and complications associated with hardware. The proposed method to extract a respiratory signal can be implemented on existing scanners and, if properly integrated, can be applied without changes to routine clinical procedures.
[Quantification of pulmonary emphysema in multislice-CT using different software tools].

PubMed

Heussel, C P; Achenbach, T; Buschsieweke, C; Kuhnigk, J; Weinheimer, O; Hammer, G; Düber, C; Kauczor, H-U

2006-10-01

The data records of thin-section MSCT of the lung with approx. 300 images are difficult to use in manual evaluation. A computer-assisted pre-diagnosis can help with reporting. Furthermore, post-processing techniques, for instance, for quantification of emphysema on the basis of three-dimensional anatomical information might be improved and the workflow might be further automated. The results of 4 programs (Pulmo, Volume, YACTA and PulmoFUNC) for the quantitative analysis of emphysema (lung and emphysema volume, mean lung density and emphysema index) of 30 consecutive thin-section MSCT datasets with different emphysema severity levels were compared. The classification result of the YACTA program for different types of emphysema was also analyzed. Pulmo and Volume have a median operating time of 105 and 59 minutes respectively due to the necessity for extensive manual correction of the lung segmentation. The programs PulmoFUNC and YACTA, which are automated to a large extent, have a median runtime of 26 and 16 minutes, respectively. The evaluation with Pulmo and Volume using 2 different datasets resulted in implausible values. PulmoFUNC crashed with 2 other datasets in a reproducible manner. Only with YACTA could all graphic datasets be evaluated. The lung volume, emphysema volume, emphysema index and mean lung density determined by YACTA and PulmoFUNC are significantly larger than the corresponding values of Volume and Pulmo (differences: Volume: 119 cm(3)/65 cm(3)/1 %/17 HU, Pulmo: 60 cm(3)/96 cm(3)/1 %/37 HU). Classification of the emphysema type was in agreement with that of the radiologist in 26 panlobular cases, in 22 paraseptalen cases and in 15 centrilobular emphysema cases. The substantial expenditure of time obstructs the employment of quantitative emphysema analysis in the clinical routine. The results of YACTA and PulmoFUNC are affected by the dedicated exclusion of the tracheobronchial system. These fully automatic tools enable not only fast quantification without manual interaction, but also a reproducible measurement without user dependence.
Performance Equivalence and Validation of the Soleris Automated System for Quantitative Microbial Content Testing Using Pure Suspension Cultures.

PubMed

Limberg, Brian J; Johnstone, Kevin; Filloon, Thomas; Catrenich, Carl

2016-09-01

Using United States Pharmacopeia-National Formulary (USP-NF) general method <1223> guidance, the Soleris(®) automated system and reagents (Nonfermenting Total Viable Count for bacteria and Direct Yeast and Mold for yeast and mold) were validated, using a performance equivalence approach, as an alternative to plate counting for total microbial content analysis using five representative microbes: Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa, Candida albicans, and Aspergillus brasiliensis. Detection times (DTs) in the alternative automated system were linearly correlated to CFU/sample (R(2) = 0.94-0.97) with ≥70% accuracy per USP General Chapter <1223> guidance. The LOD and LOQ of the automated system were statistically similar to the traditional plate count method. This system was significantly more precise than plate counting (RSD 1.2-2.9% for DT, 7.8-40.6% for plate counts), was statistically comparable to plate counting with respect to variations in analyst, vial lots, and instruments, and was robust when variations in the operating detection thresholds (dTs; ±2 units) were used. The automated system produced accurate results, was more precise and less labor-intensive, and met or exceeded criteria for a valid alternative quantitative method, consistent with USP-NF general method <1223> guidance.
A quantitative measure for degree of automation and its relation to system performance and mental load.

PubMed

Wei, Z G; Macwan, A P; Wieringa, P A

1998-06-01

In this paper we quantitatively model degree of automation (DofA) in supervisory control as a function of the number and nature of tasks to be performed by the operator and automation. This model uses a task weighting scheme in which weighting factors are obtained from task demand load, task mental load, and task effect on system performance. The computation of DofA is demonstrated using an experimental system. Based on controlled experiments using operators, analyses of the task effect on system performance, the prediction and assessment of task demand load, and the prediction of mental load were performed. Each experiment had a different DofA. The effect of a change in DofA on system performance and mental load was investigated. It was found that system performance became less sensitive to changes in DofA at higher levels of DofA. The experimental data showed that when the operator controlled a partly automated system, perceived mental load could be predicted from the task mental load for each task component, as calculated by analyzing a situation in which all tasks were manually controlled. Actual or potential applications of this research include a methodology to balance and optimize the automation of complex industrial systems.
Influence of sample preparation and reliability of automated numerical refocusing in stain-free analysis of dissected tissues with quantitative phase digital holographic microscopy

NASA Astrophysics Data System (ADS)

Kemper, Björn; Lenz, Philipp; Bettenworth, Dominik; Krausewitz, Philipp; Domagk, Dirk; Ketelhut, Steffi

2015-05-01

Digital holographic microscopy (DHM) has been demonstrated to be a versatile tool for high resolution non-destructive quantitative phase imaging of surfaces and multi-modal minimally-invasive monitoring of living cell cultures in-vitro. DHM provides quantitative monitoring of physiological processes through functional imaging and structural analysis which, for example, gives new insight into signalling of cellular water permeability and cell morphology changes due to toxins and infections. Also the analysis of dissected tissues quantitative DHM phase contrast prospects application fields by stain-free imaging and the quantification of tissue density changes. We show that DHM allows imaging of different tissue layers with high contrast in unstained tissue sections. As the investigation of fixed samples represents a very important application field in pathology, we also analyzed the influence of the sample preparation. The retrieved data demonstrate that the quality of quantitative DHM phase images of dissected tissues depends strongly on the fixing method and common staining agents. As in DHM the reconstruction is performed numerically, multi-focus imaging is achieved from a single digital hologram. Thus, we evaluated the automated refocussing feature of DHM for application on different types of dissected tissues and revealed that on moderately stained samples highly reproducible holographic autofocussing can be achieved. Finally, it is demonstrated that alterations of the spatial refractive index distribution in murine and human tissue samples represent a reliable absolute parameter that is related of different degrees of inflammation in experimental colitis and Crohn's disease. This paves the way towards the usage of DHM in digital pathology for automated histological examinations and further studies to elucidate the translational potential of quantitative phase microscopy for the clinical management of patients, e.g., with inflammatory bowel disease.
Early prediction of coma recovery after cardiac arrest with blinded pupillometry.

PubMed

Solari, Daria; Rossetti, Andrea O; Carteron, Laurent; Miroz, John-Paul; Novy, Jan; Eckert, Philippe; Oddo, Mauro

2017-06-01

Prognostication studies on comatose cardiac arrest (CA) patients are limited by lack of blinding, potentially causing overestimation of outcome predictors and self-fulfilling prophecy. Using a blinded approach, we analyzed the value of quantitative automated pupillometry to predict neurological recovery after CA. We examined a prospective cohort of 103 comatose adult patients who were unconscious 48 hours after CA and underwent repeated measurements of quantitative pupillary light reflex (PLR) using the Neurolight-Algiscan device. Clinical examination, electroencephalography (EEG), somatosensory evoked potentials (SSEP), and serum neuron-specific enolase were performed in parallel, as part of standard multimodal assessment. Automated pupillometry results were blinded to clinicians involved in patient care. Cerebral Performance Categories (CPC) at 1 year was the outcome endpoint. Survivors (n = 50 patients; 32 CPC 1, 16 CPC 2, 2 CPC 3) had higher quantitative PLR (median = 20 [range = 13-41] vs 11 [0-55] %, p < 0.0001) and constriction velocity (1.46 [0.85-4.63] vs 0.94 [0.16-4.97] mm/s, p < 0.0001) than nonsurvivors. At 48 hours, a quantitative PLR < 13% had 100% specificity and positive predictive value to predict poor recovery (0% false-positive rate), and provided equal performance to that of EEG and SSEP. Reduced quantitative PLR correlated with higher serum neuron-specific enolase (Spearman r = -0.52, p < 0.0001). Reduced quantitative PLR correlates with postanoxic brain injury and, when compared to standard multimodal assessment, is highly accurate in predicting long-term prognosis after CA. This is the first prognostication study to show the value of automated pupillometry using a blinded approach to minimize self-fulfilling prophecy. Ann Neurol 2017;81:804-810. © 2017 American Neurological Association.
Bayesian ISOLA: new tool for automated centroid moment tensor inversion

NASA Astrophysics Data System (ADS)

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 order to be applicable in various networks ranging from local to regional. The method can be applied either to the everyday network data flow, or to process large previously existing earthquake catalogues and data sets.
Technical Assessment of the Transette Transit System

DOT National Transportation Integrated Search

1981-10-01

This report describes an assessment of the Transette system located at the Georgia Institute of Technology in Atlanta, Georgia. The Transette system is a unique, fully-automated, engineering prototype transportation test system installed on the campu...
A standardized kit for automated quantitative assessment of candidate protein biomarkers in human plasma.

PubMed

Percy, Andrew J; Mohammed, Yassene; Yang, Juncong; Borchers, Christoph H

2015-12-01

An increasingly popular mass spectrometry-based quantitative approach for health-related research in the biomedical field involves the use of stable isotope-labeled standards (SIS) and multiple/selected reaction monitoring (MRM/SRM). To improve inter-laboratory precision and enable more widespread use of this 'absolute' quantitative technique in disease-biomarker assessment studies, methods must be standardized. Results/methodology: Using this MRM-with-SIS-peptide approach, we developed an automated method (encompassing sample preparation, processing and analysis) for quantifying 76 candidate protein markers (spanning >4 orders of magnitude in concentration) in neat human plasma. The assembled biomarker assessment kit - the 'BAK-76' - contains the essential materials (SIS mixes), methods (for acquisition and analysis), and tools (Qualis-SIS software) for performing biomarker discovery or verification studies in a rapid and standardized manner.
Automated high resolution full-field spatial coherence tomography for quantitative phase imaging of human red blood cells

NASA Astrophysics Data System (ADS)

Singla, Neeru; Dubey, Kavita; Srivastava, Vishal; Ahmad, Azeem; Mehta, D. S.

2018-02-01

We developed an automated high-resolution full-field spatial coherence tomography (FF-SCT) microscope for quantitative phase imaging that is based on the spatial, rather than the temporal, coherence gating. The Red and Green color laser light was used for finding the quantitative phase images of unstained human red blood cells (RBCs). This study uses morphological parameters of unstained RBCs phase images to distinguish between normal and infected cells. We recorded the single interferogram by a FF-SCT microscope for red and green color wavelength and average the two phase images to further reduced the noise artifacts. In order to characterize anemia infected from normal cells different morphological features were extracted and these features were used to train machine learning ensemble model to classify RBCs with high accuracy.
Nonparticipatory Stiffness in the Male Perioral Complex

ERIC Educational Resources Information Center

Chu, Shin-Ying; Barlow, Steven M.; Lee, Jaehoon

2009-01-01

Purpose: The objective of this study was to extend previous published findings in the authors' laboratory using a new automated technology to quantitatively characterize nonparticipatory perioral stiffness in healthy male adults. Method: Quantitative measures of perioral stiffness were sampled during a nonparticipatory task using a…

Automated Dissolution for Enteric-Coated Aspirin Tablets: A Case Study for Method Transfer to a RoboDis II.

PubMed

Ibrahim, Sarah A; Martini, Luigi

2014-08-01

Dissolution method transfer is a complicated yet common process in the pharmaceutical industry. With increased pharmaceutical product manufacturing and dissolution acceptance requirements, dissolution testing has become one of the most labor-intensive quality control testing methods. There is an increased trend for automation in dissolution testing, particularly for large pharmaceutical companies to reduce variability and increase personnel efficiency. There is no official guideline for dissolution testing method transfer from a manual, semi-automated, to automated dissolution tester. In this study, a manual multipoint dissolution testing procedure for an enteric-coated aspirin tablet was transferred effectively and reproducibly to a fully automated dissolution testing device, RoboDis II. Enteric-coated aspirin samples were used as a model formulation to assess the feasibility and accuracy of media pH change during continuous automated dissolution testing. Several RoboDis II parameters were evaluated to ensure the integrity and equivalency of dissolution method transfer from a manual dissolution tester. This current study provides a systematic outline for the transfer of the manual dissolution testing protocol to an automated dissolution tester. This study further supports that automated dissolution testers compliant with regulatory requirements and similar to manual dissolution testers facilitate method transfer. © 2014 Society for Laboratory Automation and Screening.
Comparison of Actual Costs to Integrate Commercial Buildings with the Grid

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

Piette, Mary Ann; Black, Doug; Yin, Rongxin

During the past decade, the technology to automate demand response (DR) in buildings and industrial facilities has advanced significantly. Automation allows rapid, repeatable, reliable operation. This study focuses on costs for DR automation in commercial buildings with some discussion on residential buildings and industrial facilities. DR automation technology relies on numerous components, including communication systems, hardware and software gateways, standards-based messaging protocols, controls and integration platforms, and measurement and telemetry systems. This paper discusses the impact factors that contribute to the costs of automated DR systems, with a focus on OpenADR 1.0 and 2.0 systems. In addition, this report comparesmore » cost data from several DR automation programs and pilot projects, evaluates trends in the cost per unit of DR and kilowatts (kW) available from automated systems, and applies a standard naming convention and classification or taxonomy for system elements. In summary, median costs for the 56 installed automated DR systems studied here are about $200/kW. The deviation around this median is large with costs in some cases being an order of magnitude greater or less than median. Costs to automate fast DR systems for ancillary services are not fully analyzed in this report because additional research is needed to determine the total such costs.« less
Transitioning Resolution Responsibility between the Controller and Automation Team in Simulated NextGen Separation Assurance

NASA Technical Reports Server (NTRS)

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

PubMed

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.
Design and implementation of an automated compound management system in support of lead optimization.

PubMed

Quintero, Catherine; Kariv, Ilona

2009-06-01

To meet the needs of the increasingly rapid and parallelized lead optimization process, a fully integrated local compound storage and liquid handling system was designed and implemented to automate the generation of assay-ready plates directly from newly submitted and cherry-picked compounds. A key feature of the system is the ability to create project- or assay-specific compound-handling methods, which provide flexibility for any combination of plate types, layouts, and plate bar-codes. Project-specific workflows can be created by linking methods for processing new and cherry-picked compounds and control additions to produce a complete compound set for both biological testing and local storage in one uninterrupted workflow. A flexible cherry-pick approach allows for multiple, user-defined strategies to select the most appropriate replicate of a compound for retesting. Examples of custom selection parameters include available volume, compound batch, and number of freeze/thaw cycles. This adaptable and integrated combination of software and hardware provides a basis for reducing cycle time, fully automating compound processing, and ultimately increasing the rate at which accurate, biologically relevant results can be produced for compounds of interest in the lead optimization process.
RAPID-L Highly Automated Fast Reactor Concept Without Any Control Rods (2) Critical experiment of lithium-6 used in LEM and LIM

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

Tsunoda, Hirokazu; Sato, Osamu; Okajima, Shigeaki

2002-07-01

In order to achieve fully automated reactor operation of RAPID-L reactor, innovative reactivity control systems LEM, LIM, and LRM are equipped with lithium-6 as a liquid poison. Because lithium-6 has not been used as a neutron absorbing material of conventional fast reactors, measurements of the reactivity worth of Lithium-6 were performed at the Fast Critical Assembly (FCA) of Japan Atomic Energy Research Institute (JAERI). The FCA core was composed of highly enriched uranium and stainless steel samples so as to simulate the core spectrum of RAPID-L. The samples of 95% enriched lithium-6 were inserted into the core parallel to themore » core axis for the measurement of the reactivity worth at each position. It was found that the measured reactivity worth in the core region well agreed with calculated value by the method for the core designs of RAPID-L. Bias factors for the core design method were obtained by comparing between experimental and calculated results. The factors were used to determine the number of LEM and LIM equipped in the core to achieve fully automated operation of RAPID-L. (authors)« less
Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images

NASA Astrophysics Data System (ADS)

Amrute, Junedh M.; Athanasiou, Lambros S.; Rikhtegar, Farhad; de la Torre Hernández, José M.; Camarero, Tamara García; Edelman, Elazer R.

2018-03-01

Polymeric endovascular implants are the next step in minimally invasive vascular interventions. As an alternative to traditional metallic drug-eluting stents, these often-erodible scaffolds present opportunities and challenges for patients and clinicians. Theoretically, as they resorb and are absorbed over time, they obviate the long-term complications of permanent implants, but in the short-term visualization and therefore positioning is problematic. Polymeric scaffolds can only be fully imaged using optical coherence tomography (OCT) imaging-they are relatively invisible via angiography-and segmentation of polymeric struts in OCT images is performed manually, a laborious and intractable procedure for large datasets. Traditional lumen detection methods using implant struts as boundary limits fail in images with polymeric implants. Therefore, it is necessary to develop an automated method to detect polymeric struts and luminal borders in OCT images; we present such a fully automated algorithm. Accuracy was validated using expert annotations on 1140 OCT images with a positive predictive value of 0.93 for strut detection and an R2 correlation coefficient of 0.94 between detected and expert-annotated lumen areas. The proposed algorithm allows for rapid, accurate, and automated detection of polymeric struts and the luminal border in OCT images.
IntelliCages and automated assessment of learning in group-housed mice

NASA Astrophysics Data System (ADS)

Puścian, Alicja; Knapska, Ewelina

2014-11-01

IntelliCage is a fully automated, computer controlled system, which can be used for long-term monitoring of behavior of group-housed mice. Using standardized experimental protocols we can assess cognitive abilities and behavioral flexibility in appetitively and aversively motivated tasks, as well as measure social influences on learning of the subjects. We have also identified groups of neurons specifically activated by appetitively and aversively motivated learning within the amygdala, function of which we are going to investigate optogenetically in the future.
Gravity-driven pH adjustment for site-specific protein pKa measurement by solution-state NMR

NASA Astrophysics Data System (ADS)

Li, Wei

2017-12-01

To automate pH adjustment in site-specific protein pKa measurement by solution-state NMR, I present a funnel with two caps for the standard 5 mm NMR tube. The novelty of this simple-to-build and inexpensive apparatus is that it allows automatic gravity-driven pH adjustment within the magnet, and consequently results in a fully automated NMR-monitored pH titration without any hardware modification on the NMR spectrometer.
Automated, per pixel Cloud Detection from High-Resolution VNIR Data

NASA Technical Reports Server (NTRS)

Varlyguin, Dmitry L.

2007-01-01

CASA is a fully automated software program for the per-pixel detection of clouds and cloud shadows from medium- (e.g., Landsat, SPOT, AWiFS) and high- (e.g., IKONOS, QuickBird, OrbView) resolution imagery without the use of thermal data. CASA is an object-based feature extraction program which utilizes a complex combination of spectral, spatial, and contextual information available in the imagery and the hierarchical self-learning logic for accurate detection of clouds and their shadows.
Hierarchically Parallelized Constrained Nonlinear Solvers with Automated Substructuring

NASA Technical Reports Server (NTRS)

Padovan, Joe; Kwang, Abel

1994-01-01

This paper develops a parallelizable multilevel multiple constrained nonlinear equation solver. The substructuring process is automated to yield appropriately balanced partitioning of each succeeding level. Due to the generality of the procedure,_sequential, as well as partially and fully parallel environments can be handled. This includes both single and multiprocessor assignment per individual partition. Several benchmark examples are presented. These illustrate the robustness of the procedure as well as its capability to yield significant reductions in memory utilization and calculational effort due both to updating and inversion.
Frapid: achieving full automation of FRAP for chemical probe validation

PubMed Central

Yapp, Clarence; Rogers, Catherine; Savitsky, Pavel; Philpott, Martin; Müller, Susanne

2016-01-01

Fluorescence Recovery After Photobleaching (FRAP) is an established method for validating chemical probes against the chromatin reading bromodomains, but so far requires constant human supervision. Here, we present Frapid, an automated open source code implementation of FRAP that fully handles cell identification through fuzzy logic analysis, drug dispensing with a custom-built fluid handler, image acquisition & analysis, and reporting. We successfully tested Frapid on 3 bromodomains as well as on spindlin1 (SPIN1), a methyl lysine binder, for the first time. PMID:26977352
A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries

PubMed Central

2011-01-01

Genome targeting methods enable cost-effective capture of specific subsets of the genome for sequencing. We present here an automated, highly scalable method for carrying out the Solution Hybrid Selection capture approach that provides a dramatic increase in scale and throughput of sequence-ready libraries produced. Significant process improvements and a series of in-process quality control checkpoints are also added. These process improvements can also be used in a manual version of the protocol. PMID:21205303
Application of heuristic satellite plan synthesis algorithms to requirements of the WARC-88 allotment plan

NASA Technical Reports Server (NTRS)

Heyward, Ann O.; Reilly, Charles H.; Walton, Eric K.; Mata, Fernando; Olen, Carl

1990-01-01

Creation of an Allotment Plan for the Fixed Satellite Service at the 1988 Space World Administrative Radio Conference (WARC) represented a complex satellite plan synthesis problem, involving a large number of planned and existing systems. Solutions to this problem at WARC-88 required the use of both automated and manual procedures to develop an acceptable set of system positions. Development of an Allotment Plan may also be attempted through solution of an optimization problem, known as the Satellite Location Problem (SLP). Three automated heuristic procedures, developed specifically to solve SLP, are presented. The heuristics are then applied to two specific WARC-88 scenarios. Solutions resulting from the fully automated heuristics are then compared with solutions obtained at WARC-88 through a combination of both automated and manual planning efforts.
Automated solar cell assembly team process research

NASA Astrophysics Data System (ADS)

Nowlan, M. J.; Hogan, S. J.; Darkazalli, G.; Breen, W. F.; Murach, J. M.; Sutherland, S. F.; Patterson, J. S.

1994-06-01

This report describes work done under the Photovoltaic Manufacturing Technology (PVMaT) project, Phase 3A, which addresses problems that are generic to the photovoltaic (PV) industry. Spire's objective during Phase 3A was to use its light soldering technology and experience to design and fabricate solar cell tabbing and interconnecting equipment to develop new, high-yield, high-throughput, fully automated processes for tabbing and interconnecting thin cells. Areas that were addressed include processing rates, process control, yield, throughput, material utilization efficiency, and increased use of automation. Spire teamed with Solec International, a PV module manufacturer, and the University of Massachusetts at Lowell's Center for Productivity Enhancement (CPE), automation specialists, who are lower-tier subcontractors. A number of other PV manufacturers, including Siemens Solar, Mobil Solar, Solar Web, and Texas instruments, agreed to evaluate the processes developed under this program.
Diatomite filters--methods of automation

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

Maloney, G.F.

1966-01-01

Following an introduction of subject material, diatomite filters are discussed in the following categories: a filter system, the manual station, the decision to automate, equipment, the automated filter, and the fail-safe methods. Diagrams and pictures of the equipment and its operation are included. Many aspects of the uses of both the automatic and manually operated diatomite filtering systems are reviewed. The fully automated station may be ideally suited to the remotely located waterflood since it requires virtually no attention or perhaps only periodic inspection. On the other hand, floods large enough to employ full-time personnel, who can maintain a constantmore » vigil and peiodically scrutinize the filtering operation, probably require nothing more than a semiautomatic operation. The reduction of human error can save money, and the introduction of consistency into any unit operation is certain to be beneficial.« less
Automated MAD and MIR structure solution

PubMed Central

Terwilliger, Thomas C.; Berendzen, Joel

1999-01-01

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. PMID:10089316
Automation - Changes in cognitive demands and mental workload

NASA Technical Reports Server (NTRS)

Tsang, Pamela S.; Johnson, Walter W.

1987-01-01

The effect of partial automation on mental workloads in man/machine tasks is investigated experimentally. Subjective workload measures are obtained from six subjects after performance of a task battery comprising two manual (flight-path control, FC, and target acquisition, TA) tasks and one decisionmaking (engine failure, EF) task; the FC task was performed in both a fully manual (altitude and lateral control) mode and in a semiautomated mode (autmatic latitude control). The performance results and subjective evaluations are presented in graphs and characterized in detail. The automation is shown to improve objective performance and lower subjective workload significantly in the combined FC/TA task, but not in the FC task alone or in the FC/EF task.
BOREAS TF-3 Automated Chamber CO2 Flux Data from the NSA-OBS

NASA Technical Reports Server (NTRS)

Goulden, Michael L.; Crill, Patrick M.; Hall, Forrest G. (Editor); Conrad, Sara (Editor)

2000-01-01

The BOReal Ecosystem Atmosphere Study Tower Flux (BOREAS TF-3) and Trace Gas Biogeochemistry (TGB-1) teams collected automated CO2 chamber flux data in their efforts to fully describe the CO2 flux at the Northern Study Area-Old Black Spruce (NSA-OBS) site. This data set contains fluxes of CO2 at the NSA-OBS site measured using automated chambers. In addition to reporting the CO2 flux, it reports chamber air temperature, moss temperature, and light levels during each measurement. The data set covers the period from 23-Sep-1995 through 26-Oct-1995 and from 28-May-1996 through 21-Oct-1996. The data are stored in tabular ASCII files.
Devising tissue ingrowth metrics: a contribution to the computational characterization of engineered soft tissue healing.

PubMed

Alves, Antoine; Attik, Nina; Bayon, Yves; Royet, Elodie; Wirth, Carine; Bourges, Xavier; Piat, Alexis; Dolmazon, Gaëlle; Clermont, Gaëlle; Boutrand, Jean-Pierre; Grosgogeat, Brigitte; Gritsch, Kerstin

2018-03-14

The paradigm shift brought about by the expansion of tissue engineering and regenerative medicine away from the use of biomaterials, currently questions the value of histopathologic methods in the evaluation of biological changes. To date, the available tools of evaluation are not fully consistent and satisfactory for these advanced therapies. We have developed a new, simple and inexpensive quantitative digital approach that provides key metrics for structural and compositional characterization of the regenerated tissues. For example, metrics provide the tissue ingrowth rate (TIR) which integrates two separate indicators; the cell ingrowth rate (CIR) and the total collagen content (TCC) as featured in the equation, TIR% = CIR% + TCC%. Moreover a subset of quantitative indicators describing the directional organization of the collagen (relating structure and mechanical function of tissues), the ratio of collagen I to collagen III (remodeling quality) and the optical anisotropy property of the collagen (maturity indicator) was automatically assessed as well. Using an image analyzer, all metrics were extracted from only two serial sections stained with either Feulgen & Rossenbeck (cell specific) or Picrosirius Red F3BA (collagen specific). To validate this new procedure, three-dimensional (3D) scaffolds were intraperitoneally implanted in healthy and in diabetic rats. It was hypothesized that quantitatively, the healing tissue would be significantly delayed and of poor quality in diabetic rats in comparison to healthy rats. In addition, a chemically modified 3D scaffold was similarly implanted in a third group of healthy rats with the assumption that modulation of the ingrown tissue would be quantitatively present in comparison to the 3D scaffold-healthy group. After 21 days of implantation, both hypotheses were verified by use of this novel computerized approach. When the two methods were run in parallel, the quantitative results revealed fine details and differences not detected by the semi-quantitative assessment, demonstrating the importance of quantitative analysis in the performance evaluation of soft tissue healing. This automated and supervised method reduced operator dependency and proved to be simple, sensitive, cost-effective and time-effective. It supports objective therapeutic comparisons and helps to elucidate regeneration and the dynamics of a functional tissue.

[Clinical evaluation of a novel HBsAg quantitative assay].

PubMed

Takagi, Kazumi; Tanaka, Yasuhito; Naganuma, Hatsue; Hiramatsu, Kumiko; Iida, Takayasu; Takasaka, Yoshimitsu; Mizokami, Masashi

2007-07-01

The clinical implication of the hepatitis B surface antigen (HBsAg) concentrations in HBV-infected individuals remains unclear. The aim of this study was to evaluate a novel fully automated Chemiluminescence Enzyme Immunoassay (Sysmex HBsAg quantitative assay) by comparative measurements of the reference serum samples versus two independent commercial assays (Lumipulse f or Architect HBsAg QT). Furthermore, clinical usefulness was assessed for monitoring of the serum HBsAg levels during antiviral therapy. A dilution test using 5 reference-serum samples showed linear correlation curve in range from 0.03 to 2,360 IU/ml. The HBsAg was measured in total of 400 serum samples and 99.8% had consistent results between Sysmex and Lumipulse f. Additionally, a positive linear correlation was observed between Sysmex and Architect. To compare the Architect and Sysmex, both methods were applied to quantify the HBsAg in serum samples with different HBV genotypes/subgenotypes, as well as in serum contained HBV vaccine escape mutants (126S, 145R). Correlation between the methods was observed in results for escape mutants and common genotypes (A, B, C) in Japan. Observed during lamivudine therapy, an increase in HBsAg and HBV DNA concentrations preceded the aminotransferase (ALT) elevation associated with drug-resistant HBV variant emergence (breakthrough hepatitis). In conclusion, reliability of the Sysmex HBsAg quantitative assay was confirmed for all HBV genetic variants common in Japan. Monitoring of serum HBsAg concentrations in addition to HBV DNA quantification, is helpful in evaluation of the response to lamivudine treatment and diagnosis of the breakthrough hepatitis.
A method for normalizing pathology images to improve feature extraction for quantitative pathology

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

Tam, Allison; Barker, Jocelyn; Rubin, Daniel

Purpose: With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. Methods: To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology imagesmore » by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. Results: The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. Conclusions: ICHE may be a useful preprocessing step a digital pathology image processing pipeline.« less
SARA South Observatory: A Fully Automated Boller & Chivens 0.6-m Telescope at C.T.I.O.

NASA Astrophysics Data System (ADS)

Mack, Peter; KanniahPadmanaban, S. Y.; Kaitchuck, R.; Borstad, A.; Luzier, N.

2010-05-01

The SARA South Observatory is the re-birth of the Lowell 24-inch telescope located on the south-east ridge of Cerro Tololo, Chile. Installed in 1968 this Boller & Chivens telescope fell into disuse for almost 20 years. The telescope and observatory have undergone a major restoration. A new dome with a wide slit has been fully automated with an ACE SmartDome controller featuring autonomous closure. The telescope was completely gutted, repainted, and virtually every electronic component and wire replaced. Modern infrastructure, such as USB, Ethernet and video ports have been incorporated into the telescope tube saddle boxes. Absolute encoders have been placed on the Hour Angle and declination axes with a resolution of less than 0.7 arc seconds. The secondary mirror is also equipped with an absolute encoder and temperature sensor to allow for fully automated focus. New mirror coatings, automated mirror covers, a new 150mm refractor, and new instrumentation have been deployed. An integrated X-stage guider and dual filter wheel containing 18 filters is used for direct imaging. The guider camera can be easily removed and a standard 2-inch eyepiece used for occasional viewing by VIP's at C.T.I.O. A 12 megapixel all-sky camera produces color images every 30 seconds showing details in the Milky Way and Magellanic Clouds. Two low light level cameras are deployed; one on the finder and one at the top of the telescope showing a 30° field. Other auxiliary equipment, including daytime color video cameras, weather station and remotely controllable power outlets permit complete control and servicing of the system. The SARA Consortium (www.saraobservatory.org), a collection of ten eastern universities, also operates a 0.9-m telescope at the Kitt Peak National Observatory using an almost identical set of instruments with the same ACE control system. This project was funded by the SARA Consortium.
Soft robot design methodology for `push-button' manufacturing

NASA Astrophysics Data System (ADS)

Paik, Jamie

2018-06-01

`Push-button' or fully automated manufacturing would enable the production of robots with zero intervention from human hands. Realizing this utopia requires a fundamental shift from a sequential (design-materials-manufacturing) to a concurrent design methodology.
Space Applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 4: Supplement, Appendix 4.3: Candidate ARAMIS Capabilities

NASA Technical Reports Server (NTRS)

Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

1982-01-01

Potential applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities, and to their related ground support functions, in the years 1985-2000, so that NASA may make informed decisions on which aspects of ARAMIS to develop. The study first identifies the specific tasks which will be required by future space projects. It then defines ARAMIS options which are candidates for those space project tasks, and evaluates the relative merits of these options. Finally, the study identifies promising applications of ARAMIS, and recommends specific areas for further research. The ARAMIS options defined and researched by the study group span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.
Solvepol: A Reduction Pipeline for Imaging Polarimetry Data

NASA Astrophysics Data System (ADS)

Ramírez, Edgar A.; Magalhães, Antônio M.; Davidson, James W., Jr.; Pereyra, Antonio; Rubinho, Marcelo

2017-05-01

We present a newly, fully automated, data pipeline, Solvepol, designed to reduce and analyze polarimetric data. It has been optimized for imaging data from the Instituto de Astronomía, Geofísica e Ciências Atmosféricas (IAG) of the University of São Paulo (USP), calcite Savart prism plate-based IAGPOL polarimeter. Solvepol is also the basis of a reduction pipeline for the wide-field optical polarimeter that will execute SOUTH POL, a survey of the polarized southern sky. Solvepol was written using the Interactive data language (IDL) and is based on the Image Reduction and Analysis Facility (IRAF) task PCCDPACK, developed by our polarimetry group. We present and discuss reduced data from standard stars and other fields and compare these results with those obtained in the IRAF environment. Our analysis shows that Solvepol, in addition to being a fully automated pipeline, produces results consistent with those reduced by PCCDPACK and reported in the literature.
Real-time piloted simulation of fully automatic guidance and control for rotorcraft nap-of-the-earth (NOE) flight following planned profiles

NASA Technical Reports Server (NTRS)

Clement, Warren F.; Gorder, Pater J.; Jewell, Wayne F.; Coppenbarger, Richard

1990-01-01

Developing a single-pilot all-weather NOE capability requires fully automatic NOE navigation and flight control. Innovative guidance and control concepts are being investigated to (1) organize the onboard computer-based storage and real-time updating of NOE terrain profiles and obstacles; (2) define a class of automatic anticipative pursuit guidance algorithms to follow the vertical, lateral, and longitudinal guidance commands; (3) automate a decision-making process for unexpected obstacle avoidance; and (4) provide several rapid response maneuvers. Acquired knowledge from the sensed environment is correlated with the recorded environment which is then used to determine an appropriate evasive maneuver if a nonconformity is observed. This research effort has been evaluated in both fixed-base and moving-base real-time piloted simulations thereby evaluating pilot acceptance of the automated concepts, supervisory override, manual operation, and reengagement of the automatic system.
Self-consistent hybrid functionals for solids: a fully-automated implementation

NASA Astrophysics Data System (ADS)

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.
Quantification of liver fat: A comprehensive review.

PubMed

Goceri, Evgin; Shah, Zarine K; Layman, Rick; Jiang, Xia; Gurcan, Metin N

2016-04-01

Fat accumulation in the liver causes metabolic diseases such as obesity, hypertension, diabetes or dyslipidemia by affecting insulin resistance, and increasing the risk of cardiac complications and cardiovascular disease mortality. Fatty liver diseases are often reversible in their early stage; therefore, there is a recognized need to detect their presence and to assess its severity to recognize fat-related functional abnormalities in the liver. This is crucial in evaluating living liver donors prior to transplantation because fat content in the liver can change liver regeneration in the recipient and donor. There are several methods to diagnose fatty liver, measure the amount of fat, and to classify and stage liver diseases (e.g. hepatic steatosis, steatohepatitis, fibrosis and cirrhosis): biopsy (the gold-standard procedure), clinical (medical physics based) and image analysis (semi or fully automated approaches). Liver biopsy has many drawbacks: it is invasive, inappropriate for monitoring (i.e., repeated evaluation), and assessment of steatosis is somewhat subjective. Qualitative biomarkers are mostly insufficient for accurate detection since fat has to be quantified by a varying threshold to measure disease severity. Therefore, a quantitative biomarker is required for detection of steatosis, accurate measurement of severity of diseases, clinical decision-making, prognosis and longitudinal monitoring of therapy. This study presents a comprehensive review of both clinical and automated image analysis based approaches to quantify liver fat and evaluate fatty liver diseases from different medical imaging modalities. Copyright © 2016 Elsevier Ltd. All rights reserved.
Comprehensive automatic assessment of retinal vascular abnormalities for computer-assisted retinopathy grading.

PubMed

Joshi, Vinayak; Agurto, Carla; VanNess, Richard; Nemeth, Sheila; Soliz, Peter; Barriga, Simon

2014-01-01

One of the most important signs of systemic disease that presents on the retina is vascular abnormalities such as in hypertensive retinopathy. Manual analysis of fundus images by human readers is qualitative and lacks in accuracy, consistency and repeatability. Present semi-automatic methods for vascular evaluation are reported to increase accuracy and reduce reader variability, but require extensive reader interaction; thus limiting the software-aided efficiency. Automation thus holds a twofold promise. First, decrease variability while increasing accuracy, and second, increasing the efficiency. In this paper we propose fully automated software as a second reader system for comprehensive assessment of retinal vasculature; which aids the readers in the quantitative characterization of vessel abnormalities in fundus images. This system provides the reader with objective measures of vascular morphology such as tortuosity, branching angles, as well as highlights of areas with abnormalities such as artery-venous nicking, copper and silver wiring, and retinal emboli; in order for the reader to make a final screening decision. To test the efficacy of our system, we evaluated the change in performance of a newly certified retinal reader when grading a set of 40 color fundus images with and without the assistance of the software. The results demonstrated an improvement in reader's performance with the software assistance, in terms of accuracy of detection of vessel abnormalities, determination of retinopathy, and reading time. This system enables the reader in making computer-assisted vasculature assessment with high accuracy and consistency, at a reduced reading time.
In vivo laser confocal microscopy after non-Descemet's stripping automated endothelial keratoplasty.

PubMed

Kobayashi, Akira; Yokogawa, Hideaki; Sugiyama, Kazuhisa

2009-07-01

To investigate in vivo corneal changes in patients with bullous keratopathy who underwent non-Descemet's stripping automated endothelial keratoplasty (nDSAEK) with the use of laser confocal microscopy. Single-center, prospective clinical study. Ten eyes (10 patients; 3 men and 7 women; mean age, 73.5+/-6.6 years [mean+/-standard deviation]) with bullous keratopathy were evaluated in this study. In vivo laser confocal microscopy was performed before and 1, 3, and 6 months after nDSAEK. Selected confocal images of corneal layers were evaluated qualitatively and quantitatively for degree of haze and density of deposits. Before surgery, the following were observed in all patients: corneal epithelial edema, subepithelial haze, keratocytes in a honeycomb pattern, and tiny needle-shaped materials in the stroma. After nDSAEK, subepithelial haze, donor-recipient interface haze, and interface particles were observed in all measurable cases; postoperative haze, interface particles, and needle-shaped materials decreased statistically significantly (P<0.05) over the course of follow-up. In addition, hyperreflective giant interface particles were observed after nDSAEK in all patients. In vivo laser confocal microscopy can identify subclinical corneal abnormalities after nDSAEK such as subepithelial haze, host-recipient interface haze, host stromal needle-shaped materials, and host-recipient interface particles with characteristic giant particles. Further studies with this technology in a large number of patients and long-term follow-up are needed to understand fully the long-term corneal stromal changes after nDSAEK.
Voxel-based Gaussian naïve Bayes classification of ischemic stroke lesions in individual T1-weighted MRI scans.

PubMed

Griffis, Joseph C; Allendorfer, Jane B; Szaflarski, Jerzy P

2016-01-15

Manual lesion delineation by an expert is the standard for lesion identification in MRI scans, but it is time-consuming and can introduce subjective bias. Alternative methods often require multi-modal MRI data, user interaction, scans from a control population, and/or arbitrary statistical thresholding. We present an approach for automatically identifying stroke lesions in individual T1-weighted MRI scans using naïve Bayes classification. Probabilistic tissue segmentation and image algebra were used to create feature maps encoding information about missing and abnormal tissue. Leave-one-case-out training and cross-validation was used to obtain out-of-sample predictions for each of 30 cases with left hemisphere stroke lesions. Our method correctly predicted lesion locations for 30/30 un-trained cases. Post-processing with smoothing (8mm FWHM) and cluster-extent thresholding (100 voxels) was found to improve performance. Quantitative evaluations of post-processed out-of-sample predictions on 30 cases revealed high spatial overlap (mean Dice similarity coefficient=0.66) and volume agreement (mean percent volume difference=28.91; Pearson's r=0.97) with manual lesion delineations. Our automated approach agrees with manual tracing. It provides an alternative to automated methods that require multi-modal MRI data, additional control scans, or user interaction to achieve optimal performance. Our fully trained classifier has applications in neuroimaging and clinical contexts. Copyright © 2015 Elsevier B.V. All rights reserved.
Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

PubMed Central

Howat, William J; Blows, Fiona M; Provenzano, Elena; Brook, Mark N; Morris, Lorna; Gazinska, Patrycja; Johnson, Nicola; McDuffus, Leigh‐Anne; Miller, Jodi; Sawyer, Elinor J; Pinder, Sarah; van Deurzen, Carolien H M; Jones, Louise; Sironen, Reijo; Visscher, Daniel; Caldas, Carlos; Daley, Frances; Coulson, Penny; Broeks, Annegien; Sanders, Joyce; Wesseling, Jelle; Nevanlinna, Heli; Fagerholm, Rainer; Blomqvist, Carl; Heikkilä, Päivi; Ali, H Raza; Dawson, Sarah‐Jane; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli‐Matti; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W; Couch, Fergus J; Olson, Janet E; Devillee, Peter; Mesker, Wilma E; Seyaneve, Caroline M; Hollestelle, Antoinette; Benitez, Javier; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Bolla, Manjeet K; Easton, Douglas F; Schmidt, Marjanka K; Pharoah, Paul D; Sherman, Mark E

2014-01-01

Abstract Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results. PMID:27499890
Space station automation: the role of robotics and artificial intelligence (Invited Paper)

NASA Astrophysics Data System (ADS)

Park, W. T.; Firschein, O.

1985-12-01

Automation of the space station is necessary to make more effective use of the crew, to carry out repairs that are impractical or dangerous, and to monitor and control the many space station subsystems. Intelligent robotics and expert systems play a strong role in automation, and both disciplines are highly dependent on a common artificial intelligence (Al) technology base. The AI technology base provides the reasoning and planning capabilities needed in robotic tasks, such as perception of the environment and planning a path to a goal, and in expert systems tasks, such as control of subsystems and maintenance of equipment. This paper describes automation concepts for the space station, the specific robotic and expert systems required to attain this automation, and the research and development required. It also presents an evolutionary development plan that leads to fully automatic mobile robots for servicing satellites. Finally, we indicate the sequence of demonstrations and the research and development needed to confirm the automation capabilities. We emphasize that advanced robotics requires AI, and that to advance, AI needs the "real-world" problems provided by robotics.
Automated structure solution, density modification and model building.

PubMed

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.
Harnessing Vehicle Automation for Public Mobility -- An Overview of Ongoing Efforts

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

Young, Stanley E.

This presentation takes a look at the efforts to harness automated vehicle technology for public transport. The European CityMobil2 is the leading demonstration project in which automated shuttles were, or are planned to be, demonstrated in several cities and regions. The presentation provides a brief overview of the demonstrations at Oristano, Italy (July 2014), LaRochelle, France (Dec 2014), Lausanne, Switzerland (Apr 2015), Vantaa, Finland (July 2015), and Trikala, Greece (Sept 2015). In addition to technology exposition, the objectives included generating a legal framework for operation in each location and gaging the reaction of the public to unmanned shuttles, both ofmore » which were successfully achieved. Several such demonstrations are planned throughout the world, including efforts in North America in conjunction with the GoMentum Station in California. These early demonstration with low-speed automated shuttles provide a glimpse of the possible with a fully automated fleet of driverless vehicle providing a public transit service.« less
Bayesian ISOLA: new tool for automated centroid moment tensor inversion

NASA Astrophysics Data System (ADS)

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

2017-08-01

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 are rejected and full-waveform inversion in a space-time grid around a provided hypocentre. 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 frequency ranges. The method is tested on synthetic and observed data. It is applied on a data set from the Swiss seismic network and the results are compared with the existing high-quality MT catalogue. The software package programmed in Python is designed to be as versatile as possible in order to be applicable in various networks ranging from local to regional. The method can be applied either to the everyday network data flow, or to process large pre-existing earthquake catalogues and data sets.
Human-Automation Cooperation for Separation Assurance in Future NextGen Environments

NASA Technical Reports Server (NTRS)

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.
Current status and future prospects of an automated sample exchange system PAM for protein crystallography

NASA Astrophysics Data System (ADS)

Hiraki, M.; Yamada, Y.; Chavas, L. M. G.; Matsugaki, N.; Igarashi, N.; Wakatsuki, S.

2013-03-01

To achieve fully-automated and/or remote data collection in high-throughput X-ray experiments, the Structural Biology Research Centre at the Photon Factory (PF) has installed PF automated mounting system (PAM) for sample exchange robots at PF macromolecular crystallography beamlines BL-1A, BL-5A, BL-17A, AR-NW12A and AR-NE3A. We are upgrading the experimental systems, including the PAM for stable and efficient operation. To prevent human error in automated data collection, we installed a two-dimensional barcode reader for identification of the cassettes and sample pins. Because no liquid nitrogen pipeline in the PF experimental hutch is installed, the users commonly add liquid nitrogen using a small Dewar. To address this issue, an automated liquid nitrogen filling system that links a 100-liter tank to the robot Dewar has been installed on the PF macromolecular beamline. Here we describe this new implementation, as well as future prospects.
Signal amplification of FISH for automated detection using image cytometry.

PubMed

Truong, K; Boenders, J; Maciorowski, Z; Vielh, P; Dutrillaux, B; Malfoy, B; Bourgeois, C A

1997-05-01

The purpose of this study was to improve the detection of FISH signals, in order that spot counting by a fully automated image cytometer be comparable to that obtained visually under the microscope. Two systems of spot scoring, visual and automated counting, were investigated in parallel on stimulated human lymphocytes with FISH using a biotinylated centromeric probe for chromosome 3. Signal characteristics were first analyzed on images recorded with a coupled charge device (CCD) camera. Number of spots per nucleus were scored visually on these recorded images versus automatically with a DISCOVERY image analyzer. Several fluochromes, amplification and pretreatments were tested. Our results for both visual and automated scoring show that the tyramide amplification system (TSA) gives the best amplification of signal if pepsin treatment is applied prior to FISH. Accuracy of the automated scoring, however, remained low (58% of nuclei containing two spots) compared to the visual scoring because of the high intranuclear variation between FISH spots.

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