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

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.

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.

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.

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, ...

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.

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.

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

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).

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.

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

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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 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.

An automated method for the analysis of phenolic acids in plasma based on ion-pairing micro-extraction coupled on-line to gas chromatography/mass spectrometry with in-liner derivatisation.

PubMed

Peters, Sonja; Kaal, Erwin; Horsting, Iwan; Janssen, Hans-Gerd

2012-02-24

A new method is presented for the analysis of phenolic acids in plasma based on ion-pairing 'Micro-extraction in packed sorbent' (MEPS) coupled on-line to in-liner derivatisation-gas chromatography-mass spectrometry (GC-MS). The ion-pairing reagent served a dual purpose. It was used both to improve extraction yields of the more polar analytes and as the methyl donor in the automated in-liner derivatisation method. In this way, a fully automated procedure for the extraction, derivatisation and injection of a wide range of phenolic acids in plasma samples has been obtained. An extensive optimisation of the extraction and derivatisation procedure has been performed. The entire method showed excellent repeatabilities of under 10% and linearities of 0.99 or better for all phenolic acids. The limits of detection of the optimised method for the majority of phenolic acids were 10ng/mL or lower with three phenolic acids having less-favourable detection limits of around 100 ng/mL. Finally, the newly developed method has been applied in a human intervention trial in which the bioavailability of polyphenols from wine and tea was studied. Forty plasma samples could be analysed within 24h in a fully automated method including sample extraction, derivatisation and gas chromatographic analysis. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

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.

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

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.

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.

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.

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.

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.

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...

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.

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.

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 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.

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.

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

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

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.

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...

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

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

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.

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.

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

Fully automated tumor segmentation based on improved fuzzy connectedness algorithm in brain MR images.

PubMed

Harati, Vida; Khayati, Rasoul; Farzan, Abdolreza

2011-07-01

Uncontrollable and unlimited cell growth leads to tumor genesis in the brain. If brain tumors are not diagnosed early and cured properly, they could cause permanent brain damage or even death to patients. As in all methods of treatments, any information about tumor position and size is important for successful treatment; hence, finding an accurate and a fully automated method to give information to physicians is necessary. A fully automatic and accurate method for tumor region detection and segmentation in brain magnetic resonance (MR) images is suggested. The presented approach is an improved fuzzy connectedness (FC) algorithm based on a scale in which the seed point is selected automatically. This algorithm is independent of the tumor type in terms of its pixels intensity. Tumor segmentation evaluation results based on similarity criteria (similarity index (SI), overlap fraction (OF), and extra fraction (EF) are 92.89%, 91.75%, and 3.95%, respectively) indicate a higher performance of the proposed approach compared to the conventional methods, especially in MR images, in tumor regions with low contrast. Thus, the suggested method is useful for increasing the ability of automatic estimation of tumor size and position in brain tissues, which provides more accurate investigation of the required surgery, chemotherapy, and radiotherapy procedures. Copyright © 2011 Elsevier Ltd. All rights reserved.

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...

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.

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.

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.

Normalized gradient fields cross-correlation for automated detection of prostate in magnetic resonance images

NASA Astrophysics Data System (ADS)

Fotin, Sergei V.; Yin, Yin; Periaswamy, Senthil; Kunz, Justin; Haldankar, Hrishikesh; Muradyan, Naira; Cornud, François; Turkbey, Baris; Choyke, Peter L.

2012-02-01

Fully automated prostate segmentation helps to address several problems in prostate cancer diagnosis and treatment: it can assist in objective evaluation of multiparametric MR imagery, provides a prostate contour for MR-ultrasound (or CT) image fusion for computer-assisted image-guided biopsy or therapy planning, may facilitate reporting and enables direct prostate volume calculation. Among the challenges in automated analysis of MR images of the prostate are the variations of overall image intensities across scanners, the presence of nonuniform multiplicative bias field within scans and differences in acquisition setup. Furthermore, images acquired with the presence of an endorectal coil suffer from localized high-intensity artifacts at the posterior part of the prostate. In this work, a three-dimensional method for fast automated prostate detection based on normalized gradient fields cross-correlation, insensitive to intensity variations and coil-induced artifacts, is presented and evaluated. The components of the method, offline template learning and the localization algorithm, are described in detail. The method was validated on a dataset of 522 T2-weighted MR images acquired at the National Cancer Institute, USA that was split in two halves for development and testing. In addition, second dataset of 29 MR exams from Centre d'Imagerie Médicale Tourville, France were used to test the algorithm. The 95% confidence intervals for the mean Euclidean distance between automatically and manually identified prostate centroids were 4.06 +/- 0.33 mm and 3.10 +/- 0.43 mm for the first and second test datasets respectively. Moreover, the algorithm provided the centroid within the true prostate volume in 100% of images from both datasets. Obtained results demonstrate high utility of the detection method for a fully automated prostate segmentation.

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.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation.

PubMed

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

2017-04-01

With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.

On automating domain connectivity for overset grids

NASA Technical Reports Server (NTRS)

Chiu, Ing-Tsau

1994-01-01

An alternative method for domain connectivity among systems of overset grids is presented. Reference uniform Cartesian systems of points are used to achieve highly efficient domain connectivity, and form the basis for a future fully automated system. The Cartesian systems are used to approximated body surfaces and to map the computational space of component grids. By exploiting the characteristics of Cartesian Systems, Chimera type hole-cutting and identification of donor elements for intergrid boundary points can be carried out very efficiently. The method is tested for a range of geometrically complex multiple-body overset grid systems.

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.

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

Automation and Intensity Modulated Radiation Therapy for Individualized High-Quality Tangent Breast Treatment Plans

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

Purdie, Thomas G., E-mail: Tom.Purdie@rmp.uhn.on.ca; Department of Radiation Oncology, University of Toronto, Toronto, Ontario; Techna Institute, University Health Network, Toronto, Ontario

Purpose: To demonstrate the large-scale clinical implementation and performance of an automated treatment planning methodology for tangential breast intensity modulated radiation therapy (IMRT). Methods and Materials: Automated planning was used to prospectively plan tangential breast IMRT treatment for 1661 patients between June 2009 and November 2012. The automated planning method emulates the manual steps performed by the user during treatment planning, including anatomical segmentation, beam placement, optimization, dose calculation, and plan documentation. The user specifies clinical requirements of the plan to be generated through a user interface embedded in the planning system. The automated method uses heuristic algorithms to definemore » and simplify the technical aspects of the treatment planning process. Results: Automated planning was used in 1661 of 1708 patients receiving tangential breast IMRT during the time interval studied. Therefore, automated planning was applicable in greater than 97% of cases. The time for treatment planning using the automated process is routinely 5 to 6 minutes on standard commercially available planning hardware. We have shown a consistent reduction in plan rejections from plan reviews through the standard quality control process or weekly quality review multidisciplinary breast rounds as we have automated the planning process for tangential breast IMRT. Clinical plan acceptance increased from 97.3% using our previous semiautomated inverse method to 98.9% using the fully automated method. Conclusions: Automation has become the routine standard method for treatment planning of tangential breast IMRT at our institution and is clinically feasible on a large scale. The method has wide clinical applicability and can add tremendous efficiency, standardization, and quality to the current treatment planning process. The use of automated methods can allow centers to more rapidly adopt IMRT and enhance access to the documented improvements in care for breast cancer patients, using technologies that are widely available and already in clinical use.« less

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.

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

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.

Automation and intensity modulated radiation therapy for individualized high-quality tangent breast treatment plans.

PubMed

Purdie, Thomas G; Dinniwell, Robert E; Fyles, Anthony; Sharpe, Michael B

2014-11-01

To demonstrate the large-scale clinical implementation and performance of an automated treatment planning methodology for tangential breast intensity modulated radiation therapy (IMRT). Automated planning was used to prospectively plan tangential breast IMRT treatment for 1661 patients between June 2009 and November 2012. The automated planning method emulates the manual steps performed by the user during treatment planning, including anatomical segmentation, beam placement, optimization, dose calculation, and plan documentation. The user specifies clinical requirements of the plan to be generated through a user interface embedded in the planning system. The automated method uses heuristic algorithms to define and simplify the technical aspects of the treatment planning process. Automated planning was used in 1661 of 1708 patients receiving tangential breast IMRT during the time interval studied. Therefore, automated planning was applicable in greater than 97% of cases. The time for treatment planning using the automated process is routinely 5 to 6 minutes on standard commercially available planning hardware. We have shown a consistent reduction in plan rejections from plan reviews through the standard quality control process or weekly quality review multidisciplinary breast rounds as we have automated the planning process for tangential breast IMRT. Clinical plan acceptance increased from 97.3% using our previous semiautomated inverse method to 98.9% using the fully automated method. Automation has become the routine standard method for treatment planning of tangential breast IMRT at our institution and is clinically feasible on a large scale. The method has wide clinical applicability and can add tremendous efficiency, standardization, and quality to the current treatment planning process. The use of automated methods can allow centers to more rapidly adopt IMRT and enhance access to the documented improvements in care for breast cancer patients, using technologies that are widely available and already in clinical use. Copyright © 2014 Elsevier Inc. All rights reserved.

Interfacing a robotic station with a gas chromatograph for the full automation of the determination of organochlorine pesticides in vegetables

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

Torres, P.; Luque de Castro, M.D.

1996-12-31

A fully automated method for the determination of organochlorine pesticides in vegetables is proposed. The overall system acts as an {open_quotes}analytical black box{close_quotes} because a robotic station performs the prelimninary operations, from weighing to capping the leached analytes and location in an autosampler of an automated gas chromatograph with electron capture detection. The method has been applied to the determination of lindane, heptachlor, captan, chlordane and metoxcychlor in tea, marjoram, cinnamon, pennyroyal, and mint with good results in most cases. A gas chromatograph has been interfaced to a robotic station for the determination of pesticides in vegetables. 15 refs., 4more » figs., 2 tabs.« less

A detailed comparison of analysis processes for MCC-IMS data in disease classification—Automated methods can replace manual peak annotations

PubMed Central

Horsch, Salome; Kopczynski, Dominik; Kuthe, Elias; Baumbach, Jörg Ingo; Rahmann, Sven

2017-01-01

Motivation Disease classification from molecular measurements typically requires an analysis pipeline from raw noisy measurements to final classification results. Multi capillary column—ion mobility spectrometry (MCC-IMS) is a promising technology for the detection of volatile organic compounds in the air of exhaled breath. From raw measurements, the peak regions representing the compounds have to be identified, quantified, and clustered across different experiments. Currently, several steps of this analysis process require manual intervention of human experts. Our goal is to identify a fully automatic pipeline that yields competitive disease classification results compared to an established but subjective and tedious semi-manual process. Method We combine a large number of modern methods for peak detection, peak clustering, and multivariate classification into analysis pipelines for raw MCC-IMS data. We evaluate all combinations on three different real datasets in an unbiased cross-validation setting. We determine which specific algorithmic combinations lead to high AUC values in disease classifications across the different medical application scenarios. Results The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace-operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology. PMID:28910313

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.

Self Consistent Bathymetric Mapping From Robotic Vehicles in the Deep Ocean

DTIC Science & Technology

2005-06-01

that have been aligned in a consistent manner. Experimental results from the fully automated processing of a multibeam survey over the TAG hydrothermal structure at the Mid-Atlantic ridge are presented to validate the proposed method.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

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.

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.

Validity of Automated Choroidal Segmentation in SS-OCT and SD-OCT.

PubMed

Zhang, Li; Buitendijk, Gabriëlle H S; Lee, Kyungmoo; Sonka, Milan; Springelkamp, Henriët; Hofman, Albert; Vingerling, Johannes R; Mullins, Robert F; Klaver, Caroline C W; Abràmoff, Michael D

2015-05-01

To evaluate the validity of a novel fully automated three-dimensional (3D) method capable of segmenting the choroid from two different optical coherence tomography scanners: swept-source OCT (SS-OCT) and spectral-domain OCT (SD-OCT). One hundred eight subjects were imaged using SS-OCT and SD-OCT. A 3D method was used to segment the choroid and quantify the choroidal thickness along each A-scan. The segmented choroidal posterior boundary was evaluated by comparing to manual segmentation. Differences were assessed to test the agreement between segmentation results of the same subject. Choroidal thickness was defined as the Euclidian distance between Bruch's membrane and the choroidal posterior boundary, and reproducibility was analyzed using automatically and manually determined choroidal thicknesses. For SS-OCT, the average choroidal thickness of the entire 6- by 6-mm2 macular region was 219.5 μm (95% confidence interval [CI], 204.9-234.2 μm), and for SD-OCT it was 209.5 μm (95% CI, 197.9-221.0 μm). The agreement between automated and manual segmentations was high: Average relative difference was less than 5 μm, and average absolute difference was less than 15 μm. Reproducibility of choroidal thickness between repeated SS-OCT scans was high (coefficient of variation [CV] of 3.3%, intraclass correlation coefficient [ICC] of 0.98), and differences between SS-OCT and SD-OCT results were small (CV of 11.0%, ICC of 0.73). We have developed a fully automated 3D method for segmenting the choroid and quantifying choroidal thickness along each A-scan. The method yielded high validity. Our method can be used reliably to study local choroidal changes and may improve the diagnosis and management of patients with ocular diseases in which the choroid is affected.

Automated acoustic localization and call association for vocalizing humpback whales on the Navy's Pacific Missile Range Facility.

PubMed

Helble, Tyler A; Ierley, Glenn R; D'Spain, Gerald L; Martin, Stephen W

2015-01-01

Time difference of arrival (TDOA) methods for acoustically localizing multiple marine mammals have been applied to recorded data from the Navy's Pacific Missile Range Facility in order to localize and track humpback whales. Modifications to established methods were necessary in order to simultaneously track multiple animals on the range faster than real-time and in a fully automated way, while minimizing the number of incorrect localizations. The resulting algorithms were run with no human intervention at computational speeds faster than the data recording speed on over forty days of acoustic recordings from the range, spanning multiple years. Spatial localizations based on correlating sequences of units originating from within the range produce estimates having a standard deviation typically 10 m or less (due primarily to TDOA measurement errors), and a bias of 20 m or less (due primarily to sound speed mismatch). An automated method for associating units to individual whales is presented, enabling automated humpback song analyses to be performed.

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.

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.

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.

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.

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.

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.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation

PubMed Central

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

2017-01-01

Abstract. With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset. PMID:28612037

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.

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.

A fully automated method for simultaneous determination of aflatoxins and ochratoxin A in dried fruits by pressurized liquid extraction and online solid-phase extraction cleanup coupled to ultra-high-pressure liquid chromatography-tandem mass spectrometry.

PubMed

Campone, Luca; Piccinelli, Anna Lisa; Celano, Rita; Russo, Mariateresa; Valdés, Alberto; Ibáñez, Clara; Rastrelli, Luca

2015-04-01

According to current demands and future perspectives in food safety, this study reports a fast and fully automated analytical method for the simultaneous analysis of the mycotoxins with high toxicity and wide spread, aflatoxins (AFs) and ochratoxin A (OTA) in dried fruits, a high-risk foodstuff. The method is based on pressurized liquid extraction (PLE), with aqueous methanol (30%) at 110 °C, of the slurried dried fruit and online solid-phase extraction (online SPE) cleanup of the PLE extracts with a C18 cartridge. The purified sample was directly analysed by ultra-high-pressure liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) for sensitive and selective determination of AFs and OTA. The proposed analytical procedure was validated for different dried fruits (vine fruit, fig and apricot), providing method detection and quantification limits much lower than the AFs and OTA maximum levels imposed by EU regulation in dried fruit for direct human consumption. Also, recoveries (83-103%) and repeatability (RSD < 8, n = 3) meet the performance criteria required by EU regulation for the determination of the levels of mycotoxins in foodstuffs. The main advantage of the proposed method is full automation of the whole analytical procedure that reduces the time and cost of the analysis, sample manipulation and solvent consumption, enabling high-throughput analysis and highly accurate and precise results.

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.

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

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

Towards fully automated structure-based function prediction in structural genomics: a case study.

PubMed

Watson, James D; Sanderson, Steve; Ezersky, Alexandra; Savchenko, Alexei; Edwards, Aled; Orengo, Christine; Joachimiak, Andrzej; Laskowski, Roman A; Thornton, Janet M

2007-04-13

As the global Structural Genomics projects have picked up pace, the number of structures annotated in the Protein Data Bank as hypothetical protein or unknown function has grown significantly. A major challenge now involves the development of computational methods to assign functions to these proteins accurately and automatically. As part of the Midwest Center for Structural Genomics (MCSG) we have developed a fully automated functional analysis server, ProFunc, which performs a battery of analyses on a submitted structure. The analyses combine a number of sequence-based and structure-based methods to identify functional clues. After the first stage of the Protein Structure Initiative (PSI), we review the success of the pipeline and the importance of structure-based function prediction. As a dataset, we have chosen all structures solved by the MCSG during the 5 years of the first PSI. Our analysis suggests that two of the structure-based methods are particularly successful and provide examples of local similarity that is difficult to identify using current sequence-based methods. No one method is successful in all cases, so, through the use of a number of complementary sequence and structural approaches, the ProFunc server increases the chances that at least one method will find a significant hit that can help elucidate function. Manual assessment of the results is a time-consuming process and subject to individual interpretation and human error. We present a method based on the Gene Ontology (GO) schema using GO-slims that can allow the automated assessment of hits with a success rate approaching that of expert manual assessment.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Fully Mechanically Controlled Automated Electron Microscopic Tomography

DOE PAGES

Liu, Jinxin; Li, Hongchang; Zhang, Lei; ...

2016-07-11

Knowledge of three-dimensional (3D) structures of each individual particles of asymmetric and flexible proteins is essential in understanding those proteins' functions; but their structures are difficult to determine. Electron tomography (ET) provides a tool for imaging a single and unique biological object from a series of tilted angles, but it is challenging to image a single protein for three-dimensional (3D) reconstruction due to the imperfect mechanical control capability of the specimen goniometer under both a medium to high magnification (approximately 50,000-160,000×) and an optimized beam coherence condition. Here, we report a fully mechanical control method for automating ET data acquisitionmore » without using beam tilt/shift processes. This method could reduce the accumulation of beam tilt/shift that used to compensate the error from the mechanical control, but downgraded the beam coherence. Our method was developed by minimizing the error of the target object center during the tilting process through a closed-loop proportional-integral (PI) control algorithm. The validations by both negative staining (NS) and cryo-electron microscopy (cryo-EM) suggest that this method has a comparable capability to other ET methods in tracking target proteins while maintaining optimized beam coherence conditions for imaging.« less

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.

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.

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...

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Retinal blood vessel segmentation using fully convolutional network with transfer learning.

PubMed

Jiang, Zhexin; Zhang, Hao; Wang, Yi; Ko, Seok-Bum

2018-04-26

Since the retinal blood vessel has been acknowledged as an indispensable element in both ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the retinal vessel tree has become the prerequisite step for automated or computer-aided diagnosis systems. In this paper, a supervised method is presented based on a pre-trained fully convolutional network through transfer learning. This proposed method has simplified the typical retinal vessel segmentation problem from full-size image segmentation to regional vessel element recognition and result merging. Meanwhile, additional unsupervised image post-processing techniques are applied to this proposed method so as to refine the final result. Extensive experiments have been conducted on DRIVE, STARE, CHASE_DB1 and HRF databases, and the accuracy of the cross-database test on these four databases is state-of-the-art, which also presents the high robustness of the proposed approach. This successful result has not only contributed to the area of automated retinal blood vessel segmentation but also supports the effectiveness of transfer learning when applying deep learning technique to medical imaging. Copyright © 2018 Elsevier Ltd. All rights reserved.

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...

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.

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

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...

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.

Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features.

PubMed

Radüntz, Thea; Scouten, Jon; Hochmuth, Olaf; Meffert, Beate

2017-08-01

Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present. In this study, we propose a new approach for automated artifact elimination, which applies machine learning algorithms to ICA-based features. We compared the performance of our classifiers with the visual classification results given by experts. The best result with an accuracy rate of 95% was achieved using features obtained by range filtering of the topoplots and IC power spectra combined with an artificial neural network. Compared with the existing automated solutions, our proposed method is not limited to specific types of artifacts, electrode configurations, or number of EEG channels. The main advantages of the proposed method is that it provides an automatic, reliable, real-time capable, and practical tool, which avoids the need for the time-consuming manual selection of ICs during artifact removal.

Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features

NASA Astrophysics Data System (ADS)

Radüntz, Thea; Scouten, Jon; Hochmuth, Olaf; Meffert, Beate

2017-08-01

Objective. Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present. Approach. In this study, we propose a new approach for automated artifact elimination, which applies machine learning algorithms to ICA-based features. Main results. We compared the performance of our classifiers with the visual classification results given by experts. The best result with an accuracy rate of 95% was achieved using features obtained by range filtering of the topoplots and IC power spectra combined with an artificial neural network. Significance. Compared with the existing automated solutions, our proposed method is not limited to specific types of artifacts, electrode configurations, or number of EEG channels. The main advantages of the proposed method is that it provides an automatic, reliable, real-time capable, and practical tool, which avoids the need for the time-consuming manual selection of ICs during artifact removal.

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

NASA Astrophysics Data System (ADS)

Jiang, Luan; Ling, Shan; Li, Qiang

2016-03-01

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

A novel flow injection chemiluminescence method for automated and miniaturized determination of phenols in smoked food samples.

PubMed

Vakh, Christina; Evdokimova, Ekaterina; Pochivalov, Aleksei; Moskvin, Leonid; Bulatov, Andrey

2017-12-15

An easily performed fully automated and miniaturized flow injection chemiluminescence (CL) method for determination of phenols in smoked food samples has been proposed. This method includes the ultrasound assisted solid-liquid extraction coupled with gas-diffusion separation of phenols from smoked food sample and analytes absorption into a NaOH solution in a specially designed gas-diffusion cell. The flow system was designed to focus on automation and miniaturization with minimal sample and reagent consumption by inexpensive instrumentation. The luminol - N-bromosuccinimide system in an alkaline medium was used for the CL determination of phenols. The limit of detection of the proposed procedure was 3·10 -8 ·molL -1 (0.01mgkg -1 ) in terms of phenol. The presented method demonstrated to be a good tool for easy, rapid and cost-effective point-of-need screening phenols in smoked food samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Novel Automated Method for Analyzing Cylindrical Computed Tomography Data

NASA Technical Reports Server (NTRS)

Roth, D. J.; Burke, E. R.; Rauser, R. W.; Martin, R. E.

2011-01-01

A novel software method is presented that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography. This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2-D sheets in the vertical direction in addition to volume rendering and normal plane views provided by traditional CT software. The method is based on interior and exterior surface edge detection and under proper conditions, is FULLY AUTOMATED and requires no input from the user except the correct voxel dimension from the CT scan. The software is available from NASA in 32- and 64-bit versions that can be applied to gigabyte-sized data sets, processing data either in random access memory or primarily on the computer hard drive. Please inquire with the presenting author if further interested. This software differentiates itself in total from other possible re-slicing software solutions due to complete automation and advanced processing and analysis capabilities.

Automated Fast Screening Method for Cocaine Identification in Seized Drug Samples Using a Portable Fourier Transform Infrared (FT-IR) Instrument.

PubMed

Mainali, Dipak; Seelenbinder, John

2016-05-01

Quick and presumptive identification of seized drug samples without destroying evidence is necessary for law enforcement officials to control the trafficking and abuse of drugs. This work reports an automated screening method to detect the presence of cocaine in seized samples using portable Fourier transform infrared (FT-IR) spectrometers. The method is based on the identification of well-defined characteristic vibrational frequencies related to the functional group of the cocaine molecule and is fully automated through the use of an expert system. Traditionally, analysts look for key functional group bands in the infrared spectra and characterization of the molecules present is dependent on user interpretation. This implies the need for user expertise, especially in samples that likely are mixtures. As such, this approach is biased and also not suitable for non-experts. The method proposed in this work uses the well-established "center of gravity" peak picking mathematical algorithm and combines it with the conditional reporting feature in MicroLab software to provide an automated method that can be successfully employed by users with varied experience levels. The method reports the confidence level of cocaine present only when a certain number of cocaine related peaks are identified by the automated method. Unlike library search and chemometric methods that are dependent on the library database or the training set samples used to build the calibration model, the proposed method is relatively independent of adulterants and diluents present in the seized mixture. This automated method in combination with a portable FT-IR spectrometer provides law enforcement officials, criminal investigators, or forensic experts a quick field-based prescreening capability for the presence of cocaine in seized drug samples. © The Author(s) 2016.

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...

RootGraph: a graphic optimization tool for automated image analysis of plant roots

PubMed Central

Cai, Jinhai; Zeng, Zhanghui; Connor, Jason N.; Huang, Chun Yuan; Melino, Vanessa; Kumar, Pankaj; Miklavcic, Stanley J.

2015-01-01

This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. PMID:26224880

Topological leakage detection and freeze-and-grow propagation for improved CT-based airway segmentation

NASA Astrophysics Data System (ADS)

Nadeem, Syed Ahmed; Hoffman, Eric A.; Sieren, Jered P.; Saha, Punam K.

2018-03-01

Numerous large multi-center studies are incorporating the use of computed tomography (CT)-based characterization of the lung parenchyma and bronchial tree to understand chronic obstructive pulmonary disease status and progression. To the best of our knowledge, there are no fully automated airway tree segmentation methods, free of the need for user review. A failure in even a fraction of segmentation results necessitates manual revision of all segmentation masks which is laborious considering the thousands of image data sets evaluated in large studies. In this paper, we present a novel CT-based airway tree segmentation algorithm using topological leakage detection and freeze-and-grow propagation. The method is fully automated requiring no manual inputs or post-segmentation editing. It uses simple intensity-based connectivity and a freeze-and-grow propagation algorithm to iteratively grow the airway tree starting from an initial seed inside the trachea. It begins with a conservative parameter and then, gradually shifts toward more generous parameter values. The method was applied on chest CT scans of fifteen subjects at total lung capacity. Airway segmentation results were qualitatively assessed and performed comparably to established airway segmentation method with no major visual leakages.

A Fully Automated Method for Quantifying and Localizing White Matter Hyperintensities on MR Images

PubMed Central

Wu, Minjie; Rosano, Caterina; Butters, Meryl; Whyte, Ellen; Nable, Megan; Crooks, Ryan; Meltzer, Carolyn C.; Reynolds, Charles F.; Aizenstein3, Howard J.

2006-01-01

White matter hyperintensities (WMH), commonly found on T2-weighted FLAIR brain MR images in the elderly, are associated with a number of neuropsychiatric disorders, including vascular dementia, Alzheimer’s disease, and late-life depression. Previous MRI studies of WMHs have primarily relied on the subjective and global (i.e., full-brain) ratings of WMH grade. In the current study we implement and validate an automated method for quantifying and localizing WMHs. We adapt a fuzzy connected algorithm to automate the segmentation of WMHs and use a demons-based image registration to automate the anatomic localization of the WMHs using the Johns Hopkins University White Matter Atlas. The method is validated using the brain MR images acquired from eleven elderly subjects with late-onset late-life depression (LLD) and eight elderly controls. This dataset was chosen because LLD subjects are known to have significant WMH burden. The volumes of WMH identified in our automated method are compared with the accepted gold standard (manual ratings). A significant correlation of the automated method and the manual ratings is found (P<0.0001), thus demonstrating similar WMH quantifications of both methods. As has been shown in other studies e.g. (Taylor, et al. 2003)), we found there was a significantly greater WMH burden in the LLD subjects versus the controls for both the manual and automated method. The effect size was greater for the automated method, suggesting that it is a more specific measure. Additionally, we describe the anatomic localization of the WMHs in LLD subjects as well as in the control subjects, and detect the regions of interest (ROIs) specific for the WMH burden of LLD patients. Given the emergence of large neuroimage databases, techniques, such as that described here, will allow for a better understanding of the relationship between WMHs and neuropsychiatric disorders. PMID:17097277

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.

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

Fully automated analysis of four tobacco-specific N-nitrosamines in mainstream cigarette smoke using two-dimensional online solid phase extraction combined with liquid chromatography-tandem mass spectrometry.

PubMed

Zhang, Jie; Bai, Ruoshi; Yi, Xiaoli; Yang, Zhendong; Liu, Xingyu; Zhou, Jun; Liang, Wei

2016-01-01

A fully automated method for the detection of four tobacco-specific nitrosamines (TSNAs) in mainstream cigarette smoke (MSS) has been developed. The new developed method is based on two-dimensional online solid-phase extraction-liquid chromatography-tandem mass spectrometry (SPE/LC-MS/MS). The two dimensional SPE was performed in the method utilizing two cartridges with different extraction mechanisms to cleanup disturbances of different polarity to minimize sample matrix effects on each analyte. Chromatographic separation was achieved using a UPLC C18 reversed phase analytical column. Under the optimum online SPE/LC-MS/MS conditions, N'-nitrosonornicotine (NNN), N'-nitrosoanatabine (NAT), N'-nitrosoanabasine (NAB), and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) were baseline separated with good peak shapes. This method appears to be the most sensitive method yet reported for determination of TSNAs in mainstream cigarette smoke. The limits of quantification for NNN, NNK, NAT and NAB reached the levels of 6.0, 1.0, 3.0 and 0.6 pg/cig, respectively, which were well below the lowest levels of TSNAs in MSS of current commercial cigarettes. The accuracy of the measurement of four TSNAs was from 92.8 to 107.3%. The relative standard deviations of intra-and inter-day analysis were less than 5.4% and 7.5%, respectively. The main advantages of the method developed are fairly high sensitivity, selectivity and accuracy of results, minimum sample pre-treatment, full automation, and high throughput. As a part of the validation procedure, the developed method was applied to evaluate TSNAs yields for 27 top-selling commercial cigarettes in China. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Quantification of 31 illicit and medicinal drugs and metabolites in whole blood by fully automated solid-phase extraction and ultra-performance liquid chromatography-tandem mass spectrometry.

PubMed

Bjørk, Marie Kjærgaard; Simonsen, Kirsten Wiese; Andersen, David Wederkinck; Dalsgaard, Petur Weihe; Sigurðardóttir, Stella Rögn; Linnet, Kristian; Rasmussen, Brian Schou

2013-03-01

An efficient method for analyzing illegal and medicinal drugs in whole blood using fully automated sample preparation and short ultra-high-performance liquid chromatography-tandem mass spectrometry (MS/MS) run time is presented. A selection of 31 drugs, including amphetamines, cocaine, opioids, and benzodiazepines, was used. In order to increase the efficiency of routine analysis, a robotic system based on automated liquid handling and capable of handling all unit operation for sample preparation was built on a Freedom Evo 200 platform with several add-ons from Tecan and third-party vendors. Solid-phase extraction was performed using Strata X-C plates. Extraction time for 96 samples was less than 3 h. Chromatography was performed using an ACQUITY UPLC system (Waters Corporation, Milford, USA). Analytes were separated on a 100 mm × 2.1 mm, 1.7 μm Acquity UPLC CSH C(18) column using a 6.5 min 0.1 % ammonia (25 %) in water/0.1 % ammonia (25 %) in methanol gradient and quantified by MS/MS (Waters Quattro Premier XE) in multiple-reaction monitoring mode. Full validation, including linearity, precision and trueness, matrix effect, ion suppression/enhancement of co-eluting analytes, recovery, and specificity, was performed. The method was employed successfully in the laboratory and used for routine analysis of forensic material. In combination with tetrahydrocannabinol analysis, the method covered 96 % of cases involving driving under the influence of drugs. The manual labor involved in preparing blood samples, solvents, etc., was reduced to a half an hour per batch. The automated sample preparation setup also minimized human exposure to hazardous materials, provided highly improved ergonomics, and eliminated manual pipetting.

Barcoding T Cell Calcium Response Diversity with Methods for Automated and Accurate Analysis of Cell Signals (MAAACS)

PubMed Central

Sergé, Arnauld; Bernard, Anne-Marie; Phélipot, Marie-Claire; Bertaux, Nicolas; Fallet, Mathieu; Grenot, Pierre; Marguet, Didier; He, Hai-Tao; Hamon, Yannick

2013-01-01

We introduce a series of experimental procedures enabling sensitive calcium monitoring in T cell populations by confocal video-microscopy. Tracking and post-acquisition analysis was performed using Methods for Automated and Accurate Analysis of Cell Signals (MAAACS), a fully customized program that associates a high throughput tracking algorithm, an intuitive reconnection routine and a statistical platform to provide, at a glance, the calcium barcode of a population of individual T-cells. Combined with a sensitive calcium probe, this method allowed us to unravel the heterogeneity in shape and intensity of the calcium response in T cell populations and especially in naive T cells, which display intracellular calcium oscillations upon stimulation by antigen presenting cells. PMID:24086124

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

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.

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods

PubMed Central

Burlina, Philippe; Billings, Seth; Joshi, Neil

2017-01-01

Objective To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Methods Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and “engineered” features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. Results The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). Conclusions This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification. PMID:28854220

Automated contour detection in X-ray left ventricular angiograms using multiview active appearance models and dynamic programming.

PubMed

Oost, Elco; Koning, Gerhard; Sonka, Milan; Oemrawsingh, Pranobe V; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2006-09-01

This paper describes a new approach to the automated segmentation of X-ray left ventricular (LV) angiograms, based on active appearance models (AAMs) and dynamic programming. A coupling of shape and texture information between the end-diastolic (ED) and end-systolic (ES) frame was achieved by constructing a multiview AAM. Over-constraining of the model was compensated for by employing dynamic programming, integrating both intensity and motion features in the cost function. Two applications are compared: a semi-automatic method with manual model initialization, and a fully automatic algorithm. The first proved to be highly robust and accurate, demonstrating high clinical relevance. Based on experiments involving 70 patient data sets, the algorithm's success rate was 100% for ED and 99% for ES, with average unsigned border positioning errors of 0.68 mm for ED and 1.45 mm for ES. Calculated volumes were accurate and unbiased. The fully automatic algorithm, with intrinsically less user interaction was less robust, but showed a high potential, mostly due to a controlled gradient descent in updating the model parameters. The success rate of the fully automatic method was 91% for ED and 83% for ES, with average unsigned border positioning errors of 0.79 mm for ED and 1.55 mm for ES.

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

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.

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.

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.

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

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...

On automating domain connectivity for overset grids

NASA Technical Reports Server (NTRS)

Chiu, Ing-Tsau; Meakin, Robert L.

1995-01-01

An alternative method for domain connectivity among systems of overset grids is presented. Reference uniform Cartesian systems of points are used to achieve highly efficient domain connectivity, and form the basis for a future fully automated system. The Cartesian systems are used to approximate body surfaces and to map the computational space of component grids. By exploiting the characteristics of Cartesian systems, Chimera type hole-cutting and identification of donor elements for intergrid boundary points can be carried out very efficiently. The method is tested for a range of geometrically complex multiple-body overset grid systems. A dynamic hole expansion/contraction algorithm is also implemented to obtain optimum domain connectivity; however, it is tested only for geometry of generic shapes.

Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods.

PubMed

Burlina, Philippe; Billings, Seth; Joshi, Neil; Albayda, Jemima

2017-01-01

To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.

Using microwave Doppler radar in automated manufacturing applications

NASA Astrophysics Data System (ADS)

Smith, Gregory C.

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

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

PubMed

Andersen, David W; Linnet, Kristian

2014-01-01

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

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…

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.

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.

Profiling of Participants in Chat Conversations Using Creativity-Based Heuristics

ERIC Educational Resources Information Center

Chiru, Costin-Gabriel; Rebedea, Traian

2017-01-01

This article proposes a new fully automated method for identifying creativity that is manifested in a divergent task. The task is represented by chat conversations in small groups, each group having to debate on the same topics, with the purpose of better understanding the discussed concepts. The chat conversations were created by undergraduate…

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

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.

Fully-Automated High-Throughput NMR System for Screening of Haploid Kernels of Maize (Corn) by Measurement of Oil Content

PubMed Central

Xu, Xiaoping; Huang, Qingming; Chen, Shanshan; Yang, Peiqiang; Chen, Shaojiang; Song, Yiqiao

2016-01-01

One of the modern crop breeding techniques uses doubled haploid plants that contain an identical pair of chromosomes in order to accelerate the breeding process. Rapid haploid identification method is critical for large-scale selections of double haploids. The conventional methods based on the color of the endosperm and embryo seeds are slow, manual and prone to error. On the other hand, there exists a significant difference between diploid and haploid seeds generated by high oil inducer, which makes it possible to use oil content to identify the haploid. This paper describes a fully-automated high-throughput NMR screening system for maize haploid kernel identification. The system is comprised of a sampler unit to select a single kernel to feed for measurement of NMR and weight, and a kernel sorter to distribute the kernel according to the measurement result. Tests of the system show a consistent accuracy of 94% with an average screening time of 4 seconds per kernel. Field test result is described and the directions for future improvement are discussed. PMID:27454427

Rapid test for the detection of hazardous microbiological material

NASA Astrophysics Data System (ADS)

Mordmueller, Mario; Bohling, Christian; John, Andreas; Schade, Wolfgang

2009-09-01

After attacks with anthrax pathogens have been committed since 2001 all over the world the fast detection and determination of biological samples has attracted interest. A very promising method for a rapid test is Laser Induced Breakdown Spectroscopy (LIBS). LIBS is an optical method which uses time-resolved or time-integrated spectral analysis of optical plasma emission after pulsed laser excitation. Even though LIBS is well established for the determination of metals and other inorganic materials the analysis of microbiological organisms is difficult due to their very similar stoichiometric composition. To analyze similar LIBS-spectra computer assisted chemometrics is a very useful approach. In this paper we report on first results of developing a compact and fully automated rapid test for the detection of hazardous microbiological material. Experiments have been carried out with two setups: A bulky one which is composed of standard laboratory components and a compact one consisting of miniaturized industrial components. Both setups work at an excitation wavelength of λ=1064nm (Nd:YAG). Data analysis is done by Principal Component Analysis (PCA) with an adjacent neural network for fully automated sample identification.

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

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

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.

A new method for automated high-dimensional lesion segmentation evaluated in vascular injury and applied to the human occipital lobe.

PubMed

Mah, Yee-Haur; Jager, Rolf; Kennard, Christopher; Husain, Masud; Nachev, Parashkev

2014-07-01

Making robust inferences about the functional neuroanatomy of the brain is critically dependent on experimental techniques that examine the consequences of focal loss of brain function. Unfortunately, the use of the most comprehensive such technique-lesion-function mapping-is complicated by the need for time-consuming and subjective manual delineation of the lesions, greatly limiting the practicability of the approach. Here we exploit a recently-described general measure of statistical anomaly, zeta, to devise a fully-automated, high-dimensional algorithm for identifying the parameters of lesions within a brain image given a reference set of normal brain images. We proceed to evaluate such an algorithm in the context of diffusion-weighted imaging of the commonest type of lesion used in neuroanatomical research: ischaemic damage. Summary performance metrics exceed those previously published for diffusion-weighted imaging and approach the current gold standard-manual segmentation-sufficiently closely for fully-automated lesion-mapping studies to become a possibility. We apply the new method to 435 unselected images of patients with ischaemic stroke to derive a probabilistic map of the pattern of damage in lesions involving the occipital lobe, demonstrating the variation of anatomical resolvability of occipital areas so as to guide future lesion-function studies of the region. Copyright © 2012 Elsevier 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).

Method of transition from 3D model to its ontological representation in aircraft design process

NASA Astrophysics Data System (ADS)

Govorkov, A. S.; Zhilyaev, A. S.; Fokin, I. V.

2018-05-01

This paper proposes the method of transition from a 3D model to its ontological representation and describes its usage in the aircraft design process. The problems of design for manufacturability and design automation are also discussed. The introduced method is to aim to ease the process of data exchange between important aircraft design phases, namely engineering and design control. The method is also intended to increase design speed and 3D model customizability. This requires careful selection of the complex systems (CAD / CAM / CAE / PDM), providing the basis for the integration of design and technological preparation of production and more fully take into account the characteristics of products and processes for their manufacture. It is important to solve this problem, as investment in the automation define the company's competitiveness in the years ahead.

Fully convolutional neural networks for polyp segmentation in colonoscopy

NASA Astrophysics Data System (ADS)

Brandao, Patrick; Mazomenos, Evangelos; Ciuti, Gastone; Caliò, Renato; Bianchi, Federico; Menciassi, Arianna; Dario, Paolo; Koulaouzidis, Anastasios; Arezzo, Alberto; Stoyanov, Danail

2017-03-01

Colorectal cancer (CRC) is one of the most common and deadliest forms of cancer, accounting for nearly 10% of all forms of cancer in the world. Even though colonoscopy is considered the most effective method for screening and diagnosis, the success of the procedure is highly dependent on the operator skills and level of hand-eye coordination. In this work, we propose to adapt fully convolution neural networks (FCN), to identify and segment polyps in colonoscopy images. We converted three established networks into a fully convolution architecture and fine-tuned their learned representations to the polyp segmentation task. We validate our framework on the 2015 MICCAI polyp detection challenge dataset, surpassing the state-of-the-art in automated polyp detection. Our method obtained high segmentation accuracy and a detection precision and recall of 73.61% and 86.31%, respectively.

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

PubMed

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

2017-01-01

To develop and evaluate a method that can fully automatically identify the vessel wall boundaries and quantify the wall thickness for both common carotid artery (CCA) and descending aorta (DAO) from axial magnetic resonance (MR) images. 3T MRI data acquired with T 1 -weighted gradient-echo black-blood imaging sequence from carotid (39 subjects) and aorta (39 subjects) were used to develop and test the algorithm. The vessel wall segmentation was achieved by respectively fitting a 3D cylindrical B-spline surface to the boundaries of lumen and outer wall. The tube-fitting was based on the edge detection performed on the signal intensity (SI) profile along the surface normal. To achieve a fully automated process, Hough Transform (HT) was developed to estimate the lumen centerline and radii for the target vessel. Using the outputs of HT, a tube model for lumen segmentation was initialized and deformed to fit the image data. Finally, lumen segmentation was dilated to initiate the adaptation procedure of outer wall tube. The algorithm was validated by determining: 1) its performance against manual tracing; 2) its interscan reproducibility in quantifying vessel wall thickness (VWT); 3) its capability of detecting VWT difference in hypertensive patients compared with healthy controls. Statistical analysis including Bland-Altman analysis, t-test, and sample size calculation were performed for the purpose of algorithm evaluation. The mean distance between the manual and automatically detected lumen/outer wall contours was 0.00 ± 0.23/0.09 ± 0.21 mm for CCA and 0.12 ± 0.24/0.14 ± 0.35 mm for DAO. No significant difference was observed between the interscan VWT assessment using automated segmentation for both CCA (P = 0.19) and DAO (P = 0.94). Both manual and automated segmentation detected significantly higher carotid (P = 0.016 and P = 0.005) and aortic (P < 0.001 and P = 0.021) wall thickness in the hypertensive patients. A reliable and reproducible pipeline for fully automatic vessel wall quantification was developed and validated on healthy volunteers as well as patients with increased vessel wall thickness. This method holds promise for helping in efficient image interpretation for large-scale cohort studies. 4 J. Magn. Reson. Imaging 2017;45:215-228. © 2016 International Society for Magnetic Resonance in Medicine.

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.

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.

Transformation From a Conventional Clinical Microbiology Laboratory to Full Automation.

PubMed

Moreno-Camacho, José L; Calva-Espinosa, Diana Y; Leal-Leyva, Yoseli Y; Elizalde-Olivas, Dolores C; Campos-Romero, Abraham; Alcántar-Fernández, Jonathan

2017-12-22

To validate the performance, reproducibility, and reliability of BD automated instruments in order to establish a fully automated clinical microbiology laboratory. We used control strains and clinical samples to assess the accuracy, reproducibility, and reliability of the BD Kiestra WCA, the BD Phoenix, and BD Bruker MALDI-Biotyper instruments and compared them to previously established conventional methods. The following processes were evaluated: sample inoculation and spreading, colony counts, sorting of cultures, antibiotic susceptibility test, and microbial identification. The BD Kiestra recovered single colonies in less time than conventional methods (e.g. E. coli, 7h vs 10h, respectively) and agreement between both methodologies was excellent for colony counts (κ=0.824) and sorting cultures (κ=0.821). Antibiotic susceptibility tests performed with BD Phoenix and disk diffusion demonstrated 96.3% agreement with both methods. Finally, we compared microbial identification in BD Phoenix and Bruker MALDI-Biotyper and observed perfect agreement (κ=1) and identification at a species level for control strains. Together these instruments allow us to process clinical urine samples in 36h (effective time). The BD automated technologies have improved performance compared with conventional methods, and are suitable for its implementation in very busy microbiology laboratories. © American Society for Clinical Pathology 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

A novel automated direct measurement method for total antioxidant capacity using a new generation, more stable ABTS radical cation.

PubMed

Erel, Ozcan

2004-04-01

To develop a novel colorimetric and automated direct measurement method for total antioxidant capacity (TAC). A new generation, more stable, colored 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid radical cation (ABTS(*+)) was employed. The ABTS(*+) is decolorized by antioxidants according to their concentrations and antioxidant capacities. This change in color is measured as a change in absorbance at 660 nm. This process is applied to an automated analyzer and the assay is calibrated with Trolox. The novel assay is linear up to 6 mmol Trolox equivalent/l, its precision values are lower than 3%, and there is no interference from hemoglobin, bilirubin, EDTA, or citrate. The method developed is significantly correlated with the Randox- total antioxidant status (TAS) assay (r = 0.897, P < 0.0001; n = 91) and with the ferric reducing ability of plasma (FRAP) assay (r = 0.863, P < 0.0001; n = 110). Serum TAC level was lower in patients with major depression (1.69 +/- 0.11 mmol Trolox equivalent/l) than in healthy subjects (1.75 +/- 0.08 mmol Trolox equivalent/l, P = 0.041). This easy, stable, reliable, sensitive, inexpensive, and fully automated method described can be used to measure total antioxidant capacity.

Automated feature detection and identification in digital point-ordered signals

DOEpatents

Oppenlander, Jane E.; Loomis, Kent C.; Brudnoy, David M.; Levy, Arthur J.

1998-01-01

A computer-based automated method to detect and identify features in digital point-ordered signals. The method is used for processing of non-destructive test signals, such as eddy current signals obtained from calibration standards. The signals are first automatically processed to remove noise and to determine a baseline. Next, features are detected in the signals using mathematical morphology filters. Finally, verification of the features is made using an expert system of pattern recognition methods and geometric criteria. The method has the advantage that standard features can be, located without prior knowledge of the number or sequence of the features. Further advantages are that standard features can be differentiated from irrelevant signal features such as noise, and detected features are automatically verified by parameters extracted from the signals. The method proceeds fully automatically without initial operator set-up and without subjective operator feature judgement.

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.

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.

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.

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.

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.

Evaluation of an artificial intelligence guided inverse planning system: clinical case study.

PubMed

Yan, Hui; Yin, Fang-Fang; Willett, Christopher

2007-04-01

An artificial intelligence (AI) guided method for parameter adjustment of inverse planning was implemented on a commercial inverse treatment planning system. For evaluation purpose, four typical clinical cases were tested and the results from both plans achieved by automated and manual methods were compared. The procedure of parameter adjustment mainly consists of three major loops. Each loop is in charge of modifying parameters of one category, which is carried out by a specially customized fuzzy inference system. A physician prescribed multiple constraints for a selected volume were adopted to account for the tradeoff between prescription dose to the PTV and dose-volume constraints for critical organs. The searching process for an optimal parameter combination began with the first constraint, and proceeds to the next until a plan with acceptable dose was achieved. The initial setup of the plan parameters was the same for each case and was adjusted independently by both manual and automated methods. After the parameters of one category were updated, the intensity maps of all fields were re-optimized and the plan dose was subsequently re-calculated. When final plan arrived, the dose statistics were calculated from both plans and compared. For planned target volume (PTV), the dose for 95% volume is up to 10% higher in plans using the automated method than those using the manual method. For critical organs, an average decrease of the plan dose was achieved. However, the automated method cannot improve the plan dose for some critical organs due to limitations of the inference rules currently employed. For normal tissue, there was no significant difference between plan doses achieved by either automated or manual method. With the application of AI-guided method, the basic parameter adjustment task can be accomplished automatically and a comparable plan dose was achieved in comparison with that achieved by the manual method. Future improvements to incorporate case-specific inference rules are essential to fully automate the inverse planning process.

Evaluating the efficacy of fully automated approaches for the selection of eye blink ICA components

PubMed Central

Pontifex, Matthew B.; Miskovic, Vladimir; Laszlo, Sarah

2017-01-01

Independent component analysis (ICA) offers a powerful approach for the isolation and removal of eye blink artifacts from EEG signals. Manual identification of the eye blink ICA component by inspection of scalp map projections, however, is prone to error, particularly when non-artifactual components exhibit topographic distributions similar to the blink. The aim of the present investigation was to determine the extent to which automated approaches for selecting eye blink related ICA components could be utilized to replace manual selection. We evaluated popular blink selection methods relying on spatial features [EyeCatch()], combined stereotypical spatial and temporal features [ADJUST()], and a novel method relying on time-series features alone [icablinkmetrics()] using both simulated and real EEG data. The results of this investigation suggest that all three methods of automatic component selection are able to accurately identify eye blink related ICA components at or above the level of trained human observers. However, icablinkmetrics(), in particular, appears to provide an effective means of automating ICA artifact rejection while at the same time eliminating human errors inevitable during manual component selection and false positive component identifications common in other automated approaches. Based upon these findings, best practices for 1) identifying artifactual components via automated means and 2) reducing the accidental removal of signal-related ICA components are discussed. PMID:28191627

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.

Fully automated calculation of cardiothoracic ratio in digital chest radiographs

NASA Astrophysics Data System (ADS)

Cong, Lin; Jiang, Luan; Chen, Gang; Li, Qiang

2017-03-01

The calculation of Cardiothoracic Ratio (CTR) in digital chest radiographs would be useful for cardiac anomaly assessment and heart enlargement related disease indication. The purpose of this study was to develop and evaluate a fully automated scheme for calculation of CTR in digital chest radiographs. Our automated method consisted of three steps, i.e., lung region localization, lung segmentation, and CTR calculation. We manually annotated the lung boundary with 84 points in 100 digital chest radiographs, and calculated an average lung model for the subsequent work. Firstly, in order to localize the lung region, generalized Hough transform was employed to identify the upper, lower, and outer boundaries of lung by use of Sobel gradient information. The average lung model was aligned to the localized lung region to obtain the initial lung outline. Secondly, we separately applied dynamic programming method to detect the upper, lower, outer and inner boundaries of lungs, and then linked the four boundaries to segment the lungs. Based on the identified outer boundaries of left lung and right lung, we corrected the center and the declination of the original radiography. Finally, CTR was calculated as a ratio of the transverse diameter of the heart to the internal diameter of the chest, based on the segmented lungs. The preliminary results on 106 digital chest radiographs showed that the proposed method could obtain accurate segmentation of lung based on subjective observation, and achieved sensitivity of 88.9% (40 of 45 abnormalities), and specificity of 100% (i.e. 61 of 61 normal) for the identification of heart enlargements.

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

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

Automated breast segmentation in ultrasound computer tomography SAFT images

NASA Astrophysics Data System (ADS)

Hopp, T.; You, W.; Zapf, M.; Tan, W. Y.; Gemmeke, H.; Ruiter, N. V.

2017-03-01

Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.

An Automated System for Skeletal Maturity Assessment by Extreme Learning Machines

PubMed Central

Mansourvar, Marjan; Shamshirband, Shahaboddin; Raj, Ram Gopal; Gunalan, Roshan; Mazinani, Iman

2015-01-01

Assessing skeletal age is a subjective and tedious examination process. Hence, automated assessment methods have been developed to replace manual evaluation in medical applications. In this study, a new fully automated method based on content-based image retrieval and using extreme learning machines (ELM) is designed and adapted to assess skeletal maturity. The main novelty of this approach is it overcomes the segmentation problem as suffered by existing systems. The estimation results of ELM models are compared with those of genetic programming (GP) and artificial neural networks (ANNs) models. The experimental results signify improvement in assessment accuracy over GP and ANN, while generalization capability is possible with the ELM approach. Moreover, the results are indicated that the ELM model developed can be used confidently in further work on formulating novel models of skeletal age assessment strategies. According to the experimental results, the new presented method has the capacity to learn many hundreds of times faster than traditional learning methods and it has sufficient overall performance in many aspects. It has conclusively been found that applying ELM is particularly promising as an alternative method for evaluating skeletal age. PMID:26402795

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

Cleaning method and apparatus

DOEpatents

Jackson, Darryl D.; Hollen, Robert M.

1983-01-01

A new automatable cleaning apparatus which makes use of a method of very thoroughly and quickly cleaning a gauze electrode used in chemical analyses is given. The method generates very little waste solution, and this is very important in analyzing radioactive materials, especially in aqueous solutions. The cleaning apparatus can be used in a larger, fully automated controlled potential coulometric apparatus. About 99.98% of a 5 mg. plutonium sample was removed in less than 3 minutes, using only about 60 ml. of rinse solution and two main rinse steps.

SEM AutoAnalysis: enhancing photomask and NIL defect disposition and review

NASA Astrophysics Data System (ADS)

Schulz, Kristian; Egodage, Kokila; Tabbone, Gilles; Ehrlich, Christian; Garetto, Anthony

2017-06-01

For defect disposition and repair verification regarding printability, AIMS™ is the state of the art measurement tool in industry. With its unique capability of capturing aerial images of photomasks it is the one method that comes closest to emulating the printing behaviour of a scanner. However for nanoimprint lithography (NIL) templates aerial images cannot be applied to evaluate the success of a repair process. Hence, for NIL defect dispositioning scanning, electron microscopy (SEM) imaging is the method of choice. In addition, it has been a standard imaging method for further root cause analysis of defects and defect review on optical photomasks which enables 2D or even 3D mask profiling at high resolutions. In recent years a trend observed in mask shops has been the automation of processes that traditionally were driven by operators. This of course has brought many advantages one of which is freeing cost intensive labour from conducting repetitive and tedious work. Furthermore, it reduces variability in processes due to different operator skill and experience levels which at the end contributes to eliminating the human factor. Taking these factors into consideration, one of the software based solutions available under the FAVOR® brand to support customer needs is the aerial image evaluation software, AIMS™ AutoAnalysis (AAA). It provides fully automated analysis of AIMS™ images and runs in parallel to measurements. This is enabled by its direct connection and communication with the AIMS™tools. As one of many positive outcomes, generating automated result reports is facilitated, standardizing the mask manufacturing workflow. Today, AAA has been successfully introduced into production at multiple customers and is supporting the workflow as described above. These trends indeed have triggered the demand for similar automation with respect to SEM measurements leading to the development of SEM AutoAnalysis (SAA). It aims towards a fully automated SEM image evaluation process utilizing a completely different algorithm due to the different nature of SEM images and aerial images. Both AAA and SAA are the building blocks towards an image evaluation suite in the mask shop industry.

Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

PubMed Central

Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.

2017-01-01

Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800

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...

Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

NASA Astrophysics Data System (ADS)

Javanshir Moghaddam, Mandana; Tan, Tao; Karssemeijer, Nico; Platel, Bram

2014-03-01

Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.

An automated method to find reaction mechanisms and solve the kinetics in organometallic catalysis.

PubMed

Varela, J A; Vázquez, S A; Martínez-Núñez, E

2017-05-01

A novel computational method is proposed in this work for use in discovering reaction mechanisms and solving the kinetics of transition metal-catalyzed reactions. The method does not rely on either chemical intuition or assumed a priori mechanisms, and it works in a fully automated fashion. Its core is a procedure, recently developed by one of the authors, that combines accelerated direct dynamics with an efficient geometry-based post-processing algorithm to find transition states (Martinez-Nunez, E., J. Comput. Chem. 2015 , 36 , 222-234). In the present work, several auxiliary tools have been added to deal with the specific features of transition metal catalytic reactions. As a test case, we chose the cobalt-catalyzed hydroformylation of ethylene because of its well-established mechanism, and the fact that it has already been used in previous automated computational studies. Besides the generally accepted mechanism of Heck and Breslow, several side reactions, such as hydrogenation of the alkene, emerged from our calculations. Additionally, the calculated rate law for the hydroformylation reaction agrees reasonably well with those obtained in previous experimental and theoretical studies.

Shallow water benthic imaging and substrate characterization using recreational-grade sidescan-sonar

USGS Publications Warehouse

Buscombe, Daniel D.

2017-01-01

In recent years, lightweight, inexpensive, vessel-mounted ‘recreational grade’ sonar systems have rapidly grown in popularity among aquatic scientists, for swath imaging of benthic substrates. To promote an ongoing ‘democratization’ of acoustical imaging of shallow water environments, methods to carry out geometric and radiometric correction and georectification of sonar echograms are presented, based on simplified models for sonar-target geometry and acoustic backscattering and attenuation in shallow water. Procedures are described for automated removal of the acoustic shadows, identification of bed-water interface for situations when the water is too turbid or turbulent for reliable depth echosounding, and for automated bed substrate classification based on singlebeam full-waveform analysis. These methods are encoded in an open-source and freely-available software package, which should further facilitate use of recreational-grade sidescan sonar, in a fully automated and objective manner. The sequential correction, mapping, and analysis steps are demonstrated using a data set from a shallow freshwater environment.

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.

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.

Towards black-box calculations of tunneling splittings obtained from vibrational structure methods based on normal coordinates.

PubMed

Neff, Michael; Rauhut, Guntram

2014-02-05

Multidimensional potential energy surfaces obtained from explicitly correlated coupled-cluster calculations and further corrections for high-order correlation contributions, scalar relativistic effects and core-correlation energy contributions were generated in a fully automated fashion for the double-minimum benchmark systems OH3(+) and NH3. The black-box generation of the potentials is based on normal coordinates, which were used in the underlying multimode expansions of the potentials and the μ-tensor within the Watson operator. Normal coordinates are not the optimal choice for describing double-minimum potentials and the question remains if they can be used for accurate calculations at all. However, their unique definition is an appealing feature, which removes remaining errors in truncated potential expansions arising from different choices of curvilinear coordinate systems. Fully automated calculations are presented, which demonstrate, that the proposed scheme allows for the determination of energy levels and tunneling splittings as a routine application. Copyright © 2013 Elsevier B.V. All rights reserved.

Automatic analysis of dividing cells in live cell movies to detect mitotic delays and correlate phenotypes in time.

PubMed

Harder, Nathalie; Mora-Bermúdez, Felipe; Godinez, William J; Wünsche, Annelie; Eils, Roland; Ellenberg, Jan; Rohr, Karl

2009-11-01

Live-cell imaging allows detailed dynamic cellular phenotyping for cell biology and, in combination with small molecule or drug libraries, for high-content screening. Fully automated analysis of live cell movies has been hampered by the lack of computational approaches that allow tracking and recognition of individual cell fates over time in a precise manner. Here, we present a fully automated approach to analyze time-lapse movies of dividing cells. Our method dynamically categorizes cells into seven phases of the cell cycle and five aberrant morphological phenotypes over time. It reliably tracks cells and their progeny and can thus measure the length of mitotic phases and detect cause and effect if mitosis goes awry. We applied our computational scheme to annotate mitotic phenotypes induced by RNAi gene knockdown of CKAP5 (also known as ch-TOG) or by treatment with the drug nocodazole. Our approach can be readily applied to comparable assays aiming at uncovering the dynamic cause of cell division phenotypes.

Fully automated measuring setup for tactile coordinate measuring machine for three dimensional measurement of freeform eyeglass frames

NASA Astrophysics Data System (ADS)

Rückwardt, M.; Göpfert, A.; Correns, M.; Schellhorn, M.; Linß, G.

2010-07-01

Coordinate measuring machines are high precession all-rounder in three dimensional measuring. Therefore the versatility of parameters and expandability of additionally hardware is very comprehensive. Consequently you need much expert knowledge of the user and mostly a lot of advanced information about the measuring object. In this paper a coordinate measuring machine and a specialized measuring machine are compared at the example of the measuring of eyeglass frames. For this case of three dimensional measuring challenges the main focus is divided into metrological and economical aspects. At first there is shown a fully automated method for tactile measuring of this abstract form. At second there is shown a comparison of the metrological characteristics of a coordinate measuring machine and a tracer for eyeglass frames. The result is in favour to the coordinate measuring machine. It was not surprising in these aspects. At last there is shown a comparison of the machine in front of the economical aspects.

Determination of 21 drugs in oral fluid using fully automated supported liquid extraction and UHPLC-MS/MS.

PubMed

Valen, Anja; Leere Øiestad, Åse Marit; Strand, Dag Helge; Skari, Ragnhild; Berg, Thomas

2017-05-01

Collection of oral fluid (OF) is easy and non-invasive compared to the collection of urine and blood, and interest in OF for drug screening and diagnostic purposes is increasing. A high-throughput ultra-high-performance liquid chromatography-tandem mass spectrometry method for determination of 21 drugs in OF using fully automated 96-well plate supported liquid extraction for sample preparation is presented. The method contains a selection of classic drugs of abuse, including amphetamines, cocaine, cannabis, opioids, and benzodiazepines. The method was fully validated for 200 μL OF/buffer mix using an Intercept OF sampling kit; validation included linearity, sensitivity, precision, accuracy, extraction recovery, matrix effects, stability, and carry-over. Inter-assay precision (RSD) and accuracy (relative error) were <15% and 13 to 5%, respectively, for all compounds at concentrations equal to or higher than the lower limit of quantification. Extraction recoveries were between 58 and 76% (RSD < 8%), except for tetrahydrocannabinol and three 7-amino benzodiazepine metabolites with recoveries between 23 and 33% (RSD between 51 and 52 % and 11 and 25%, respectively). Ion enhancement or ion suppression effects were observed for a few compounds; however, to a large degree they were compensated for by the internal standards used. Deuterium-labelled and 13 C-labelled internal standards were used for 8 and 11 of the compounds, respectively. In a comparison between Intercept and Quantisal OF kits, better recoveries and fewer matrix effects were observed for some compounds using Quantisal. The method is sensitive and robust for its purposes and has been used successfully since February 2015 for analysis of Intercept OF samples from 2600 cases in a 12-month period. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Cleaning method and apparatus

DOEpatents

Jackson, D.D.; Hollen, R.M.

1981-02-27

A method of very thoroughly and quikcly cleaning a guaze electrode used in chemical analyses is given, as well as an automobile cleaning apparatus which makes use of the method. The method generates very little waste solution, and this is very important in analyzing radioactive materials, especially in aqueous solutions. The cleaning apparatus can be used in a larger, fully automated controlled potential coulometric apparatus. About 99.98% of a 5 mg plutonium sample was removed in less than 3 minutes, using only about 60 ml of rinse solution and two main rinse steps.

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.

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

Engine condition monitoring: CF6 family 60's through the 80's

NASA Technical Reports Server (NTRS)

Kent, H. J.; Dienger, G.

1981-01-01

The on condition program is described in terms of its effectiveness as a maintenance tool both at the line station as well as at home base by the early detection of engine faults, erroneous instrumentation signals and by verification of engine health. The system encompasses all known methods from manual procedures to the fully automated airborne integrated data system.

Determination of 74 new psychoactive substances in serum using automated in-line solid-phase extraction-liquid chromatography-tandem mass spectrometry.

PubMed

Lehmann, Sabrina; Kieliba, Tobias; Beike, Justus; Thevis, Mario; Mercer-Chalmers-Bender, Katja

2017-10-01

A detailed description is given of the development and validation of a fully automated in-line solid-phase extraction-liquid chromatography-tandem mass spectrometry (SPE-LC-MS/MS) method capable of detecting 90 central-stimulating new psychoactive substances (NPS) and 5 conventional amphetamine-type stimulants (amphetamine, 3,4-methylenedioxy-methamphetamine (MDMA), 3,4-methylenedioxy-amphetamine (MDA), 3,4-methylenedioxy-N-ethyl-amphetamine (MDEA), methamphetamine) in serum. The aim was to apply the validated method to forensic samples. The preparation of 150μL of serum was performed by an Instrument Top Sample Preparation (ITSP)-SPE with mixed mode cation exchanger cartridges. The extracts were directly injected into an LC-MS/MS system, using a biphenyl column and gradient elution with 2mM ammonium formate/0.1% formic acid and acetonitrile/0.1% formic acid as mobile phases. The chromatographic run time amounts to 9.3min (including re-equilibration). The total cycle time is 11min, due to the interlacing between sample preparation and analysis. The method was fully validated using 69 NPS and five conventional amphetamine-type stimulants, according to the guidelines of the Society of Toxicological and Forensic Chemistry (GTFCh). The guidelines were fully achieved for 62 analytes (with a limit of detection (LOD) between 0.2 and 4μg/L), whilst full validation was not feasible for the remaining 12 analytes. For the fully validated analytes, the method achieved linearity in the 5μg/L (lower limit of quantification, LLOQ) to 250μg/L range (coefficients of determination>0.99). Recoveries for 69 of these compounds were greater than 50%, with relative standard deviations≤15%. The validated method was then tested for its capability in detecting a further 21 NPS, thus totalling 95 tested substances. An LOD between 0.4 and 1.6μg/L was obtained for these 21 additional qualitatively-measured substances. The method was subsequently successfully applied to 28 specimens from routine forensic case work, of which 7 samples were determined to be positive for NPS consumption. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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

McCarroll, R; UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX; Beadle, B

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

Automated tissue segmentation of MR brain images in the presence of white matter lesions.

PubMed

Valverde, Sergi; Oliver, Arnau; Roura, Eloy; González-Villà, Sandra; Pareto, Deborah; Vilanova, Joan C; Ramió-Torrentà, Lluís; Rovira, Àlex; Lladó, Xavier

2017-01-01

Over the last few years, the increasing interest in brain tissue volume measurements on clinical settings has led to the development of a wide number of automated tissue segmentation methods. However, white matter lesions are known to reduce the performance of automated tissue segmentation methods, which requires manual annotation of the lesions and refilling them before segmentation, which is tedious and time-consuming. Here, we propose a new, fully automated T1-w/FLAIR tissue segmentation approach designed to deal with images in the presence of WM lesions. This approach integrates a robust partial volume tissue segmentation with WM outlier rejection and filling, combining intensity and probabilistic and morphological prior maps. We evaluate the performance of this method on the MRBrainS13 tissue segmentation challenge database, which contains images with vascular WM lesions, and also on a set of Multiple Sclerosis (MS) patient images. On both databases, we validate the performance of our method with other state-of-the-art techniques. On the MRBrainS13 data, the presented approach was at the time of submission the best ranked unsupervised intensity model method of the challenge (7th position) and clearly outperformed the other unsupervised pipelines such as FAST and SPM12. On MS data, the differences in tissue segmentation between the images segmented with our method and the same images where manual expert annotations were used to refill lesions on T1-w images before segmentation were lower or similar to the best state-of-the-art pipeline incorporating automated lesion segmentation and filling. Our results show that the proposed pipeline achieved very competitive results on both vascular and MS lesions. A public version of this approach is available to download for the neuro-imaging community. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatic segmentation of the glenohumeral cartilages from magnetic resonance images

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

Neubert, A., E-mail: ales.neubert@csiro.au

Purpose: Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hipmore » joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders. Methods: The method involves automated segmentation of the humerus and scapula bones using 3D active shape models, the extraction of the expected bone–cartilage interface, and cartilage segmentation using a graph-based method. The cartilage segmentation uses localization, patient specific tissue estimation, and a model of the cartilage thickness variation. The accuracy of this method was experimentally validated using a leave-one-out scheme on a database of MR images acquired from 44 asymptomatic subjects with a true fast imaging with steady state precession sequence on a 3 T scanner (Siemens Trio) using a dedicated shoulder coil. The automated results were compared to manual segmentations from two experts (an experienced radiographer and an experienced musculoskeletal anatomist) using the Dice similarity coefficient (DSC) and mean absolute surface distance (MASD) metrics. Results: Accurate and precise bone segmentations were achieved with mean DSC of 0.98 and 0.93 for the humeral head and glenoid fossa, respectively. Mean DSC scores of 0.74 and 0.72 were obtained for the humeral and glenoid cartilage volumes, respectively. The manual interobserver reliability evaluated by DSC was 0.80 ± 0.03 and 0.76 ± 0.04 for the two cartilages, implying that the automated results were within an acceptable 10% difference. The MASD between the automatic and the corresponding manual cartilage segmentations was less than 0.4 mm (previous studies reported mean cartilage thickness of 1.3 mm). Conclusions: This work shows the feasibility of volumetric segmentation and separation of the glenohumeral cartilages from MR images. To their knowledge, this is the first fully automated algorithm for volumetric segmentation of the individual glenohumeral cartilages from MR images. The approach was validated against manual segmentations from experienced analysts. In future work, the approach will be validated on imaging datasets acquired with various MR contrasts in patients.« less

Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods.

PubMed

Suleimanov, Yury V; Green, William H

2015-09-08

We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation double- and single-ended transition-state optimization algorithms--the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several single-molecule systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not only "known" reaction pathways, manually detected in the previous studies, but also new, previously "unknown", reaction pathways which involve significant atom rearrangements. We believe that applying such a systematic approach to elementary reaction path finding will greatly accelerate the discovery of new chemistry and will lead to more accurate computer simulations of various chemical processes.

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.

A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+

NASA Astrophysics Data System (ADS)

Watmough, Gary R.; Atkinson, Peter M.; Hutton, Craig W.

2011-04-01

The automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 μm, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classifications.

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.

Miniaturized Mass-Spectrometry-Based Analysis System for Fully Automated Examination of Conditioned Cell Culture Media

PubMed Central

Weber, Emanuel; Pinkse, Martijn W. H.; Bener-Aksam, Eda; Vellekoop, Michael J.; Verhaert, Peter D. E. M.

2012-01-01

We present a fully automated setup for performing in-line mass spectrometry (MS) analysis of conditioned media in cell cultures, in particular focusing on the peptides therein. The goal is to assess peptides secreted by cells in different culture conditions. The developed system is compatible with MS as analytical technique, as this is one of the most powerful analysis methods for peptide detection and identification. Proof of concept was achieved using the well-known mating-factor signaling in baker's yeast, Saccharomyces cerevisiae. Our concept system holds 1 mL of cell culture medium and allows maintaining a yeast culture for, at least, 40 hours with continuous supernatant extraction (and medium replenishing). The device's small dimensions result in reduced costs for reagents and open perspectives towards full integration on-chip. Experimental data that can be obtained are time-resolved peptide profiles in a yeast culture, including information about the appearance of mating-factor-related peptides. We emphasize that the system operates without any manual intervention or pipetting steps, which allows for an improved overall sensitivity compared to non-automated alternatives. MS data confirmed previously reported aspects of the physiology of the yeast-mating process. Moreover, matingfactor breakdown products (as well as evidence for a potentially responsible protease) were found. PMID:23091722

Assessment of Automated Analyses of Cell Migration on Flat and Nanostructured Surfaces

PubMed Central

Grădinaru, Cristian; Łopacińska, Joanna M.; Huth, Johannes; Kestler, Hans A.; Flyvbjerg, Henrik; Mølhave, Kristian

2012-01-01

Motility studies of cells often rely on computer software that analyzes time-lapse recorded movies and establishes cell trajectories fully automatically. This raises the question of reproducibility of results, since different programs could yield significantly different results of such automated analysis. The fact that the segmentation routines of such programs are often challenged by nanostructured surfaces makes the question more pertinent. Here we illustrate how it is possible to track cells on bright field microscopy images with image analysis routines implemented in an open-source cell tracking program, PACT (Program for Automated Cell Tracking). We compare the automated motility analysis of three cell tracking programs, PACT, Autozell, and TLA, using the same movies as input for all three programs. We find that different programs track overlapping, but different subsets of cells due to different segmentation methods. Unfortunately, population averages based on such different cell populations, differ significantly in some cases. Thus, results obtained with one software package are not necessarily reproducible by other software. PMID:24688640

A new automated colorimetric method for measuring total oxidant status.

PubMed

Erel, Ozcan

2005-12-01

To develop a new, colorimetric and automated method for measuring total oxidation status (TOS). The assay is based on the oxidation of ferrous ion to ferric ion in the presence of various oxidant species in acidic medium and the measurement of the ferric ion by xylenol orange. The oxidation reaction of the assay was enhanced and precipitation of proteins was prevented. In addition, autoxidation of ferrous ion present in the reagent was prevented during storage. The method was applied to an automated analyzer, which was calibrated with hydrogen peroxide and the analytical performance characteristics of the assay were determined. There were important correlations with hydrogen peroxide, tert-butyl hydroperoxide and cumene hydroperoxide solutions (r=0.99, P<0.001 for all). In addition, the new assay presented a typical sigmoidal reaction pattern in copper-induced lipoprotein autoxidation. The novel assay is linear up to 200 micromol H2O2 Equiv./L and its precision value is lower than 3%. The lower detection limit is 1.13 micromol H2O2 Equiv./L. The reagents are stable for at least 6 months on the automated analyzer. Serum TOS level was significantly higher in patients with osteoarthritis (21.23+/-3.11 micromol H2O2 Equiv./L) than in healthy subjects (14.19+/-3.16 micromol H2O2 Equiv./L, P<0.001) and the results showed a significant negative correlation with total antioxidant capacity (TAC) (r=-0.66 P<0.01). This easy, stable, reliable, sensitive, inexpensive and fully automated method that is described can be used to measure total oxidant status.

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.

The BUME method: a new rapid and simple chloroform-free method for total lipid extraction of animal tissue

NASA Astrophysics Data System (ADS)

Löfgren, Lars; Forsberg, Gun-Britt; Ståhlman, Marcus

2016-06-01

In this study we present a simple and rapid method for tissue lipid extraction. Snap-frozen tissue (15-150 mg) is collected in 2 ml homogenization tubes. 500 μl BUME mixture (butanol:methanol [3:1]) is added and automated homogenization of up to 24 frozen samples at a time in less than 60 seconds is performed, followed by a 5-minute single-phase extraction. After the addition of 500 μl heptane:ethyl acetate (3:1) and 500 μl 1% acetic acid a 5-minute two-phase extraction is performed. Lipids are recovered from the upper phase by automated liquid handling using a standard 96-tip robot. A second two-phase extraction is performed using 500 μl heptane:ethyl acetate (3:1). Validation of the method showed that the extraction recoveries for the investigated lipids, which included sterols, glycerolipids, glycerophospholipids and sphingolipids were similar or better than for the Folch method. We also applied the method for lipid extraction of liver and heart and compared the lipid species profiles with profiles generated after Folch and MTBE extraction. We conclude that the BUME method is superior to the Folch method in terms of simplicity, through-put, automation, solvent consumption, economy, health and environment yet delivering lipid recoveries fully comparable to or better than the Folch method.

Automated Morphological Analysis of Microglia After Stroke.

PubMed

Heindl, Steffanie; Gesierich, Benno; Benakis, Corinne; Llovera, Gemma; Duering, Marco; Liesz, Arthur

2018-01-01

Microglia are the resident immune cells of the brain and react quickly to changes in their environment with transcriptional regulation and morphological changes. Brain tissue injury such as ischemic stroke induces a local inflammatory response encompassing microglial activation. The change in activation status of a microglia is reflected in its gradual morphological transformation from a highly ramified into a less ramified or amoeboid cell shape. For this reason, the morphological changes of microglia are widely utilized to quantify microglial activation and studying their involvement in virtually all brain diseases. However, the currently available methods, which are mainly based on manual rating of immunofluorescent microscopic images, are often inaccurate, rater biased, and highly time consuming. To address these issues, we created a fully automated image analysis tool, which enables the analysis of microglia morphology from a confocal Z-stack and providing up to 59 morphological features. We developed the algorithm on an exploratory dataset of microglial cells from a stroke mouse model and validated the findings on an independent data set. In both datasets, we could demonstrate the ability of the algorithm to sensitively discriminate between the microglia morphology in the peri-infarct and the contralateral, unaffected cortex. Dimensionality reduction by principal component analysis allowed to generate a highly sensitive compound score for microglial shape analysis. Finally, we tested for concordance of results between the novel automated analysis tool and the conventional manual analysis and found a high degree of correlation. In conclusion, our novel method for the fully automatized analysis of microglia morphology shows excellent accuracy and time efficacy compared to traditional analysis methods. This tool, which we make openly available, could find application to study microglia morphology using fluorescence imaging in a wide range of brain disease models.

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

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.

Unimolecular Reaction Pathways of a γ-Ketohydroperoxide from Combined Application of Automated Reaction Discovery Methods

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

Grambow, Colin A.; Jamal, Adeel; Li, Yi -Pei

Ketohydroperoxides are important in liquid-phase autoxidation and in gas-phase partial oxidation and pre-ignition chemistry, but because of their low concentration, instability, and various analytical chemistry limitations, it has been challenging to experimentally determine their reactivity, and only a few pathways are known. In the present work, 75 elementary-step unimolecular reactions of the simplest γ-ketohydroperoxide, 3-hydroperoxypropanal, were discovered by a combination of density functional theory with several automated transition-state search algorithms: the Berny algorithm coupled with the freezing string method, single- and double-ended growing string methods, the heuristic KinBot algorithm, and the single-component artificial force induced reaction method (SC-AFIR). The presentmore » joint approach significantly outperforms previous manual and automated transition-state searches – 68 of the reactions of γ-ketohydroperoxide discovered here were previously unknown and completely unexpected. All of the methods found the lowest-energy transition state, which corresponds to the first step of the Korcek mechanism, but each algorithm except for SC-AFIR detected several reactions not found by any of the other methods. We show that the low-barrier chemical reactions involve promising new chemistry that may be relevant in atmospheric and combustion systems. Our study highlights the complexity of chemical space exploration and the advantage of combined application of several approaches. Altogether, the present work demonstrates both the power and the weaknesses of existing fully automated approaches for reaction discovery which suggest possible directions for further method development and assessment in order to enable reliable discovery of all important reactions of any specified reactant(s).« less

Unimolecular Reaction Pathways of a γ-Ketohydroperoxide from Combined Application of Automated Reaction Discovery Methods

DOE PAGES

Grambow, Colin A.; Jamal, Adeel; Li, Yi -Pei; ...

2017-12-22

Ketohydroperoxides are important in liquid-phase autoxidation and in gas-phase partial oxidation and pre-ignition chemistry, but because of their low concentration, instability, and various analytical chemistry limitations, it has been challenging to experimentally determine their reactivity, and only a few pathways are known. In the present work, 75 elementary-step unimolecular reactions of the simplest γ-ketohydroperoxide, 3-hydroperoxypropanal, were discovered by a combination of density functional theory with several automated transition-state search algorithms: the Berny algorithm coupled with the freezing string method, single- and double-ended growing string methods, the heuristic KinBot algorithm, and the single-component artificial force induced reaction method (SC-AFIR). The presentmore » joint approach significantly outperforms previous manual and automated transition-state searches – 68 of the reactions of γ-ketohydroperoxide discovered here were previously unknown and completely unexpected. All of the methods found the lowest-energy transition state, which corresponds to the first step of the Korcek mechanism, but each algorithm except for SC-AFIR detected several reactions not found by any of the other methods. We show that the low-barrier chemical reactions involve promising new chemistry that may be relevant in atmospheric and combustion systems. Our study highlights the complexity of chemical space exploration and the advantage of combined application of several approaches. Altogether, the present work demonstrates both the power and the weaknesses of existing fully automated approaches for reaction discovery which suggest possible directions for further method development and assessment in order to enable reliable discovery of all important reactions of any specified reactant(s).« less

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.

Catch and Patch: A Pipette-Based Approach for Automating Patch Clamp That Enables Cell Selection and Fast Compound Application.

PubMed

Danker, Timm; Braun, Franziska; Silbernagl, Nikole; Guenther, Elke

2016-03-01

Manual patch clamp, the gold standard of electrophysiology, represents a powerful and versatile toolbox to stimulate, modulate, and record ion channel activity from membrane fragments and whole cells. The electrophysiological readout can be combined with fluorescent or optogenetic methods and allows for ultrafast solution exchanges using specialized microfluidic tools. A hallmark of manual patch clamp is the intentional selection of individual cells for recording, often an essential prerequisite to generate meaningful data. So far, available automation solutions rely on random cell usage in the closed environment of a chip and thus sacrifice much of this versatility by design. To parallelize and automate the traditional patch clamp technique while perpetuating the full versatility of the method, we developed an approach to automation, which is based on active cell handling and targeted electrode placement rather than on random processes. This is achieved through an automated pipette positioning system, which guides the tips of recording pipettes with micrometer precision to a microfluidic cell handling device. Using a patch pipette array mounted on a conventional micromanipulator, our automated patch clamp process mimics the original manual patch clamp as closely as possible, yet achieving a configuration where recordings are obtained from many patch electrodes in parallel. In addition, our implementation is extensible by design to allow the easy integration of specialized equipment such as ultrafast compound application tools. The resulting system offers fully automated patch clamp on purposely selected cells and combines high-quality gigaseal recordings with solution switching in the millisecond timescale.

Towards enhanced automated elution systems for waterborne protozoa using megasonic energy.

PubMed

Horton, B; Katzer, F; Desmulliez, M P Y; Bridle, H L

2018-02-01

Continuous and reliable monitoring of water sources for human consumption is imperative for public health. For protozoa, which cannot be multiplied efficiently in laboratory settings, concentration and recovery steps are key to a successful detection procedure. Recently, the use of megasonic energy was demonstrated to recover Cryptosporidium from commonly used water industry filtration procedures, forming thereby a basis for a simplified and cost effective method of elution of pathogens. In this article, we report the benefits of incorporating megasonic sonication into the current methodologies of Giardia duodenalis elution from an internationally approved filtration and elution system used within the water industry, the Filta-Max®. Megasonic energy assisted elution has many benefits over current methods since a smaller final volume of eluent allows removal of time-consuming centrifugation steps and reduces manual involvement resulting in a potentially more consistent and more cost-effective method. We also show that megasonic sonication of G. duodenalis cysts provides the option of a less damaging elution method compared to the standard Filta-Max® operation, although the elution from filter matrices is not currently fully optimised. A notable decrease in recovery of damaged cysts was observed in megasonic processed samples, potentially increasing the abilities of further genetic identification options upon isolation of the parasite from a filter sample. This work paves the way for the development of a fully automated and more cost-effective elution method of Giardia from water samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Fully automated atlas-based method for prescribing 3D PRESS MR spectroscopic imaging: Toward robust and reproducible metabolite measurements in human brain.

PubMed

Bian, Wei; Li, Yan; Crane, Jason C; Nelson, Sarah J

2018-02-01

To implement a fully automated atlas-based method for prescribing 3D PRESS MR spectroscopic imaging (MRSI). The PRESS selected volume and outer-volume suppression bands were predefined on the MNI152 standard template image. The template image was aligned to the subject T 1 -weighted image during a scan, and the resulting transformation was then applied to the predefined prescription. To evaluate the method, H-1 MRSI data were obtained in repeat scan sessions from 20 healthy volunteers. In each session, datasets were acquired twice without repositioning. The overlap ratio of the prescribed volume in the two sessions was calculated and the reproducibility of inter- and intrasession metabolite peak height and area ratios was measured by the coefficient of variation (CoV). The CoVs from intra- and intersession were compared by a paired t-test. The average overlap ratio of the automatically prescribed selection volumes between two sessions was 97.8%. The average voxel-based intersession CoVs were less than 0.124 and 0.163 for peak height and area ratios, respectively. Paired t-test showed no significant difference between the intra- and intersession CoVs. The proposed method provides a time efficient method to prescribe 3D PRESS MRSI with reproducible imaging positioning and metabolite measurements. Magn Reson Med 79:636-642, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

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)

Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms.

PubMed

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

2018-05-01

This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema. The OCT image is segmented using a novel neutrosophic transformation and a graph-based shortest path method. In neutrosophic domain, an image is transformed into three sets: (true), (indeterminate) that represents noise, and (false). This paper makes four key contributions. First, a new method is introduced to compute the indeterminacy set , and a new -correction operation is introduced to compute the set in neutrosophic domain. Second, a graph shortest-path method is applied in neutrosophic domain to segment the inner limiting membrane and the retinal pigment epithelium as regions of interest (ROI) and outer plexiform layer and inner segment myeloid as middle layers using a novel definition of the edge weights . Third, a new cost function for cluster-based fluid/cyst segmentation in ROI is presented which also includes a novel approach in estimating the number of clusters in an automated manner. Fourth, the final fluid regions are achieved by ignoring very small regions and the regions between middle layers. The proposed method is evaluated using two publicly available datasets: Duke, Optima, and a third local dataset from the UMN clinic which is available online. The proposed algorithm outperforms the previously proposed Duke algorithm by 8% with respect to the dice coefficient and by 5% with respect to precision on the Duke dataset, while achieving about the same sensitivity. Also, the proposed algorithm outperforms a prior method for Optima dataset by 6%, 22%, and 23% with respect to the dice coefficient, sensitivity, and precision, respectively. Finally, the proposed algorithm also achieves sensitivity of 67.3%, 88.8%, and 76.7%, for the Duke, Optima, and the university of minnesota (UMN) datasets, respectively.

Fully Automated Prostate Magnetic Resonance Imaging and Transrectal Ultrasound Fusion via a Probabilistic Registration Metric.

PubMed

Sparks, Rachel; Bloch, B Nicolas; Feleppa, Ernest; Barratt, Dean; Madabhushi, Anant

2013-03-08

In this work, we present a novel, automated, registration method to fuse magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) images of the prostate. Our methodology consists of: (1) delineating the prostate on MRI, (2) building a probabilistic model of prostate location on TRUS, and (3) aligning the MRI prostate segmentation to the TRUS probabilistic model. TRUS-guided needle biopsy is the current gold standard for prostate cancer (CaP) diagnosis. Up to 40% of CaP lesions appear isoechoic on TRUS, hence TRUS-guided biopsy cannot reliably target CaP lesions and is associated with a high false negative rate. MRI is better able to distinguish CaP from benign prostatic tissue, but requires special equipment and training. MRI-TRUS fusion, whereby MRI is acquired pre-operatively and aligned to TRUS during the biopsy procedure, allows for information from both modalities to be used to help guide the biopsy. The use of MRI and TRUS in combination to guide biopsy at least doubles the yield of positive biopsies. Previous work on MRI-TRUS fusion has involved aligning manually determined fiducials or prostate surfaces to achieve image registration. The accuracy of these methods is dependent on the reader's ability to determine fiducials or prostate surfaces with minimal error, which is a difficult and time-consuming task. Our novel, fully automated MRI-TRUS fusion method represents a significant advance over the current state-of-the-art because it does not require manual intervention after TRUS acquisition. All necessary preprocessing steps (i.e. delineation of the prostate on MRI) can be performed offline prior to the biopsy procedure. We evaluated our method on seven patient studies, with B-mode TRUS and a 1.5 T surface coil MRI. Our method has a root mean square error (RMSE) for expertly selected fiducials (consisting of the urethra, calcifications, and the centroids of CaP nodules) of 3.39 ± 0.85 mm.

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.

Automatic segmentation of the glenohumeral cartilages from magnetic resonance images.

PubMed

Neubert, A; Yang, Z; Engstrom, C; Xia, Y; Strudwick, M W; Chandra, S S; Fripp, J; Crozier, S

2016-10-01

Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hip joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders. The method involves automated segmentation of the humerus and scapula bones using 3D active shape models, the extraction of the expected bone-cartilage interface, and cartilage segmentation using a graph-based method. The cartilage segmentation uses localization, patient specific tissue estimation, and a model of the cartilage thickness variation. The accuracy of this method was experimentally validated using a leave-one-out scheme on a database of MR images acquired from 44 asymptomatic subjects with a true fast imaging with steady state precession sequence on a 3 T scanner (Siemens Trio) using a dedicated shoulder coil. The automated results were compared to manual segmentations from two experts (an experienced radiographer and an experienced musculoskeletal anatomist) using the Dice similarity coefficient (DSC) and mean absolute surface distance (MASD) metrics. Accurate and precise bone segmentations were achieved with mean DSC of 0.98 and 0.93 for the humeral head and glenoid fossa, respectively. Mean DSC scores of 0.74 and 0.72 were obtained for the humeral and glenoid cartilage volumes, respectively. The manual interobserver reliability evaluated by DSC was 0.80 ± 0.03 and 0.76 ± 0.04 for the two cartilages, implying that the automated results were within an acceptable 10% difference. The MASD between the automatic and the corresponding manual cartilage segmentations was less than 0.4 mm (previous studies reported mean cartilage thickness of 1.3 mm). This work shows the feasibility of volumetric segmentation and separation of the glenohumeral cartilages from MR images. To their knowledge, this is the first fully automated algorithm for volumetric segmentation of the individual glenohumeral cartilages from MR images. The approach was validated against manual segmentations from experienced analysts. In future work, the approach will be validated on imaging datasets acquired with various MR contrasts in patients.

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.

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.

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

The WHO 2016 verbal autopsy instrument: An international standard suitable for automated analysis by InterVA, InSilicoVA, and Tariff 2.0

PubMed Central

Chandramohan, Daniel; Clark, Samuel J.; Jakob, Robert; Leitao, Jordana; Rao, Chalapati; Riley, Ian; Setel, Philip W.

2018-01-01

Background Verbal autopsy (VA) is a practical method for determining probable causes of death at the population level in places where systems for medical certification of cause of death are weak. VA methods suitable for use in routine settings, such as civil registration and vital statistics (CRVS) systems, have developed rapidly in the last decade. These developments have been part of a growing global momentum to strengthen CRVS systems in low-income countries. With this momentum have come pressure for continued research and development of VA methods and the need for a single standard VA instrument on which multiple automated diagnostic methods can be developed. Methods and findings In 2016, partners harmonized a WHO VA standard instrument that fully incorporates the indicators necessary to run currently available automated diagnostic algorithms. The WHO 2016 VA instrument, together with validated approaches to analyzing VA data, offers countries solutions to improving information about patterns of cause-specific mortality. This VA instrument offers the opportunity to harmonize the automated diagnostic algorithms in the future. Conclusions Despite all improvements in design and technology, VA is only recommended where medical certification of cause of death is not possible. The method can nevertheless provide sufficient information to guide public health priorities in communities in which physician certification of deaths is largely unavailable. The WHO 2016 VA instrument, together with validated approaches to analyzing VA data, offers countries solutions to improving information about patterns of cause-specific mortality. PMID:29320495

Constructing Tissue Microarrays: Protocols and Methods Considering Potential Advantages and Disadvantages for Downstream Use.

PubMed

Bingle, Lynne; Fonseca, Felipe P; Farthing, Paula M

2017-01-01

Tissue microarrays were first constructed in the 1980s but were used by only a limited number of researchers for a considerable period of time. In the last 10 years there has been a dramatic increase in the number of publications describing the successful use of tissue microarrays in studies aimed at discovering and validating biomarkers. This, along with the increased availability of both manual and automated microarray builders on the market, has encouraged even greater use of this novel and powerful tool. This chapter describes the basic techniques required to build a tissue microarray using a manual method in order that the theory behind the practical steps can be fully explained. Guidance is given to ensure potential disadvantages of the technique are fully considered.

Automated NMR structure determination of stereo-array isotope labeled ubiquitin from minimal sets of spectra using the SAIL-FLYA system.

PubMed

Ikeya, Teppei; Takeda, Mitsuhiro; Yoshida, Hitoshi; Terauchi, Tsutomu; Jee, Jun-Goo; Kainosho, Masatsune; Güntert, Peter

2009-08-01

Stereo-array isotope labeling (SAIL) has been combined with the fully automated NMR structure determination algorithm FLYA to determine the three-dimensional structure of the protein ubiquitin from different sets of input NMR spectra. SAIL provides a complete stereo- and regio-specific pattern of stable isotopes that results in sharper resonance lines and reduced signal overlap, without information loss. Here we show that as a result of the superior quality of the SAIL NMR spectra, reliable, fully automated analyses of the NMR spectra and structure calculations are possible using fewer input spectra than with conventional uniformly 13C/15N-labeled proteins. FLYA calculations with SAIL ubiquitin, using a single three-dimensional "through-bond" spectrum (and 2D HSQC spectra) in addition to the 13C-edited and 15N-edited NOESY spectra for conformational restraints, yielded structures with an accuracy of 0.83-1.15 A for the backbone RMSD to the conventionally determined solution structure of SAIL ubiquitin. NMR structures can thus be determined almost exclusively from the NOESY spectra that yield the conformational restraints, without the need to record many spectra only for determining intermediate, auxiliary data of the chemical shift assignments. The FLYA calculations for this report resulted in 252 ubiquitin structure bundles, obtained with different input data but identical structure calculation and refinement methods. These structures cover the entire range from highly accurate structures to seriously, but not trivially, wrong structures, and thus constitute a valuable database for the substantiation of structure validation methods.

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.

Automated analysis of connected speech reveals early biomarkers of Parkinson's disease in patients with rapid eye movement sleep behaviour disorder.

PubMed

Hlavnička, Jan; Čmejla, Roman; Tykalová, Tereza; Šonka, Karel; Růžička, Evžen; Rusz, Jan

2017-02-02

For generations, the evaluation of speech abnormalities in neurodegenerative disorders such as Parkinson's disease (PD) has been limited to perceptual tests or user-controlled laboratory analysis based upon rather small samples of human vocalizations. Our study introduces a fully automated method that yields significant features related to respiratory deficits, dysphonia, imprecise articulation and dysrhythmia from acoustic microphone data of natural connected speech for predicting early and distinctive patterns of neurodegeneration. We compared speech recordings of 50 subjects with rapid eye movement sleep behaviour disorder (RBD), 30 newly diagnosed, untreated PD patients and 50 healthy controls, and showed that subliminal parkinsonian speech deficits can be reliably captured even in RBD patients, which are at high risk of developing PD or other synucleinopathies. Thus, automated vocal analysis should soon be able to contribute to screening and diagnostic procedures for prodromal parkinsonian neurodegeneration in natural environments.

Questioned document workflow for handwriting with automated tools

NASA Astrophysics Data System (ADS)

Das, Krishnanand; Srihari, Sargur N.; Srinivasan, Harish

2012-01-01

During the last few years many document recognition methods have been developed to determine whether a handwriting specimen can be attributed to a known writer. However, in practice, the work-flow of the document examiner continues to be manual-intensive. Before a systematic or computational, approach can be developed, an articulation of the steps involved in handwriting comparison is needed. We describe the work flow of handwritten questioned document examination, as described in a standards manual, and the steps where existing automation tools can be used. A well-known ransom note case is considered as an example, where one encounters testing for multiple writers of the same document, determining whether the writing is disguised, known writing is formal while questioned writing is informal, etc. The findings for the particular ransom note case using the tools are given. Also observations are made for developing a more fully automated approach to handwriting examination.

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.

Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance.

PubMed

Ngo, Tuan Anh; Lu, Zhi; Carneiro, Gustavo

2017-01-01

We introduce a new methodology that combines deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance (MR) data. This combination is relevant for segmentation problems, where the visual object of interest presents large shape and appearance variations, but the annotated training set is small, which is the case for various medical image analysis applications, including the one considered in this paper. In particular, level set methods are based on shape and appearance terms that use small training sets, but present limitations for modelling the visual object variations. Deep learning methods can model such variations using relatively small amounts of annotated training, but they often need to be regularised to produce good generalisation. Therefore, the combination of these methods brings together the advantages of both approaches, producing a methodology that needs small training sets and produces accurate segmentation results. We test our methodology on the MICCAI 2009 left ventricle segmentation challenge database (containing 15 sequences for training, 15 for validation and 15 for testing), where our approach achieves the most accurate results in the semi-automated problem and state-of-the-art results for the fully automated challenge. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

An automated technique to stage lower third molar development on panoramic radiographs for age estimation: a pilot study.

PubMed

De Tobel, J; Radesh, P; Vandermeulen, D; Thevissen, P W

2017-12-01

Automated methods to evaluate growth of hand and wrist bones on radiographs and magnetic resonance imaging have been developed. They can be applied to estimate age in children and subadults. Automated methods require the software to (1) recognise the region of interest in the image(s), (2) evaluate the degree of development and (3) correlate this to the age of the subject based on a reference population. For age estimation based on third molars an automated method for step (1) has been presented for 3D magnetic resonance imaging and is currently being optimised (Unterpirker et al. 2015). To develop an automated method for step (2) based on lower third molars on panoramic radiographs. A modified Demirjian staging technique including ten developmental stages was developed. Twenty panoramic radiographs per stage per gender were retrospectively selected for FDI element 38. Two observers decided in consensus about the stages. When necessary, a third observer acted as a referee to establish the reference stage for the considered third molar. This set of radiographs was used as training data for machine learning algorithms for automated staging. First, image contrast settings were optimised to evaluate the third molar of interest and a rectangular bounding box was placed around it in a standardised way using Adobe Photoshop CC 2017 software. This bounding box indicated the region of interest for the next step. Second, several machine learning algorithms available in MATLAB R2017a software were applied for automated stage recognition. Third, the classification performance was evaluated in a 5-fold cross-validation scenario, using different validation metrics (accuracy, Rank-N recognition rate, mean absolute difference, linear kappa coefficient). Transfer Learning as a type of Deep Learning Convolutional Neural Network approach outperformed all other tested approaches. Mean accuracy equalled 0.51, mean absolute difference was 0.6 stages and mean linearly weighted kappa was 0.82. The overall performance of the presented automated pilot technique to stage lower third molar development on panoramic radiographs was similar to staging by human observers. It will be further optimised in future research, since it represents a necessary step to achieve a fully automated dental age estimation method, which to date is not available.

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

Advantages of automation in plasma sample preparation prior to HPLC/MS/MS quantification: application to the determination of cilazapril and cilazaprilat in a bioequivalence study.

PubMed

Kolocouri, Filomila; Dotsikas, Yannis; Apostolou, Constantinos; Kousoulos, Constantinos; Soumelas, Georgios-Stefanos; Loukas, Yannis L

2011-01-01

An HPLC/MS/MS method characterized by complete automation and high throughput was developed for the determination of cilazapril and its active metabolite cilazaprilat in human plasma. All sample preparation and analysis steps were performed by using 2.2 mL 96 deep-well plates, while robotic liquid handling workstations were utilized for all liquid transfer steps, including liquid-liquid extraction. The whole procedure was very fast compared to a manual procedure with vials and no automation. The method also had a very short chromatographic run time of 1.5 min. Sample analysis was performed by RP-HPLC/MS/MS with positive electrospray ionization using multiple reaction monitoring. The calibration curve was linear in the range of 0.500-300 and 0.250-150 ng/mL for cilazapril and cilazaprilat, respectively. The proposed method was fully validated and proved to be selective, accurate, precise, reproducible, and suitable for the determination of cilazapril and cilazaprilat in human plasma. Therefore, it was applied to a bioequivalence study after per os administration of 2.5 mg tablet formulations of cilazapril.

Smart fast blood counting of trace volumes of body fluids from various mammalian species using a compact custom-built microscope cytometer (Conference Presentation)

NASA Astrophysics Data System (ADS)

Smith, Zachary J.; Gao, Tingjuan; Lin, Tzu-Yin; Carrade-Holt, Danielle; Lane, Stephen M.; Matthews, Dennis L.; Dwyre, Denis M.; Wachsmann-Hogiu, Sebastian

2016-03-01

Cell counting in human body fluids such as blood, urine, and CSF is a critical step in the diagnostic process for many diseases. Current automated methods for cell counting are based on flow cytometry systems. However, these automated methods are bulky, costly, require significant user expertise, and are not well suited to counting cells in fluids other than blood. Therefore, their use is limited to large central laboratories that process enough volume of blood to recoup the significant capital investment these instruments require. We present in this talk a combination of a (1) low-cost microscope system, (2) simple sample preparation method, and (3) fully automated analysis designed for providing cell counts in blood and body fluids. We show results on both humans and companion and farm animals, showing that accurate red cell, white cell, and platelet counts, as well as hemoglobin concentration, can be accurately obtained in blood, as well as a 3-part white cell differential in human samples. We can also accurately count red and white cells in body fluids with a limit of detection ~3 orders of magnitude smaller than current automated instruments. This method uses less than 1 microliter of blood, and less than 5 microliters of body fluids to make its measurements, making it highly compatible with finger-stick style collections, as well as appropriate for small animals such as laboratory mice where larger volume blood collections are dangerous to the animal's health.

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

Automated Reconstruction of Historic Roof Structures from Point Clouds - Development and Examples

NASA Astrophysics Data System (ADS)

Pöchtrager, M.; Styhler-Aydın, G.; Döring-Williams, M.; Pfeifer, N.

2017-08-01

The analysis of historic roof constructions is an important task for planning the adaptive reuse of buildings or for maintenance and restoration issues. Current approaches to modeling roof constructions consist of several consecutive operations that need to be done manually or using semi-automatic routines. To increase efficiency and allow the focus to be on analysis rather than on data processing, a set of methods was developed for the fully automated analysis of the roof constructions, including integration of architectural and structural modeling. Terrestrial laser scanning permits high-detail surveying of large-scale structures within a short time. Whereas 3-D laser scan data consist of millions of single points on the object surface, we need a geometric description of structural elements in order to obtain a structural model consisting of beam axis and connections. Preliminary results showed that the developed methods work well for beams in flawless condition with a quadratic cross section and no bending. Deformations or damages such as cracks and cuts on the wooden beams can lead to incomplete representations in the model. Overall, a high degree of automation was achieved.

Dual ant colony operational modal analysis parameter estimation method

NASA Astrophysics Data System (ADS)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

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...

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.

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

PubMed

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

2017-02-01

Mammographic density (MD) is an independent risk factor for breast cancer and may have a future role for stratified screening. Automated software can estimate MD but the relationship between breast thickness reduction and MD is not fully understood. Our aim is to develop a deformable breast phantom to assess automated density software and the impact of breast thickness reduction on MD. Several different configurations of poly vinyl alcohol (PVAL) phantoms were created. Three methods were used to estimate their density. Raw image data of mammographic images were processed using Volpara to estimate volumetric breast density (VBD%); Hounsfield units (HU) were measured on CT images; and physical density (g/cm 3 ) was calculated using a formula involving mass and volume. Phantom volume versus contact area and phantom volume versus phantom thickness was compared to values of real breasts. Volpara recognized all deformable phantoms as female breasts. However, reducing the phantom thickness caused a change in phantom density and the phantoms were not able to tolerate same level of compression and thickness reduction experienced by female breasts during mammography. Our results are promising as all phantoms resulted in valid data for automated breast density measurement. Further work should be conducted on PVAL and other materials to produce deformable phantoms that mimic female breast structure and density with the ability of being compressed to the same level as female breasts. We are the first group to have produced deformable phantoms that are recognized as breasts by Volpara software. Copyright © 2016 The College of Radiographers. All rights reserved.

ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data.

PubMed

Wu, Wei; Keller, Corey J; Rogasch, Nigel C; Longwell, Parker; Shpigel, Emmanuel; Rolle, Camarin E; Etkin, Amit

2018-04-01

Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings. © 2018 Wiley Periodicals, Inc.

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.

Automated retinofugal visual pathway reconstruction with multi-shell HARDI and FOD-based analysis.

PubMed

Kammen, Alexandra; Law, Meng; Tjan, Bosco S; Toga, Arthur W; Shi, Yonggang

2016-01-15

Diffusion MRI tractography provides a non-invasive modality to examine the human retinofugal projection, which consists of the optic nerves, optic chiasm, optic tracts, the lateral geniculate nuclei (LGN) and the optic radiations. However, the pathway has several anatomic features that make it particularly challenging to study with tractography, including its location near blood vessels and bone-air interface at the base of the cerebrum, crossing fibers at the chiasm, somewhat-tortuous course around the temporal horn via Meyer's Loop, and multiple closely neighboring fiber bundles. To date, these unique complexities of the visual pathway have impeded the development of a robust and automated reconstruction method using tractography. To overcome these challenges, we develop a novel, fully automated system to reconstruct the retinofugal visual pathway from high-resolution diffusion imaging data. Using multi-shell, high angular resolution diffusion imaging (HARDI) data, we reconstruct precise fiber orientation distributions (FODs) with high order spherical harmonics (SPHARM) to resolve fiber crossings, which allows the tractography algorithm to successfully navigate the complicated anatomy surrounding the retinofugal pathway. We also develop automated algorithms for the identification of ROIs used for fiber bundle reconstruction. In particular, we develop a novel approach to extract the LGN region of interest (ROI) based on intrinsic shape analysis of a fiber bundle computed from a seed region at the optic chiasm to a target at the primary visual cortex. By combining automatically identified ROIs and FOD-based tractography, we obtain a fully automated system to compute the main components of the retinofugal pathway, including the optic tract and the optic radiation. We apply our method to the multi-shell HARDI data of 215 subjects from the Human Connectome Project (HCP). Through comparisons with post-mortem dissection measurements, we demonstrate the retinotopic organization of the optic radiation including a successful reconstruction of Meyer's loop. Then, using the reconstructed optic radiation bundle from the HCP cohort, we construct a probabilistic atlas and demonstrate its consistency with a post-mortem atlas. Finally, we generate a shape-based representation of the optic radiation for morphometry analysis. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-02-01

Background Breast radiologists of the Norwegian Breast Cancer Screening Program subjectively classified mammographic density using a three-point scale between 1996 and 2012 and changed into the fourth edition of the BI-RADS classification since 2013. In 2015, an automated volumetric breast density assessment software was installed at two screening units. Purpose To compare volumetric breast density measurements from the automated method with two subjective methods: the three-point scale and the BI-RADS density classification. Material and Methods Information on subjective and automated density assessment was obtained from screening examinations of 3635 women recalled for further assessment due to positive screening mammography between 2007 and 2015. The score of the three-point scale (I = fatty; II = medium dense; III = dense) was available for 2310 women. The BI-RADS density score was provided for 1325 women. Mean volumetric breast density was estimated for each category of the subjective classifications. The automated software assigned volumetric breast density to four categories. The agreement between BI-RADS and volumetric breast density categories was assessed using weighted kappa (k w ). Results Mean volumetric breast density was 4.5%, 7.5%, and 13.4% for categories I, II, and III of the three-point scale, respectively, and 4.4%, 7.5%, 9.9%, and 13.9% for the BI-RADS density categories, respectively ( P for trend < 0.001 for both subjective classifications). The agreement between BI-RADS and volumetric breast density categories was k w  = 0.5 (95% CI = 0.47-0.53; P < 0.001). Conclusion Mean values of volumetric breast density increased with increasing density category of the subjective classifications. The agreement between BI-RADS and volumetric breast density categories was moderate.

Comparison of two methods for measuring γ-H2AX nuclear fluorescence as a marker of DNA damage in cultured human cells: applications for microbeam radiation therapy

NASA Astrophysics Data System (ADS)

Anderson, D.; Andrais, B.; Mirzayans, R.; Siegbahn, E. A.; Fallone, B. G.; Warkentin, B.

2013-06-01

Microbeam radiation therapy (MRT) delivers single fractions of very high doses of synchrotron x-rays using arrays of microbeams. In animal experiments, MRT has achieved higher tumour control and less normal tissue toxicity compared to single-fraction broad beam irradiations of much lower dose. The mechanism behind the normal tissue sparing of MRT has yet to be fully explained. An accurate method for evaluating DNA damage, such as the γ-H2AX immunofluorescence assay, will be important for understanding the role of cellular communication in the radiobiological response of normal and cancerous cell types to MRT. We compare two methods of quantifying γ-H2AX nuclear fluorescence for uniformly irradiated cell cultures: manual counting of γ-H2AX foci by eye, and an automated, MATLAB-based fluorescence intensity measurement. We also demonstrate the automated analysis of cell cultures irradiated with an array of microbeams. In addition to offering a relatively high dynamic range of γ-H2AX signal versus irradiation dose ( > 10 Gy), our automated method provides speed, robustness, and objectivity when examining a series of images. Our in-house analysis facilitates the automated extraction of the spatial distribution of the γ-H2AX intensity with respect to the microbeam array — for example, the intensities in the peak (high dose area) and valley (area between two microbeams) regions. The automated analysis is particularly beneficial when processing a large number of samples, as is needed to systematically study the relationship between the numerous dosimetric and geometric parameters involved with MRT (e.g., microbeam width, microbeam spacing, microbeam array dimensions, peak dose, valley dose, and geometric arrangement of multiple arrays) and the resulting DNA damage.

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 low-cost, manufacturable method for fabricating capillary and optical fiber interconnects for microfluidic devices.

PubMed

Hartmann, Daniel M; Nevill, J Tanner; Pettigrew, Kenneth I; Votaw, Gregory; Kung, Pang-Jen; Crenshaw, Hugh C

2008-04-01

Microfluidic chips require connections to larger macroscopic components, such as light sources, light detectors, and reagent reservoirs. In this article, we present novel methods for integrating capillaries, optical fibers, and wires with the channels of microfluidic chips. The method consists of forming planar interconnect channels in microfluidic chips and inserting capillaries, optical fibers, or wires into these channels. UV light is manually directed onto the ends of the interconnects using a microscope. UV-curable glue is then allowed to wick to the end of the capillaries, fibers, or wires, where it is cured to form rigid, liquid-tight connections. In a variant of this technique, used with light-guiding capillaries and optical fibers, the UV light is directed into the capillaries or fibers, and the UV-glue is cured by the cone of light emerging from the end of each capillary or fiber. This technique is fully self-aligned, greatly improves both the quality and the manufacturability of the interconnects, and has the potential to enable the fabrication of interconnects in a fully automated fashion. Using these methods, including a semi-automated implementation of the second technique, over 10,000 interconnects have been formed in almost 2000 microfluidic chips made of a variety of rigid materials. The resulting interconnects withstand pressures up to at least 800psi, have unswept volumes estimated to be less than 10 femtoliters, and have dead volumes defined only by the length of the capillary.

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.

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.

Implementation and Evaluation of a Fully Automated Multiplex Real-Time PCR Assay on the BD Max Platform to Detect and Differentiate Herpesviridae from Cerebrospinal Fluids

PubMed Central

Köller, Thomas; Kurze, Daniel; Lange, Mirjam; Scherdin, Martin; Podbielski, Andreas; Warnke, Philipp

2016-01-01

A fully automated multiplex real-time PCR assay—including a sample process control and a plasmid based positive control—for the detection and differentiation of herpes simplex virus 1 (HSV1), herpes simplex virus 2 (HSV2) and varicella-zoster virus (VZV) from cerebrospinal fluids (CSF) was developed on the BD Max platform. Performance was compared to an established accredited multiplex real time PCR protocol utilizing the easyMAG and the LightCycler 480/II, both very common devices in viral molecular diagnostics. For clinical validation, 123 CSF specimens and 40 reference samples from national interlaboratory comparisons were examined with both methods, resulting in 97.6% and 100% concordance for CSF and reference samples, respectively. Utilizing the BD Max platform revealed sensitivities of 173 (CI 95%, 88–258) copies/ml for HSV1, 171 (CI 95%, 148–194) copies/ml for HSV2 and 84 (CI 95%, 5–163) copies/ml for VZV. Cross reactivity could be excluded by checking 25 common viral, bacterial and fungal human pathogens. Workflow analyses displayed shorter test duration as well as remarkable fewer and easier preparation steps with the potential to reduce error rates occurring when manually assessing patient samples. This protocol allows for a fully automated PCR assay on the BD Max platform for the simultaneously detection of herpesviridae from CSF specimens. Singular or multiple infections due to HSV1, HSV2 and VZV can reliably be differentiated with good sensitivities. Control parameters are included within the assay, thereby rendering its suitability for current quality management requirements. PMID:27092772

LC-MS/MS Peptide Mapping with Automated Data Processing for Routine Profiling of N-Glycans in Immunoglobulins

NASA Astrophysics Data System (ADS)

Shah, Bhavana; Jiang, Xinzhao Grace; Chen, Louise; Zhang, Zhongqi

2014-06-01

Protein N-Glycan analysis is traditionally performed by high pH anion exchange chromatography (HPAEC), reversed phase liquid chromatography (RPLC), or hydrophilic interaction liquid chromatography (HILIC) on fluorescence-labeled glycans enzymatically released from the glycoprotein. These methods require time-consuming sample preparations and do not provide site-specific glycosylation information. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) peptide mapping is frequently used for protein structural characterization and, as a bonus, can potentially provide glycan profile on each individual glycosylation site. In this work, a recently developed glycopeptide fragmentation model was used for automated identification, based on their MS/MS, of N-glycopeptides from proteolytic digestion of monoclonal antibodies (mAbs). Experimental conditions were optimized to achieve accurate profiling of glycoforms. Glycan profiles obtained from LC-MS/MS peptide mapping were compared with those obtained from HPAEC, RPLC, and HILIC analyses of released glycans for several mAb molecules. Accuracy, reproducibility, and linearity of the LC-MS/MS peptide mapping method for glycan profiling were evaluated. The LC-MS/MS peptide mapping method with fully automated data analysis requires less sample preparation, provides site-specific information, and may serve as an alternative method for routine profiling of N-glycans on immunoglobulins as well as other glycoproteins with simple N-glycans.

Mechanical properties of bovine cortical bone based on the automated ball indentation technique and graphics processing method.

PubMed

Zhang, Airong; Zhang, Song; Bian, Cuirong

2018-02-01

Cortical bone provides the main form of support in humans and other vertebrates against various forces. Thus, capturing its mechanical properties is important. In this study, the mechanical properties of cortical bone were investigated by using automated ball indentation and graphics processing at both the macroscopic and microstructural levels under dry conditions. First, all polished samples were photographed under a metallographic microscope, and the area ratio of the circumferential lamellae and osteons was calculated through the graphics processing method. Second, fully-computer-controlled automated ball indentation (ABI) tests were performed to explore the micro-mechanical properties of the cortical bone at room temperature and a constant indenter speed. The indentation defects were examined with a scanning electron microscope. Finally, the macroscopic mechanical properties of the cortical bone were estimated with the graphics processing method and mixture rule. Combining ABI and graphics processing proved to be an effective tool to obtaining the mechanical properties of the cortical bone, and the indenter size had a significant effect on the measurement. The methods presented in this paper provide an innovative approach to acquiring the macroscopic mechanical properties of cortical bone in a nondestructive manner. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrated Formulation of Beacon-Based Exception Analysis for Multimissions

NASA Technical Reports Server (NTRS)

Mackey, Ryan; James, Mark; Park, Han; Zak, Mickail

2003-01-01

Further work on beacon-based exception analysis for multimissions (BEAM), a method of real-time, automated diagnosis of a complex electromechanical systems, has greatly expanded its capability and suitability of application. This expanded formulation, which fully integrates physical models and symbolic analysis, is described. The new formulation of BEAM expands upon previous advanced techniques for analysis of signal data, utilizing mathematical modeling of the system physics, and expert-system reasoning,

Validation of high-throughput measurement system with microwave-assisted extraction, fully automated sample preparation device, and gas chromatography-electron capture detector for determination of polychlorinated biphenyls in whale blubber.

PubMed

Fujita, Hiroyuki; Honda, Katsuhisa; Hamada, Noriaki; Yasunaga, Genta; Fujise, Yoshihiro

2009-02-01

Validation of a high-throughput measurement system with microwave-assisted extraction (MAE), fully automated sample preparation device (SPD), and gas chromatography-electron capture detector (GC-ECD) for the determination of polychlorinated biphenyls (PCBs) in minke whale blubber was performed. PCB congeners accounting for > 95% of the total PCBs burden in blubber were efficiently extracted with a small volume (20 mL) of n-hexane using MAE due to simultaneous saponification and extraction. Further, the crude extract obtained by MAE was rapidly purified and automatically substituted to a small volume (1 mL) of toluene using SPD without using concentrators. Furthermore, the concentration of PCBs in the purified and concentrated solution was accurately determined by GC-ECD. Moreover, the result of accuracy test using a certified material (SRM 1588b; Cod liver oil) showed good agreement with the NIST certified concentration values. In addition, the method quantification limit of total-PCB in whale blubbers was 41 ng g(-1). This new measurement system for PCBs takes only four hours. Consequently, it indicated this method is the most suitable for the monitoring and screening of PCBs in the conservation of the marine ecosystem and safe distribution of foods.

Automated Detection of Synapses in Serial Section Transmission Electron Microscopy Image Stacks

PubMed Central

Kreshuk, Anna; Koethe, Ullrich; Pax, Elizabeth; Bock, Davi D.; Hamprecht, Fred A.

2014-01-01

We describe a method for fully automated detection of chemical synapses in serial electron microscopy images with highly anisotropic axial and lateral resolution, such as images taken on transmission electron microscopes. Our pipeline starts from classification of the pixels based on 3D pixel features, which is followed by segmentation with an Ising model MRF and another classification step, based on object-level features. Classifiers are learned on sparse user labels; a fully annotated data subvolume is not required for training. The algorithm was validated on a set of 238 synapses in 20 serial 7197×7351 pixel images (4.5×4.5×45 nm resolution) of mouse visual cortex, manually labeled by three independent human annotators and additionally re-verified by an expert neuroscientist. The error rate of the algorithm (12% false negative, 7% false positive detections) is better than state-of-the-art, even though, unlike the state-of-the-art method, our algorithm does not require a prior segmentation of the image volume into cells. The software is based on the ilastik learning and segmentation toolkit and the vigra image processing library and is freely available on our website, along with the test data and gold standard annotations (http://www.ilastik.org/synapse-detection/sstem). PMID:24516550

Standardization of skin cleansing in vivo: part I. Development of an Automated Cleansing Device (ACiD).

PubMed

Sonsmann, F K; Strunk, M; Gediga, K; John, C; Schliemann, S; Seyfarth, F; Elsner, P; Diepgen, T L; Kutz, G; John, S M

2014-05-01

To date, there are no legally binding requirements concerning product testing in cosmetics. This leads to various manufacturer-specific test methods and absent transparent information on skin cleansing products. A standardized in vivo test procedure for assessment of cleansing efficacy and corresponding barrier impairment by the cleaning process is needed, especially in the occupational context where repeated hand washing procedures may be performed at short intervals. For the standardization of the cleansing procedure, an Automated Cleansing Device (ACiD) was designed and evaluated. Different smooth washing surfaces of the equipment for ACiD (incl. goat hair, felt, felt covered with nitrile caps) were evaluated regarding their skin compatibility. ACiD allows an automated, fully standardized skin washing procedure. Felt covered with nitrile as washing surface of the rotating washing units leads to a homogenous cleansing result and does not cause detectable skin irritation, neither clinically nor as assessed by skin bioengineering methods (transepidermal water loss, chromametry). Automated Cleansing Device may be useful for standardized evaluation of the cleansing effectiveness and parallel assessment of the corresponding irritancy potential of industrial skin cleansers. This will allow objectifying efficacy and safety of industrial skin cleansers, thus enabling market transparency and facilitating rational choice of products. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

ACQUA: Automated Cyanobacterial Quantification Algorithm for toxic filamentous genera using spline curves, pattern recognition and machine learning.

PubMed

Gandola, Emanuele; Antonioli, Manuela; Traficante, Alessio; Franceschini, Simone; Scardi, Michele; Congestri, Roberta

2016-05-01

Toxigenic cyanobacteria are one of the main health risks associated with water resources worldwide, as their toxins can affect humans and fauna exposed via drinking water, aquaculture and recreation. Microscopy monitoring of cyanobacteria in water bodies and massive growth systems is a routine operation for cell abundance and growth estimation. Here we present ACQUA (Automated Cyanobacterial Quantification Algorithm), a new fully automated image analysis method designed for filamentous genera in Bright field microscopy. A pre-processing algorithm has been developed to highlight filaments of interest from background signals due to other phytoplankton and dust. A spline-fitting algorithm has been designed to recombine interrupted and crossing filaments in order to perform accurate morphometric analysis and to extract the surface pattern information of highlighted objects. In addition, 17 specific pattern indicators have been developed and used as input data for a machine-learning algorithm dedicated to the recognition between five widespread toxic or potentially toxic filamentous genera in freshwater: Aphanizomenon, Cylindrospermopsis, Dolichospermum, Limnothrix and Planktothrix. The method was validated using freshwater samples from three Italian volcanic lakes comparing automated vs. manual results. ACQUA proved to be a fast and accurate tool to rapidly assess freshwater quality and to characterize cyanobacterial assemblages in aquatic environments. Copyright © 2016 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

LAMBADA and InflateGRO2: efficient membrane alignment and insertion of membrane proteins for molecular dynamics simulations.

PubMed

Schmidt, Thomas H; Kandt, Christian

2012-10-22

At the beginning of each molecular dynamics membrane simulation stands the generation of a suitable starting structure which includes the working steps of aligning membrane and protein and seamlessly accommodating the protein in the membrane. Here we introduce two efficient and complementary methods based on pre-equilibrated membrane patches, automating these steps. Using a voxel-based cast of the coarse-grained protein, LAMBADA computes a hydrophilicity profile-derived scoring function based on which the optimal rotation and translation operations are determined to align protein and membrane. Employing an entirely geometrical approach, LAMBADA is independent from any precalculated data and aligns even large membrane proteins within minutes on a regular workstation. LAMBADA is the first tool performing the entire alignment process automatically while providing the user with the explicit 3D coordinates of the aligned protein and membrane. The second tool is an extension of the InflateGRO method addressing the shortcomings of its predecessor in a fully automated workflow. Determining the exact number of overlapping lipids based on the area occupied by the protein and restricting expansion, compression and energy minimization steps to a subset of relevant lipids through automatically calculated and system-optimized operation parameters, InflateGRO2 yields optimal lipid packing and reduces lipid vacuum exposure to a minimum preserving as much of the equilibrated membrane structure as possible. Applicable to atomistic and coarse grain structures in MARTINI format, InflateGRO2 offers high accuracy, fast performance, and increased application flexibility permitting the easy preparation of systems exhibiting heterogeneous lipid composition as well as embedding proteins into multiple membranes. Both tools can be used separately, in combination with other methods, or in tandem permitting a fully automated workflow while retaining a maximum level of usage control and flexibility. To assess the performance of both methods, we carried out test runs using 22 membrane proteins of different size and transmembrane structure.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Fully automated methods for the determination of hydrochlorothiazide in human plasma and urine.

PubMed

Hsieh, J Y; Lin, C; Matuszewski, B K; Dobrinska, M R

1994-12-01

LC assays utilizing fully automated sample preparation procedures on Zymark PyTechnology Robot and BenchMate Workstation for the quantification of hydrochlorothiazide (HCTZ) in human plasma and urine have been developed. After aliquoting plasma and urine samples, and adding internal standard (IS) manually, the robot executed buffer and organic solvent addition, liquid-liquid extraction, solvent evaporation and on-line LC injection steps for plasma samples, whereas, BenchMate performed buffer and organic solvent addition, liquid-liquid and solid-phase extractions, and on-line LC injection steps for urine samples. Chromatographic separations were carried out on Beckman Octyl Ultrasphere column using the mobile phase composed of 12% (v/v) acetonitrile and 88% of either an ion-pairing reagent (plasma) or 0.1% trifluoroacetic acid (urine). The eluent from the column was monitored with UV detector (271 nm). Peak heights for HCTZ and IS were automatically processed using a PE-Nelson ACCESS*CHROM laboratory automation system. The assays have been validated in the concentration range of 2-100 ng ml-1 in plasma and 0.1-20 micrograms ml-1 in urine. Both plasma and urine assays have the sensitivity and specificity necessary to determine plasma and urine concentrations of HCTZ from low dose (6.25/12.5 mg) administration of HCTZ to human subjects in the presence or absence of losartan.

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.

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.

Fully automated determination of nicotine and its major metabolites in whole blood by means of a DBS online-SPE LC-HR-MS/MS approach for sports drug testing.

PubMed

Tretzel, Laura; Thomas, Andreas; Piper, Thomas; Hedeland, Mikael; Geyer, Hans; Schänzer, Wilhelm; Thevis, Mario

2016-05-10

Dried blood spots (DBS) represent a sample matrix collected under minimal-invasive, straightforward and robust conditions. DBS specimens have been shown to provide appropriate test material for different analytical disciplines, e.g., preclinical drug development, therapeutic drug monitoring, forensic toxicology and diagnostic analysis of metabolic disorders in newborns. However, the sample preparation has occasionally been reported as laborious and time consuming. In order to minimize the manual workload and to substantiate the suitability of DBS for high sample-throughput, the automation of sample preparation processes is of paramount interest. In the current study, the development and validation of a fully automated DBS extraction method coupled to online solid-phase extraction using the example of nicotine, its major metabolites nornicotine, cotinine and trans-3'-hydroxycotinine and the tobacco alkaloids anabasine and anatabine is presented, based on the rationale that the use of nicotine-containing products for performance-enhancing purposes has been monitored by the World Anti-Doping Agency (WADA) for several years. Automation-derived DBS sample extracts were directed online to liquid chromatography high resolution/high mass accuracy tandem mass spectrometry, and target analytes were determined with support of four deuterated internal standards. Validation of the method yielded precise (CV <7.5% for intraday and <12.3% for interday measurements) and linear (r(2)>0.998) results. The limit of detection was established at 5 ng mL(-1) for all studied compounds, the extraction recovery ranged from 25 to 44%, and no matrix effects were observed. To exemplify the applicability of the DBS online-SPE LC-MS/MS approach for sports drug testing purposes, the method was applied to authentic DBS samples obtained from smokers, snus users, and e-cigarette users. Statistical evaluation of the obtained results indicated differences in metabolic behavior depending on the route of administration (inhalative versus buccal absorption) in terms of the ratio of nicotine and nornicotine. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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 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 automated framework for NMR resonance assignment through simultaneous slice picking and spin system forming.

PubMed

Abbas, Ahmed; Guo, Xianrong; Jing, Bing-Yi; Gao, Xin

2014-06-01

Despite significant advances in automated nuclear magnetic resonance-based protein structure determination, the high numbers of false positives and false negatives among the peaks selected by fully automated methods remain a problem. These false positives and negatives impair the performance of resonance assignment methods. One of the main reasons for this problem is that the computational research community often considers peak picking and resonance assignment to be two separate problems, whereas spectroscopists use expert knowledge to pick peaks and assign their resonances at the same time. We propose a novel framework that simultaneously conducts slice picking and spin system forming, an essential step in resonance assignment. Our framework then employs a genetic algorithm, directed by both connectivity information and amino acid typing information from the spin systems, to assign the spin systems to residues. The inputs to our framework can be as few as two commonly used spectra, i.e., CBCA(CO)NH and HNCACB. Different from the existing peak picking and resonance assignment methods that treat peaks as the units, our method is based on 'slices', which are one-dimensional vectors in three-dimensional spectra that correspond to certain ([Formula: see text]) values. Experimental results on both benchmark simulated data sets and four real protein data sets demonstrate that our method significantly outperforms the state-of-the-art methods while using a less number of spectra than those methods. Our method is freely available at http://sfb.kaust.edu.sa/Pages/Software.aspx.

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.

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.

An automated benchmarking platform for MHC class II binding prediction methods.

PubMed

Andreatta, Massimo; Trolle, Thomas; Yan, Zhen; Greenbaum, Jason A; Peters, Bjoern; Nielsen, Morten

2018-05-01

Computational methods for the prediction of peptide-MHC binding have become an integral and essential component for candidate selection in experimental T cell epitope discovery studies. The sheer amount of published prediction methods-and often discordant reports on their performance-poses a considerable quandary to the experimentalist who needs to choose the best tool for their research. With the goal to provide an unbiased, transparent evaluation of the state-of-the-art in the field, we created an automated platform to benchmark peptide-MHC class II binding prediction tools. The platform evaluates the absolute and relative predictive performance of all participating tools on data newly entered into the Immune Epitope Database (IEDB) before they are made public, thereby providing a frequent, unbiased assessment of available prediction tools. The benchmark runs on a weekly basis, is fully automated, and displays up-to-date results on a publicly accessible website. The initial benchmark described here included six commonly used prediction servers, but other tools are encouraged to join with a simple sign-up procedure. Performance evaluation on 59 data sets composed of over 10 000 binding affinity measurements suggested that NetMHCIIpan is currently the most accurate tool, followed by NN-align and the IEDB consensus method. Weekly reports on the participating methods can be found online at: http://tools.iedb.org/auto_bench/mhcii/weekly/. mniel@bioinformatics.dtu.dk. Supplementary data are available at Bioinformatics online.

Principal axes estimation using the vibration modes of physics-based deformable models.

PubMed

Krinidis, Stelios; Chatzis, Vassilios

2008-06-01

This paper addresses the issue of accurate, effective, computationally efficient, fast, and fully automated 2-D object orientation and scaling factor estimation. The object orientation is calculated using object principal axes estimation. The approach relies on the object's frequency-based features. The frequency-based features used by the proposed technique are extracted by a 2-D physics-based deformable model that parameterizes the objects shape. The method was evaluated on synthetic and real images. The experimental results demonstrate the accuracy of the method, both in orientation and the scaling estimations.

A Fully Automated Stage for Optical Waveguide Measurements

DTIC Science & Technology

1993-09-01

method, as in the case of the out-of-plane method, also relies on a certain level of uniformity in the waveguide. Accurate loss measurements over a...2 . The S1227-66BQ has a response from 190 nm to 1000 nm with a peak at 720 nm and a typical radiant sensitivity of 0.35 A/W at the peak wavelength 3... levels . The current generated in the detector due to incident light is converted to a voltage at the output of the operational amplifier (op-amp

[Point of Care 2.0: Coagulation Monitoring Using Rotem® Sigma and Teg® 6S].

PubMed

Weber, Christian Friedrich; Zacharowski, Kai

2018-06-01

New-generation methods for point of care based coagulation monitoring enable fully automated viscoelastic analyses for the assessment of particular parts of hemostasis. Contrary to the measuring techniques of former models, the viscoelastic ROTEM ® sigma and TEG ® 6s analyses are performed in single-use test cartridges without time- and personnel-intensive pre-analytical procedures. This review highlights methodical strengths and limitations of the devices and meets concerns associated with their integration in routine clinical practice. Georg Thieme Verlag KG Stuttgart · New York.

Implementation and Challenges of Direct Acoustic Dosing into Cell-Based Assays.

PubMed

Roberts, Karen; Callis, Rowena; Ikeda, Tim; Paunovic, Amalia; Simpson, Carly; Tang, Eric; Turton, Nick; Walker, Graeme

2016-02-01

Since the adoption of Labcyte Echo Acoustic Droplet Ejection (ADE) technology by AstraZeneca in 2005, ADE has become the preferred method for compound dosing into both biochemical and cell-based assays across AstraZeneca research and development globally. The initial implementation of Echos and the direct dosing workflow provided AstraZeneca with a unique set of challenges. In this article, we outline how direct Echo dosing has evolved over the past decade in AstraZeneca. We describe the practical challenges of applying ADE technology to 96-well, 384-well, and 1536-well assays and how AstraZeneca developed and applied software and robotic solutions to generate fully automated and effective cell-based assay workflows. © 2015 Society for Laboratory Automation and Screening.

An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study

USGS Publications Warehouse

Maddox, Brian G.; Swadley, Casey L.

2002-01-01

Attempts at fully automated object recognition systems have met with varying levels of success over the years. However, none of the systems have achieved high enough accuracy rates to be run unattended. One of the reasons for this may be that they are designed from the computer's point of view and rely mainly on image-processing methods. A better solution to this problem may be to make use of modern advances in computational intelligence and distributed processing to try to mimic how the human brain is thought to recognize objects. As humans combine cognitive processes with detection techniques, such a system would combine traditional image-processing techniques with computer-based intelligence to determine the identity of various objects in a scene.

An automatic experimental apparatus to study arm reaching in New World monkeys.

PubMed

Yin, Allen; An, Jehi; Lehew, Gary; Lebedev, Mikhail A; Nicolelis, Miguel A L

2016-05-01

Several species of the New World monkeys have been used as experimental models in biomedical and neurophysiological research. However, a method for controlled arm reaching tasks has not been developed for these species. We have developed a fully automated, pneumatically driven, portable, and reconfigurable experimental apparatus for arm-reaching tasks suitable for these small primates. We have utilized the apparatus to train two owl monkeys in a visually-cued arm-reaching task. Analysis of neural recordings demonstrates directional tuning of the M1 neurons. Our apparatus allows automated control, freeing the experimenter from manual experiments. The presented apparatus provides a valuable tool for conducting neurophysiological research on New World monkeys. Copyright © 2016. Published by Elsevier B.V.

A Tool for Requirements-Based Programming

NASA Technical Reports Server (NTRS)

Rash, James L.; Hinchey, Michael G.; Rouff, Christopher A.; Gracanin, Denis; Erickson, John

2005-01-01

Absent a general method for mathematically sound, automated transformation of customer requirements into a formal model of the desired system, developers must resort to either manual application of formal methods or to system testing (either manual or automated). While formal methods have afforded numerous successes, they present serious issues, e.g., costs to gear up to apply them (time, expensive staff), and scalability and reproducibility when standards in the field are not settled. The testing path cannot be walked to the ultimate goal, because exhaustive testing is infeasible for all but trivial systems. So system verification remains problematic. System or requirements validation is similarly problematic. The alternatives available today depend on either having a formal model or pursuing enough testing to enable the customer to be certain that system behavior meets requirements. The testing alternative for non-trivial systems always have some system behaviors unconfirmed and therefore is not the answer. To ensure that a formal model is equivalent to the customer s requirements necessitates that the customer somehow fully understands the formal model, which is not realistic. The predominant view that provably correct system development depends on having a formal model of the system leads to a desire for a mathematically sound method to automate the transformation of customer requirements into a formal model. Such a method, an augmentation of requirements-based programming, will be briefly described in this paper, and a prototype tool to support it will be described. The method and tool enable both requirements validation and system verification for the class of systems whose behavior can be described as scenarios. An application of the tool to a prototype automated ground control system for NASA mission is presented.

A Bright Future for Evolutionary Methods in Drug Design.

PubMed

Le, Tu C; Winkler, David A

2015-08-01

Most medicinal chemists understand that chemical space is extremely large, essentially infinite. Although high-throughput experimental methods allow exploration of drug-like space more rapidly, they are still insufficient to fully exploit the opportunities that such large chemical space offers. Evolutionary methods can synergistically blend automated synthesis and characterization methods with computational design to identify promising regions of chemical space more efficiently. We describe how evolutionary methods are implemented, and provide examples of published drug development research in which these methods have generated molecules with increased efficacy. We anticipate that evolutionary methods will play an important role in future drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

AISLE: an automatic volumetric segmentation method for the study of lung allometry.

PubMed

Ren, Hongliang; Kazanzides, Peter

2011-01-01

We developed a fully automatic segmentation method for volumetric CT (computer tomography) datasets to support construction of a statistical atlas for the study of allometric laws of the lung. The proposed segmentation method, AISLE (Automated ITK-Snap based on Level-set), is based on the level-set implementation from an existing semi-automatic segmentation program, ITK-Snap. AISLE can segment the lung field without human interaction and provide intermediate graphical results as desired. The preliminary experimental results show that the proposed method can achieve accurate segmentation, in terms of volumetric overlap metric, by comparing with the ground-truth segmentation performed by a radiologist.

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.

A new automated turbidimetric immunoassay for the measurement of canine C-reactive protein.

PubMed

Piñeiro, Matilde; Pato, Raquel; Soler, Lourdes; Peña, Raquel; García, Natalia; Torrente, Carlos; Saco, Yolanda; Lampreave, Fermín; Bassols, Anna; Canalias, Francesca

2018-03-01

In dogs, as in humans, C-reactive protein (CRP) is a major acute phase protein that is rapidly and prominently increased after exposure to inflammatory stimuli. CRP measurements are used in the diagnosis and monitoring of infectious and inflammatory diseases. The study aim was to develop and validate a turbidimetric immunoassay for the quantification of canine CRP (cCRP), using canine-specific reagents and standards. A particle-enhanced turbidimetric immunoassay was developed. The assay was set up in a fully automated analyzer, and studies of imprecision, limits of linearity, limits of detection, prozone effects, and interferences were carried out. The new method was compared with 2 other commercially available automated immunoassays for cCRP: one turbidimetric immunoassay (Gentian CRP) and one point-of-care assay based on magnetic permeability (Life Assays CRP). The within-run and between-day imprecision were <1.7% and 4.2%, respectively. The assay quantified CRP proportionally in an analytic range up to 150 mg/L, with a prozone effect appearing at cCRP concentrations >320 mg/L. No interference from hemoglobin (20 g/L), triglycerides (10 g/L), or bilirubin (150 mg/L) was detected. Good agreement was observed between the results obtained with the new method and the Gentian cCRP turbidimetric immunoassay. The new turbidimetric immunoassay (Turbovet canine CRP, Acuvet Biotech) is a rapid, robust, precise, and accurate method for the quantification of cCRP. The method can be easily set up in automated analyzers, providing a suitable tool for routine clinical use. © 2018 American Society for Veterinary Clinical Pathology.

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.

Liver vessels segmentation using a hybrid geometrical moments/graph cuts method

PubMed Central

Esneault, Simon; Lafon, Cyril; Dillenseger, Jean-Louis

2010-01-01

This paper describes a fast and fully-automatic method for liver vessel segmentation on CT scan pre-operative images. The basis of this method is the introduction of a 3-D geometrical moment-based detector of cylindrical shapes within the min-cut/max-flow energy minimization framework. This method represents an original way to introduce a data term as a constraint into the widely used Boykov’s graph cuts algorithm and hence, to automate the segmentation. The method is evaluated and compared with others on a synthetic dataset. Finally, the relevancy of our method regarding the planning of a -necessarily accurate- percutaneous high intensity focused ultrasound surgical operation is demonstrated with some examples. PMID:19783500

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.

Evaluation of a next generation direct whole blood enzymatic assay for hemoglobin A1c on the ARCHITECT c8000 chemistry system.

PubMed

Teodoro-Morrison, Tracy; Janssen, Marcel J W; Mols, Jasper; Hendrickx, Ben H E; Velmans, Mathieu H; Lotz, Johannes; Lackner, Karl; Lennartz, Lieselotte; Armbruster, David; Maine, Gregory; Yip, Paul M

2015-01-01

The utility of HbA1c for the diagnosis of type 2 diabetes requires an accurate, precise and robust test measurement system. Currently, immunoassay and HPLC are the most popular methods for HbA1c quantification, noting however the limitations associated with some platforms, such as imprecision or interference from common hemoglobin variants. Abbott Diagnostics has introduced a fully automated direct enzymatic method for the quantification of HbA1c from whole blood on the ARCHITECT chemistry system. Here we completed a method evaluation of the ARCHITECT HbA1c enzymatic assay for imprecision, accuracy, method comparison, interference from hemoglobin variants and specimen stability. This was completed at three independent clinical laboratories in North America and Europe. The total imprecision ranged from 0.5% to 2.2% CV with low and high level control materials. Around the diagnostic cut-off of 48 mmol/mol, the total imprecision was 0.6% CV. Mean bias using reference samples from IFCC and CAP ranged from -1.1 to 1.0 mmol/mol. The enzymatic assay also showed excellent agreement with HPLC methods, with slopes of 1.01 and correlation coefficients ranging from 0.984 to 0.996 compared to Menarini Adams HA-8160, Bio-Rad Variant II and Variant II Turbo instruments. Finally, no significant effect was observed for erythrocyte sedimentation or interference from common hemoglobin variants in patient samples containing heterozygous HbS, HbC, HbD, HbE, and up to 10% HbF. The ARCHITECT enzymatic assay for HbA1c is a robust and fully automated method that meets the performance requirements to support the diagnosis of type 2 diabetes.

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.

Flood mapping in ungauged basins using fully continuous hydrologic-hydraulic modeling

NASA Astrophysics Data System (ADS)

Grimaldi, Salvatore; Petroselli, Andrea; Arcangeletti, Ettore; Nardi, Fernando

2013-04-01

SummaryIn this work, a fully-continuous hydrologic-hydraulic modeling framework for flood mapping is introduced and tested. It is characterized by a simulation of a long rainfall time series at sub-daily resolution that feeds a continuous rainfall-runoff model producing a discharge time series that is directly given as an input to a bi-dimensional hydraulic model. The main advantage of the proposed approach is to avoid the use of the design hyetograph and the design hydrograph that constitute the main source of subjective analysis and uncertainty for standard methods. The proposed procedure is optimized for small and ungauged watersheds where empirical models are commonly applied. Results of a simple real case study confirm that this experimental fully-continuous framework may pave the way for the implementation of a less subjective and potentially automated procedure for flood hazard mapping.

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

PubMed Central

Burns, Joseph E.; Yao, Jianhua; Muñoz, Hector

2016-01-01

Purpose To design and validate a fully automated computer system for the detection and anatomic localization of traumatic thoracic and lumbar vertebral body fractures at computed tomography (CT). Materials and Methods This retrospective study was HIPAA compliant. Institutional review board approval was obtained, and informed consent was waived. CT examinations in 104 patients (mean age, 34.4 years; range, 14–88 years; 32 women, 72 men), consisting of 94 examinations with positive findings for fractures (59 with vertebral body fractures) and 10 control examinations (without vertebral fractures), were performed. There were 141 thoracic and lumbar vertebral body fractures in the case set. The locations of fractures were marked and classified by a radiologist according to Denis column involvement. The CT data set was divided into training and testing subsets (37 and 67 subsets, respectively) for analysis by means of prototype software for fully automated spinal segmentation and fracture detection. Free-response receiver operating characteristic analysis was performed. Results Training set sensitivity for detection and localization of fractures within each vertebra was 0.82 (28 of 34 findings; 95% confidence interval [CI]: 0.68, 0.90), with a false-positive rate of 2.5 findings per patient. The sensitivity for fracture localization to the correct vertebra was 0.88 (23 of 26 findings; 95% CI: 0.72, 0.96), with a false-positive rate of 1.3. Testing set sensitivity for the detection and localization of fractures within each vertebra was 0.81 (87 of 107 findings; 95% CI: 0.75, 0.87), with a false-positive rate of 2.7. The sensitivity for fracture localization to the correct vertebra was 0.92 (55 of 60 findings; 95% CI: 0.79, 0.94), with a false-positive rate of 1.6. The most common cause of false-positive findings was nutrient foramina (106 of 272 findings [39%]). Conclusion The fully automated computer system detects and anatomically localizes vertebral body fractures in the thoracic and lumbar spine on CT images with a high sensitivity and a low false-positive rate. © RSNA, 2015 Online supplemental material is available for this article. PMID:26172532

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.

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

NASA Astrophysics Data System (ADS)

Pandey, Shivendra Kumar; Manivannan, Anbarasu

2018-03-01

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

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 Inspection of Power Line Corridors to Measure Vegetation Undercut Using Uav-Based Images

NASA Astrophysics Data System (ADS)

Maurer, M.; Hofer, M.; Fraundorfer, F.; Bischof, H.

2017-08-01

Power line corridor inspection is a time consuming task that is performed mostly manually. As the development of UAVs made huge progress in recent years, and photogrammetric computer vision systems became well established, it is time to further automate inspection tasks. In this paper we present an automated processing pipeline to inspect vegetation undercuts of power line corridors. For this, the area of inspection is reconstructed, geo-referenced, semantically segmented and inter class distance measurements are calculated. The presented pipeline performs an automated selection of the proper 3D reconstruction method for on the one hand wiry (power line), and on the other hand solid objects (surrounding). The automated selection is realized by performing pixel-wise semantic segmentation of the input images using a Fully Convolutional Neural Network. Due to the geo-referenced semantic 3D reconstructions a documentation of areas where maintenance work has to be performed is inherently included in the distance measurements and can be extracted easily. We evaluate the influence of the semantic segmentation according to the 3D reconstruction and show that the automated semantic separation in wiry and dense objects of the 3D reconstruction routine improves the quality of the vegetation undercut inspection. We show the generalization of the semantic segmentation to datasets acquired using different acquisition routines and to varied seasons in time.

Comparison of water-quality samples collected by siphon samplers and automatic samplers in Wisconsin

USGS Publications Warehouse

Graczyk, David J.; Robertson, Dale M.; Rose, William J.; Steur, Jeffrey J.

2000-01-01

In small streams, flow and water-quality concentrations often change quickly in response to meteorological events. Hydrologists, field technicians, or locally hired stream ob- servers involved in water-data collection are often unable to reach streams quickly enough to observe or measure these rapid changes. Therefore, in hydrologic studies designed to describe changes in water quality, a combination of manual and automated sampling methods have commonly been used manual methods when flow is relatively stable and automated methods when flow is rapidly changing. Auto- mated sampling, which makes use of equipment programmed to collect samples in response to changes in stage and flow of a stream, has been shown to be an effective method of sampling to describe the rapid changes in water quality (Graczyk and others, 1993). Because of the high cost of automated sampling, however, especially for studies examining a large number of sites, alternative methods have been considered for collecting samples during rapidly changing stream conditions. One such method employs the siphon sampler (fig. 1). also referred to as the "single-stage sampler." Siphon samplers are inexpensive to build (about $25- $50 per sampler), operate, and maintain, so they are cost effective to use at a large number of sites. Their ability to collect samples representing the average quality of water passing though the entire cross section of a stream, however, has not been fully demonstrated for many types of stream sites.

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

A Fully Automated Supraglacial lake area and volume Tracking ("FAST") algorithm: development and application using MODIS imagery of West Greenland

NASA Astrophysics Data System (ADS)

Williamson, Andrew; Arnold, Neil; Banwell, Alison; Willis, Ian

2017-04-01

Supraglacial lakes (SGLs) on the Greenland Ice Sheet (GrIS) influence ice dynamics if draining rapidly by hydrofracture, which can occur in under 24 hours. MODerate-resolution Imaging Spectroradiometer (MODIS) data are often used to investigate SGLs, including calculating SGL area changes through time, but no existing work presents a method that tracks changes in individual (and total) SGL volume in MODIS imagery over a melt season. Here, we present such a method. First, we tested three automated approaches to derive SGL areas from MODIS imagery by comparing calculated areas for the Paakitsoq and Store Glacier regions in West Greenland with areas derived from Landsat-8 (LS8) images. Second, we applied a physically-based depth-calculation algorithm to the pixels within the SGL boundaries from the best performing method, and validated the resultant depths with those calculated using the same method applied to LS8 imagery. Our results indicated that SGL areas are most accurately generated using dynamic thresholding of MODIS band 1 (red) with a 0.640 threshold value. Calculated SGL area, depth and volume values from MODIS were closely comparable to those derived from LS8. The best performing area- and depth-detection methods were then incorporated into a Fully Automated SGL Tracking ("FAST") algorithm that tracks individual SGLs between successive MODIS images. It identified 43 (Paakitsoq) and 19 (Store Glacier) rapidly draining SGLs during 2014, representing 21% and 15% of the respective total SGL populations, including some clusters of rapidly draining SGLs. We found no relationship between the water volumes contained within these rapidly draining SGLs and the ice thicknesses beneath them, indicating that a critical water volume linearly related to ice thickness cannot explain the incidence of rapid drainage. The FAST algorithm, which we believe to be the most comprehensive SGL tracking algorithm developed to date, has the potential to investigate statistical relationships between SGL areas, volumes and drainage events over wide areas of the GrIS, and over multiple seasons. It could also allow further insights into factors that may trigger rapid SGL drainage.

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

PubMed

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

2018-05-01

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

Automated seismic waveform location using Multichannel Coherency Migration (MCM)-I. Theory

NASA Astrophysics Data System (ADS)

Shi, Peidong; Angus, Doug; Rost, Sebastian; Nowacki, Andy; Yuan, Sanyi

2018-03-01

With the proliferation of dense seismic networks sampling the full seismic wavefield, recorded seismic data volumes are getting bigger and automated analysis tools to locate seismic events are essential. Here, we propose a novel Multichannel Coherency Migration (MCM) method to locate earthquakes in continuous seismic data and reveal the location and origin time of seismic events directly from recorded waveforms. By continuously calculating the coherency between waveforms from different receiver pairs, MCM greatly expands the available information which can be used for event location. MCM does not require phase picking or phase identification, which allows fully automated waveform analysis. By migrating the coherency between waveforms, MCM leads to improved source energy focusing. We have tested and compared MCM to other migration-based methods in noise-free and noisy synthetic data. The tests and analysis show that MCM is noise resistant and can achieve more accurate results compared with other migration-based methods. MCM is able to suppress strong interference from other seismic sources occurring at a similar time and location. It can be used with arbitrary 3D velocity models and is able to obtain reasonable location results with smooth but inaccurate velocity models. MCM exhibits excellent location performance and can be easily parallelized giving it large potential to be developed as a real-time location method for very large datasets.

A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients

NASA Astrophysics Data System (ADS)

Agn, Mikael; Law, Ian; Munck af Rosenschöld, Per; Van Leemput, Koen

2016-03-01

We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which uses convolutional restricted Boltzmann machines to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma patients by comparing segmentations of gross tumor volume, brainstem and hippocampus. The preliminary results demonstrate the feasibility of the method.

Unsupervised automated high throughput phenotyping of RNAi time-lapse movies.

PubMed

Failmezger, Henrik; Fröhlich, Holger; Tresch, Achim

2013-10-04

Gene perturbation experiments in combination with fluorescence time-lapse cell imaging are a powerful tool in reverse genetics. High content applications require tools for the automated processing of the large amounts of data. These tools include in general several image processing steps, the extraction of morphological descriptors, and the grouping of cells into phenotype classes according to their descriptors. This phenotyping can be applied in a supervised or an unsupervised manner. Unsupervised methods are suitable for the discovery of formerly unknown phenotypes, which are expected to occur in high-throughput RNAi time-lapse screens. We developed an unsupervised phenotyping approach based on Hidden Markov Models (HMMs) with multivariate Gaussian emissions for the detection of knockdown-specific phenotypes in RNAi time-lapse movies. The automated detection of abnormal cell morphologies allows us to assign a phenotypic fingerprint to each gene knockdown. By applying our method to the Mitocheck database, we show that a phenotypic fingerprint is indicative of a gene's function. Our fully unsupervised HMM-based phenotyping is able to automatically identify cell morphologies that are specific for a certain knockdown. Beyond the identification of genes whose knockdown affects cell morphology, phenotypic fingerprints can be used to find modules of functionally related genes.

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.

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

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...

Human Papillomavirus (HPV) Genotyping: Automation and Application in Routine Laboratory Testing

PubMed Central

Torres, M; Fraile, L; Echevarria, JM; Hernandez Novoa, B; Ortiz, M

2012-01-01

A large number of assays designed for genotyping human papillomaviruses (HPV) have been developed in the last years. They perform within a wide range of analytical sensitivity and specificity values for the different viral types, and are used either for diagnosis, epidemiological studies, evaluation of vaccines and implementing and monitoring of vaccination programs. Methods for specific genotyping of HPV-16 and HPV-18 are also useful for the prevention of cervical cancer in screening programs. Some commercial tests are, in addition, fully or partially automated. Automation of HPV genotyping presents advantages such as the simplicity of the testing procedure for the operator, the ability to process a large number of samples in a short time, and the reduction of human errors from manual operations, allowing a better quality assurance and a reduction of cost. The present review collects information about the current HPV genotyping tests, with special attention to practical aspects influencing their use in clinical laboratories. PMID:23248734

The discriminatory power of ribotyping as automatable technique for differentiation of bacteria.

PubMed

Schumann, Peter; Pukall, Rüdiger

2013-09-01

Since the introduction of ribonucleic acid gene restriction patterns as taxonomic tools in 1986, ribotyping has become an established method for systematics, epidemiological, ecological and population studies of microorganisms. In the last 25 years, several modifications have improved the convenience, reproducibility and turn-around time of this technique. The technological development culminated in the automation of ribotyping which allowed for high-throughput applications e.g. in the quality control of food production, pharmaceutical industry and culture collections. The capability of the fully automated RiboPrinter(®) System for the differentiation of bacteria below the species level is compared with the discriminatory power of traditional ribotyping, of molecular fingerprint techniques like PFGE, MLST and MLVA as well as of MALDI-TOF mass spectrometry. While automated RiboPrinting is advantageous with respect to standardization, ease and speed, PCR ribotyping has proved being a highly discriminatory, flexible, robust and cost-efficient routine technique which makes inter-laboratory comparison and build of ribotype databases possible, too. Copyright © 2013 Elsevier GmbH. All rights reserved.

Rapid, automated mosaicking of the human corneal subbasal nerve plexus.

PubMed

Vaishnav, Yash J; Rucker, Stuart A; Saharia, Keshav; McNamara, Nancy A

2017-11-27

Corneal confocal microscopy (CCM) is an in vivo technique used to study corneal nerve morphology. The largest proportion of nerves innervating the cornea lie within the subbasal nerve plexus, where their morphology is altered by refractive surgery, diabetes and dry eye. The main limitations to clinical use of CCM as a diagnostic tool are the small field of view of CCM images and the lengthy time needed to quantify nerves in collected images. Here, we present a novel, rapid, fully automated technique to mosaic individual CCM images into wide-field maps of corneal nerves. We implemented an OpenCV image stitcher that accounts for corneal deformation and uses feature detection to stitch CCM images into a montage. The method takes 3-5 min to process and stitch 40-100 frames on an Amazon EC2 Micro instance. The speed, automation and ease of use conferred by this technique is the first step toward point of care evaluation of wide-field subbasal plexus (SBP) maps in a clinical setting.

DNA fingerprinting of Shiga-toxin producing Escherichia coli O157 based on Multiple-Locus Variable-Number Tandem-Repeats Analysis (MLVA)

PubMed Central

Lindstedt, Bjørn-Arne; Heir, Even; Gjernes, Elisabet; Vardund, Traute; Kapperud, Georg

2003-01-01

Background The ability to react early to possible outbreaks of Escherichia coli O157:H7 and to trace possible sources relies on the availability of highly discriminatory and reliable techniques. The development of methods that are fast and has the potential for complete automation is needed for this important pathogen. Methods In all 73 isolates of shiga-toxin producing E. coli O157 (STEC) were used in this study. The two available fully sequenced STEC genomes were scanned for tandem repeated stretches of DNA, which were evaluated as polymorphic markers for isolate identification. Results The 73 E. coli isolates displayed 47 distinct patterns and the MLVA assay was capable of high discrimination between the E. coli O157 strains. The assay was fast and all the steps can be automated. Conclusion The findings demonstrate a novel high discriminatory molecular typing method for the important pathogen E. coli O157 that is fast, robust and offers many advantages compared to current methods. PMID:14664722

Integrating Online and Offline Three-Dimensional Deep Learning for Automated Polyp Detection in Colonoscopy Videos.

PubMed

Lequan Yu; Hao Chen; Qi Dou; Jing Qin; Pheng Ann Heng

2017-01-01

Automated polyp detection in colonoscopy videos has been demonstrated to be a promising way for colorectal cancer prevention and diagnosis. Traditional manual screening is time consuming, operator dependent, and error prone; hence, automated detection approach is highly demanded in clinical practice. However, automated polyp detection is very challenging due to high intraclass variations in polyp size, color, shape, and texture, and low interclass variations between polyps and hard mimics. In this paper, we propose a novel offline and online three-dimensional (3-D) deep learning integration framework by leveraging the 3-D fully convolutional network (3D-FCN) to tackle this challenging problem. Compared with the previous methods employing hand-crafted features or 2-D convolutional neural network, the 3D-FCN is capable of learning more representative spatio-temporal features from colonoscopy videos, and hence has more powerful discrimination capability. More importantly, we propose a novel online learning scheme to deal with the problem of limited training data by harnessing the specific information of an input video in the learning process. We integrate offline and online learning to effectively reduce the number of false positives generated by the offline network and further improve the detection performance. Extensive experiments on the dataset of MICCAI 2015 Challenge on Polyp Detection demonstrated the better performance of our method when compared with other competitors.

Automated assay for screening the enzymatic release of reducing sugars from micronized biomass.

PubMed

Navarro, David; Couturier, Marie; da Silva, Gabriela Ghizzi Damasceno; Berrin, Jean-Guy; Rouau, Xavier; Asther, Marcel; Bignon, Christophe

2010-07-16

To reduce the production cost of bioethanol obtained from fermentation of the sugars provided by degradation of lignocellulosic biomass (i.e., second generation bioethanol), it is necessary to screen for new enzymes endowed with more efficient biomass degrading properties. This demands the set-up of high-throughput screening methods. Several methods have been devised all using microplates in the industrial SBS format. Although this size reduction and standardization has greatly improved the screening process, the published methods comprise one or more manual steps that seriously decrease throughput. Therefore, we worked to devise a screening method devoid of any manual steps. We describe a fully automated assay for measuring the amount of reducing sugars released by biomass-degrading enzymes from wheat-straw and spruce. The method comprises two independent and automated steps. The first step is the making of "substrate plates". It consists of filling 96-well microplates with slurry suspensions of micronized substrate which are then stored frozen until use. The second step is an enzymatic activity assay. After thawing, the substrate plates are supplemented by the robot with cell-wall degrading enzymes where necessary, and the whole process from addition of enzymes to quantification of released sugars is autonomously performed by the robot. We describe how critical parameters (amount of substrate, amount of enzyme, incubation duration and temperature) were selected to fit with our specific use. The ability of this automated small-scale assay to discriminate among different enzymatic activities was validated using a set of commercial enzymes. Using an automatic microplate sealer solved three main problems generally encountered during the set-up of methods for measuring the sugar-releasing activity of plant cell wall-degrading enzymes: throughput, automation, and evaporation losses. In its present set-up, the robot can autonomously process 120 triplicate wheat-straw samples per day. This throughput can be doubled if the incubation time is reduced from 24 h to 4 h (for initial rates measurements, for instance). This method can potentially be used with any insoluble substrate that is micronizable. A video illustrating the method can be seen at the following URL: http://www.youtube.com/watch?v=NFg6TxjuMWU.

A Fully Automated Method of Locating Building Shadows for Aerosol Optical Depth Calculations in High-Resolution Satellite Imagery

DTIC Science & Technology

2010-09-01

absorption, limiting the effectiveness of intelligence collection and weapon systems that operate in those portions of the spectrum by reducing the amount of... Intelligence Agency Web site in NITF 2.0 format. This study used basic imagery from DigitalGlobe (QuickBird, WorldView-1). This imagery is not...databases. Militarily, FASTEC could enable in-scene correction in intelligence collection and possibly influence electro- optical targeting decisions

A semi-automated region of interest detection method in the scintigraphic glomerular filtration rate determination for patients with abnormal low renal function.

PubMed

Tian, Cancan; Zheng, Xiujuan; Han, Yuan; Sun, Xiaoguang; Chen, Kewei; Huang, Qiu

2013-11-01

This work presents a novel semi-automated renal region-of-interest (ROI) determination method that is user friendly, time saving, and yet provides a robust glomerular filtration rate (GFR) estimation highly consistent with the reference method. We reviewed data from 57 patients who underwent (99m)Tc-diethylenetriaminepentaacetic acid renal scintigraphy and were diagnosed with abnormal renal function. The renal and background ROIs were delineated by the proposed multi-step, semi-automated method, which integrates temporal/morphologic information via visual inspection and computer-aided calculations. The total GFR was estimated using the proposed method (sGFR) performed by 2 junior clinicians (A and B) with 1 and 3 years of experience, respectively (sGFR_a, sGFR_b), and compared with the reference total GFR (rGFR) estimated by a senior clinician with 20 years of experience who manually delineated the kidney and background ROIs. All GFR calculations herein were conducted using the Gates method. Data from 10 patients with unilateral or non-functioning kidneys were excluded from the analysis. For the remaining patients, sGFR correlated well with rGFR (r(s/rGFR_a) = 0.957, P < 0.001 and r(s/rGFR_b) = 0.951, P < 0.001) and sGFR_a correlated well with sGFR_b (r(a/b) = 0.997, P < 0.001). Moreover, the Bland-Altman plots for sGFR_a and sGFR_b confirm the high reproducibility of the proposed method between different operators. Finally, the proposed procedure is almost 3 times faster than the routinely used procedure in clinical practice. The results suggest that this method is easy to use, highly reproducible, and accurate in measuring the GFR of patients with low renal function. The method is being further extended to a fully automated procedure.

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.

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

Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

NASA Astrophysics Data System (ADS)

Roth, Holger; Oda, Masahiro; Shimizu, Natsuki; Oda, Hirohisa; Hayashi, Yuichiro; Kitasaka, Takayuki; Fujiwara, Michitaka; Misawa, Kazunari; Mori, Kensaku

2018-03-01

Pancreas segmentation in computed tomography imaging has been historically difficult for automated methods because of the large shape and size variations between patients. In this work, we describe a custom-build 3D fully convolutional network (FCN) that can process a 3D image including the whole pancreas and produce an automatic segmentation. We investigate two variations of the 3D FCN architecture; one with concatenation and one with summation skip connections to the decoder part of the network. We evaluate our methods on a dataset from a clinical trial with gastric cancer patients, including 147 contrast enhanced abdominal CT scans acquired in the portal venous phase. Using the summation architecture, we achieve an average Dice score of 89.7 +/- 3.8 (range [79.8, 94.8])% in testing, achieving the new state-of-the-art performance in pancreas segmentation on this dataset.

Segmentation of anatomical branching structures based on texture features and conditional random field

NASA Astrophysics Data System (ADS)

Nuzhnaya, Tatyana; Bakic, Predrag; Kontos, Despina; Megalooikonomou, Vasileios; Ling, Haibin

2012-02-01

This work is a part of our ongoing study aimed at understanding a relation between the topology of anatomical branching structures with the underlying image texture. Morphological variability of the breast ductal network is associated with subsequent development of abnormalities in patients with nipple discharge such as papilloma, breast cancer and atypia. In this work, we investigate complex dependence among ductal components to perform segmentation, the first step for analyzing topology of ductal lobes. Our automated framework is based on incorporating a conditional random field with texture descriptors of skewness, coarseness, contrast, energy and fractal dimension. These features are selected to capture the architectural variability of the enhanced ducts by encoding spatial variations between pixel patches in galactographic image. The segmentation algorithm was applied to a dataset of 20 x-ray galactograms obtained at the Hospital of the University of Pennsylvania. We compared the performance of the proposed approach with fully and semi automated segmentation algorithms based on neural network classification, fuzzy-connectedness, vesselness filter and graph cuts. Global consistency error and confusion matrix analysis were used as accuracy measurements. For the proposed approach, the true positive rate was higher and the false negative rate was significantly lower compared to other fully automated methods. This indicates that segmentation based on CRF incorporated with texture descriptors has potential to efficiently support the analysis of complex topology of the ducts and aid in development of realistic breast anatomy phantoms.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

SU-G-TeP1-05: Development and Clinical Introduction of Automated Radiotherapy Treatment Planning for Prostate Cancer

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

Winkel, D; Bol, GH; Asselen, B van

Purpose: To develop an automated radiotherapy treatment planning and optimization workflow for prostate cancer in order to generate clinical treatment plans. Methods: A fully automated radiotherapy treatment planning and optimization workflow was developed based on the treatment planning system Monaco (Elekta AB, Stockholm, Sweden). To evaluate our method, a retrospective planning study (n=100) was performed on patients treated for prostate cancer with 5 field intensity modulated radiotherapy, receiving a dose of 35×2Gy to the prostate and vesicles and a simultaneous integrated boost of 35×0.2Gy to the prostate only. A comparison was made between the dosimetric values of the automatically andmore » manually generated plans. Operator time to generate a plan and plan efficiency was measured. Results: A comparison of the dosimetric values show that automatically generated plans yield more beneficial dosimetric values. In automatic plans reductions of 43% in the V72Gy of the rectum and 13% in the V72Gy of the bladder are observed when compared to the manually generated plans. Smaller variance in dosimetric values is seen, i.e. the intra- and interplanner variability is decreased. For 97% of the automatically generated plans and 86% of the clinical plans all criteria for target coverage and organs at risk constraints are met. The amount of plan segments and monitor units is reduced by 13% and 9% respectively. Automated planning requires less than one minute of operator time compared to over an hour for manual planning. Conclusion: The automatically generated plans are highly suitable for clinical use. The plans have less variance and a large gain in time efficiency has been achieved. Currently, a pilot study is performed, comparing the preference of the clinician and clinical physicist for the automatic versus manual plan. Future work will include expanding our automated treatment planning method to other tumor sites and develop other automated radiotherapy workflows.« less

Automated image analysis of alpha-particle autoradiographs of human bone

NASA Astrophysics Data System (ADS)

Hatzialekou, Urania; Henshaw, Denis L.; Fews, A. Peter

1988-01-01

Further techniques [4,5] for the analysis of CR-39 α-particle autoradiographs have been developed for application to α-autoradiography of autopsy bone at natural levels for exposure. The most significant new approach is the use of fully automated image analysis using a system developed in this laboratory. A 5 cm × 5 cm autoradiograph of tissue in which the activity is below 1 Bq kg -1 is scanned to both locate and measure the recorded α-particle tracks at a rate of 5 cm 2/h. Improved methods of calibration have also been developed. The techniques are described and in order to illustrate their application, a bone sample contaminated with 239Pu is analysed. Results from natural levels are the subject of a separate publication.

Microvessel prediction in H&E Stained Pathology Images using fully convolutional neural networks.

PubMed

Yi, Faliu; Yang, Lin; Wang, Shidan; Guo, Lei; Huang, Chenglong; Xie, Yang; Xiao, Guanghua

2018-02-27

Pathological angiogenesis has been identified in many malignancies as a potential prognostic factor and target for therapy. In most cases, angiogenic analysis is based on the measurement of microvessel density (MVD) detected by immunostaining of CD31 or CD34. However, most retrievable public data is generally composed of Hematoxylin and Eosin (H&E)-stained pathology images, for which is difficult to get the corresponding immunohistochemistry images. The role of microvessels in H&E stained images has not been widely studied due to their complexity and heterogeneity. Furthermore, identifying microvessels manually for study is a labor-intensive task for pathologists, with high inter- and intra-observer variation. Therefore, it is important to develop automated microvessel-detection algorithms in H&E stained pathology images for clinical association analysis. In this paper, we propose a microvessel prediction method using fully convolutional neural networks. The feasibility of our proposed algorithm is demonstrated through experimental results on H&E stained images. Furthermore, the identified microvessel features were significantly associated with the patient clinical outcomes. This is the first study to develop an algorithm for automated microvessel detection in H&E stained pathology images.

Restructuring of international council for standardization in haematology (ICSH) in Asia.

PubMed

Tatsumi, N; Lewis, S M

2002-08-01

Standardization and harmonization in Laboratory testing are a key issue in the midst of globalization era, because most of laboratory testing has been currently achieved with various kinds of automated systems. In the developed countries, automated systems with highly-regulated principles are commonly used in the routine laboratory. However, there are so many undeveloped and developing countries in Asia that diversity of testing levels can be observed in the area. Some laboratories use glass chamber method for blood cell counting, while other laboratory use semi-automated or fully automated analyzers for complete blood count. International standardization on Hematology is focused on the developed system but not for the developing system. Established standardized documents therefore whould not be unsuitable for Asian societies. In the context, International Council for Standardization in Hematology (ICSH) changed its rules to adjust our Asian Societies and ICSH started to restructure the body. International ICSH society is divided into 5 region sub-groups. Asian area is able to possess one new sub-society, ICSH-Asia. Its reconstruction work has been just started with Asain colleagues, and we are now extending the new societies to discuss Asian problems on the quality of hematology testing.

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

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.

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.

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.

Artificial Neural Networks as a powerful numerical tool to classify specific features of a tooth based on 3D scan data.

PubMed

Raith, Stefan; Vogel, Eric Per; Anees, Naeema; Keul, Christine; Güth, Jan-Frederik; Edelhoff, Daniel; Fischer, Horst

2017-01-01

Chairside manufacturing based on digital image acquisition is gainingincreasing importance in dentistry. For the standardized application of these methods, it is paramount to have highly automated digital workflows that can process acquired 3D image data of dental surfaces. Artificial Neural Networks (ANNs) arenumerical methods primarily used to mimic the complex networks of neural connections in the natural brain. Our hypothesis is that an ANNcan be developed that is capable of classifying dental cusps with sufficient accuracy. This bears enormous potential for an application in chairside manufacturing workflows in the dental field, as it closes the gap between digital acquisition of dental geometries and modern computer-aided manufacturing techniques.Three-dimensional surface scans of dental casts representing natural full dental arches were transformed to range image data. These data were processed using an automated algorithm to detect candidates for tooth cusps according to salient geometrical features. These candidates were classified following common dental terminology and used as training data for a tailored ANN.For the actual cusp feature description, two different approaches were developed and applied to the available data: The first uses the relative location of the detected cusps as input data and the second method directly takes the image information given in the range images. In addition, a combination of both was implemented and investigated.Both approaches showed high performance with correct classifications of 93.3% and 93.5%, respectively, with improvements by the combination shown to be minor.This article presents for the first time a fully automated method for the classification of teeththat could be confirmed to work with sufficient precision to exhibit the potential for its use in clinical practice,which is a prerequisite for automated computer-aided planning of prosthetic treatments with subsequent automated chairside manufacturing. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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.

MIMoSA: An Automated Method for Intermodal Segmentation Analysis of Multiple Sclerosis Brain Lesions.

PubMed

Valcarcel, Alessandra M; Linn, Kristin A; Vandekar, Simon N; Satterthwaite, Theodore D; Muschelli, John; Calabresi, Peter A; Pham, Dzung L; Martin, Melissa Lynne; Shinohara, Russell T

2018-03-08

Magnetic resonance imaging (MRI) is crucial for in vivo detection and characterization of white matter lesions (WMLs) in multiple sclerosis. While WMLs have been studied for over two decades using MRI, automated segmentation remains challenging. Although the majority of statistical techniques for the automated segmentation of WMLs are based on single imaging modalities, recent advances have used multimodal techniques for identifying WMLs. Complementary modalities emphasize different tissue properties, which help identify interrelated features of lesions. Method for Inter-Modal Segmentation Analysis (MIMoSA), a fully automatic lesion segmentation algorithm that utilizes novel covariance features from intermodal coupling regression in addition to mean structure to model the probability lesion is contained in each voxel, is proposed. MIMoSA was validated by comparison with both expert manual and other automated segmentation methods in two datasets. The first included 98 subjects imaged at Johns Hopkins Hospital in which bootstrap cross-validation was used to compare the performance of MIMoSA against OASIS and LesionTOADS, two popular automatic segmentation approaches. For a secondary validation, a publicly available data from a segmentation challenge were used for performance benchmarking. In the Johns Hopkins study, MIMoSA yielded average Sørensen-Dice coefficient (DSC) of .57 and partial AUC of .68 calculated with false positive rates up to 1%. This was superior to performance using OASIS and LesionTOADS. The proposed method also performed competitively in the segmentation challenge dataset. MIMoSA resulted in statistically significant improvements in lesion segmentation performance compared with LesionTOADS and OASIS, and performed competitively in an additional validation study. Copyright © 2018 by the American Society of Neuroimaging.

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.

Techniques for Targeted Fermi-GBM Follow-Up of Gravitational-Wave Events

NASA Technical Reports Server (NTRS)

Blackburn, L.; Camp, J.; Briggs, M. S.; Connaughton, V.; Jenke, P.; Christensen, N.; Veitch, J.

2012-01-01

The Advanced LIGO and Advanced Virgo ground-based gravitational-wave (GW) detectors are projected to come online 2015 2016, reaching a final sensitivity sufficient to observe dozens of binary neutron star mergers per year by 2018. We present a fully-automated, targeted search strategy for prompt gamma-ray counterparts in offline Fermi-GBM data. The multi-detector method makes use of a detailed model response of the instrument, and benefits from time and sky location information derived from the gravitational-wave signal.

Brain tissues volume measurements from 2D MRI using parametric approach

NASA Astrophysics Data System (ADS)

L'vov, A. A.; Toropova, O. A.; Litovka, Yu. V.

2018-04-01

The purpose of the paper is to propose a fully automated method of volume assessment of structures within human brain. Our statistical approach uses maximum interdependency principle for decision making process of measurements consistency and unequal observations. Detecting outliers performed using maximum normalized residual test. We propose a statistical model which utilizes knowledge of tissues distribution in human brain and applies partial data restoration for precision improvement. The approach proposes completed computationally efficient and independent from segmentation algorithm used in the application.

SU-E-J-168: Automated Pancreas Segmentation Based On Dynamic MRI

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

Gou, S; Rapacchi, S; Hu, P

2014-06-01

Purpose: MRI guided radiotherapy is particularly attractive for abdominal targets with low CT contrast. To fully utilize this modality for pancreas tracking, automated segmentation tools are needed. A hybrid gradient, region growth and shape constraint (hGReS) method to segment 2D upper abdominal dynamic MRI is developed for this purpose. Methods: 2D coronal dynamic MR images of 2 healthy volunteers were acquired with a frame rate of 5 f/second. The regions of interest (ROIs) included the liver, pancreas and stomach. The first frame was used as the source where the centers of the ROIs were annotated. These center locations were propagatedmore » to the next dynamic MRI frame. 4-neighborhood region transfer growth was performed from these initial seeds for rough segmentation. To improve the results, gradient, edge and shape constraints were applied to the ROIs before final refinement using morphological operations. Results from hGReS and 3 other automated segmentation methods using edge detection, region growth and level set were compared to manual contouring. Results: For the first patient, hGReS resulted in the organ segmentation accuracy as measure by the Dices index (0.77) for the pancreas. The accuracy was slightly superior to the level set method (0.72), and both are significantly more accurate than the edge detection (0.53) and region growth methods (0.42). For the second healthy volunteer, hGReS reliably segmented the pancreatic region, achieving a Dices index of 0.82, 0.92 and 0.93 for the pancreas, stomach and liver, respectively, comparing to manual segmentation. Motion trajectories derived from the hGReS, level set and manual segmentation methods showed high correlation to respiratory motion calculated using a lung blood vessel as the reference while the other two methods showed substantial motion tracking errors. hGReS was 10 times faster than level set. Conclusion: We have shown the feasibility of automated segmentation of the pancreas anatomy based on dynamic MRI.« less

“Smart” RCTs: Development of a Smartphone App for Fully Automated Nutrition-Labeling Intervention Trials

PubMed Central

Li, Nicole; Dunford, Elizabeth; Eyles, Helen; Crino, Michelle; Michie, Jo; Ni Mhurchu, Cliona

2016-01-01

Background There is substantial interest in the effects of nutrition labels on consumer food-purchasing behavior. However, conducting randomized controlled trials on the impact of nutrition labels in the real world presents a significant challenge. Objective The Food Label Trial (FLT) smartphone app was developed to enable conducting fully automated trials, delivering intervention remotely, and collecting individual-level data on food purchases for two nutrition-labeling randomized controlled trials (RCTs) in New Zealand and Australia. Methods Two versions of the smartphone app were developed: one for a 5-arm trial (Australian) and the other for a 3-arm trial (New Zealand). The RCT protocols guided requirements for app functionality, that is, obtaining informed consent, two-stage eligibility check, questionnaire administration, randomization, intervention delivery, and outcome assessment. Intervention delivery (nutrition labels) and outcome data collection (individual shopping data) used the smartphone camera technology, where a barcode scanner was used to identify a packaged food and link it with its corresponding match in a food composition database. Scanned products were either recorded in an electronic list (data collection mode) or allocated a nutrition label on screen if matched successfully with an existing product in the database (intervention delivery mode). All recorded data were transmitted to the RCT database hosted on a server. Results In total approximately 4000 users have downloaded the FLT app to date; 606 (Australia) and 1470 (New Zealand) users met the eligibility criteria and were randomized. Individual shopping data collected by participants currently comprise more than 96,000 (Australia) and 229,000 (New Zealand) packaged food and beverage products. Conclusions The FLT app is one of the first smartphone apps to enable conducting fully automated RCTs. Preliminary app usage statistics demonstrate large potential of such technology, both for intervention delivery and data collection. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12614000964617. New Zealand trial: Australian New Zealand Clinical Trials Registry ACTRN12614000644662. PMID:26988128

Automated 3D structure composition for large RNAs

PubMed Central

Popenda, Mariusz; Szachniuk, Marta; Antczak, Maciej; Purzycka, Katarzyna J.; Lukasiak, Piotr; Bartol, Natalia; Blazewicz, Jacek; Adamiak, Ryszard W.

2012-01-01

Understanding the numerous functions that RNAs play in living cells depends critically on knowledge of their three-dimensional structure. Due to the difficulties in experimentally assessing structures of large RNAs, there is currently great demand for new high-resolution structure prediction methods. We present the novel method for the fully automated prediction of RNA 3D structures from a user-defined secondary structure. The concept is founded on the machine translation system. The translation engine operates on the RNA FRABASE database tailored to the dictionary relating the RNA secondary structure and tertiary structure elements. The translation algorithm is very fast. Initial 3D structure is composed in a range of seconds on a single processor. The method assures the prediction of large RNA 3D structures of high quality. Our approach needs neither structural templates nor RNA sequence alignment, required for comparative methods. This enables the building of unresolved yet native and artificial RNA structures. The method is implemented in a publicly available, user-friendly server RNAComposer. It works in an interactive mode and a batch mode. The batch mode is designed for large-scale modelling and accepts atomic distance restraints. Presently, the server is set to build RNA structures of up to 500 residues. PMID:22539264

An Automatic Quality Control Pipeline for High-Throughput Screening Hit Identification.

PubMed

Zhai, Yufeng; Chen, Kaisheng; Zhong, Yang; Zhou, Bin; Ainscow, Edward; Wu, Ying-Ta; Zhou, Yingyao

2016-09-01

The correction or removal of signal errors in high-throughput screening (HTS) data is critical to the identification of high-quality lead candidates. Although a number of strategies have been previously developed to correct systematic errors and to remove screening artifacts, they are not universally effective and still require fair amount of human intervention. We introduce a fully automated quality control (QC) pipeline that can correct generic interplate systematic errors and remove intraplate random artifacts. The new pipeline was first applied to ~100 large-scale historical HTS assays; in silico analysis showed auto-QC led to a noticeably stronger structure-activity relationship. The method was further tested in several independent HTS runs, where QC results were sampled for experimental validation. Significantly increased hit confirmation rates were obtained after the QC steps, confirming that the proposed method was effective in enriching true-positive hits. An implementation of the algorithm is available to the screening community. © 2016 Society for Laboratory Automation and Screening.

Calibration and application of an automated seepage meter for monitoring water flow across the sediment-water interface.

PubMed

Zhu, Tengyi; Fu, Dafang; Jenkinson, Byron; Jafvert, Chad T

2015-04-01

The advective flow of sediment pore water is an important parameter for understanding natural geochemical processes within lake, river, wetland, and marine sediments and also for properly designing permeable remedial sediment caps placed over contaminated sediments. Automated heat pulse seepage meters can be used to measure the vertical component of sediment pore water flow (i.e., vertical Darcy velocity); however, little information on meter calibration as a function of ambient water temperature exists in the literature. As a result, a method with associated equations for calibrating a heat pulse seepage meter as a function of ambient water temperature is fully described in this paper. Results of meter calibration over the temperature range 7.5 to 21.2 °C indicate that errors in accuracy are significant if proper temperature-dependence calibration is not performed. The proposed calibration method allows for temperature corrections to be made automatically in the field at any ambient water temperature. The significance of these corrections is discussed.

Automated Infrared Inspection Of Jet Engine Turbine Blades

NASA Astrophysics Data System (ADS)

Bantel, T.; Bowman, D.; Halase, J.; Kenue, S.; Krisher, R.; Sippel, T.

1986-03-01

The detection of blocked surface cooling holes in hollow jet engine turbine blades and vanes during either manufacture or overhaul can be crucial to the integrity and longevity of the parts when in service. A fully automated infrared inspection system is being established under a tri-service's Manufacturing Technology (ManTech) contract administered by the Air Force to inspect these surface cooling holes for blockages. The method consists of viewing the surface holes of the blade with a scanning infrared radiometer when heated air is flushed through the blade. As the airfoil heats up, the resultant infrared images are written directly into computer memory where image analysis is performed. The computer then makes a determination of whether or not the holes are open from the inner plenum to the exterior surface and ultimately makes an accept/reject decision based on previously programmed criteria. A semiautomatic version has already been implemented and is more cost effective and more reliable than the previous manual inspection methods.

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

A Modular Hierarchical Approach to 3D Electron Microscopy Image Segmentation

PubMed Central

Liu, Ting; Jones, Cory; Seyedhosseini, Mojtaba; Tasdizen, Tolga

2014-01-01

The study of neural circuit reconstruction, i.e., connectomics, is a challenging problem in neuroscience. Automated and semi-automated electron microscopy (EM) image analysis can be tremendously helpful for connectomics research. In this paper, we propose a fully automatic approach for intra-section segmentation and inter-section reconstruction of neurons using EM images. A hierarchical merge tree structure is built to represent multiple region hypotheses and supervised classification techniques are used to evaluate their potentials, based on which we resolve the merge tree with consistency constraints to acquire final intra-section segmentation. Then, we use a supervised learning based linking procedure for the inter-section neuron reconstruction. Also, we develop a semi-automatic method that utilizes the intermediate outputs of our automatic algorithm and achieves intra-segmentation with minimal user intervention. The experimental results show that our automatic method can achieve close-to-human intra-segmentation accuracy and state-of-the-art inter-section reconstruction accuracy. We also show that our semi-automatic method can further improve the intra-segmentation accuracy. PMID:24491638

Automated in Situ Measurement of Gas Solubility in Liquids with a Simple Tube-in-Tube Reactor.

PubMed

Zhang, Jisong; Teixeira, Andrew R; Zhang, Haomiao; Jensen, Klavs F

2017-08-15

Data on the solubilities of gases in liquids are foundational for assessing a variety of multiphase separations and gas-liquid reactions. Taking advantage of the tube-in-tube reactor design built with semipermeable Teflon AF-2400 tubes, liquids can be rapidly saturated without direct contacting of gas and liquid. The gas solubility can be determined by performing steady-state flux balances of both the gas and liquid flowing into the reactor system. Using this type of reactor, a fully automated strategy has been developed for the rapid in situ measurement of gas solubilities in liquids. The developed strategy enables precise gas solubility measurements within 2-5 min compared with 4-5 h using conventional methods. This technique can be extended to the discrete multipoint steady-state and continuous ramped-multipoint data acquisition methods. The accuracy of this method has been validated against several gas-liquid systems, showing less than 2% deviation from known values. Finally, this strategy has been extended to measure the temperature dependence of gas solubilities in situ and to estimate the local enthalpy of dissolution across a defined temperature range.

Fully automated lobe-based airway taper index calculation in a low dose MDCT CF study over 4 time-points

NASA Astrophysics Data System (ADS)

Weinheimer, Oliver; Wielpütz, Mark O.; Konietzke, Philip; Heussel, Claus P.; Kauczor, Hans-Ulrich; Brochhausen, Christoph; Hollemann, David; Savage, Dasha; Galbán, Craig J.; Robinson, Terry E.

2017-02-01

Cystic Fibrosis (CF) results in severe bronchiectasis in nearly all cases. Bronchiectasis is a disease where parts of the airways are permanently dilated. The development and the progression of bronchiectasis is not evenly distributed over the entire lungs - rather, individual functional units are affected differently. We developed a fully automated method for the precise calculation of lobe-based airway taper indices. To calculate taper indices, some preparatory algorithms are needed. The airway tree is segmented, skeletonized and transformed to a rooted acyclic graph. This graph is used to label the airways. Then a modified version of the previously validated integral based method (IBM) for airway geometry determination is utilized. The rooted graph, the airway lumen and wall information are then used to calculate the airway taper indices. Using a computer-generated phantom simulating 10 cross sections of airways we present results showing a high accuracy of the modified IBM. The new taper index calculation method was applied to 144 volumetric inspiratory low-dose MDCT scans. The scans were acquired from 36 children with mild CF at 4 time-points (baseline, 3 month, 1 year, 2 years). We found a moderate correlation with the visual lobar Brody bronchiectasis scores by three raters (r2 = 0.36, p < .0001). The taper index has the potential to be a precise imaging biomarker but further improvements are needed. In combination with other imaging biomarkers, taper index calculation can be an important tool for monitoring the progression and the individual treatment of patients with bronchiectasis.

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

PubMed

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

2013-07-01

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

The length of the glaciers in the world - a straightforward method for the automated calculation of glacier center lines

NASA Astrophysics Data System (ADS)

Machguth, H.; Huss, M.

2014-05-01

Glacier length is an important measure of glacier geometry but global glacier inventories are mostly lacking length data. Only recently semi-automated approaches to measure glacier length have been developed and applied regionally. Here we present a first global assessment of glacier length using a fully automated method based on glacier surface slope, distance to the glacier margins and a set of trade-off functions. The method is developed for East Greenland, evaluated for the same area as well as for Alaska, and eventually applied to all ∼200 000 glaciers around the globe. The evaluation highlights accurately calculated glacier length where DEM quality is good (East Greenland) and limited precision on low quality DEMs (parts of Alaska). Measured length of very small glaciers is subject to a certain level of ambiguity. The global calculation shows that only about 1.5% of all glaciers are longer than 10 km with Bering Glacier (Alaska/Canada) being the longest glacier in the world at a length of 196 km. Based on model output we derive global and regional area-length scaling laws. Differences among regional scaling parameters appear to be related to characteristics of topography and glacier mass balance. The present study adds glacier length as a central parameter to global glacier inventories. Global and regional scaling laws might proof beneficial in conceptual glacier models.

A volumetric pulmonary CT segmentation method with applications in emphysema assessment

NASA Astrophysics Data System (ADS)

Silva, José Silvestre; Silva, Augusto; Santos, Beatriz S.

2006-03-01

A segmentation method is a mandatory pre-processing step in many automated or semi-automated analysis tasks such as region identification and densitometric analysis, or even for 3D visualization purposes. In this work we present a fully automated volumetric pulmonary segmentation algorithm based on intensity discrimination and morphologic procedures. Our method first identifies the trachea as well as primary bronchi and then the pulmonary region is identified by applying a threshold and morphologic operations. When both lungs are in contact, additional procedures are performed to obtain two separated lung volumes. To evaluate the performance of the method, we compared contours extracted from 3D lung surfaces with reference contours, using several figures of merit. Results show that the worst case generally occurs at the middle sections of high resolution CT exams, due the presence of aerial and vascular structures. Nevertheless, the average error is inferior to the average error associated with radiologist inter-observer variability, which suggests that our method produces lung contours similar to those drawn by radiologists. The information created by our segmentation algorithm is used by an identification and representation method in pulmonary emphysema that also classifies emphysema according to its severity degree. Two clinically proved thresholds are applied which identify regions with severe emphysema, and with highly severe emphysema. Based on this thresholding strategy, an application for volumetric emphysema assessment was developed offering new display paradigms concerning the visualization of classification results. This framework is easily extendable to accommodate other classifiers namely those related with texture based segmentation as it is often the case with interstitial diseases.

Automated multi-slice extracellular and patch-clamp experiments using the WinLTP data acquisition system with automated perfusion control

PubMed Central

Anderson, William W.; Fitzjohn, Stephen M.; Collingridge, Graham L.

2012-01-01

WinLTP is a data acquisition program for studying long-term potentiation (LTP) and other aspects of synaptic function. Earlier versions of WinLTP (J. Neurosci. Methods, 162:346–356, 2007) provided automated electrical stimulation and data acquisition capable of running nearly an entire synaptic plasticity experiment, with the primary exception that perfusion solutions had to be changed manually. This automated stimulation and acquisition was done by using ‘Sweep’, ‘Loop’ and ‘Delay’ events to build scripts using the ‘Protocol Builder’. However, this did not allow automatic changing of many solutions while running multiple slice experiments, or solution changing when this had to be performed rapidly and with accurate timing during patch-clamp experiments. We report here the addition of automated perfusion control to WinLTP. First, perfusion change between sweeps is enabled by adding the ‘Perfuse’ event to Protocol Builder scripting and is used in slice experiments. Second, fast perfusion changes during as well as between sweeps is enabled by using the Perfuse event in the protocol scripts to control changes between sweeps, and also by changing digital or analog output during a sweep and is used for single cell single-line perfusion patch-clamp experiments. The addition of stepper control of tube placement allows dual- or triple-line perfusion patch-clamp experiments for up to 48 solutions. The ability to automate perfusion changes and fully integrate them with the already automated stimulation and data acquisition goes a long way toward complete automation of multi-slice extracellularly recorded and single cell patch-clamp experiments. PMID:22524994

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.

An Automated Directed Spectral Search Methodology for Small Target Detection

NASA Astrophysics Data System (ADS)

Grossman, Stanley I.

Much of the current efforts in remote sensing tackle macro-level problems such as determining the extent of wheat in a field, the general health of vegetation or the extent of mineral deposits in an area. However, for many of the remaining remote sensing challenges being studied currently, such as border protection, drug smuggling, treaty verification, and the war on terror, most targets are very small in nature - a vehicle or even a person. While in typical macro-level problems the objective vegetation is in the scene, for small target detection problems it is not usually known if the desired small target even exists in the scene, never mind finding it in abundance. The ability to find specific small targets, such as vehicles, typifies this problem. Complicating the analyst's life, the growing number of available sensors is generating mountains of imagery outstripping the analysts' ability to visually peruse them. This work presents the important factors influencing spectral exploitation using multispectral data and suggests a different approach to small target detection. The methodology of directed search is presented, including the use of scene-modeled spectral libraries, various search algorithms, and traditional statistical and ROC curve analysis. The work suggests a new metric to calibrate analysis labeled the analytic sweet spot as well as an estimation method for identifying the sweet spot threshold for an image. It also suggests a new visualization aid for highlighting the target in its entirety called nearest neighbor inflation (NNI). It brings these all together to propose that these additions to the target detection arena allow for the construction of a fully automated target detection scheme. This dissertation next details experiments to support the hypothesis that the optimum detection threshold is the analytic sweet spot and that the estimation method adequately predicts it. Experimental results and analysis are presented for the proposed directed search techniques of spectral image based small target detection. It offers evidence of the functionality of the NNI visualization and also provides evidence that the increased spectral dimensionality of the 8-band Worldview-2 datasets provides noteworthy improvement in results over traditional 4-band multispectral datasets. The final experiment presents the results from a prototype fully automated target detection scheme in support of the overarching premise. This work establishes the analytic sweet spot as the optimum threshold defined as the point where error detection rate curves -- false detections vs. missing detections -- cross. At this point the errors are minimized while the detection rate is maximized. It then demonstrates that taking the first moment statistic of the histogram of calculated target detection values from a detection search with test threshold set arbitrarily high will estimate the analytic sweet spot for that image. It also demonstrates that directed search techniques -- when utilized with appropriate scene-specific modeled signatures and atmospheric compensations -- perform at least as well as in-scene search techniques 88% of the time and grossly under-performing only 11% of the time; the in-scene only performs as well or better 50% of the time. It further demonstrates the clear advantage increased multispectral dimensionality brings to detection searches improving performance in 50% of the cases while performing at least as well 72% of the time. Lastly, it presents evidence that a fully automated prototype performs as anticipated laying the groundwork for further research into fully automated processes for small target detection.

Automated Gait Analysis Through Hues and Areas (AGATHA): a method to characterize the spatiotemporal pattern of rat gait

PubMed Central

Kloefkorn, Heidi E.; Pettengill, Travis R.; Turner, Sara M. F.; Streeter, Kristi A.; Gonzalez-Rothi, Elisa J.; Fuller, David D.; Allen, Kyle D.

2016-01-01

While rodent gait analysis can quantify the behavioral consequences of disease, significant methodological differences exist between analysis platforms and little validation has been performed to understand or mitigate these sources of variance. By providing the algorithms used to quantify gait, open-source gait analysis software can be validated and used to explore methodological differences. Our group is introducing, for the first time, a fully-automated, open-source method for the characterization of rodent spatiotemporal gait patterns, termed Automated Gait Analysis Through Hues and Areas (AGATHA). This study describes how AGATHA identifies gait events, validates AGATHA relative to manual digitization methods, and utilizes AGATHA to detect gait compensations in orthopaedic and spinal cord injury models. To validate AGATHA against manual digitization, results from videos of rodent gait, recorded at 1000 frames per second (fps), were compared. To assess one common source of variance (the effects of video frame rate), these 1000 fps videos were re-sampled to mimic several lower fps and compared again. While spatial variables were indistinguishable between AGATHA and manual digitization, low video frame rates resulted in temporal errors for both methods. At frame rates over 125 fps, AGATHA achieved a comparable accuracy and precision to manual digitization for all gait variables. Moreover, AGATHA detected unique gait changes in each injury model. These data demonstrate AGATHA is an accurate and precise platform for the analysis of rodent spatiotemporal gait patterns. PMID:27554674

Automated Gait Analysis Through Hues and Areas (AGATHA): A Method to Characterize the Spatiotemporal Pattern of Rat Gait.

PubMed

Kloefkorn, Heidi E; Pettengill, Travis R; Turner, Sara M F; Streeter, Kristi A; Gonzalez-Rothi, Elisa J; Fuller, David D; Allen, Kyle D

2017-03-01

While rodent gait analysis can quantify the behavioral consequences of disease, significant methodological differences exist between analysis platforms and little validation has been performed to understand or mitigate these sources of variance. By providing the algorithms used to quantify gait, open-source gait analysis software can be validated and used to explore methodological differences. Our group is introducing, for the first time, a fully-automated, open-source method for the characterization of rodent spatiotemporal gait patterns, termed Automated Gait Analysis Through Hues and Areas (AGATHA). This study describes how AGATHA identifies gait events, validates AGATHA relative to manual digitization methods, and utilizes AGATHA to detect gait compensations in orthopaedic and spinal cord injury models. To validate AGATHA against manual digitization, results from videos of rodent gait, recorded at 1000 frames per second (fps), were compared. To assess one common source of variance (the effects of video frame rate), these 1000 fps videos were re-sampled to mimic several lower fps and compared again. While spatial variables were indistinguishable between AGATHA and manual digitization, low video frame rates resulted in temporal errors for both methods. At frame rates over 125 fps, AGATHA achieved a comparable accuracy and precision to manual digitization for all gait variables. Moreover, AGATHA detected unique gait changes in each injury model. These data demonstrate AGATHA is an accurate and precise platform for the analysis of rodent spatiotemporal gait patterns.

Automated Antibody De Novo Sequencing and Its Utility in Biopharmaceutical Discovery

NASA Astrophysics Data System (ADS)

Sen, K. Ilker; Tang, Wilfred H.; Nayak, Shruti; Kil, Yong J.; Bern, Marshall; Ozoglu, Berk; Ueberheide, Beatrix; Davis, Darryl; Becker, Christopher

2017-05-01

Applications of antibody de novo sequencing in the biopharmaceutical industry range from the discovery of new antibody drug candidates to identifying reagents for research and determining the primary structure of innovator products for biosimilar development. When murine, phage display, or patient-derived monoclonal antibodies against a target of interest are available, but the cDNA or the original cell line is not, de novo protein sequencing is required to humanize and recombinantly express these antibodies, followed by in vitro and in vivo testing for functional validation. Availability of fully automated software tools for monoclonal antibody de novo sequencing enables efficient and routine analysis. Here, we present a novel method to automatically de novo sequence antibodies using mass spectrometry and the Supernovo software. The robustness of the algorithm is demonstrated through a series of stress tests.

Automated processing of first-pass radioisotope ventriculography data to determine essential central circulation parameters

NASA Astrophysics Data System (ADS)

Krotov, Aleksei; Pankin, Victor

2017-09-01

The assessment of central circulation (including heart function) parameters is vital in the preventive diagnostics of inherent and acquired heart failures and during polychemotherapy. The protocols currently applied in Russia do not fully utilize the first-pass assessment (FPRNA) and that results in poor data formalization, while the FPRNA is the one of the fastest, affordable and compact methods among other radioisotope diagnostics protocols. A non-imaging algorithm basing on existing protocols has been designed to use the readings of an additional detector above vena subclavia to determine the total blood volume (TBV), not requiring blood sampling in contrast to current protocols. An automated processing of precordial detector readings is presented, in order to determine the heart strike volume (SV). Two techniques to estimate the ejection fraction (EF) of the heart are discussed.

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.

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.

Improved quality-by-design compliant methodology for method development in reversed-phase liquid chromatography.

PubMed

Debrus, Benjamin; Guillarme, Davy; Rudaz, Serge

2013-10-01

A complete strategy dedicated to quality-by-design (QbD) compliant method development using design of experiments (DOE), multiple linear regressions responses modelling and Monte Carlo simulations for error propagation was evaluated for liquid chromatography (LC). The proposed approach includes four main steps: (i) the initial screening of column chemistry, mobile phase pH and organic modifier, (ii) the selectivity optimization through changes in gradient time and mobile phase temperature, (iii) the adaptation of column geometry to reach sufficient resolution, and (iv) the robust resolution optimization and identification of the method design space. This procedure was employed to obtain a complex chromatographic separation of 15 antipsychotic basic drugs, widely prescribed. To fully automate and expedite the QbD method development procedure, short columns packed with sub-2 μm particles were employed, together with a UHPLC system possessing columns and solvents selection valves. Through this example, the possibilities of the proposed QbD method development workflow were exposed and the different steps of the automated strategy were critically discussed. A baseline separation of the mixture of antipsychotic drugs was achieved with an analysis time of less than 15 min and the robustness of the method was demonstrated simultaneously with the method development phase. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Multi-tissue and multi-scale approach for nuclei segmentation in H&E stained images.

PubMed

Salvi, Massimo; Molinari, Filippo

2018-06-20

Accurate nuclei detection and segmentation in histological images is essential for many clinical purposes. While manual annotations are time-consuming and operator-dependent, full automated segmentation remains a challenging task due to the high variability of cells intensity, size and morphology. Most of the proposed algorithms for the automated segmentation of nuclei were designed for specific organ or tissues. The aim of this study was to develop and validate a fully multiscale method, named MANA (Multiscale Adaptive Nuclei Analysis), for nuclei segmentation in different tissues and magnifications. MANA was tested on a dataset of H&E stained tissue images with more than 59,000 annotated nuclei, taken from six organs (colon, liver, bone, prostate, adrenal gland and thyroid) and three magnifications (10×, 20×, 40×). Automatic results were compared with manual segmentations and three open-source software designed for nuclei detection. For each organ, MANA obtained always an F1-score higher than 0.91, with an average F1 of 0.9305 ± 0.0161. The average computational time was about 20 s independently of the number of nuclei to be detected (anyway, higher than 1000), indicating the efficiency of the proposed technique. To the best of our knowledge, MANA is the first fully automated multi-scale and multi-tissue algorithm for nuclei detection. Overall, the robustness and versatility of MANA allowed to achieve, on different organs and magnifications, performances in line or better than those of state-of-art algorithms optimized for single tissues.

The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers.

PubMed

Ash, Samuel Y; Harmouche, Rola; Ross, James C; Diaz, Alejandro A; Hunninghake, Gary M; Putman, Rachel K; Onieva, Jorge; Martinez, Fernando J; Choi, Augustine M; Lynch, David A; Hatabu, Hiroto; Rosas, Ivan O; Estepar, Raul San Jose; Washko, George R

2017-08-01

Previous investigation suggests that visually detected interstitial changes in the lung parenchyma of smokers are highly clinically relevant and predict outcomes, including death. Visual subjective analysis to detect these changes is time-consuming, insensitive to subtle changes, and requires training to enhance reproducibility. Objective detection of such changes could provide a method of disease identification without these limitations. The goal of this study was to develop and test a fully automated image processing tool to objectively identify radiographic features associated with interstitial abnormalities in the computed tomography scans of a large cohort of smokers. An automated tool that uses local histogram analysis combined with distance from the pleural surface was used to detect radiographic features consistent with interstitial lung abnormalities in computed tomography scans from 2257 individuals from the Genetic Epidemiology of COPD study, a longitudinal observational study of smokers. The sensitivity and specificity of this tool was determined based on its ability to detect the visually identified presence of these abnormalities. The tool had a sensitivity of 87.8% and a specificity of 57.5% for the detection of interstitial lung abnormalities, with a c-statistic of 0.82, and was 100% sensitive and 56.7% specific for the detection of the visual subtype of interstitial abnormalities called fibrotic parenchymal abnormalities, with a c-statistic of 0.89. In smokers, a fully automated image processing tool is able to identify those individuals who have interstitial lung abnormalities with moderate sensitivity and specificity. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Fully automatic detection of salient features in 3-d transesophageal images.

PubMed

Curiale, Ariel H; Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Ren, Ben; Aja-Fernández, Santiago; Bosch, Johan G

2014-12-01

Most automated segmentation approaches to the mitral valve and left ventricle in 3-D echocardiography require a manual initialization. In this article, we propose a fully automatic scheme to initialize a multicavity segmentation approach in 3-D transesophageal echocardiography by detecting the left ventricle long axis, the mitral valve and the aortic valve location. Our approach uses a probabilistic and structural tissue classification to find structures such as the mitral and aortic valves; the Hough transform for circles to find the center of the left ventricle; and multidimensional dynamic programming to find the best position for the left ventricle long axis. For accuracy and agreement assessment, the proposed method was evaluated in 19 patients with respect to manual landmarks and as initialization of a multicavity segmentation approach for the left ventricle, the right ventricle, the left atrium, the right atrium and the aorta. The segmentation results revealed no statistically significant differences between manual and automated initialization in a paired t-test (p > 0.05). Additionally, small biases between manual and automated initialization were detected in the Bland-Altman analysis (bias, variance) for the left ventricle (-0.04, 0.10); right ventricle (-0.07, 0.18); left atrium (-0.01, 0.03); right atrium (-0.04, 0.13); and aorta (-0.05, 0.14). These results indicate that the proposed approach provides robust and accurate detection to initialize a multicavity segmentation approach without any user interaction. Copyright © 2014 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Evaluation of three fully automated immunoassay systems for detection of IgA anti-beta 2-glycoprotein I antibodies.

PubMed

Pérez, D; Martínez-Flores, J A; Serrano, M; Lora, D; Paz-Artal, E; Morales, J M; Serrano, A

2016-10-01

In recent years, we have been witnessing increased clinical interest in the determination of IgA anti-beta 2-glycoprotein I (aB2GPI) antibodies as well as increased demand for this test. Some ELISA-based diagnostic systems for IgA aB2GPI antibodies detection are suboptimal to detect it. The aim of our study was to determine whether the diagnostic yield of modern detection systems based on automatic platforms to measure IgA aB2GPI is equivalent to that of the well-optimized ELISA-based assays. In total, 130 patients were analyzed for IgA aB2GPI by three fully automated immunoassays using an ELISA-based assay as reference. The three systems were also analyzed for IgG aB2GPI with 58 patients. System 1 was able to detect IgA aB2GPI with good sensitivity and kappa index (99% and 0.72, respectively). The other two systems had also poor sensitivity (20% and 15%) and kappa index (0.10 and 0.07), respectively. On the other hand, kappa index for IgG aB2GPI was >0.89 in the three systems. Some analytical methods to detect IgA aB2GPI are suboptimal as well as some ELISA-based diagnostic systems. It is important that the scientific community work to standardize analytical methods to determine IgA aB2GPI antibodies. © 2016 John Wiley & Sons Ltd.

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

PubMed

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

2018-01-01

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

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.

Fully Automated Quantification of the Striatal Uptake Ratio of [99mTc]-TRODAT with SPECT Imaging: Evaluation of the Diagnostic Performance in Parkinson's Disease and the Temporal Regression of Striatal Tracer Uptake

PubMed Central

Fang, Yu-Hua Dean; Chiu, Shao-Chieh; Lu, Chin-Song; Weng, Yi-Hsin

2015-01-01

Purpose. We aimed at improving the existing methods for the fully automatic quantification of striatal uptake of [99mTc]-TRODAT with SPECT imaging. Procedures. A normal [99mTc]-TRODAT template was first formed based on 28 healthy controls. Images from PD patients (n = 365) and nPD subjects (28 healthy controls and 33 essential tremor patients) were spatially normalized to the normal template. We performed an inverse transform on the predefined striatal and reference volumes of interest (VOIs) and applied the transformed VOIs to the original image data to calculate the striatal-to-reference ratio (SRR). The diagnostic performance of the SRR was determined through receiver operating characteristic (ROC) analysis. Results. The SRR measured with our new and automatic method demonstrated excellent diagnostic performance with 92% sensitivity, 90% specificity, 92% accuracy, and an area under the curve (AUC) of 0.94. For the evaluation of the mean SRR and the clinical duration, a quadratic function fit the data with R 2 = 0.84. Conclusions. We developed and validated a fully automatic method for the quantification of the SRR in a large study sample. This method has an excellent diagnostic performance and exhibits a strong correlation between the mean SRR and the clinical duration in PD patients. PMID:26366413

Fully Automated Quantification of the Striatal Uptake Ratio of [(99m)Tc]-TRODAT with SPECT Imaging: Evaluation of the Diagnostic Performance in Parkinson's Disease and the Temporal Regression of Striatal Tracer Uptake.

PubMed

Fang, Yu-Hua Dean; Chiu, Shao-Chieh; Lu, Chin-Song; Yen, Tzu-Chen; Weng, Yi-Hsin

2015-01-01

We aimed at improving the existing methods for the fully automatic quantification of striatal uptake of [(99m)Tc]-TRODAT with SPECT imaging. A normal [(99m)Tc]-TRODAT template was first formed based on 28 healthy controls. Images from PD patients (n = 365) and nPD subjects (28 healthy controls and 33 essential tremor patients) were spatially normalized to the normal template. We performed an inverse transform on the predefined striatal and reference volumes of interest (VOIs) and applied the transformed VOIs to the original image data to calculate the striatal-to-reference ratio (SRR). The diagnostic performance of the SRR was determined through receiver operating characteristic (ROC) analysis. The SRR measured with our new and automatic method demonstrated excellent diagnostic performance with 92% sensitivity, 90% specificity, 92% accuracy, and an area under the curve (AUC) of 0.94. For the evaluation of the mean SRR and the clinical duration, a quadratic function fit the data with R (2) = 0.84. We developed and validated a fully automatic method for the quantification of the SRR in a large study sample. This method has an excellent diagnostic performance and exhibits a strong correlation between the mean SRR and the clinical duration in PD patients.

Feasibility of rapid and automated importation of 3D echocardiographic left ventricular (LV) geometry into a finite element (FEM) analysis model

PubMed Central

Verhey, Janko F; Nathan, Nadia S

2004-01-01

Background Finite element method (FEM) analysis for intraoperative modeling of the left ventricle (LV) is presently not possible. Since 3D structural data of the LV is now obtainable using standard transesophageal echocardiography (TEE) devices intraoperatively, the present study describes a method to transfer this data into a commercially available FEM analysis system: ABAQUS©. Methods In this prospective study TomTec LV Analysis TEE© Software was used for semi-automatic endocardial border detection, reconstruction, and volume-rendering of the clinical 3D echocardiographic data. A newly developed software program MVCP FemCoGen©, written in Delphi, reformats the TomTec file structures in five patients for use in ABAQUS and allows visualization of regional deformation of the LV. Results This study demonstrates that a fully automated importation of 3D TEE data into FEM modeling is feasible and can be efficiently accomplished in the operating room. Conclusion For complete intraoperative 3D LV finite element analysis, three input elements are necessary: 1. time-gaited, reality-based structural information, 2. continuous LV pressure and 3. instantaneous tissue elastance. The first of these elements is now available using the methods presented herein. PMID:15473901

Methods for automated semantic definition of manufacturing structures (mBOM) in mechanical engineering companies

NASA Astrophysics Data System (ADS)

Stekolschik, Alexander, Prof.

2017-10-01

The bill of materials (BOM), which involves all parts and assemblies of the product, is the core of any mechanical or electronic product. The flexible and integrated management of engineering (Engineering Bill of Materials [eBOM]) and manufacturing (Manufacturing Bill of Materials [mBOM]) structures is the key to the creation of modern products in mechanical engineering companies. This paper presents a method framework for the creation and control of e- and, especially, mBOM. The requirements, resulting from the process of differentiation between companies that produce serialized or engineered-to-order products, are considered in the analysis phase. The main part of the paper describes different approaches to fully or partly automated creation of mBOM. The first approach is the definition of part selection rules in the generic mBOM templates. The mBOM can be derived from the eBOM for partly standardized products by using this method. Another approach is the simultaneous use of semantic rules, options, and parameters in both structures. The implementation of the method framework (selection of use cases) in a standard product lifecycle management (PLM) system is part of the research.

Fully automatic segmentation of the femur from 3D-CT images using primitive shape recognition and statistical shape models.

PubMed

Ben Younes, Lassad; Nakajima, Yoshikazu; Saito, Toki

2014-03-01

Femur segmentation is well established and widely used in computer-assisted orthopedic surgery. However, most of the robust segmentation methods such as statistical shape models (SSM) require human intervention to provide an initial position for the SSM. In this paper, we propose to overcome this problem and provide a fully automatic femur segmentation method for CT images based on primitive shape recognition and SSM. Femur segmentation in CT scans was performed using primitive shape recognition based on a robust algorithm such as the Hough transform and RANdom SAmple Consensus. The proposed method is divided into 3 steps: (1) detection of the femoral head as sphere and the femoral shaft as cylinder in the SSM and the CT images, (2) rigid registration between primitives of SSM and CT image to initialize the SSM into the CT image, and (3) fitting of the SSM to the CT image edge using an affine transformation followed by a nonlinear fitting. The automated method provided good results even with a high number of outliers. The difference of segmentation error between the proposed automatic initialization method and a manual initialization method is less than 1 mm. The proposed method detects primitive shape position to initialize the SSM into the target image. Based on primitive shapes, this method overcomes the problem of inter-patient variability. Moreover, the results demonstrate that our method of primitive shape recognition can be used for 3D SSM initialization to achieve fully automatic segmentation of the femur.

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.

Evaluation of immunoturbidimetric rheumatoid factor method from Diagam on Abbott c8000 analyzer: comparison with immunonephelemetric method.

PubMed

Dupuy, Anne Marie; Hurstel, Rémy; Bargnoux, Anne Sophie; Badiou, Stéphanie; Cristol, Jean Paul

2014-01-01

Rheumatoid factor (RF) consists of autoantibodies and because of its heterogeneity its determination is not easy. Currently, nephelometry and Elisa method are considered as reference methods. Due to consolidation, many laboratories have fully automated turbidimetric apparatus, and specific nephelemetric systems are not always available. In addition, nephelemetry is more accurate, but time consuming, expensive, and requires a specific device, resulting in a lower efficiency. Turbidimetry could be an attractive alternative. The turbidimetric RF test from Diagam meets the requirements of accuracy and precision for optimal clinical use, with an acceptable measuring range, and could be an alternative in the determination of RF, without the associated cost of a dedicated instrument, making consolidation and saving blood possible.

Phase editing as a signal pre-processing step for automated bearing fault detection

NASA Astrophysics Data System (ADS)

Barbini, L.; Ompusunggu, A. P.; Hillis, A. J.; du Bois, J. L.; Bartic, A.

2017-07-01

Scheduled maintenance and inspection of bearing elements in industrial machinery contributes significantly to the operating costs. Savings can be made through automatic vibration-based damage detection and prognostics, to permit condition-based maintenance. However automation of the detection process is difficult due to the complexity of vibration signals in realistic operating environments. The sensitivity of existing methods to the choice of parameters imposes a requirement for oversight from a skilled operator. This paper presents a novel approach to the removal of unwanted vibrational components from the signal: phase editing. The approach uses a computationally-efficient full-band demodulation and requires very little oversight. Its effectiveness is tested on experimental data sets from three different test-rigs, and comparisons are made with two state-of-the-art processing techniques: spectral kurtosis and cepstral pre- whitening. The results from the phase editing technique show a 10% improvement in damage detection rates compared to the state-of-the-art while simultaneously improving on the degree of automation. This outcome represents a significant contribution in the pursuit of fully automatic fault detection.

Automated in vivo identification of fungal infection on human scalp using optical coherence tomography and machine learning

NASA Astrophysics Data System (ADS)

Dubey, Kavita; Srivastava, Vishal; Singh Mehta, Dalip

2018-04-01

Early identification of fungal infection on the human scalp is crucial for avoiding hair loss. The diagnosis of fungal infection on the human scalp is based on a visual assessment by trained experts or doctors. Optical coherence tomography (OCT) has the ability to capture fungal infection information from the human scalp with a high resolution. In this study, we present a fully automated, non-contact, non-invasive optical method for rapid detection of fungal infections based on the extracted features from A-line and B-scan images of OCT. A multilevel ensemble machine model is designed to perform automated classification, which shows the superiority of our classifier to the best classifier based on the features extracted from OCT images. In this study, 60 samples (30 fungal, 30 normal) were imaged by OCT and eight features were extracted. The classification algorithm had an average sensitivity, specificity and accuracy of 92.30, 90.90 and 91.66%, respectively, for identifying fungal and normal human scalps. This remarkable classifying ability makes the proposed model readily applicable to classifying the human scalp.

Automated assay for screening the enzymatic release of reducing sugars from micronized biomass

PubMed Central

2010-01-01

Background To reduce the production cost of bioethanol obtained from fermentation of the sugars provided by degradation of lignocellulosic biomass (i.e., second generation bioethanol), it is necessary to screen for new enzymes endowed with more efficient biomass degrading properties. This demands the set-up of high-throughput screening methods. Several methods have been devised all using microplates in the industrial SBS format. Although this size reduction and standardization has greatly improved the screening process, the published methods comprise one or more manual steps that seriously decrease throughput. Therefore, we worked to devise a screening method devoid of any manual steps. Results We describe a fully automated assay for measuring the amount of reducing sugars released by biomass-degrading enzymes from wheat-straw and spruce. The method comprises two independent and automated steps. The first step is the making of "substrate plates". It consists of filling 96-well microplates with slurry suspensions of micronized substrate which are then stored frozen until use. The second step is an enzymatic activity assay. After thawing, the substrate plates are supplemented by the robot with cell-wall degrading enzymes where necessary, and the whole process from addition of enzymes to quantification of released sugars is autonomously performed by the robot. We describe how critical parameters (amount of substrate, amount of enzyme, incubation duration and temperature) were selected to fit with our specific use. The ability of this automated small-scale assay to discriminate among different enzymatic activities was validated using a set of commercial enzymes. Conclusions Using an automatic microplate sealer solved three main problems generally encountered during the set-up of methods for measuring the sugar-releasing activity of plant cell wall-degrading enzymes: throughput, automation, and evaporation losses. In its present set-up, the robot can autonomously process 120 triplicate wheat-straw samples per day. This throughput can be doubled if the incubation time is reduced from 24 h to 4 h (for initial rates measurements, for instance). This method can potentially be used with any insoluble substrate that is micronizable. A video illustrating the method can be seen at the following URL: http://www.youtube.com/watch?v=NFg6TxjuMWU PMID:20637080

General Tool for Evaluating High-Contrast Coronagraphic Telescope Performance Error Budgets

NASA Technical Reports Server (NTRS)

Marchen, Luis F.

2011-01-01

The Coronagraph Performance Error Budget (CPEB) tool automates many of the key steps required to evaluate the scattered starlight contrast in the dark hole of a space-based coronagraph. The tool uses a Code V prescription of the optical train, and uses MATLAB programs to call ray-trace code that generates linear beam-walk and aberration sensitivity matrices for motions of the optical elements and line-of-sight pointing, with and without controlled fine-steering mirrors (FSMs). The sensitivity matrices are imported by macros into Excel 2007, where the error budget is evaluated. The user specifies the particular optics of interest, and chooses the quality of each optic from a predefined set of PSDs. The spreadsheet creates a nominal set of thermal and jitter motions, and combines that with the sensitivity matrices to generate an error budget for the system. CPEB also contains a combination of form and ActiveX controls with Visual Basic for Applications code to allow for user interaction in which the user can perform trade studies such as changing engineering requirements, and identifying and isolating stringent requirements. It contains summary tables and graphics that can be instantly used for reporting results in view graphs. The entire process to obtain a coronagraphic telescope performance error budget has been automated into three stages: conversion of optical prescription from Zemax or Code V to MACOS (in-house optical modeling and analysis tool), a linear models process, and an error budget tool process. The first process was improved by developing a MATLAB package based on the Class Constructor Method with a number of user-defined functions that allow the user to modify the MACOS optical prescription. The second process was modified by creating a MATLAB package that contains user-defined functions that automate the process. The user interfaces with the process by utilizing an initialization file where the user defines the parameters of the linear model computations. Other than this, the process is fully automated. The third process was developed based on the Terrestrial Planet Finder coronagraph Error Budget Tool, but was fully automated by using VBA code, form, and ActiveX controls.

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.

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.

TU-C-BRE-11: 3D EPID-Based in Vivo Dosimetry: A Major Step Forward Towards Optimal Quality and Safety in Radiation Oncology Practice

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

Mijnheer, B; Mans, A; Olaciregui-Ruiz, I

Purpose: To develop a 3D in vivo dosimetry method that is able to substitute pre-treatment verification in an efficient way, and to terminate treatment delivery if the online measured 3D dose distribution deviates too much from the predicted dose distribution. Methods: A back-projection algorithm has been further developed and implemented to enable automatic 3D in vivo dose verification of IMRT/VMAT treatments using a-Si EPIDs. New software tools were clinically introduced to allow automated image acquisition, to periodically inspect the record-and-verify database, and to automatically run the EPID dosimetry software. The comparison of the EPID-reconstructed and planned dose distribution is donemore » offline to raise automatically alerts and to schedule actions when deviations are detected. Furthermore, a software package for online dose reconstruction was also developed. The RMS of the difference between the cumulative planned and reconstructed 3D dose distributions was used for triggering a halt of a linac. Results: The implementation of fully automated 3D EPID-based in vivo dosimetry was able to replace pre-treatment verification for more than 90% of the patient treatments. The process has been fully automated and integrated in our clinical workflow where over 3,500 IMRT/VMAT treatments are verified each year. By optimizing the dose reconstruction algorithm and the I/O performance, the delivered 3D dose distribution is verified in less than 200 ms per portal image, which includes the comparison between the reconstructed and planned dose distribution. In this way it was possible to generate a trigger that can stop the irradiation at less than 20 cGy after introducing large delivery errors. Conclusion: The automatic offline solution facilitated the large scale clinical implementation of 3D EPID-based in vivo dose verification of IMRT/VMAT treatments; the online approach has been successfully tested for various severe delivery errors.« less

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/.

Detection of motile micro-organisms in biological samples by means of a fully automated image processing system

NASA Astrophysics Data System (ADS)

Alanis, Elvio; Romero, Graciela; Alvarez, Liliana; Martinez, Carlos C.; Hoyos, Daniel; Basombrio, Miguel A.

2001-08-01

A fully automated image processing system for detection of motile microorganism is biological samples is presented. The system is specifically calibrated for determining the concentration of Trypanosoma Cruzi parasites in blood samples of mice infected with Chagas disease. The method can be adapted for use in other biological samples. A thin layer of blood infected by T. cruzi parasites is examined in a common microscope in which the images of the vision field are taken by a CCD camera and temporarily stored in the computer memory. In a typical field, a few motile parasites are observable surrounded by blood red cells. The parasites have low contrast. Thus, they are difficult to detect visually but their great motility betrays their presence by the movement of the nearest neighbor red cells. Several consecutive images of the same field are taken, decorrelated with each other where parasites are present, and digitally processed in order to measure the number of parasites present in the field. Several fields are sequentially processed in the same fashion, displacing the sample by means of step motors driven by the computer. A direct advantage of this system is that its results are more reliable and the process is less time consuming than the current subjective evaluations made visually by technicians.

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

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

PubMed

Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

2009-10-27

The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.

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.

A fully automated primary screening system for the discovery of therapeutic antibodies directly from B cells.

PubMed

Tickle, Simon; Howells, Louise; O'Dowd, Victoria; Starkie, Dale; Whale, Kevin; Saunders, Mark; Lee, David; Lightwood, Daniel

2015-04-01

For a therapeutic antibody to succeed, it must meet a range of potency, stability, and specificity criteria. Many of these characteristics are conferred by the amino acid sequence of the heavy and light chain variable regions and, for this reason, can be screened for during antibody selection. However, it is important to consider that antibodies satisfying all these criteria may be of low frequency in an immunized animal; for this reason, it is essential to have a mechanism that allows for efficient sampling of the immune repertoire. UCB's core antibody discovery platform combines high-throughput B cell culture screening and the identification and isolation of single, antigen-specific IgG-secreting B cells through a proprietary technique called the "fluorescent foci" method. Using state-of-the-art automation to facilitate primary screening, extremely efficient interrogation of the natural antibody repertoire is made possible; more than 1 billion immune B cells can now be screened to provide a useful starting point from which to identify the rare therapeutic antibody. This article will describe the design, construction, and commissioning of a bespoke automated screening platform and two examples of how it was used to screen for antibodies against two targets. © 2014 Society for Laboratory Automation and Screening.

Automatized set-up procedure for transcranial magnetic stimulation protocols.

PubMed

Harquel, S; Diard, J; Raffin, E; Passera, B; Dall'Igna, G; Marendaz, C; David, O; Chauvin, A

2017-06-01

Transcranial Magnetic Stimulation (TMS) established itself as a powerful technique for probing and treating the human brain. Major technological evolutions, such as neuronavigation and robotized systems, have continuously increased the spatial reliability and reproducibility of TMS, by minimizing the influence of human and experimental factors. However, there is still a lack of efficient set-up procedure, which prevents the automation of TMS protocols. For example, the set-up procedure for defining the stimulation intensity specific to each subject is classically done manually by experienced practitioners, by assessing the motor cortical excitability level over the motor hotspot (HS) of a targeted muscle. This is time-consuming and introduces experimental variability. Therefore, we developed a probabilistic Bayesian model (AutoHS) that automatically identifies the HS position. Using virtual and real experiments, we compared the efficacy of the manual and automated procedures. AutoHS appeared to be more reproducible, faster, and at least as reliable as classical manual procedures. By combining AutoHS with robotized TMS and automated motor threshold estimation methods, our approach constitutes the first fully automated set-up procedure for TMS protocols. The use of this procedure decreases inter-experimenter variability while facilitating the handling of TMS protocols used for research and clinical routine. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural Network Assisted Inverse Dynamic Guidance for Terminally Constrained Entry Flight

PubMed Central

Chen, Wanchun

2014-01-01

This paper presents a neural network assisted entry guidance law that is designed by applying Bézier approximation. It is shown that a fully constrained approximation of a reference trajectory can be made by using the Bézier curve. Applying this approximation, an inverse dynamic system for an entry flight is solved to generate guidance command. The guidance solution thus gotten ensures terminal constraints for position, flight path, and azimuth angle. In order to ensure terminal velocity constraint, a prediction of the terminal velocity is required, based on which, the approximated Bézier curve is adjusted. An artificial neural network is used for this prediction of the terminal velocity. The method enables faster implementation in achieving fully constrained entry flight. Results from simulations indicate improved performance of the neural network assisted method. The scheme is expected to have prospect for further research on automated onboard control of terminal velocity for both reentry and terminal guidance laws. PMID:24723821

Discriminative parameter estimation for random walks segmentation.

PubMed

Baudin, Pierre-Yves; Goodman, Danny; Kumrnar, Puneet; Azzabou, Noura; Carlier, Pierre G; Paragios, Nikos; Kumar, M Pawan

2013-01-01

The Random Walks (RW) algorithm is one of the most efficient and easy-to-use probabilistic segmentation methods. By combining contrast terms with prior terms, it provides accurate segmentations of medical images in a fully automated manner. However, one of the main drawbacks of using the RW algorithm is that its parameters have to be hand-tuned. we propose a novel discriminative learning framework that estimates the parameters using a training dataset. The main challenge we face is that the training samples are not fully supervised. Specifically, they provide a hard segmentation of the images, instead of a probabilistic segmentation. We overcome this challenge by treating the optimal probabilistic segmentation that is compatible with the given hard segmentation as a latent variable. This allows us to employ the latent support vector machine formulation for parameter estimation. We show that our approach significantly outperforms the baseline methods on a challenging dataset consisting of real clinical 3D MRI volumes of skeletal muscles.

Automated discovery and construction of surface phase diagrams using machine learning

DOE PAGES

Ulissi, Zachary W.; Singh, Aayush R.; Tsai, Charlie; ...

2016-08-24

Surface phase diagrams are necessary for understanding surface chemistry in electrochemical catalysis, where a range of adsorbates and coverages exist at varying applied potentials. These diagrams are typically constructed using intuition, which risks missing complex coverages and configurations at potentials of interest. More accurate cluster expansion methods are often difficult to implement quickly for new surfaces. We adopt a machine learning approach to rectify both issues. Using a Gaussian process regression model, the free energy of all possible adsorbate coverages for surfaces is predicted for a finite number of adsorption sites. Our result demonstrates a rational, simple, and systematic approachmore » for generating accurate free-energy diagrams with reduced computational resources. Finally, the Pourbaix diagram for the IrO 2(110) surface (with nine coverages from fully hydrogenated to fully oxygenated surfaces) is reconstructed using just 20 electronic structure relaxations, compared to approximately 90 using typical search methods. Similar efficiency is demonstrated for the MoS 2 surface.« less

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.

New method of contour-based mask-shape compiler

NASA Astrophysics Data System (ADS)

Matsuoka, Ryoichi; Sugiyama, Akiyuki; Onizawa, Akira; Sato, Hidetoshi; Toyoda, Yasutaka

2007-10-01

We have developed a new method of accurately profiling a mask shape by utilizing a Mask CD-SEM. The method is intended to realize high accuracy, stability and reproducibility of the Mask CD-SEM adopting an edge detection algorithm as the key technology used in CD-SEM for high accuracy CD measurement. In comparison with a conventional image processing method for contour profiling, it is possible to create the profiles with much higher accuracy which is comparable with CD-SEM for semiconductor device CD measurement. In this report, we will introduce the algorithm in general, the experimental results and the application in practice. As shrinkage of design rule for semiconductor device has further advanced, an aggressive OPC (Optical Proximity Correction) is indispensable in RET (Resolution Enhancement Technology). From the view point of DFM (Design for Manufacturability), a dramatic increase of data processing cost for advanced MDP (Mask Data Preparation) for instance and surge of mask making cost have become a big concern to the device manufacturers. In a sense, it is a trade-off between the high accuracy RET and the mask production cost, while it gives a significant impact on the semiconductor market centered around the mask business. To cope with the problem, we propose the best method for a DFM solution in which two dimensional data are extracted for an error free practical simulation by precise reproduction of a real mask shape in addition to the mask data simulation. The flow centering around the design data is fully automated and provides an environment where optimization and verification for fully automated model calibration with much less error is available. It also allows complete consolidation of input and output functions with an EDA system by constructing a design data oriented system structure. This method therefore is regarded as a strategic DFM approach in the semiconductor metrology.

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.

Automated measurement of cell motility and proliferation

PubMed Central

Bahnson, Alfred; Athanassiou, Charalambos; Koebler, Douglas; Qian, Lei; Shun, Tongying; Shields, Donna; Yu, Hui; Wang, Hong; Goff, Julie; Cheng, Tao; Houck, Raymond; Cowsert, Lex

2005-01-01

Background Time-lapse microscopic imaging provides a powerful approach for following changes in cell phenotype over time. Visible responses of whole cells can yield insight into functional changes that underlie physiological processes in health and disease. For example, features of cell motility accompany molecular changes that are central to the immune response, to carcinogenesis and metastasis, to wound healing and tissue regeneration, and to the myriad developmental processes that generate an organism. Previously reported image processing methods for motility analysis required custom viewing devices and manual interactions that may introduce bias, that slow throughput, and that constrain the scope of experiments in terms of the number of treatment variables, time period of observation, replication and statistical options. Here we describe a fully automated system in which images are acquired 24/7 from 384 well plates and are automatically processed to yield high-content motility and morphological data. Results We have applied this technology to study the effects of different extracellular matrix compounds on human osteoblast-like cell lines to explore functional changes that may underlie processes involved in bone formation and maintenance. We show dose-response and kinetic data for induction of increased motility by laminin and collagen type I without significant effects on growth rate. Differential motility response was evident within 4 hours of plating cells; long-term responses differed depending upon cell type and surface coating. Average velocities were increased approximately 0.1 um/min by ten-fold increases in laminin coating concentration in some cases. Comparison with manual tracking demonstrated the accuracy of the automated method and highlighted the comparative imprecision of human tracking for analysis of cell motility data. Quality statistics are reported that associate with stage noise, interference by non-cell objects, and uncertainty in the outlining and positioning of cells by automated image analysis. Exponential growth, as monitored by total cell area, did not linearly correlate with absolute cell number, but proved valuable for selection of reliable tracking data and for disclosing between-experiment variations in cell growth. Conclusion These results demonstrate the applicability of a system that uses fully automated image acquisition and analysis to study cell motility and growth. Cellular motility response is determined in an unbiased and comparatively high throughput manner. Abundant ancillary data provide opportunities for uniform filtering according to criteria that select for biological relevance and for providing insight into features of system performance. Data quality measures have been developed that can serve as a basis for the design and quality control of experiments that are facilitated by automation and the 384 well plate format. This system is applicable to large-scale studies such as drug screening and research into effects of complex combinations of factors and matrices on cell phenotype. PMID:15831094

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

Protein model quality assessment prediction by combining fragment comparisons and a consensus Cα contact potential

PubMed Central

Zhou, Hongyi; Skolnick, Jeffrey

2009-01-01

In this work, we develop a fully automated method for the quality assessment prediction of protein structural models generated by structure prediction approaches such as fold recognition servers, or ab initio methods. The approach is based on fragment comparisons and a consensus Cα contact potential derived from the set of models to be assessed and was tested on CASP7 server models. The average Pearson linear correlation coefficient between predicted quality and model GDT-score per target is 0.83 for the 98 targets which is better than those of other quality assessment methods that participated in CASP7. Our method also outperforms the other methods by about 3% as assessed by the total GDT-score of the selected top models. PMID:18004783

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.

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

PubMed

Schmaljohann, Jörn; Schirrmacher, Esther; Wängler, Björn; Wängler, Carmen; Schirrmacher, Ralf; Guhlke, Stefan

2011-02-01

2-[(18)F]Fluoroethyl-choline ([(18)F]FECH) is a promising tracer for the detection of prostate cancer as well as brain tumors with positron emission tomography (PET). [(18)F]FECH is actively transported into mammalian cells, becomes phosphorylated by choline kinase and gets incorporated into the cell membrane after being metabolized to phosphatidylcholine. So far, its synthesis is a two-step procedure involving at least one HPLC purification step. To allow a wider dissemination of this tracer, finding a purification method avoiding HPLC is highly desirable and would result in easier accessibility and more reliable production of [(18)F]FECH. [(18)F]FECH was synthesized by reaction of 2-bromo-1-[(18)F]fluoroethane ([(18)F]BFE) with dimethylaminoethanol (DMAE) in DMSO. We applied a novel and very reliable work-up procedure for the synthesis of [(18)F]BFE. Based on a combination of three different solid-phase cartridges, the purification of [(18)F]BFE from its precursor 2-bromoethyl-4-nitrobenzenesulfonate (BENos) could be achieved without using HPLC. Following the subsequent reaction of the purified [(18)F]BFE with DMAE, the final product [(18)F]FECH was obtained as a sterile solution by passing the crude reaction mixture through a combination of two CM plus cartridges and a sterile filter. The fully automated synthesis was performed using as well a Raytest SynChrom module (Raytest, Germany) or a Scintomics HotboxIII module (Scintomics, Germany). The radiotracer [(18)F]FECH can be synthesized in reliable radiochemical yields (RCY) of 37±5% (Synchrom module) and 33±5% (Hotbox III unit) in less than 1 h using these two fully automated commercially available synthesis units without HPLC involvement for purification. Detailed quality control of the final injectable [(18)F]FECH solution proved the high radiochemical purity and the absence of Kryptofix2.2.2, DMAE and DMSO used in the course of synthesis. Sterility and bacterial endotoxin testing following standard procedures verified that the described production method for [(18)F]FECH is suitable for human applications. The routine production of [(18)F]FECH with sufficient RCYs was established by reliable and fast solid-phase extraction purifications of both the secondary labeling precursor [(18)F]BFE and the final product [(18)F]FECH, avoiding complex and sensitive HPLC equipment. The purity of the product was >95%, rendering the tracer suitable for human application. The newly developed purification procedure for [(18)F]BFE significantly reduces the complexity of the automated synthesis unit, hence reducing the cost for routine production in a clinical setup and allowing easy transfer to different synthesis modules. Copyright © 2011 Elsevier Inc. All rights reserved.

Constraint factor graph cut-based active contour method for automated cellular image segmentation in RNAi screening.

PubMed

Chen, C; Li, H; Zhou, X; Wong, S T C

2008-05-01

Image-based, high throughput genome-wide RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Automated screening of such experiments generates a large number of images with great variations in image quality, which makes manual analysis unreasonably time-consuming. Therefore, effective techniques for automatic image analysis are urgently needed, in which segmentation is one of the most important steps. This paper proposes a fully automatic method for cells segmentation in genome-wide RNAi screening images. The method consists of two steps: nuclei and cytoplasm segmentation. Nuclei are extracted and labelled to initialize cytoplasm segmentation. Since the quality of RNAi image is rather poor, a novel scale-adaptive steerable filter is designed to enhance the image in order to extract long and thin protrusions on the spiky cells. Then, constraint factor GCBAC method and morphological algorithms are combined to be an integrated method to segment tight clustered cells. Compared with the results obtained by using seeded watershed and the ground truth, that is, manual labelling results by experts in RNAi screening data, our method achieves higher accuracy. Compared with active contour methods, our method consumes much less time. The positive results indicate that the proposed method can be applied in automatic image analysis of multi-channel image screening data.

VizieR Online Data Catalog: Proper motions of PM2000 open clusters (Krone-Martins+, 2010)

NASA Astrophysics Data System (ADS)

Krone-Martins, A.; Soubiran, C.; Ducourant, C.; Teixeira, R.; Le Campion, J. F.

2010-04-01

We present lists of proper-motions and kinematic membership probabilities in the region of 49 open clusters or possible open clusters. The stellar proper motions were taken from the Bordeaux PM2000 catalogue. The segregation between cluster and field stars and the assignment of membership probabilities was accomplished by applying a fully automated method based on parametrisations for the probability distribution functions and genetic algorithm optimisation heuristics associated with a derivative-based hill climbing algorithm for the likelihood optimization. (3 data files).

Automation of Endmember Pixel Selection in SEBAL/METRIC Model

NASA Astrophysics Data System (ADS)

Bhattarai, N.; Quackenbush, L. J.; Im, J.; Shaw, S. B.

2015-12-01

The commonly applied surface energy balance for land (SEBAL) and its variant, mapping evapotranspiration (ET) at high resolution with internalized calibration (METRIC) models require manual selection of endmember (i.e. hot and cold) pixels to calibrate sensible heat flux. Current approaches for automating this process are based on statistical methods and do not appear to be robust under varying climate conditions and seasons. In this paper, we introduce a new approach based on simple machine learning tools and search algorithms that provides an automatic and time efficient way of identifying endmember pixels for use in these models. The fully automated models were applied on over 100 cloud-free Landsat images with each image covering several eddy covariance flux sites in Florida and Oklahoma. Observed land surface temperatures at automatically identified hot and cold pixels were within 0.5% of those from pixels manually identified by an experienced operator (coefficient of determination, R2, ≥ 0.92, Nash-Sutcliffe efficiency, NSE, ≥ 0.92, and root mean squared error, RMSE, ≤ 1.67 K). Daily ET estimates derived from the automated SEBAL and METRIC models were in good agreement with their manual counterparts (e.g., NSE ≥ 0.91 and RMSE ≤ 0.35 mm day-1). Automated and manual pixel selection resulted in similar estimates of observed ET across all sites. The proposed approach should reduce time demands for applying SEBAL/METRIC models and allow for their more widespread and frequent use. This automation can also reduce potential bias that could be introduced by an inexperienced operator and extend the domain of the models to new users.

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.

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 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.

Nanoliter-Scale Protein Crystallization and Screening with a Microfluidic Droplet Robot

PubMed Central

Zhu, Ying; Zhu, Li-Na; Guo, Rui; Cui, Heng-Jun; Ye, Sheng; Fang, Qun

2014-01-01

Large-scale screening of hundreds or even thousands of crystallization conditions while with low sample consumption is in urgent need, in current structural biology research. Here we describe a fully-automated droplet robot for nanoliter-scale crystallization screening that combines the advantages of both automated robotics technique for protein crystallization screening and the droplet-based microfluidic technique. A semi-contact dispensing method was developed to achieve flexible, programmable and reliable liquid-handling operations for nanoliter-scale protein crystallization experiments. We applied the droplet robot in large-scale screening of crystallization conditions of five soluble proteins and one membrane protein with 35–96 different crystallization conditions, study of volume effects on protein crystallization, and determination of phase diagrams of two proteins. The volume for each droplet reactor is only ca. 4–8 nL. The protein consumption significantly reduces 50–500 fold compared with current crystallization stations. PMID:24854085

Nanoliter-scale protein crystallization and screening with a microfluidic droplet robot.

PubMed

Zhu, Ying; Zhu, Li-Na; Guo, Rui; Cui, Heng-Jun; Ye, Sheng; Fang, Qun

2014-05-23

Large-scale screening of hundreds or even thousands of crystallization conditions while with low sample consumption is in urgent need, in current structural biology research. Here we describe a fully-automated droplet robot for nanoliter-scale crystallization screening that combines the advantages of both automated robotics technique for protein crystallization screening and the droplet-based microfluidic technique. A semi-contact dispensing method was developed to achieve flexible, programmable and reliable liquid-handling operations for nanoliter-scale protein crystallization experiments. We applied the droplet robot in large-scale screening of crystallization conditions of five soluble proteins and one membrane protein with 35-96 different crystallization conditions, study of volume effects on protein crystallization, and determination of phase diagrams of two proteins. The volume for each droplet reactor is only ca. 4-8 nL. The protein consumption significantly reduces 50-500 fold compared with current crystallization stations.

The enhanced Software Life Cyle Support Environment (ProSLCSE): Automation for enterprise and process modeling

NASA Technical Reports Server (NTRS)

Milligan, James R.; Dutton, James E.

1993-01-01

In this paper, we have introduced a comprehensive method for enterprise modeling that addresses the three important aspects of how an organization goes about its business. FirstEP includes infrastructure modeling, information modeling, and process modeling notations that are intended to be easy to learn and use. The notations stress the use of straightforward visual languages that are intuitive, syntactically simple, and semantically rich. ProSLCSE will be developed with automated tools and services to facilitate enterprise modeling and process enactment. In the spirit of FirstEP, ProSLCSE tools will also be seductively easy to use. Achieving fully managed, optimized software development and support processes will be long and arduous for most software organizations, and many serious problems will have to be solved along the way. ProSLCSE will provide the ability to document, communicate, and modify existing processes, which is the necessary first step.

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

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.

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.

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.

Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes

PubMed Central

Erkol, Bulent; Moss, Randy H.; Stanley, R. Joe; Stoecker, William V.; Hvatum, Erik

2011-01-01

Background Malignant melanoma has a good prognosis if treated early. Dermoscopy images of pigmented lesions are most commonly taken at × 10 magnification under lighting at a low angle of incidence while the skin is immersed in oil under a glass plate. Accurate skin lesion segmentation from the background skin is important because some of the features anticipated to be used for diagnosis deal with shape of the lesion and others deal with the color of the lesion compared with the color of the surrounding skin. Methods In this research, gradient vector flow (GVF) snakes are investigated to find the border of skin lesions in dermoscopy images. An automatic initialization method is introduced to make the skin lesion border determination process fully automated. Results Skin lesion segmentation results are presented for 70 benign and 30 melanoma skin lesion images for the GVF-based method and a color histogram analysis technique. The average errors obtained by the GVF-based method are lower for both the benign and melanoma image sets than for the color histogram analysis technique based on comparison with manually segmented lesions determined by a dermatologist. Conclusions The experimental results for the GVF-based method demonstrate promise as an automated technique for skin lesion segmentation in dermoscopy images. PMID:15691255

Correction of spin diffusion during iterative automated NOE assignment

NASA Astrophysics Data System (ADS)

Linge, Jens P.; Habeck, Michael; Rieping, Wolfgang; Nilges, Michael

2004-04-01

Indirect magnetization transfer increases the observed nuclear Overhauser enhancement (NOE) between two protons in many cases, leading to an underestimation of target distances. Wider distance bounds are necessary to account for this error. However, this leads to a loss of information and may reduce the quality of the structures generated from the inter-proton distances. Although several methods for spin diffusion correction have been published, they are often not employed to derive distance restraints. This prompted us to write a user-friendly and CPU-efficient method to correct for spin diffusion that is fully integrated in our program ambiguous restraints for iterative assignment (ARIA). ARIA thus allows automated iterative NOE assignment and structure calculation with spin diffusion corrected distances. The method relies on numerical integration of the coupled differential equations which govern relaxation by matrix squaring and sparse matrix techniques. We derive a correction factor for the distance restraints from calculated NOE volumes and inter-proton distances. To evaluate the impact of our spin diffusion correction, we tested the new calibration process extensively with data from the Pleckstrin homology (PH) domain of Mus musculus β-spectrin. By comparing structures refined with and without spin diffusion correction, we show that spin diffusion corrected distance restraints give rise to structures of higher quality (notably fewer NOE violations and a more regular Ramachandran map). Furthermore, spin diffusion correction permits the use of tighter error bounds which improves the distinction between signal and noise in an automated NOE assignment scheme.

Performance of Kiestra Total Laboratory Automation Combined with MS in Clinical Microbiology Practice

PubMed Central

Hodiamont, Caspar J.; de Jong, Menno D.; Overmeijer, Hendri P. J.; van den Boogaard, Mandy; Visser, Caroline E.

2014-01-01

Background Microbiological laboratories seek technologically innovative solutions to cope with large numbers of samples and limited personnel and financial resources. One platform that has recently become available is the Kiestra Total Laboratory Automation (TLA) system (BD Kiestra B.V., the Netherlands). This fully automated sample processing system, equipped with digital imaging technology, allows superior detection of microbial growth. Combining this approach with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MS) (Bruker Daltonik, Germany) is expected to enable more rapid identification of pathogens. Methods Early growth detection by digital imaging using Kiestra TLA combined with MS was compared to conventional methods (CM) of detection. Accuracy and time taken for microbial identification were evaluated for the two methods in 219 clinical blood culture isolates. The possible clinical impact of earlier microbial identification was assessed according to antibiotic treatment prescription. Results Pathogen identification using Kiestra TLA combined with MS resulted in a 30.6 hr time gain per isolate compared to CM. Pathogens were successfully identified in 98.4% (249/253) of all tested isolates. Early microbial identification without susceptibility testing led to an adjustment of antibiotic regimen in 12% (24/200) of patients. Conclusions The requisite 24 hr incubation time for microbial pathogens to reach sufficient growth for susceptibility testing and identification would be shortened by the implementation of Kiestra TLA in combination with MS, compared to the use of CM. Not only can this method optimize workflow and reduce costs, but it can allow potentially life-saving switches in antibiotic regimen to be initiated sooner. PMID:24624346

An automated approach for annual layer counting in ice cores

NASA Astrophysics Data System (ADS)

Winstrup, M.; Svensson, A.; Rasmussen, S. O.; Winther, O.; Steig, E.; Axelrod, A.

2012-04-01

The temporal resolution of some ice cores is sufficient to preserve seasonal information in the ice core record. In such cases, annual layer counting represents one of the most accurate methods to produce a chronology for the core. Yet, manual layer counting is a tedious and sometimes ambiguous job. As reliable layer recognition becomes more difficult, a manual approach increasingly relies on human interpretation of the available data. Thus, much may be gained by an automated and therefore objective approach for annual layer identification in ice cores. We have developed a novel method for automated annual layer counting in ice cores, which relies on Bayesian statistics. It uses algorithms from the statistical framework of Hidden Markov Models (HMM), originally developed for use in machine speech recognition. The strength of this layer detection algorithm lies in the way it is able to imitate the manual procedures for annual layer counting, while being based on purely objective criteria for annual layer identification. With this methodology, it is possible to determine the most likely position of multiple layer boundaries in an entire section of ice core data at once. It provides a probabilistic uncertainty estimate of the resulting layer count, hence ensuring a proper treatment of ambiguous layer boundaries in the data. Furthermore multiple data series can be incorporated to be used at once, hence allowing for a full multi-parameter annual layer counting method similar to a manual approach. In this study, the automated layer counting algorithm has been applied to data from the NGRIP ice core, Greenland. The NGRIP ice core has very high temporal resolution with depth, and hence the potential to be dated by annual layer counting far back in time. In previous studies [Andersen et al., 2006; Svensson et al., 2008], manual layer counting has been carried out back to 60 kyr BP. A comparison between the counted annual layers based on the two approaches will be presented and their differences discussed. Within the estimated uncertainties, the two methodologies agree. This shows the potential for a fully automated annual layer counting method to be operational for data sections where the annual layering is unknown.

High-density grids for efficient data collection from multiple crystals

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

Baxter, Elizabeth L.; Aguila, Laura; Alonso-Mori, Roberto

Higher throughput methods to mount and collect data from multiple small and radiation-sensitive crystals are important to support challenging structural investigations using microfocus synchrotron beamlines. Furthermore, efficient sample-delivery methods are essential to carry out productive femtosecond crystallography experiments at X-ray free-electron laser (XFEL) sources such as the Linac Coherent Light Source (LCLS). To address these needs, a high-density sample grid useful as a scaffold for both crystal growth and diffraction data collection has been developed and utilized for efficient goniometer-based sample delivery at synchrotron and XFEL sources. A single grid contains 75 mounting ports and fits inside an SSRL cassettemore » or uni-puck storage container. The use of grids with an SSRL cassette expands the cassette capacity up to 7200 samples. Grids may also be covered with a polymer film or sleeve for efficient room-temperature data collection from multiple samples. New automated routines have been incorporated into theBlu-Ice/DCSSexperimental control system to support grids, including semi-automated grid alignment, fully automated positioning of grid ports, rastering and automated data collection. Specialized tools have been developed to support crystallization experiments on grids, including a universal adaptor, which allows grids to be filled by commercial liquid-handling robots, as well as incubation chambers, which support vapor-diffusion and lipidic cubic phase crystallization experiments. Experiments in which crystals were loaded into grids or grown on grids using liquid-handling robots and incubation chambers are described. As a result, crystals were screened at LCLS-XPP and SSRL BL12-2 at room temperature and cryogenic temperatures.« less

High-density grids for efficient data collection from multiple crystals

PubMed Central

Baxter, Elizabeth L.; Aguila, Laura; Alonso-Mori, Roberto; Barnes, Christopher O.; Bonagura, Christopher A.; Brehmer, Winnie; Brunger, Axel T.; Calero, Guillermo; Caradoc-Davies, Tom T.; Chatterjee, Ruchira; Degrado, William F.; Fraser, James S.; Ibrahim, Mohamed; Kern, Jan; Kobilka, Brian K.; Kruse, Andrew C.; Larsson, Karl M.; Lemke, Heinrik T.; Lyubimov, Artem Y.; Manglik, Aashish; McPhillips, Scott E.; Norgren, Erik; Pang, Siew S.; Soltis, S. M.; Song, Jinhu; Thomaston, Jessica; Tsai, Yingssu; Weis, William I.; Woldeyes, Rahel A.; Yachandra, Vittal; Yano, Junko; Zouni, Athina; Cohen, Aina E.

2016-01-01

Higher throughput methods to mount and collect data from multiple small and radiation-sensitive crystals are important to support challenging structural investigations using microfocus synchrotron beamlines. Furthermore, efficient sample-delivery methods are essential to carry out productive femtosecond crystallography experiments at X-ray free-electron laser (XFEL) sources such as the Linac Coherent Light Source (LCLS). To address these needs, a high-density sample grid useful as a scaffold for both crystal growth and diffraction data collection has been developed and utilized for efficient goniometer-based sample delivery at synchrotron and XFEL sources. A single grid contains 75 mounting ports and fits inside an SSRL cassette or uni-puck storage container. The use of grids with an SSRL cassette expands the cassette capacity up to 7200 samples. Grids may also be covered with a polymer film or sleeve for efficient room-temperature data collection from multiple samples. New automated routines have been incorporated into the Blu-Ice/DCSS experimental control system to support grids, including semi-automated grid alignment, fully automated positioning of grid ports, rastering and automated data collection. Specialized tools have been developed to support crystallization experiments on grids, including a universal adaptor, which allows grids to be filled by commercial liquid-handling robots, as well as incubation chambers, which support vapor-diffusion and lipidic cubic phase crystallization experiments. Experiments in which crystals were loaded into grids or grown on grids using liquid-handling robots and incubation chambers are described. Crystals were screened at LCLS-XPP and SSRL BL12-2 at room temperature and cryogenic temperatures. PMID:26894529

Advances in the simulation and automated measurement of well-sorted granular material: 2. Direct measures of particle properties

USGS Publications Warehouse

Buscombe, Daniel D.; Rubin, David M.

2012-01-01

1. In this, the second of a pair of papers on the structure of well-sorted natural granular material (sediment), new methods are described for automated measurements from images of sediment, of: 1) particle-size standard deviation (arithmetic sorting) with and without apparent void fraction; and 2) mean particle size in material with void fraction. A variety of simulations of granular material are used for testing purposes, in addition to images of natural sediment. Simulations are also used to establish that the effects on automated particle sizing of grains visible through the interstices of the grains at the very surface of a granular material continue to a depth of approximately 4 grain diameters and that this is independent of mean particle size. Ensemble root-mean squared error between observed and estimated arithmetic sorting coefficients for 262 images of natural silts, sands and gravels (drawn from 8 populations) is 31%, which reduces to 27% if adjusted for bias (slope correction between observed and estimated values). These methods allow non-intrusive and fully automated measurements of surfaces of unconsolidated granular material. With no tunable parameters or empirically derived coefficients, they should be broadly universal in appropriate applications. However, empirical corrections may need to be applied for the most accurate results. Finally, analytical formulas are derived for the one-step pore-particle transition probability matrix, estimated from the image's autocorrelogram, from which void fraction of a section of granular material can be estimated directly. This model gives excellent predictions of bulk void fraction yet imperfect predictions of pore-particle transitions.

Advances in the simulation and automated measurement of well-sorted granular material: 2. Direct measures of particle properties

NASA Astrophysics Data System (ADS)

Buscombe, D.; Rubin, D. M.

2012-06-01

In this, the second of a pair of papers on the structure of well-sorted natural granular material (sediment), new methods are described for automated measurements from images of sediment, of: 1) particle-size standard deviation (arithmetic sorting) with and without apparent void fraction; and 2) mean particle size in material with void fraction. A variety of simulations of granular material are used for testing purposes, in addition to images of natural sediment. Simulations are also used to establish that the effects on automated particle sizing of grains visible through the interstices of the grains at the very surface of a granular material continue to a depth of approximately 4 grain diameters and that this is independent of mean particle size. Ensemble root-mean squared error between observed and estimated arithmetic sorting coefficients for 262 images of natural silts, sands and gravels (drawn from 8 populations) is 31%, which reduces to 27% if adjusted for bias (slope correction between observed and estimated values). These methods allow non-intrusive and fully automated measurements of surfaces of unconsolidated granular material. With no tunable parameters or empirically derived coefficients, they should be broadly universal in appropriate applications. However, empirical corrections may need to be applied for the most accurate results. Finally, analytical formulas are derived for the one-step pore-particle transition probability matrix, estimated from the image's autocorrelogram, from which void fraction of a section of granular material can be estimated directly. This model gives excellent predictions of bulk void fraction yet imperfect predictions of pore-particle transitions.

BEACON: automated tool for Bacterial GEnome Annotation ComparisON.

PubMed

Kalkatawi, Manal; Alam, Intikhab; Bajic, Vladimir B

2015-08-18

Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs). The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACON's utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27%, while the number of genes without any function assignment is reduced. We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/ .

High-density grids for efficient data collection from multiple crystals

DOE PAGES

Baxter, Elizabeth L.; Aguila, Laura; Alonso-Mori, Roberto; ...

2015-11-03

Higher throughput methods to mount and collect data from multiple small and radiation-sensitive crystals are important to support challenging structural investigations using microfocus synchrotron beamlines. Furthermore, efficient sample-delivery methods are essential to carry out productive femtosecond crystallography experiments at X-ray free-electron laser (XFEL) sources such as the Linac Coherent Light Source (LCLS). To address these needs, a high-density sample grid useful as a scaffold for both crystal growth and diffraction data collection has been developed and utilized for efficient goniometer-based sample delivery at synchrotron and XFEL sources. A single grid contains 75 mounting ports and fits inside an SSRL cassettemore » or uni-puck storage container. The use of grids with an SSRL cassette expands the cassette capacity up to 7200 samples. Grids may also be covered with a polymer film or sleeve for efficient room-temperature data collection from multiple samples. New automated routines have been incorporated into theBlu-Ice/DCSSexperimental control system to support grids, including semi-automated grid alignment, fully automated positioning of grid ports, rastering and automated data collection. Specialized tools have been developed to support crystallization experiments on grids, including a universal adaptor, which allows grids to be filled by commercial liquid-handling robots, as well as incubation chambers, which support vapor-diffusion and lipidic cubic phase crystallization experiments. Experiments in which crystals were loaded into grids or grown on grids using liquid-handling robots and incubation chambers are described. As a result, crystals were screened at LCLS-XPP and SSRL BL12-2 at room temperature and cryogenic temperatures.« less

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.

Through oven transfer adsorption-desorption interface for the analysis of methyl jasmonate in aromatic samples by on-line RPLC-GC.

PubMed

Flores, Gema; Blanch, Gracia Patricia; Ruiz del Castillo, Maria Luisa

2008-04-01

A fully automated method for the determination of medium volatility compounds in aromatic samples was developed. Specifically, the determination of methyl jasmonate in jasmine fragrances was performed by using the through oven transfer adsorption-desorption (TOTAD) interface for the on-line coupling between RPLC-GC. A study of the most relevant variables involved in the performance of the TOTAD interface for medium volatility compounds was carried out by testing different values of helium flow (100, 300, 400, and 500 mL/min), transfer speed (0.1, 0.3, 0.5, and 2.0 mL/min), and methanol/water percentages (86:14, 85:15, 83:17, 80:20, and 70:30). The method developed provided satisfactory repeatability (RSD for retention times of 0.15% and for peak areas of 9.4%) and recovery (71%) as well as excellent LOD (0.01 mg/L) for methyl jasmonate in commercial jasmine essence under the experimental conditions selected as optimum. Additional advantages of the automated RPLC-TOTAD-GC method proposed in the present work are its rapidness, reliability, and the possibility of directly introducing the sample with no further pretreatment.

A fully automated non-external marker 4D-CT sorting algorithm using a serial cine scanning protocol.

PubMed

Carnes, Greg; Gaede, Stewart; Yu, Edward; Van Dyk, Jake; Battista, Jerry; Lee, Ting-Yim

2009-04-07

Current 4D-CT methods require external marker data to retrospectively sort image data and generate CT volumes. In this work we develop an automated 4D-CT sorting algorithm that performs without the aid of data collected from an external respiratory surrogate. The sorting algorithm requires an overlapping cine scan protocol. The overlapping protocol provides a spatial link between couch positions. Beginning with a starting scan position, images from the adjacent scan position (which spatial match the starting scan position) are selected by maximizing the normalized cross correlation (NCC) of the images at the overlapping slice position. The process was continued by 'daisy chaining' all couch positions using the selected images until an entire 3D volume was produced. The algorithm produced 16 phase volumes to complete a 4D-CT dataset. Additional 4D-CT datasets were also produced using external marker amplitude and phase angle sorting methods. The image quality of the volumes produced by the different methods was quantified by calculating the mean difference of the sorted overlapping slices from adjacent couch positions. The NCC sorted images showed a significant decrease in the mean difference (p < 0.01) for the five patients.

Determination of aberration center of Ronchigram for automated aberration correctors in scanning transmission electron microscopy.

PubMed

Sannomiya, Takumi; Sawada, Hidetaka; Nakamichi, Tomohiro; Hosokawa, Fumio; Nakamura, Yoshio; Tanishiro, Yasumasa; Takayanagi, Kunio

2013-12-01

A generic method to determine the aberration center is established, which can be utilized for aberration calculation and axis alignment for aberration corrected electron microscopes. In this method, decentering induced secondary aberrations from inherent primary aberrations are minimized to find the appropriate axis center. The fitness function to find the optimal decentering vector for the axis was defined as a sum of decentering induced secondary aberrations with properly distributed weight values according to the aberration order. Since the appropriate decentering vector is determined from the aberration values calculated at an arbitrary center axis, only one aberration measurement is in principle required to find the center, resulting in /very fast center search. This approach was tested for the Ronchigram based aberration calculation method for aberration corrected scanning transmission electron microscopy. Both in simulation and in experiments, the center search was confirmed to work well although the convergence to find the best axis becomes slower with larger primary aberrations. Such aberration center determination is expected to fully automatize the aberration correction procedures, which used to require pre-alignment of experienced users. This approach is also applicable to automated aperture positioning. Copyright © 2013 Elsevier B.V. All rights reserved.

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

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

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.

An automated microfluidic platform for C. elegans embryo arraying, phenotyping, and long-term live imaging

NASA Astrophysics Data System (ADS)

Cornaglia, Matteo; Mouchiroud, Laurent; Marette, Alexis; Narasimhan, Shreya; Lehnert, Thomas; Jovaisaite, Virginija; Auwerx, Johan; Gijs, Martin A. M.

2015-05-01

Studies of the real-time dynamics of embryonic development require a gentle embryo handling method, the possibility of long-term live imaging during the complete embryogenesis, as well as of parallelization providing a population’s statistics, while keeping single embryo resolution. We describe an automated approach that fully accomplishes these requirements for embryos of Caenorhabditis elegans, one of the most employed model organisms in biomedical research. We developed a microfluidic platform which makes use of pure passive hydrodynamics to run on-chip worm cultures, from which we obtain synchronized embryo populations, and to immobilize these embryos in incubator microarrays for long-term high-resolution optical imaging. We successfully employ our platform to investigate morphogenesis and mitochondrial biogenesis during the full embryonic development and elucidate the role of the mitochondrial unfolded protein response (UPRmt) within C. elegans embryogenesis. Our method can be generally used for protein expression and developmental studies at the embryonic level, but can also provide clues to understand the aging process and age-related diseases in particular.

Automated total and radioactive strontium separation and preconcentration in samples of environmental interest exploiting a lab-on-valve system.

PubMed

Rodríguez, Rogelio; Avivar, Jessica; Ferrer, Laura; Leal, Luz O; Cerdà, Victor

2012-07-15

A novel lab-on-valve system has been developed for strontium determination in environmental samples. Miniaturized lab-on-valve system potentially offers facilities to allow any kind of chemical and physical processes, including fluidic and microcarrier bead control, homogenous reaction and liquid-solid interaction. A rapid, inexpensive and fully automated method for the separation and preconcentration of total and radioactive strontium, using a solid phase extraction material (Sr-Resin), has been developed. Total strontium concentrations are determined by ICP-OES and (90)Sr activities by a low background proportional counter. The method has been successfully applied to different water samples of environmental interest. The proposed system offers minimization of sample handling, drastic reduction of reagent volume, improvement of the reproducibility and sample throughput and attains a significant decrease of both time and cost per analysis. The LLD of the total Sr reached is 1.8ng and the minimum detectable activity for (90)Sr is 0.008Bq. The repeatability of the separation procedure is 1.2% (n=10). Copyright © 2011 Elsevier B.V. All rights reserved.

A Procedural Electroencephalogram Simulator for Evaluation of Anesthesia Monitors.

PubMed

Petersen, Christian Leth; Görges, Matthias; Massey, Roslyn; Dumont, Guy Albert; Ansermino, J Mark

2016-11-01

Recent research and advances in the automation of anesthesia are driving the need to better understand electroencephalogram (EEG)-based anesthesia end points and to test the performance of anesthesia monitors. This effort is currently limited by the need to collect raw EEG data directly from patients. A procedural method to synthesize EEG signals was implemented in a mobile software application. The application is capable of sending the simulated signal to an anesthesia depth of hypnosis monitor. Systematic sweeps of the simulator generate functional monitor response profiles reminiscent of how network analyzers are used to test electronic components. Three commercial anesthesia monitors (Entropy, NeuroSENSE, and BIS) were compared with this new technology, and significant response and feature variations between the monitor models were observed; this includes reproducible, nonmonotonic apparent multistate behavior and significant hysteresis at light levels of anesthesia. Anesthesia monitor response to a procedural simulator can reveal significant differences in internal signal processing algorithms. The ability to synthesize EEG signals at different anesthetic depths potentially provides a new method for systematically testing EEG-based monitors and automated anesthesia systems with all sensor hardware fully operational before human trials.

A Fully Automated and Robust Method to Incorporate Stamping Data in Crash, NVH and Durability Analysis

NASA Astrophysics Data System (ADS)

Palaniswamy, Hariharasudhan; Kanthadai, Narayan; Roy, Subir; Beauchesne, Erwan

2011-08-01

Crash, NVH (Noise, Vibration, Harshness), and durability analysis are commonly deployed in structural CAE analysis for mechanical design of components especially in the automotive industry. Components manufactured by stamping constitute a major portion of the automotive structure. In CAE analysis they are modeled at a nominal state with uniform thickness and no residual stresses and strains. However, in reality the stamped components have non-uniformly distributed thickness and residual stresses and strains resulting from stamping. It is essential to consider the stamping information in CAE analysis to accurately model the behavior of the sheet metal structures under different loading conditions. Especially with the current emphasis on weight reduction by replacing conventional steels with aluminum and advanced high strength steels it is imperative to avoid over design. Considering this growing need in industry, a highly automated and robust method has been integrated within Altair Hyperworks® to initialize sheet metal components in CAE models with stamping data. This paper demonstrates this new feature and the influence of stamping data for a full car frontal crash analysis.

Automated smoother for the numerical decoupling of dynamics models.

PubMed

Vilela, Marco; Borges, Carlos C H; Vinga, Susana; Vasconcelos, Ana Tereza R; Santos, Helena; Voit, Eberhard O; Almeida, Jonas S

2007-08-21

Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure. In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from in-vivo NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations. The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.

Aptima HIV-1 Quant Dx--A fully automated assay for both diagnosis and quantification of HIV-1.

PubMed

Nair, Sangeetha Vijaysri; Kim, Hee Cheol; Fortunko, Jacqueline; Foote, Tracy; Peling, Tashi; Tran, Cuong; Nugent, Charles Thomas; Joo, Sunghae; Kang, Youna; Wilkins, Bana; Lednovich, Kristen; Worlock, Andrew

2016-04-01

Separate assays are available for diagnosis and viral load (VL) monitoring of HIV-1. Studies have shown that using a single test for both confirmatory diagnosis and VL increases linkage to care. To validate a single assay for both diagnosis and VL monitoring of HIV-1 on the fully automated Panther platform. Validate the assay by assessing specificity, sensitivity, subtype detection, seroconversion, reproducibility and linearity. Also assess diagnostic agreement with the Procleix(®) Ultrio Elite™ discriminatory assay (Procleix), and agreement of VL results (method comparison) with Ampliprep/COBAS TaqMan HIV-1 version 2.0 (CAP/CTM), using clinical samples. The assay was specific (100%) and sensitive with a 95% limit of detection of 12 copies/mL with the 3rd WHO standards. Aptima detected HIV in seroconversion panels 6 and 11 days before p24 antigen and antibody tests, respectively. Diagnostic agreement with Procleix, was 100%. Regression analysis showed good agreement of VL results between Aptima and CAP/CTM with a slope of 1.02, intercept of 0.07, and correlation coefficient (R(2)) of 0.97. Aptima was more sensitive than CAP/CTM. Equivalent quantification was seen on testing clinical samples and isolates belonging to HIV group M, N, O and P and commercially available subtype panels. Assay results were linear (R(2) 0.9994) with standard deviation of <0.17 log copies across assay range. The good specificity, sensitivity, precision, subtype performance and clinical agreement with other assays demonstrated by Aptima combined with the complete automation provided by the Panther platform makes Aptima a good candidate for both VL monitoring and diagnosis of HIV-1. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

OptoDyCE: Automated system for high-throughput all-optical dynamic cardiac electrophysiology

NASA Astrophysics Data System (ADS)

Klimas, Aleksandra; Yu, Jinzhu; Ambrosi, Christina M.; Williams, John C.; Bien, Harold; Entcheva, Emilia

2016-02-01

In the last two decades, <30% of drugs withdrawals from the market were due to cardiac toxicity, where unintended interactions with ion channels disrupt the heart's normal electrical function. Consequently, all new drugs must undergo preclinical testing for cardiac liability, adding to an already expensive and lengthy process. Recognition that proarrhythmic effects often result from drug action on multiple ion channels demonstrates a need for integrative and comprehensive measurements. Additionally, patient-specific therapies relying on emerging technologies employing stem-cell derived cardiomyocytes (e.g. induced pluripotent stem-cell-derived cardiomyocytes, iPSC-CMs) require better screening methods to become practical. However, a high-throughput, cost-effective approach for cellular cardiac electrophysiology has not been feasible. Optical techniques for manipulation and recording provide a contactless means of dynamic, high-throughput testing of cells and tissues. Here, we consider the requirements for all-optical electrophysiology for drug testing, and we implement and validate OptoDyCE, a fully automated system for all-optical cardiac electrophysiology. We demonstrate the high-throughput capabilities using multicellular samples in 96-well format by combining optogenetic actuation with simultaneous fast high-resolution optical sensing of voltage or intracellular calcium. The system can also be implemented using iPSC-CMs and other cell-types by delivery of optogenetic drivers, or through the modular use of dedicated light-sensitive somatic cells in conjunction with non-modified cells. OptoDyCE provides a truly modular and dynamic screening system, capable of fully-automated acquisition of high-content information integral for improved discovery and development of new drugs and biologics, as well as providing a means of better understanding of electrical disturbances in the heart.

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

NASA Technical Reports Server (NTRS)

Jong, Jen-Yi

1997-01-01

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

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.

Αutomated 2D shoreline detection from coastal video imagery: an example from the island of Crete

NASA Astrophysics Data System (ADS)

Velegrakis, A. F.; Trygonis, V.; Vousdoukas, M. I.; Ghionis, G.; Chatzipavlis, A.; Andreadis, O.; Psarros, F.; Hasiotis, Th.

2015-06-01

Beaches are both sensitive and critical coastal system components as they: (i) are vulnerable to coastal erosion (due to e.g. wave regime changes and the short- and long-term sea level rise) and (ii) form valuable ecosystems and economic resources. In order to identify/understand the current and future beach morphodynamics, effective monitoring of the beach spatial characteristics (e.g. the shoreline position) at adequate spatio-temporal resolutions is required. In this contribution we present the results of a new, fully-automated detection method of the (2-D) shoreline positions using high resolution video imaging from a Greek island beach (Ammoudara, Crete). A fully-automated feature detection method was developed/used to monitor the shoreline position in geo-rectified coastal imagery obtained through a video system set to collect 10 min videos every daylight hour with a sampling rate of 5 Hz, from which snapshot, time-averaged (TIMEX) and variance images (SIGMA) were generated. The developed coastal feature detector is based on a very fast algorithm using a localised kernel that progressively grows along the SIGMA or TIMEX digital image, following the maximum backscatter intensity along the feature of interest; the detector results were found to compare very well with those obtained from a semi-automated `manual' shoreline detection procedure. The automated procedure was tested on video imagery obtained from the eastern part of Ammoudara beach in two 5-day periods, a low wave energy period (6-10 April 2014) and a high wave energy period (1 -5 November 2014). The results showed that, during the high wave energy event, there have been much higher levels of shoreline variance which, however, appeared to be similarly unevenly distributed along the shoreline as that related to the low wave energy event, Shoreline variance `hot spots' were found to be related to the presence/architecture of an offshore submerged shallow beachrock reef, found at a distance of 50-80 m from the shoreline. Hydrodynamic observations during the high wave energy period showed (a) that there is very significant wave energy attenuation by the offshore reef and (b) the generation of significant longshore and rip flows. The study results suggest that the developed methodology can provide a fast, powerful and efficient beach monitoring tool, particularly if combined with pertinent hydrodynamic observations.

Automated brain tumor segmentation in magnetic resonance imaging based on sliding-window technique and symmetry analysis.

PubMed

Lian, Yanyun; Song, Zhijian

2014-01-01

Brain tumor segmentation from magnetic resonance imaging (MRI) is an important step toward surgical planning, treatment planning, monitoring of therapy. However, manual tumor segmentation commonly used in clinic is time-consuming and challenging, and none of the existed automated methods are highly robust, reliable and efficient in clinic application. An accurate and automated tumor segmentation method has been developed for brain tumor segmentation that will provide reproducible and objective results close to manual segmentation results. Based on the symmetry of human brain, we employed sliding-window technique and correlation coefficient to locate the tumor position. At first, the image to be segmented was normalized, rotated, denoised, and bisected. Subsequently, through vertical and horizontal sliding-windows technique in turn, that is, two windows in the left and the right part of brain image moving simultaneously pixel by pixel in two parts of brain image, along with calculating of correlation coefficient of two windows, two windows with minimal correlation coefficient were obtained, and the window with bigger average gray value is the location of tumor and the pixel with biggest gray value is the locating point of tumor. At last, the segmentation threshold was decided by the average gray value of the pixels in the square with center at the locating point and 10 pixels of side length, and threshold segmentation and morphological operations were used to acquire the final tumor region. The method was evaluated on 3D FSPGR brain MR images of 10 patients. As a result, the average ratio of correct location was 93.4% for 575 slices containing tumor, the average Dice similarity coefficient was 0.77 for one scan, and the average time spent on one scan was 40 seconds. An fully automated, simple and efficient segmentation method for brain tumor is proposed and promising for future clinic use. Correlation coefficient is a new and effective feature for tumor location.