An automated method for the selection of complex railway lines that accounts for multiple feature constraints

2019 ◽  
Vol 23 (6) ◽  
pp. 1296-1316
Author(s):  
Chengming Li ◽  
Xiaoli Liu ◽  
Wei Wu ◽  
Pengda Wu
Keyword(s):  
Automated Method ◽  
Multiple Feature ◽  
Feature Constraints ◽  
Selection Of

A fully automated method for late ventricular diastole frame selection in post-dive echocardiography without ECG gating

2021 ◽  
pp. 73-80
Author(s):  
Eric Markley ◽  
◽  
David Q. Le ◽  
Peter Germonpré ◽  
Costantino Balestra ◽  
...  
Keyword(s):  
Field Experiments ◽  
High Reliability ◽  
Rater Bias ◽  
Algorithm Performance ◽  
Frame Selection ◽  
Automated Method ◽  
Significant Difference ◽  
Computer Automation ◽  
Decompression Stress ◽  
Selection Of

Venous gas emboli (VGE) are often quantified as a marker of decompression stress on echocardiograms. Bubble-counting has been proposed as an easy to learn method, but remains time-consuming, rendering large dataset analysis impractical. Computer automation of VGE counting following this method has therefore been suggested as a means to eliminate rater bias and save time. A necessary step for this automation relies on the selection of a frame during late ventricular diastole (LVD) for each cardiac cycle of the recording. Since electrocardiograms (ECG) are not always recorded in field experiments, here we propose a fully automated method for LVD frame selection based on regional intensity minimization. The algorithm is tested on 20 previously acquired echocardiography recordings (from the original bubble-counting publication), half of which were acquired at rest (Rest) and the other half after leg flexions (Flex). From the 7,140 frames analyzed, sensitivity was found to be 0.913 [95% CI: 0.875-0.940] and specificity 0.997 [95% CI: 0.996-0.998]. The method’s performance is also compared to that of random chance selection and found to perform significantly better (p<0.0001). No trend in algorithm performance was found with respect to VGE counts, and no significant difference was found between Flex and Rest (p>0.05). In conclusion, full automation of LVD frame selection for the purpose of bubble counting in post-dive echocardiography has been established with excellent accuracy, although we caution that high quality acquisitions remain paramount in retaining high reliability.

scholarly journals Ruler Detection for Autoscaling Forensic Images

2014 ◽  
Vol 6 (1) ◽  
pp. 9-27 ◽  
Author(s):  
Abhir Bhalerao ◽  
Gregory Reynolds
Keyword(s):  
Spectral Analysis ◽  
Image Segmentation ◽  
Crime Scene ◽  
Poor Quality ◽  
Fingerprint Matching ◽  
Standard Measurement ◽  
Automated Method ◽  
Manual Selection ◽  
Measurement Units ◽  
Selection Of

The assessment of forensic photographs often requires the calibration of the resolution of the image so that accurate measurements can be taken of crime-scene exhibits or latent marks. In the case of latent marks, such as fingerprints, image calibration to a given dots-per-inch is a necessary step for image segmentation, preprocessing, extraction of feature minutiae and subsequent fingerprint matching. To enable scaling, such photographs are taken with forensic rulers in the frame so that image pixel distances can be converted to standard measurement units (metric or imperial). In forensic bureaus, this is commonly achieved by manual selection of two or more points on the ruler within the image, and entering the units of the measure distance. The process can be laborious and inaccurate, especially when the ruler graduations are indistinct because of poor contrast, noise or insufficient resolution. Here the authors present a fully automated method for detecting and estimating the direction and graduation spacing of rulers in forensic photographs. The method detects the location of the ruler in the image and then uses spectral analysis to estimate the direction and wavelength of the ruler graduations. The authors detail the steps of the algorithm and demonstrate the accuracy of the estimation on both a calibrated set of test images and a wide collection of good and poor quality crime-scene images. The method is shown to be fast and accurate and has wider application in other imaging disciplines, such as radiography, archaeology and surveying.

Automation of Methods for Meat and Meat Products. I. Determination of Protein

1970 ◽  
Vol 53 (5) ◽  
pp. 907-910 ◽  
Author(s):  
Jon E Mcneal ◽  
Albert Karasz ◽  
Elmer George
Keyword(s):  
Meat Products ◽  
Automated Method ◽  
Kjeldahl Method ◽  
Standards Development ◽  
Meat Samples ◽  
Selection Of

Abstract An automated method for the analysis of protein in meat was studied. The investigation included selection of proper standards, development of a method for presolubilizing meat samples for presentation to the AutoAnalyzer, and the construction of AutoAnalyzer manifolds to give protein results comparable to those obtained by the official AOAC Kjeldahl method. The method was found to be applicable to meat and meat products ranging from 5 to 25% protein.

scholarly journals EPOS: EEG Processing Open-Source Scripts

2021 ◽  
Vol 15 ◽  
Author(s):  
Johannes Rodrigues ◽  
Martin Weiß ◽  
Johannes Hewig ◽  
John J. B. Allen
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Degrees Of Freedom ◽  
Automated Analysis ◽  
Eeg Analysis ◽  
Automated Method ◽  
Replication Crisis ◽  
Complete Procedure ◽  
Automated Pipeline ◽  
Selection Of

BackgroundSince the replication crisis, standardization has become even more important in psychological science and neuroscience. As a result, many methods are being reconsidered, and researchers’ degrees of freedom in these methods are being discussed as a potential source of inconsistencies across studies.New MethodWith the aim of addressing these subjectivity issues, we have been working on a tutorial-like EEG (pre-)processing pipeline to achieve an automated method based on the semi-automated analysis proposed by Delorme and Makeig.ResultsTwo scripts are presented and explained step-by-step to perform basic, informed ERP and frequency-domain analyses, including data export to statistical programs and visual representations of the data. The open-source software EEGlab in MATLAB is used as the data handling platform, but scripts based on code provided by Mike Cohen (2014) are also included.Comparison with existing methodsThis accompanying tutorial-like article explains and shows how the processing of our automated pipeline affects the data and addresses, especially beginners in EEG-analysis, as other (pre)-processing chains are mostly targeting rather informed users in specialized areas or only parts of a complete procedure. In this context, we compared our pipeline with a selection of existing approaches.ConclusionThe need for standardization and replication is evident, yet it is equally important to control the plausibility of the suggested solution by data exploration. Here, we provide the community with a tool to enhance the understanding and capability of EEG-analysis. We aim to contribute to comprehensive and reliable analyses for neuro-scientific research.

scholarly journals Best-Quality Vessel Identification Using Vessel Quality Measure in Multiple-Phase Coronary CT Angiography

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Lubomir Hadjiiski ◽  
Jordan Liu ◽  
Heang-Ping Chan ◽  
Chuan Zhou ◽  
Jun Wei ◽  
...  
Keyword(s):  
Ct Angiography ◽  
Coronary Ct Angiography ◽  
Quality Measure ◽  
Arterial Tree ◽  
Coronary Ct ◽  
Automated Method ◽  
Multiple Phase ◽  
Preference Study ◽  
Selection Of

The detection of stenotic plaques strongly depends on the quality of the coronary arterial tree imaged with coronary CT angiography (cCTA). However, it is time consuming for the radiologist to select the best-quality vessels from the multiple-phase cCTA for interpretation in clinical practice. We are developing an automated method for selection of the best-quality vessels from coronary arterial trees in multiple-phase cCTA to facilitate radiologist’s reading or computerized analysis. Our automated method consists of vessel segmentation, vessel registration, corresponding vessel branch matching, vessel quality measure (VQM) estimation, and automatic selection of best branches based on VQM. For every branch, the VQM was calculated as the average radial gradient. An observer preference study was conducted to visually compare the quality of the selected vessels. 167 corresponding branch pairs were evaluated by two radiologists. The agreement between the first radiologist and the automated selection was 76% with kappa of 0.49. The agreement between the second radiologist and the automated selection was also 76% with kappa of 0.45. The agreement between the two radiologists was 81% with kappa of 0.57. The observer preference study demonstrated the feasibility of the proposed automated method for the selection of the best-quality vessels from multiple cCTA phases.

scholarly journals EXPERIMENTAL STUDIES OF BENDING CHARACTERISTICS FOR SELECTION OF MODERN OF STIFFENING FABRICS

2021 ◽  
Vol 52 (2) ◽  
pp. 33-37
Author(s):  
Veronika V. Zamyshlyaeva ◽  
Tat’yana L. Akindinova
Keyword(s):  
Reference Data ◽  
Experimental Studies ◽  
Structure Stability ◽  
Technological Properties ◽  
Shape Stability ◽  
High Quality ◽  
Automated Method ◽  
Bending Process ◽  
The Difference ◽  
Selection Of

The article presents the results of studies of the bending characteristics of modern stiffening fabrics of different fibrous composition. The studies were carried out by an automated method that allows im-plementing a graphical record of the bending process and recovery after bending using specially developed software. The method allows determining not only standard, but also new bending characteristics. New quality indicators, which determine the ability of stiffening fabrics to be processed into high-quality stiffening pads and allow assessing the garment shape stability during operation, are proposed. The expediency of experimental evaluation of these indicators for the modern range of stiffening fabrics is established. The reference data on indicators of technological properties of stiffening fabrics allowing digitalising selection is given. A new algorithm for the rational choice of shape-stable fabrics is proposed, focused on new characteristics of bending – the structure stability coefficient and the difference in work.

scholarly journals Automated identification of implausible values in growth data from pediatric electronic health records

2017 ◽  
Vol 24 (6) ◽  
pp. 1080-1087 ◽  
Author(s):  
Carrie Daymont ◽  
Michelle E Ross ◽  
A Russell Localio ◽  
Alexander G Fiks ◽  
Richard C Wasserman ◽  
...  
Keyword(s):  
Primary Care ◽  
Moving Average ◽  
Standard Deviation Score ◽  
Growth Data ◽  
Automated Identification ◽  
Automated Method ◽  
Primary Care Site ◽  
Electronic Health ◽  
Weighted Moving Average ◽  
Selection Of

Abstract Objective Large electronic health record (EHR) datasets are increasingly used to facilitate research on growth, but measurement and recording errors can lead to biased results. We developed and tested an automated method for identifying implausible values in pediatric EHR growth data. Materials and Methods Using deidentified data from 46 primary care sites, we developed an algorithm to identify weight and height values that should be excluded from analysis, including implausible values and values that were recorded repeatedly without remeasurement. The foundation of the algorithm is a comparison of each measurement, expressed as a standard deviation score, with a weighted moving average of a child’s other measurements. We evaluated the performance of the algorithm by (1) comparing its results with the judgment of physician reviewers for a stratified random selection of 400 measurements and (2) evaluating its accuracy in a dataset with simulated errors. Results Of 2 000 595 growth measurements from 280 610 patients 1 to 21 years old, 3.8% of weight and 4.5% of height values were identified as implausible or excluded for other reasons. The proportion excluded varied widely by primary care site. The automated method had a sensitivity of 97% (95% confidence interval [CI], 94–99%) and a specificity of 90% (95% CI, 85–94%) for identifying implausible values compared to physician judgment, and identified 95% (weight) and 98% (height) of simulated errors. Discussion and Conclusion This automated, flexible, and validated method for preparing large datasets will facilitate the use of pediatric EHR growth datasets for research.

Diagnostics of trichinosis in the early stages of larval development

2016 ◽  
Vol 3 (1) ◽  
pp. 58-66
Author(s):  
Скворцова ◽  
F. Skvortsova ◽  
Успенский ◽  
A. Uspenskiy
Keyword(s):  
Early Diagnosis ◽  
Muscle Tissue ◽  
Morphological Development ◽  
Main Mass ◽  
Automated Method ◽  
Research Material ◽  
Hindlimb Muscle ◽  
Successful Infection ◽  
White Mongrel ◽  
Selection Of

Objective of research. The purpose of the study is the Confirmation of the diagnosis of trichinosis depends on many factors, among which is the sampling of muscle tissue from some of the most infested parts of the carcass, method of research and the equipment used. Materials and methods. The research material were samples of muscle tissue from experimentally T. spiralis infected rats. Was infected 18 white mongrel rats weighing 90-100g at a dose of 10 l/G. For the early diagnosis of trichinosis when the rats were killed with 6 to day 24 after infection. First investigated by the compressor method available and the most affected muscles: the diaphragm, masseter and chest muscles by increasing (x 25, 50, 100). Each term is made photomicrographs of larvae on the slices. Then the samples of the hindlimb muscle mass of 50 g was investigated by automated method of peptonize apparatus Gastros. At the end of the cycle of operation of the apparatus when microscopy was considered the quantity of larvae and their morphological development. Selected larvae 16 to 18 days of age have been infected mice (bioassay). After 35-36 days carcass mice were fully exposed topatolisfor the detection of Trichinella spp. Results and discussion. When peptonize automated method muscle tissue of rats infected with larvae of T. spiralis, found that larvae aged from 10 to 15 days after infection by the method are not detected. Trichinae isolated from 16-day-old, identified by microscopy, despite the lack of size of the larvae. The massive selection of Trichinella spp. begins with the 17th day after infection, when most of the larvae reaches invasionist. Non-encapsulated trichinae 16 days of age become invasive, which showed successful infection of white mice with larvae that are highlighted after peptonize. According to the results of a biosample main mass of larvae becomes infective to 19-20 days after infection. Thus, an automated method of peptonize muscle tissue easily diagnose the infection of animals with non-encapsulated larvae of Trichinella spp. that are difficult or sometimes impossible in compressor research. Diagnosis of trichinosis by automated method is most effective when the larvae of invasionist.

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