scholarly journals Combining images and anatomical knowledge to improve automated vein segmentation in MRI

2017 ◽  
Author(s):  
Phillip G. D. Ward ◽  
Nicholas J. Ferris ◽  
Parnesh Raniga ◽  
David L. Dowe ◽  
Amanda C. L. Ng ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Anatomical Location ◽  
Automated Segmentation ◽  
Data Set ◽  
Common Space ◽  
Cohen’S D ◽  
Performance Metric ◽  
Susceptibility Maps ◽  
Cohen's D ◽  
Better Than

AbstractPurposeTo improve the accuracy of automated vein segmentation by combining susceptibility-weighted images (SWI), quantitative susceptibility maps (QSM), and a vein atlas to produce a resultant image called a composite vein image (CV image).MethodAn atlas was constructed in common space from 1072 manually traced 2D-slices. The composite vein image was derived for each subject as a weighted sum of three inputs; a SWI image, a QSM image and the vein atlas. The weights for each input and each anatomical location, called template priors, were derived by assessing the accuracy of each input over an independent data set. The accuracy of venograms derived automatically from each of the CV image, SWI, and QSM image sets was assessed by comparison with manual tracings. Three different automated vein segmentation techniques were used, and ten performance metrics evaluated.ResultsVein segmentations using the CV image were comprehensively better than those derived from SWI or QSM images (mean Cohen’s d = 1.1). Sixty permutations of performance metric and automated segmentation technique were evaluated. Vein identification improvements that were both large and significant (Cohen’s d>0.80, p<0.05) were found in 77% of the permutations, compared to no improvement in 5%.ConclusionThe accuracy of automated venograms derived from the composite vein image was overwhelmingly superior to venograms derived from SWI or QSM alone.

The Italian Spine Youth Quality of Life questionnaire measures health-related quality of life of adolescents with spinal deformities better than the reference standard, the Scoliosis Research Society 22 questionnaire

2019 ◽  
Vol 33 (8) ◽  
pp. 1404-1415 ◽  
Author(s):  
Antonio Caronni ◽  
Sabrina Donzelli ◽  
Fabio Zaina ◽  
Stefano Negrini
Keyword(s):  
Quality Of Life ◽  
Research Society ◽  
Spinal Deformities ◽  
Scoliosis Research Society ◽  
Cohen’S D ◽  
Related Quality ◽  
Health Related ◽  
Cohen's D ◽  
Better Than

Objective: To compare the validity of the Italian Spine Youth Quality of Life (ISYQOL) questionnaire with that of the Scoliosis Research Society 22 (SRS22) questionnaire, the criterion standard for health-related quality of life (HRQOL) measurement in adolescents with spinal deformities. Design: Cross-sectional study. Setting: Outpatient clinic. Subjects: Consecutive adolescents (10–18 years; 541 wearing brace) affected by idiopathic scoliosis (642 females, 100 males) or hyperkyphosis (87 females, 109 males). Interventions: NA. Main measures: The Spearman’s correlation coefficient (rho) between ISYQOL and SRS22 was used to assess ISYQOL concurrent validity. Sex, age, severity, bracing, trunk appearance and deformity type were assessed for known-groups validity. Cohen’s d quantified between-groups differences. Multiple linear regression exploring the effect of sex, age, body mass index (BMI), severity, bone age, trunk appearance, physiotherapy, bracing and sport on HRQOL of scoliosis patients was used to assess concurrent validity further. Results: Satisfactory correlations were found between ISYQOL and SRS22 (scoliosis, rho = 0.71; kyphosis, rho = 0.56). Known-groups validity analysis showed that ISYQOL detects all the between-groups differences detected by SRS22 and a males-females difference undetected by SRS22. ISYQOL Cohen’s d was larger than SRS22 Cohen’s d in three between-groups comparisons and similar in the others. Brace, sport and scoliosis severity were independently related to ISYQOL (linear regression: R2 = 0.23; p < 0.001). Brace, sport and physiotherapy were related to SRS22 ( R2 = 0.17). Conclusions: ISYQOL showed high validity when used to measure HRQOL in adolescents with spinal deformities. Moreover, ISYQOL performs better than SRS22, having better known-groups validity and (contrary to SRS22) detecting the impact of disease severity on HRQOL.

Case Study using Probe Vehicle Speeds to Assess Roadway Safety in Georgia

2020 ◽  
Vol 2674 (11) ◽  
pp. 554-562
Author(s):  
David J. Ederer ◽  
Michael O. Rodgers ◽  
Michael P. Hunter ◽  
Kari E. Watkins
Keyword(s):  
Performance Monitoring ◽  
Negative Binomial ◽  
Performance Metrics ◽  
Large Body ◽  
Vehicle Speed ◽  
Crash Frequency ◽  
Data Set ◽  
Probe Vehicle ◽  
Performance Metric ◽  
The Relationship

Speed is a primary risk factor for road crashes and injuries. Previous research has attempted to ascertain the relationship between individual vehicle speeds, aggregated speeds, and crash frequency on roadways. Although there is a large body of research linking vehicle speeds to safety outcomes, there is not a widely applied performance metric for safety based on regularly reported speeds. With the increasingly widespread availability of probe vehicle speed data, there is an opportunity to develop network-level safety performance metrics. This analysis examined the relationship between percentile speeds and crashes on a principal arterial in Metropolitan Atlanta. This study used data from the National Performance Metric Research Data Set (NPMRDS), the Georgia Electronic Accident Reporting System, and the Highway Performance Monitoring System. Negative binomial regression models were used to analyze the relationship between speed percentiles, and speed differences to crash frequency on roadway sections. Results suggested that differences in speed percentiles, a measure of speed dispersion, are related to the frequency of crashes. Based on the models, the difference in the 85th percentile and median speed is proposed as a performance metric. This difference is easily measured using NPMRDS probe vehicle speeds, and provides a practical performance metric for assessing safety on roadways.

Wall Drop Punt Kick & Catch: Contributions towards the creation of a new gross manipulative coordination test

2021 ◽  
pp. 174795412110375
Author(s):  
Rui Matos ◽  
Diogo Monteiro ◽  
Ricardo Rebelo-Gonçalves ◽  
Luís Coelho ◽  
Rogério Salvador ◽  
...  
Keyword(s):  
Effect Sizes ◽  
Front Wall ◽  
Motor Competence ◽  
Cohen’S D ◽  
Coordination Test ◽  
D Values ◽  
Competence Test ◽  
Cohen's D ◽  
Validation Testing ◽  
Better Than

This study aimed to search for age and sex differences on a manipulative eye-segmental (hand and foot) coordination task. It represents the first step towards a possible creation of a manipulative eye-hand and eye-foot coordination test that may be used in motor competence test batteries. One hundred and sixty-eight children (85 boys and 83 girls), with a mean age of 12.79 years old (±1.56) were assessed. Subjects had 30 seconds to achieve as many ball impacts as possible on a front wall (two meters apart), following a drop punt kick, rebound on the wall and catch sequence. Compared to girls’, boys’ performance was significantly better (p < .001) on each studied age (10, 11, 13 and 14), with large effect sizes (all four Cohen’s d values over 1.30). Besides, 10 and 11 years-old subjects’ performance, both in boys and in girls, was significantly lower than their 13 and 14 years-old subjects’ counterparts (p < .001, except for the comparison between 13 and 14 years-old subjects, on girls, where p < .01). All related effect sizes were large (all Cohen’s d values over 1.03). Results confirm literature, as boys’ performance on this manipulative task was significantly better than girls’ one. The results seem to be promising about the possible use of the task in question as an eye-hand and eye-foot coordination test in future. Further research needs to be performed, namely aiming its validation (testing its reliability and concurrent validity).

scholarly journals Sprinting with prosthetic versus biological legs: insight from experimental data

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Owen N. Beck ◽  
Paolo Taboga ◽  
Alena M. Grabowski
Keyword(s):  
Experimental Data ◽  
Aerobic Capacity ◽  
Performance Metrics ◽  
Maximum Velocity ◽  
Running Performance ◽  
Unfair Advantage ◽  
Performance Metric ◽  
The World ◽  
World Class ◽  
Better Than

Running-prostheses have enabled exceptional athletes with bilateral leg amputations to surpass Olympic 400 m athletics qualifying standards. Due to the world-class performances and relatively fast race finishes of these athletes, many people assume that running-prostheses provide users an unfair advantage over biologically legged competitors during long sprint races. These assumptions have led athletics governing bodies to prohibit the use of running-prostheses in sanctioned non-amputee (NA) competitions, such as at the Olympics. However, here we show that no athlete with bilateral leg amputations using running-prostheses, including the fastest such athlete, exhibits a single 400 m running performance metric that is better than those achieved by NA athletes. Specifically, the best experimentally measured maximum running velocity and sprint endurance profile of athletes with prosthetic legs are similar to, but not better than those of NA athletes. Further, the best experimentally measured initial race acceleration (from 0 to 20 m), maximum velocity around curves, and velocity at aerobic capacity of athletes with prosthetic legs were 40%, 1–3% and 19% slower compared to NA athletes, respectively. Therefore, based on these 400 m performance metrics, use of prosthetic legs during 400 m running races is not unequivocally advantageous compared to the use of biological legs.

Phonologische Verarbeitung bei Grundschulkindern mit schwacher Lesefähigkeit

2013 ◽  
Vol 2 (4) ◽  
pp. 199-215 ◽  
Author(s):  
Maria Klatte ◽  
Claudia Steinbrink ◽  
Kirstin Bergström ◽  
Thomas Lachmann
Keyword(s):  
Cohen’S D ◽  
Phonologische Verarbeitung ◽  
Cohen's D

Defizite in der phonologischen Informationsverarbeitung werden heute als Kernsymptom der Lese-Rechtschreibstörung betrachtet. In Trainingsstudien mit betroffenen Kindern erwiesen sich Phonemwahrnehmungsfähigkeiten als trainierbar, und Programme, in denen Aufgaben zur phonologischen Bewusstheit mit der systematischen Vermittlung von Phonem-Graphem-Zuordnungen kombiniert wurden, zeigten Transfereffekte auf Lese- und Rechtschreibleistungen. Ausgehend von diesen Erkenntnissen wurde ein computerbasiertes Trainingsprogramm zur Förderung der Phonemwahrnehmung, der phonologischen Bewusstheit und der Graphem-Phonem-Zuordnungen für deutschsprachige Grundschulkinder mit Lese-Rechtschreibstörung entwickelt. Aufgrund der besonderen Relevanz der Vokallänge für die deutsche Orthographie enthält das Programm neben Aufgaben, die auf Konsonanten fokussieren, auch Vokallängenaufgaben. Bei der Konzipierung des Programms wurden etablierte, ursprünglich für andere Sprachen entwickelte Aufgaben an die deutsche Phonologie angepasst und in ein computerbasiertes Format übersetzt. Im Rahmen der vorliegenden Studie sollte überprüft werden, ob die konstruierten Trainingsaufgaben die spezifischen Defizite von Kindern mit Lese-Rechtschreibstörung wie intendiert abbilden. Hierzu wurden leseschwache Dritt- und Viertklässler (n = 35) mit mindestens durchschnittlichen Lesern derselben Klassenstufen (n = 75; Kontrollgruppe) hinsichtlich ihrer Leistungen in den Aufgaben verglichen. Die leseschwachen Kinder zeigten in allen Aufgaben schlechtere Leistungen als die Kontrollgruppe. Die Effektstärken der Gruppenunterschiede (Cohen's d) lagen im mittleren bis hohen Bereich (0.50 – 2.19). Die Ergebnisse bestätigen, dass die Aufgaben des Trainingsprogramms die spezifischen Defizite leseschwacher Kinder abbilden. Ein Training mit diesen Aufgaben erscheint daher grundsätzlich sinnvoll. Die Wirkungen eines solchen Trainings auf die schriftsprachlichen Leistungen von Kindern mit Lese-Rechtschreibstörung werden in zukünftigen Studien überprüft.

Political Inclusion Reduces Political Prejudice

2019 ◽  
Author(s):  
Jan G. Voelkel ◽  
Dongning Ren ◽  
Mark John Brandt
Keyword(s):  
The Political ◽  
Political Discussion ◽  
Total N ◽  
Cohen’S D ◽  
Promising Strategy ◽  
Political Inclusion ◽  
Cohen's D ◽  
Political Divide ◽  
Scenario Study ◽  
Fair Chance

The political divide is characterized by liberals and conservatives who hold strong prejudice against each other. Here we introduce one possible strategy for reducing political prejudice: political inclusion. We define political inclusion as receiving a fair chance to voice one’s opinions in a discussion of political topics with political outgroup members. This strategy may reduce political prejudice by inducing perceptions of the political outgroup as fair and respectful; however, such a strategy may also highlight conflicting attitudes and worldviews, thereby further exacerbating prejudice. In three preregistered studies (total N = 799), we test if political inclusion reduces or increases prejudice toward the political outgroup. Specifically, political inclusion was manipulated with either an imagined scenario (Study 1) or a concurrent experience in an ostensible online political discussion (Studies 2 &amp; 3). Across all studies, participants who were politically included by political outgroup members reported reduced prejudice toward their outgroup compared to participants in a neutral control condition (Cohen’s d [-0.27, -0.50]). This effect was mediated by perceptions of the political outgroup as fairer and less dissimilar in their worldviews. Our results indicate that political discussions that are politically inclusive do not cause additional prejudice via worldview conflict, but instead give others a feeling of being heard. It is a promising strategy to reduce political prejudice.

Evaluation for estimating of the PDF and the CDF of Generalized Inverted Exponential Distribution with Application in Industry

2020 ◽  
pp. 507-522
Author(s):  
Parisa Torkaman
Keyword(s):  
Least Squares ◽  
Exponential Distribution ◽  
Mean Squared Error ◽  
Weighted Least Squares ◽  
Real Data ◽  
Minimum Variance ◽  
Cumulative Distribution ◽  
Estimation Methods ◽  
Data Set ◽  
Better Than

The generalized inverted exponential distribution is introduced as a lifetime model with good statistical properties. This paper, the estimation of the probability density function and the cumulative distribution function of with five different estimation methods: uniformly minimum variance unbiased(UMVU), maximum likelihood(ML), least squares(LS), weighted least squares (WLS) and percentile(PC) estimators are considered. The performance of these estimation procedures, based on the mean squared error (MSE) by numerical simulations are compared. Simulation studies express that the UMVU estimator performs better than others and when the sample size is large enough the ML and UMVU estimators are almost equivalent and efficient than LS, WLS and PC. Finally, the result using a real data set are analyzed.

A Computational Method for the Identification of Endolysins and Autolysins

2020 ◽  
Vol 27 (4) ◽  
pp. 329-336 ◽  
Author(s):  
Lei Xu ◽  
Guangmin Liang ◽  
Baowen Chen ◽  
Xu Tan ◽  
Huaikun Xiang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Cell Wall ◽  
Experimental Results ◽  
Computational Method ◽  
Lytic Enzyme ◽  
Support Vector ◽  
Lytic Enzymes ◽  
Data Set ◽  
Optimal Feature ◽  
Better Than

Background: Cell lytic enzyme is a kind of highly evolved protein, which can destroy the cell structure and kill the bacteria. Compared with antibiotics, cell lytic enzyme will not cause serious problem of drug resistance of pathogenic bacteria. Thus, the study of cell wall lytic enzymes aims at finding an efficient way for curing bacteria infectious. Compared with using antibiotics, the problem of drug resistance becomes more serious. Therefore, it is a good choice for curing bacterial infections by using cell lytic enzymes. Cell lytic enzyme includes endolysin and autolysin and the difference between them is the purpose of the break of cell wall. The identification of the type of cell lytic enzymes is meaningful for the study of cell wall enzymes. Objective: In this article, our motivation is to predict the type of cell lytic enzyme. Cell lytic enzyme is helpful for killing bacteria, so it is meaningful for study the type of cell lytic enzyme. However, it is time consuming to detect the type of cell lytic enzyme by experimental methods. Thus, an efficient computational method for the type of cell lytic enzyme prediction is proposed in our work. Method: We propose a computational method for the prediction of endolysin and autolysin. First, a data set containing 27 endolysins and 41 autolysins is built. Then the protein is represented by tripeptides composition. The features are selected with larger confidence degree. At last, the classifier is trained by the labeled vectors based on support vector machine. The learned classifier is used to predict the type of cell lytic enzyme. Results: Following the proposed method, the experimental results show that the overall accuracy can attain 97.06%, when 44 features are selected. Compared with Ding's method, our method improves the overall accuracy by nearly 4.5% ((97.06-92.9)/92.9%). The performance of our proposed method is stable, when the selected feature number is from 40 to 70. The overall accuracy of tripeptides optimal feature set is 94.12%, and the overall accuracy of Chou's amphiphilic PseAAC method is 76.2%. The experimental results also demonstrate that the overall accuracy is improved by nearly 18% when using the tripeptides optimal feature set. Conclusion: The paper proposed an efficient method for identifying endolysin and autolysin. In this paper, support vector machine is used to predict the type of cell lytic enzyme. The experimental results show that the overall accuracy of the proposed method is 94.12%, which is better than some existing methods. In conclusion, the selected 44 features can improve the overall accuracy for identification of the type of cell lytic enzyme. Support vector machine performs better than other classifiers when using the selected feature set on the benchmark data set.

scholarly journals Lower Extremity Rehabilitation in Patients with Post-Stroke Sequelae through Virtual Reality Associated with Mirror Therapy

2021 ◽  
Vol 18 (5) ◽  
pp. 2654
Author(s):  
Roxana Steliana Miclaus ◽  
Nadinne Roman ◽  
Ramona Henter ◽  
Silviu Caloian
Keyword(s):  
Virtual Reality ◽  
Muscle Strength ◽  
Lower Extremity ◽  
Range Of Motion ◽  
Control Group ◽  
Mirror Therapy ◽  
Cohen’S D ◽  
Cohen's D ◽  
Experimental Group ◽  
Post Therapy

More innovative technologies are used worldwide in patient’s rehabilitation after stroke, as it represents a significant cause of disability. The majority of the studies use a single type of therapy in therapeutic protocols. We aimed to identify if the association of virtual reality (VR) therapy and mirror therapy (MT) exercises have better outcomes in lower extremity rehabilitation in post-stroke patients compared to standard physiotherapy. Fifty-nine inpatients from 76 initially identified were included in the research. One experimental group (n = 31) received VR therapy and MT, while the control group (n = 28) received standard physiotherapy. Each group performed seventy minutes of therapy per day for ten days. Statistical analysis was performed with nonparametric tests. Wilcoxon Signed-Rank test showed that both groups registered significant differences between pre-and post-therapy clinical status for the range of motion and muscle strength (p < 0.001 and Cohen’s d between 0.324 and 0.645). Motor Fugl Meyer Lower Extremity Assessment also suggested significant differences pre-and post-therapy for both groups (p < 0.05 and Cohen’s d 0.254 for the control group and 0.685 for the experimental group). Mann-Whitney results suggested that VR and MT as a therapeutic intervention have better outcomes than standard physiotherapy in range of motion (p < 0.05, Cohen’s d 0.693), muscle strength (p < 0.05, Cohen’s d 0.924), lower extremity functionality (p < 0.05, Cohen’s d 0.984) and postural balance (p < 0.05, Cohen’s d 0.936). Our research suggests that VR therapy associated with MT may successfully substitute classic physiotherapy in lower extremity rehabilitation after stroke.

scholarly journals An efficient technique for CT scan images classification of COVID-19

2020 ◽  
pp. 1-14
Author(s):  
Esraa Hassan ◽  
Noha A. Hikal ◽  
Samir Elmuogy
Keyword(s):  
Neural Network ◽  
Diagnostic Tool ◽  
Deep Neural Network ◽  
Data Augmentation ◽  
Performance Metrics ◽  
Classification Model ◽  
Data Set ◽  
Training Models ◽  
The Earth ◽  
Diagnostic Time

Nowadays, Coronavirus (COVID-19) considered one of the most critical pandemics in the earth. This is due its ability to spread rapidly between humans as well as animals. COVID_19 expected to outbreak around the world, around 70 % of the earth population might infected with COVID-19 in the incoming years. Therefore, an accurate and efficient diagnostic tool is highly required, which the main objective of our study. Manual classification was mainly used to detect different diseases, but it took too much time in addition to the probability of human errors. Automatic image classification reduces doctors diagnostic time, which could save human’s life. We propose an automatic classification architecture based on deep neural network called Worried Deep Neural Network (WDNN) model with transfer learning. Comparative analysis reveals that the proposed WDNN model outperforms by using three pre-training models: InceptionV3, ResNet50, and VGG19 in terms of various performance metrics. Due to the shortage of COVID-19 data set, data augmentation was used to increase the number of images in the positive class, then normalization used to make all images have the same size. Experimentation is done on COVID-19 dataset collected from different cases with total 2623 where (1573 training,524 validation,524 test). Our proposed model achieved 99,046, 98,684, 99,119, 98,90 In terms of Accuracy, precision, Recall, F-score, respectively. The results are compared with both the traditional machine learning methods and those using Convolutional Neural Networks (CNNs). The results demonstrate the ability of our classification model to use as an alternative of the current diagnostic tool.

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