scholarly journals Minimally Interactive Knowledge-based Coronary Tracking in CTA using a Minimal Cost Path

2008 ◽  
Author(s):  
Karl Krissian ◽  
Hrvoje Bogunovic ◽  
Hrvoje Bogunovic ◽  
Jose Maria Pozo ◽  
Maria Cruz Villa-Uriol ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Cost Function ◽  
Region Of Interest ◽  
Feature Space ◽  
Coronary Vessel ◽  
Minimal Cost ◽  
End Point ◽  
Knowledge Based ◽  
Starting Point ◽  
Tracking Ability

An algorithm for minimally interactive coronary artery tracking is presented. Tracking ability and accuracy results are demonstrated on 16 images CTA images. First, a region of interest is automatically selected and a denoising filter applied. Then, for each voxel the probability of belonging to a coronary vessel is estimated from a feature space and a vesselness measure is used to obtain a cost function. The vessel starting point is obtained automatically, while the end point is provided by the user. Finally, the centerline is obtained as the minimal cost path between both points.

scholarly journals Two Point Minimum Cost Path Approach for CTA Coronary Centerline Extraction

2008 ◽  
Author(s):  
Coert Metz ◽  
Michiel Schaap ◽  
Theo van Walsum ◽  
Wiro Niessen
Keyword(s):  
Coronary Artery ◽  
Minimum Cost ◽  
Window Function ◽  
Minimal Cost ◽  
Centerline Extraction ◽  
End Point ◽  
Coronary Centerline ◽  
Definition Of ◽  
The Cost

In this work a minimum cost path approach is adopted to extract coronary artery centerlines from CTA data. The algorithm depends on the manual definition of the start and end point of the vessel. The cost image used in the minimal cost path approach is based on a vesselness measure and a smooth window function on intensity. In the majority of the cases the method was able to extract the centerlines successfully (overlap > 90%). Accuracy of the method is around two times the voxelsize of the datasets. To conclude, minimum cost path approaches have potential for coronary artery centerline extraction, but improvements, especially regarding the accuracy of the method, still need investigations.

The utility of coronary artery calcium in non-gated high resolution CT thorax scans in predicting cardiac events as compared to the Framingham risk score: a retrospective study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Saluja ◽  
H Contractor ◽  
M Daniells ◽  
J Sobolewska ◽  
K Khan ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Retrospective Study ◽  
Coronary Artery ◽  
Risk Score ◽  
Framingham Risk Score ◽  
Cardiac Events ◽  
End Point ◽  
Framingham Risk ◽  
Good Concordance

Abstract Background There is existing evidence to suggest a correlation between coronary artery calcification (CAC) measured using ECG-triggered chest computed tomography and cardiovascular disease. Further evidence has emerged to suggest a correlation between CAC measured using non-gated CT scans and cardiovascular disease. Herein, we sought to ascertain the utility of incidental findings of CAC on non-triggered high resolution CT (HRCT) thorax used for patients undergoing lung cancer screening or follow-up for interstitial lung disease and Framingham risk score (FRS) in predicting cardiovascular events. Methods The Computerised Radiology Information Service (CRIS) database was manually searched to determine all HRCT scans performed in a single trust from 05/2015 to 05/2016. The reports issued by Radiologists and images of selected studies were reviewed. For patients with CAC, we calculated the calcium score for patients using the Agatston method. Clinical events were determined from the electronic medical record without knowledge of patients' CAC findings. For these patients, the Framingham Risk Score (FRS) was also calculated. The primary end point of the study was composite of all-cause mortality and cardiac events (non-fatal myocardial infarction, coronary revascularization, new atrial fibrillation or heart failure episode requiring hospitalization). Results We selected 300 scans from a total of approximately 2000 scans performed over this time. Data at follow up was available for 100% of the patients, with a median duration of follow up of 1.6 years. Moderate to severe CAC was found in 35% of people. Multivariable analysis showed good concordance between CAC and FRS in predicting composite clinical end point. The Odds Ratio for cardiac events in patients with moderate to severe CAC was 5.3 (p<0.01) and for composite clinical end point was 3.4 (p<0.01). This is similar to the OR predicted by the FRS: 4.8; p<0.01 and 3.1; p<0.01 respectively. Only 6.2% of patients with moderate to severe CAC were currently statin treated. Conclusion In this retrospective study of patients with respiratory disease attending for HRCT scanning, co-incidentally detected CAC predicts cardiac events, with good concordance with the FRS. The incidental finding of CAC on non-gated CT scanning should be reported with Agatston score calculation allowing consideration of intervention to mitigate cardiovascular risk and optimize. Further multi-centre prospective studies of this strategy, with a larger patient cohort should be conducted to clarify the utility of CAC as a prediction tool to modify cardiac risk. Funding Acknowledgement Type of funding source: None

Constrained optimal terrain following/threat avoidance trajectory planning using network flow

2014 ◽  
Vol 118 (1203) ◽  
pp. 523-539 ◽  
Author(s):  
R. Zardashti ◽  
A. A. Nikkhah ◽  
M. J. Yazdanpanah
Keyword(s):  
Cost Function ◽  
Trajectory Planning ◽  
Network Flow ◽  
Equations Of Motion ◽  
Minimum Cost ◽  
Masking Effect ◽  
Search Problem ◽  
Starting Point ◽  
Terrain Following ◽  
Threat Avoidance

AbstractThis paper focuses on the trajectory planning for a UAV on a low altitude terrain following/threat avoidance (TF/TA) mission. Using a grid-based approximated discretisation scheme, the continuous constrained optimisation problem into a search problem is transformed over a finite network. A variant of the Minimum Cost Network Flow (MCNF) to this problem is then applied. Based on using the Digital Terrain Elevation Data (DTED) and discrete dynamic equations of motion, the four-dimensional (4D) trajectory (three spatial and one time dimensions) from a starting point to an end point is obtained by minimising a cost function subject to dynamic and mission constraints of the UAV. For each arc in the grid, a cost function is considered as the combination of the arc length, fuel consumption and flight time. The proposed algorithm which considers dynamic and altitude constraints of the UAV explicitly is then used to obtain the feasible trajectory. The resultant trajectory can increase the survivability of the UAV using the threat region avoidance and the terrain masking effect. After obtaining the feasible trajectory, an improved algorithm is proposed to smooth the trajectory. The numeric results are presented to verify the capability of the proposed approach to generate admissible trajectory in minimum possible time in comparison to the previous works.

A Collaborative Approach for Minimal-Cost Monitor Deployment in Cloud Environment

2015 ◽  
Vol 25 (06) ◽  
pp. 935-960
Author(s):  
Yuan-Hsin Tung ◽  
Shian-Shyong Tseng ◽  
Wei-Tek Tsai
Keyword(s):  
Approximate Solutions ◽  
Relationship Matrix ◽  
Minimal Cost ◽  
Cloud Environment ◽  
Cloud Infrastructure ◽  
Domain Experts ◽  
Knowledge Based ◽  
Expert Opinions ◽  
Service Oriented ◽  
System Maintenance

Monitoring is widely applied in problem diagnosis, fault localization, and system maintenance. And since the cloud infrastructure is complex, the applications on the cloud are therefore complex, which makes monitoring in cloud more difficult. Rich monitors that contain composite and heterogeneous probes are often used in service-oriented system monitoring. These rich monitors often involve multiple entities, and the interpretation may require expert opinions from multiple domains. This paper proposes a knowledge-based collaborative monitoring approach to find out minimal cost monitor deployment in a cloud environment. The approach contains two main phases. In the knowledge acquisition phase, three acquisition tables, monitor-probe relationship matrix, cost of monitoring, and probe-problem dependence matrix, are generated according to diagnosis ontology and monitor ontology acquired from domain experts. And then based upon the three acquisition tables and three consensus building strategies, we formulate the problem of optimizing the cost of monitoring as an Integer Linear Programming (ILP) problem, which is NP-Complete. In the monitor deployment phase, the proposed algorithm applies two heuristic rules to address the problem. Three experiments are conducted to evaluate the performance of the proposed approach. The results from the experiments show that our approach is effective and produce quality approximate solutions in monitor deployment.

scholarly journals Method for determining the kinematic parameters of the vertical rotor blades for the destruction of the tuberous layer

2020 ◽  
pp. 82-90
Author(s):  
V. A. Volsky V. A. ◽  
V. S. Bonchik
Keyword(s):  
Hydraulic Drive ◽  
Extreme Points ◽  
Geometric Shape ◽  
Kinematic Parameters ◽  
End Points ◽  
End Point ◽  
Vertical Rotor ◽  
Starting Point ◽  
The Absolute ◽  
Angle Of Rotation

Annotation Purpose. Development of a technique for determining the velocities of collision of the blades with the tuberous layer, the trajectory of movement, the magnitude and direction of the velocities of the most characteristic points. Methods. The research was carried out using the basic provisions of theoretical mechanics, statistics, probability theory, methods of differential calculations, mathematical modeling and applied programming. The studies were carried out on a specially designed laboratory installation using a vertical rotor hydraulic drive and strain gauge equipment mounted on a tractor, as well as a set of variable connecting plates for setting the machine operating modes. Results. The calculations of the absolute collision velocities of the blades of the lower and upper beaters of the vertical rotor at the start and end points, respectively, are performed. The geometric shape of the working surfaces and the direction of rotation for the extreme points of the outer contours of the blades of the lower and upper beaters of the vertical rotor of the potato harvester are substantiated. Conclusions. Using the above technique, as well as graphical dependences, we calculated the rational kinematic parameters of the blades of the lower and upper beaters of the vertical rotor, respectively, at the start and end points, where the greatest destruction of the tuber layer. For the lower beater blade, the absolute collision speed at the angle of rotation ωнt = 120° at the starting point = 1.6 m/s, at the end point – = 1.94 m/s. For the upper beater blade, the absolute collision speed at the angle of rotation ωвt = 120° at the starting point = 1.4 m/s, at the end point – = 1.92 m/s. Therefore, according to the specified rational kinematic parameters of the blades of the lower and upper beaters of the vertical rotor, it is possible to design the geometric shape of the surfaces of the crushing working bodies of potato harvesters. Keywords: blade, breaking surface, breasts, potatoes.

Preoperative plasma fibrinogen levels predict mortality after coronary artery bypass grafting

2003 ◽  
Vol 89 (05) ◽  
pp. 885-891 ◽  
Author(s):  
Daniel Robinson ◽  
Volker Kleine ◽  
Sabine Hertwig ◽  
Christian Schwahn ◽  
Rita Grimm ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Coronary Artery Bypass ◽  
Artery Bypass ◽  
Bypass Graft ◽  
Multivariable Analysis ◽  
Myocardial Revascularization ◽  
Total Mortality ◽  
Plasma Fibrinogen ◽  
Entire Cohort ◽  
End Point

SummaryThis study was designed to investigate whether plasma fibrinogen levels as well as the β-fibrinogen –455 G/A genotype are associated with outcome after coronary artery bypass graft (CABG) operation.We enrolled 249 consecutive CAD patients one day before they underwent a CABG operation. Data from 220 patients with available plasma fibrinogen levels were analyzed. The primary end-point was total mortality, the secondary end-point mortality from cardiac causes or the need for myocardial revascularization. The 2-year total mortality was 9.1% in the entire cohort. Multivariable analysis revealed an independent relationship between the primary end-point and preoperative plasma fibrinogen levels but not the β-fibrinogen –455 G/A geno-type. Neither preoperative plasma fibrinogen levels nor the β-fibrinogen –455 G/A genotype could predict the secondary end-point.We conclude, that elevated preoperative plasma fibrinogen levels, but not the β-fibrinogen -455 G/A genotype predict the total mortality after CABG operation.

scholarly journals Flood Mapping in Vegetated Areas Using an Unsupervised Clustering Approach on Sentinel-1 and -2 Imagery

2020 ◽  
Vol 12 (21) ◽  
pp. 3611
Author(s):  
Lisa Landuyt ◽  
Niko E. C. Verhoest ◽  
Frieke M. B. Van Coillie
Keyword(s):  
Optimal Parameter ◽  
Complex Mixture ◽  
Region Of Interest ◽  
Region Growing ◽  
Feature Space ◽  
Flood Mapping ◽  
Dry Land ◽  
Object Based ◽  
Forested Areas ◽  
Sar Imagery

The European Space Agency’s Sentinel-1 constellation provides timely and freely available dual-polarized C-band Synthetic Aperture Radar (SAR) imagery. The launch of these and other SAR sensors has boosted the field of SAR-based flood mapping. However, flood mapping in vegetated areas remains a topic under investigation, as backscatter is the result of a complex mixture of backscattering mechanisms and strongly depends on the wave and vegetation characteristics. In this paper, we present an unsupervised object-based clustering framework capable of mapping flooding in the presence and absence of flooded vegetation based on freely and globally available data only. Based on a SAR image pair, the region of interest is segmented into objects, which are converted to a SAR-optical feature space and clustered using K-means. These clusters are then classified based on automatically determined thresholds, and the resulting classification is refined by means of several region growing post-processing steps. The final outcome discriminates between dry land, permanent water, open flooding, and flooded vegetation. Forested areas, which might hide flooding, are indicated as well. The framework is presented based on four case studies, of which two contain flooded vegetation. For the optimal parameter combination, three-class F1 scores between 0.76 and 0.91 are obtained depending on the case, and the pixel- and object-based thresholding benchmarks are outperformed. Furthermore, this framework allows an easy integration of additional data sources when these become available.

scholarly journals Quasi-static ensemble variational data assimilation: a theoretical and numerical study with the iterative ensemble Kalman smoother

2018 ◽  
Vol 25 (2) ◽  
pp. 315-334 ◽  
Author(s):  
Anthony Fillion ◽  
Marc Bocquet ◽  
Serge Gratton
Keyword(s):  
Data Assimilation ◽  
Cost Function ◽  
Global Minimum ◽  
Numerical Study ◽  
Variational Data Assimilation ◽  
Kalman Smoother ◽  
Local Extrema ◽  
Starting Point ◽  
The Cost ◽  
Temporal Extent

Abstract. The analysis in nonlinear variational data assimilation is the solution of a non-quadratic minimization. Thus, the analysis efficiency relies on its ability to locate a global minimum of the cost function. If this minimization uses a Gauss–Newton (GN) method, it is critical for the starting point to be in the attraction basin of a global minimum. Otherwise the method may converge to a local extremum, which degrades the analysis. With chaotic models, the number of local extrema often increases with the temporal extent of the data assimilation window, making the former condition harder to satisfy. This is unfortunate because the assimilation performance also increases with this temporal extent. However, a quasi-static (QS) minimization may overcome these local extrema. It accomplishes this by gradually injecting the observations in the cost function. This method was introduced by Pires et al. (1996) in a 4D-Var context. We generalize this approach to four-dimensional strong-constraint nonlinear ensemble variational (EnVar) methods, which are based on both a nonlinear variational analysis and the propagation of dynamical error statistics via an ensemble. This forces one to consider the cost function minimizations in the broader context of cycled data assimilation algorithms. We adapt this QS approach to the iterative ensemble Kalman smoother (IEnKS), an exemplar of nonlinear deterministic four-dimensional EnVar methods. Using low-order models, we quantify the positive impact of the QS approach on the IEnKS, especially for long data assimilation windows. We also examine the computational cost of QS implementations and suggest cheaper algorithms.

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