From Image-Based Modeling to the Modeling of Imaging with the Virtual Population

2016 ◽  
pp. 45-54 ◽  
Author(s):  
Esra Neufeld ◽  
Bryn Lloyd ◽  
Niels Kuster
Keyword(s):  
Image Based Modeling ◽  
Virtual Population

scholarly journals Image-based modeling of acute myocardial ischemia using experimentally derived ischemic zone source representations

2018 ◽  
Vol 51 (4) ◽  
pp. 725-733 ◽  
Author(s):  
B.M. Burton ◽  
K.K. Aras ◽  
W.W. Good ◽  
J.D. Tate ◽  
B. Zenger ◽  
...  
Keyword(s):  
Myocardial Ischemia ◽  
Acute Myocardial Ischemia ◽  
Image Based Modeling

Virtual Population Analysis (VPA) Equations for Nonhomogeneous Populations, and a Family of Approximations Including Improvements on Pope's Cohort Analysis

1986 ◽  
Vol 43 (12) ◽  
pp. 2406-2409 ◽  
Author(s):  
Alec D. MacCall
Keyword(s):  
Mortality Rate ◽  
Population Analysis ◽  
Seasonal Pattern ◽  
Cohort Analysis ◽  
Natural Mortality ◽  
Close Approximation ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Special Case

A set of "backward" virtual population analysis (VPA) equations relates catch (Ct) from continuous fishing between times t and t + 1 to population n size (Nt, Nt+1) when a portion of the stock is unavailable to fishing. The usual VPA equations become a special case where the entire stock is available (i.e. the stock is homogeneous). A close approximation to the VPA equations is Nt = Nt+1 exp(M) + CtM/(1 − exp(−M)), which has properties similar to Pope's "cohort analysis" and is somewhat more accurate in the case of a continuous fishery, especially if the natural mortality rate (M) is large. Much closer simple approximations are possible if the seasonal pattern of catches is known.

Recent methods for image-based modeling and rendering

2003 ◽  
Author(s):  
D. Burschka ◽  
G.D. Hager ◽  
Z. Dodds ◽  
M. Jagersand ◽  
D. Cobzas ◽  
...  
Keyword(s):  
Image Based Modeling

scholarly journals Image-Based Modeling Using Viewpoint Entropy

2002 ◽  
pp. 267-279 ◽  
Author(s):  
Pere-Pau Vázquez ◽  
Miquel Feixast ◽  
Mateu Sbert ◽  
Wolfgang Heidrich
Keyword(s):  
Image Based Modeling ◽  
Viewpoint Entropy

scholarly journals In silico trial of baroreflex activation therapy for the treatment of obesity-induced hypertension

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259917
Author(s):  
John S. Clemmer ◽  
W. Andrew Pruett ◽  
Robert L. Hester
Keyword(s):  
Current Model ◽  
Plasma Renin ◽  
Model Parameters ◽  
Experimental Population ◽  
Baroreflex Activation Therapy ◽  
Virtual Population ◽  
Key Variables ◽  
Activation Therapy ◽  
Antihypertensive Response ◽  
Experimental Findings

Clinical trials evaluating the efficacy of chronic electrical stimulation of the carotid baroreflex for the treatment of hypertension (HTN) are ongoing. However, the mechanisms by which this device lowers blood pressure (BP) are unclear, and it is uncertain which patients are most likely to receive clinical benefit. Mathematical modeling provides the ability to analyze complicated interrelated effects across multiple physiological systems. Our current model HumMod is a large physiological simulator that has been used previously to investigate mechanisms responsible for BP lowering during baroreflex activation therapy (BAT). First, we used HumMod to create a virtual population in which model parameters (n = 335) were randomly varied, resulting in unique models (n = 6092) that we define as a virtual population. This population was calibrated using data from hypertensive obese dogs (n = 6) subjected to BAT. The resultant calibrated virtual population (n = 60) was based on tuning model parameters to match the experimental population in 3 key variables: BP, glomerular filtration rate, and plasma renin activity, both before and after BAT. In the calibrated population, responses of these 3 key variables to chronic BAT were statistically similar to experimental findings. Moreover, blocking suppression of renal sympathetic nerve activity (RSNA) and/or increased secretion of atrial natriuretic peptide (ANP) during BAT markedly blunted the antihypertensive response in the virtual population. These data suggest that in obesity-mediated HTN, RSNA and ANP responses are key factors that contribute to BP lowering during BAT. This modeling approach may be of value in predicting BAT responses in future clinical studies.

scholarly journals Image-Based Modeling from a High -Resolution Route Panorama

2010 ◽  
Vol 9 (1) ◽  
pp. 27-35
Author(s):  
Ryuji Shibata ◽  
Hajime Nagahara
Keyword(s):  
Belief Propagation ◽  
3D Models ◽  
Single Image ◽  
Multiple Viewpoints ◽  
Modeling Methods ◽  
Image Based Modeling ◽  
Spatio Temporal ◽  
Effective Use ◽  
Scene Depth ◽  
Route Panorama

Image-based modeling methods for generating 3D models from an image sequence have been widely studied. Most of these methods, however, require huge redundant spatio-temporal images to estimate scene depth. This is not an effective use of capturing higher resolution texture. On the other hand, a route panorama, which is a continuous panoramic image along a path, is an efficient way of consolidating information from multiple viewpoints into a single image. A route panorama captured by a line camera also has the advantage of capturing higher resolution easily. In this paper, we propose a method for estimating the depth of an image from a route panorama using color drifts. The proposed method detects color drift by deformable window matching of the color channels. It also uses a hierarchical belief propagation to estimate the depth stably and decrease the computation cost thereof.

scholarly journals Computational Eurotransplant kidney allocation simulations demonstrate the feasibility and benefit of T-cell epitope matching

2021 ◽  
Vol 17 (7) ◽  
pp. e1009248
Author(s):  
Matthias Niemann ◽  
Nils Lachmann ◽  
Kirsten Geneugelijk ◽  
Eric Spierings
Keyword(s):  
T Cell ◽  
Cell Epitope ◽  
Haplotype Frequency ◽  
Deceased Donor ◽  
Waiting List ◽  
T Cell Epitopes ◽  
Kidney Allocation ◽  
Virtual Population ◽  
Considerable Impact ◽  
The Impact

The EuroTransplant Kidney Allocation System (ETKAS) aims at allocating organs to patients on the waiting list fairly whilst optimizing HLA match grades. ETKAS currently considers the number of HLA-A, -B, -DR mismatches. Evidently, epitope matching is biologically and clinically more relevant. We here executed ETKAS-based computer simulations to evaluate the impact of epitope matching on allocation and compared the strategies. A virtual population of 400,000 individuals was generated using the National Marrow Donor Program (NMDP) haplotype frequency dataset of 2011. Using this population, a waiting list of 10,400 patients was constructed and maintained during simulation, matching the 2015 Eurotransplant Annual Report characteristics. Unacceptable antigens were assigned randomly relative to their frequency using HLAMatchmaker. Over 22,600 kidneys were allocated in 10 years in triplicate using Markov Chain Monte Carlo simulations on 32-CPU-core cloud-computing instances. T-cell epitopes were calculated using the www.pirche.com portal. Waiting list effects were evaluated against ETKAS for five epitope matching scenarios. Baseline simulations of ETKAS slightly overestimated reported average HLA match grades. The best balanced scenario maintained prioritisation of HLA A-B-DR fully matched donors while replacing the HLA match grade by PIRCHE-II score and exchanging the HLA mismatch probability (MMP) by epitope MMP. This setup showed no considerable impact on kidney exchange rates and waiting time. PIRCHE-II scores improved, whereas the average HLA match grade diminishes slightly, yet leading to an improved estimated graft survival. We conclude that epitope-based matching in deceased donor kidney allocation is feasible while maintaining equal balances on the waiting list.

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