scholarly journals Patient Specific Dosimetry Phantoms Using Multichannel LDDMM of the Whole Body

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Daniel J. Tward ◽  
Can Ceritoglu ◽  
Anthony Kolasny ◽  
Gregory M. Sturgeon ◽  
W. Paul Segars ◽  
...  
Keyword(s):  
Pediatric Patients ◽  
Parallel Implementation ◽  
Computation Time ◽  
Whole Body ◽  
Patient Specific ◽  
Data Set ◽  
Pediatric Dosimetry ◽  
Small Set ◽  
Diffeomorphic Metric Mapping ◽  
And Performance

This paper describes an automated procedure for creating detailed patient-specific pediatric dosimetry phantoms from a small set of segmented organs in a child's CT scan. The algorithm involves full body mappings from adult template to pediatric images using multichannel large deformation diffeomorphic metric mapping (MC-LDDMM). The parallel implementation and performance of MC-LDDMM for this application is studied here for a sample of 4 pediatric patients, and from 1 to 24 processors. 93.84% of computation time is parallelized, and the efficiency of parallelization remains high until more than 8 processors are used. The performance of the algorithm was validated on a set of 24 male and 18 female pediatric patients. It was found to be accurate typically to within 1-2 voxels (2–4 mm) and robust across this large and variable data set.

Improving the Performance of kNN in the MapReduce Framework Using Locality Sensitive Hashing

2019 ◽  
Vol 10 (4) ◽  
pp. 1-16
Author(s):  
Sikha Bagui ◽  
Arup Kumar Mondal ◽  
Subhash Bagui
Keyword(s):  
Nearest Neighbor ◽  
Parallel Implementation ◽  
Block Size ◽  
Computation Time ◽  
Locality Sensitive Hashing ◽  
K Nearest Neighbor ◽  
Mapreduce Framework ◽  
Data Set ◽  
Data Object ◽  
Very Large Datasets

In this work the authors present a parallel k nearest neighbor (kNN) algorithm using locality sensitive hashing to preprocess the data before it is classified using kNN in Hadoop's MapReduce framework. This is compared with the sequential (conventional) implementation. Using locality sensitive hashing's similarity measure with kNN, the iterative procedure to classify a data object is performed within a hash bucket rather than the whole data set, greatly reducing the computation time needed for classification. Several experiments were run that showed that the parallel implementation performed better than the sequential implementation on very large datasets. The study also experimented with a few map and reduce side optimization features for the parallel implementation and presented some optimum map and reduce side parameters. Among the map side parameters, the block size and input split size were varied, and among the reduce side parameters, the number of planes were varied, and their effects were studied.

Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body $^{18}{\hbox{F-FDG}}$ Distributions for Oncology Applications

2009 ◽  
Vol 97 (12) ◽  
pp. 2026-2038 ◽  
Author(s):  
Amandine Le Maitre ◽  
William Paul Segars ◽  
Simon Marache ◽  
Anthonin Reilhac ◽  
Mathieu Hatt ◽  
...  
Keyword(s):  
Whole Body ◽  
Patient Specific

scholarly journals 2329. Preliminary Safety and Effectiveness of Whole-Body MRI in Pediatric Patients With Persistent Bacteremia or Febrile Illness

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S692-S692
Author(s):  
Edwin Hayes ◽  
Lindsay Miranda ◽  
Anna-Kathryn Burch ◽  
Matthew Marcus ◽  
Helmut Albrecht ◽  
...  
Keyword(s):  
Pediatric Patients ◽  
Febrile Illness ◽  
Whole Body ◽  
Whole Body Mri ◽  
Persistent Bacteremia

Development and Validation of a Cognitive Reserve Index in HIV

2021 ◽  
pp. 1-9
Author(s):  
Navaldeep Kaur ◽  
Lesley K. Fellows ◽  
Marie-Josée Brouillette ◽  
Nancy Mayo
Keyword(s):  
Cognitive Reserve ◽  
Study Entry ◽  
Video Gaming ◽  
Everyday Functioning ◽  
Data Set ◽  
Multiple Indicators ◽  
And Performance ◽  
Competitive Games ◽  
Development And Validation

Abstract Objectives: In the neuroHIV literature, cognitive reserve has most often been operationalized using education, occupation, and IQ. The effects of other cognitively stimulating activities that might be more amenable to interventions have been little studied. The purpose of this study was to develop an index of cognitive reserve in people with HIV, combining multiple indicators of cognitively stimulating lifetime experiences into a single value. Methods: The data set was obtained from a Canadian longitudinal study (N = 856). Potential indicators of cognitive reserve captured at the study entry included education, occupation, engagement in six cognitively stimulating activities, number of languages spoken, and social resources. Cognitive performance was measured using a computerized test battery. A cognitive reserve index was formulated using logistic regression weights. For the evidence on concurrent and predictive validity of the index, the measures of cognition and self-reported everyday functioning were each regressed on the index scores at study entry and at the last follow-up [mean duration: 25.9 months (SD 7.2)], respectively. Corresponding regression coefficients and 95% confidence intervals (CIs) were computed. Results: Professional sports [odds ratio (OR): 2.9; 95% CI 0.59–14.7], visual and performance arts (any level of engagement), professional/amateur music, complex video gaming and competitive games, and travel outside North America were associated with higher cognitive functioning. The effects of cognitive reserve on the outcomes at the last follow-up visit were closely similar to those at study entry. Conclusion: This work contributes evidence toward the relative benefit of engaging in specific cognitively stimulating life experiences in HIV.

Distributed learning with indefinite kernels

2019 ◽  
Vol 17 (06) ◽  
pp. 947-975 ◽  
Author(s):  
Lei Shi
Keyword(s):  
Large Scale ◽  
Substantial Reduction ◽  
Computation Time ◽  
Distributed Learning ◽  
Rates Of Convergence ◽  
Regression Problem ◽  
Data Set ◽  
Regularization Scheme ◽  
Original Algorithm ◽  
Indefinite Kernel

We investigate the distributed learning with coefficient-based regularization scheme under the framework of kernel regression methods. Compared with the classical kernel ridge regression (KRR), the algorithm under consideration does not require the kernel function to be positive semi-definite and hence provides a simple paradigm for designing indefinite kernel methods. The distributed learning approach partitions a massive data set into several disjoint data subsets, and then produces a global estimator by taking an average of the local estimator on each data subset. Easy exercisable partitions and performing algorithm on each subset in parallel lead to a substantial reduction in computation time versus the standard approach of performing the original algorithm on the entire samples. We establish the first mini-max optimal rates of convergence for distributed coefficient-based regularization scheme with indefinite kernels. We thus demonstrate that compared with distributed KRR, the concerned algorithm is more flexible and effective in regression problem for large-scale data sets.

scholarly journals A method for evaluation of patient-specific lean body mass from limited-coverage CT images and its application in PERCIST: comparison with predictive equation

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jingjie Shang ◽  
Zhiqiang Tan ◽  
Yong Cheng ◽  
Yongjin Tang ◽  
Bin Guo ◽  
...  
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Whole Body ◽  
Patient Specific ◽  
Predictive Equation ◽  
Reference Standard ◽  
Pet Ct ◽  
Before And After ◽  
Percist 1.0 ◽  
Limited Coverage

Abstract Background Standardized uptake value (SUV) normalized by lean body mass ([LBM] SUL) is recommended as metric by PERCIST 1.0. The James predictive equation (PE) is a frequently used formula for LBM estimation, but may cause substantial error for an individual. The purpose of this study was to introduce a novel and reliable method for estimating LBM by limited-coverage (LC) CT images from PET/CT examinations and test its validity, then to analyse whether SUV normalised by LC-based LBM could change the PERCIST 1.0 response classifications, based on LBM estimated by the James PE. Methods First, 199 patients who received whole-body PET/CT examinations were retrospectively retrieved. A patient-specific LBM equation was developed based on the relationship between LC fat volumes (FVLC) and whole-body fat mass (FMWB). This equation was cross-validated with an independent sample of 97 patients who also received whole-body PET/CT examinations. Its results were compared with the measurement of LBM from whole-body CT (reference standard) and the results of the James PE. Then, 241 patients with solid tumours who underwent PET/CT examinations before and after treatment were retrospectively retrieved. The treatment responses were evaluated according to the PE-based and LC-based PERCIST 1.0. Concordance between them was assessed using Cohen’s κ coefficient and Wilcoxon’s signed-ranks test. The impact of differing LBM algorithms on PERCIST 1.0 classification was evaluated. Results The FVLC were significantly correlated with the FMWB (r=0.977). Furthermore, the results of LBM measurement evaluated with LC images were much closer to the reference standard than those obtained by the James PE. The PE-based and LC-based PERCIST 1.0 classifications were discordant in 27 patients (11.2%; κ = 0.823, P=0.837). These discordant patients’ percentage changes of peak SUL (SULpeak) were all in the interval above or below 10% from the threshold (±30%), accounting for 43.5% (27/62) of total patients in this region. The degree of variability is related to changes in LBM before and after treatment. Conclusions LBM algorithm-dependent variability in PERCIST 1.0 classification is a notable issue. SUV normalised by LC-based LBM could change PERCIST 1.0 response classifications based on LBM estimated by the James PE, especially for patients with a percentage variation of SULpeak close to the threshold.

Cyclic Breathing Simulations in Large Scale Models of the Lung Airway From the Oronasal Opening to the Terminal Bronchioles

2012 ◽  
Author(s):  
D. Keith Walters ◽  
Greg W. Burgreen ◽  
Robert L. Hester ◽  
David S. Thompson ◽  
David M. Lavallee ◽  
...  
Keyword(s):  
Steady State ◽  
Boundary Conditions ◽  
Large Scale ◽  
Whole Body ◽  
Patient Specific ◽  
Cfd Simulations ◽  
Reduced Order ◽  
Scale Models ◽  
Steady State Simulation ◽  
Conducting Zone

Computational fluid dynamics (CFD) simulations were performed for unsteady periodic breathing conditions, using large-scale models of the human lung airway. The computational domain included fully coupled representations of the orotracheal region and large conducting zone up to generation four (G4) obtained from patient-specific CT data, and the small conducting zone (to G16) obtained from a stochastically generated airway tree with statistically realistic geometrical characteristics. A reduced-order geometry was used, in which several airway branches in each generation were truncated, and only select flow paths were retained to G16. The inlet and outlet flow boundaries corresponded to the oronasal opening (superior), the inlet/outlet planes in terminal bronchioles (distal), and the unresolved airway boundaries arising from the truncation procedure (intermediate). The cyclic flow was specified according to the predicted ventilation patterns for a healthy adult male at three different activity levels, supplied by the whole-body modeling software HumMod. The CFD simulations were performed using Ansys FLUENT. The mass flow distribution at the distal boundaries was prescribed using a previously documented methodology, in which the percentage of the total flow for each boundary was first determined from a steady-state simulation with an applied flow rate equal to the average during the inhalation phase of the breathing cycle. The distal pressure boundary conditions for the steady-state simulation were set using a stochastic coupling procedure to ensure physiologically realistic flow conditions. The results show that: 1) physiologically realistic flow is obtained in the model, in terms of cyclic mass conservation and approximately uniform pressure distribution in the distal airways; 2) the predicted alveolar pressure is in good agreement with previously documented values; and 3) the use of reduced-order geometry modeling allows accurate and efficient simulation of large-scale breathing lung flow, provided care is taken to use a physiologically realistic geometry and to properly address the unsteady boundary conditions.

How do resources and diversification strategy explain the performance consequences of internationalization?

2014 ◽  
Vol 52 (5) ◽  
pp. 897-915 ◽  
Author(s):  
Yan Chen ◽  
Yiwei Jiang ◽  
Chengqi Wang ◽  
Wen Chung Hsu
Keyword(s):  
Emerging Market ◽  
Product Diversification ◽  
Firm Resources ◽  
Diversification Strategy ◽  
Data Set ◽  
Content Type ◽  
Listed Firms ◽  
Performance Consequences ◽  
Performance Effects ◽  
And Performance

Purpose – The purpose of this paper is to examine how firm resources and diversification strategy explain the performance consequences of internationalization of emerging market enterprises. Design/methodology/approach – The paper conducts a regression analysis by using a novel panel data set comprising of 685 listed Chinese firms over the period of 2008-2011. Findings – The results show that the relationship between internationalization and performance is inverse U-shaped. Further, marketing resources play a greater role in enhancing the performance effects of internationalization than technological resources do. Related product diversification enhances the performance effects, while unrelated product diversification does the contrary. Research limitations/implications – The study focusses on listed firms in one country, and as a result, the findings cannot be generalized to non-listed firms and firms in other countries. Practical implications – This paper offers guidelines for international managers to improve performance of internationalization by developing a particular type of resources and diversification strategy. Originality/value – This paper extends the literature on the functional form of the internationalization-performance relationship, and further suggests that the analysis of the performance consequences of internationalization should go beyond the nexus between internationalization and performance, and focusses on firm-specific resources and strategies that may facilitate or constrain the performance effects of internationalization.

Increasing revenue and attendance in Canadian Baptist churches

2015 ◽  
Vol 42 (12) ◽  
pp. 1071-1089
Author(s):  
Alan Chan ◽  
Bruce G. Fawcett ◽  
Shu-Kam Lee
Keyword(s):  
Church Health ◽  
Eastern Canada ◽  
Data Set ◽  
Content Type ◽  
Factors Affecting ◽  
Scarce Resources ◽  
Baptist Churches ◽  
And Performance ◽  
The Impact ◽  
Simulation Exercises

Purpose – Church giving and attendance are two important indicators of church health and performance. In the literature, they are usually understood to be simultaneously determined. The purpose of this paper is to estimate if there a sustainable church congregation size using Wintrobe’s (1998) dictatorship model. The authors want to examine the impact of youth and adult ministry as well. Design/methodology/approach – Using the data collected from among Canadian Baptist churches in Eastern Canada, this study investigates the factors affecting the level of the two indicators by the panel-instrumental variable technique. Applying Wintrobe’s (1998) political economy model on dictatorship, the equilibrium level of worship attendance and giving is predicted. Findings – Through various simulation exercises, the actual church congregation sizes is approximately 50 percent of the predicted value, implying inefficiency and misallocation of church resources. The paper concludes with insights on effective ways church leaders can allocate scarce resources to promote growth within churches. Originality/value – The authors are the only researchers getting the permission from the Atlantic Canada Baptist Convention to use their mega data set on church giving and congregation sizes as per the authors’ knowledge. The authors are also applying a theoretical model on dictatorship to religious/not for profits organizations.

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