检索结果-内蒙古大学图书馆

Data clustering to select clinically-relevant test cases for algorithm benchmarking and characterization

PHYSICS IN MEDICINE AND BIOLOGY 2020年第5期65卷 055014-055014页

作者： Weppler, Sarah Schinkel, Colleen Kirkby, Charles Smith, Wendy Univ Calgary Dept Phys & Astron Calgary AB T2N 1N4 Canada Tom Baker Canc Clin Dept Med Phys 1331 29 St NW Calgary AB T2N 4N2 Canada Univ Calgary Dept Oncol 2500 Univ Dr NW Calgary AB T2N 1N4 Canada Jack Ady Canc Ctr Dept Med Phys 960 19 St S Lethbridge AB T1J 1W5 Canada

algorithm benchmarking and characterization are an important part of algorithm development and validation prior to clinical implementation. However, benchmarking may be limited to a small collection of test cases due to the resource-intensive nature of establishing 'ground-truth' references. This study proposes a framework for selecting test cases to assess algorithm and workflow equivalence. Effective test case selection may minimize the number of ground-truth comparisons required to establish robust and clinically relevant benchmarking and characterization results. To demonstrate the proposed framework, we clustered differences between two independent workflows estimating during-treatment dose objective violations for 15 head and neck cancer patients (15 planning CTs, 105 on-unit CBCTs). Each workflow used a different deformable image registration algorithm to estimate inter-fractional anatomy and contour changes. The Hopkins statistic tested whether workflow output was inherently clustered and k-medoid clustering formalized cluster assignment. Further statistical analyses verified the relevance of clusters to algorithm output. Data at cluster centers ('medoids') were considered as candidate test cases representative of workflow-relevant algorithm differences. The framework indicated that differences in estimated dose objective violations were naturally grouped (Hopkins = 0.75, providing 90% confidence). K-medoid clustering identified five clusters which stratified workflow differences (MANOVA: p < 0.001) in estimated parotid gland D50%, spinal cord/brainstem Dmax, and high dose CTV coverage dose violations (Kendall's tau: p < 0.05). Systematic algorithm differences resulting in workflow discrepancies were: parotid gland volumes (ANOVA: p < 0.001), external contour deformations (t-test: p = 0.022), and CTV-to-PTV margins (t-test: 0.009), respectively. Five candidate test cases were verified as representative of the five clusters. The framework successfully cluster

关键词： algorithm benchmarking data clustering test case selection

来源：评论

学校读者我要写书评

暂无评论

WASPAS Application and Evolutionary algorithm benchmarking in Optimal Reservoir Optimization Problems

引用

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2017年第1期143卷 1-13页

作者： Bozorg-Haddad, Omid Azarnivand, Ali Hosseini-Moghari, Seyed-Mohammad Loaiciga, Hugo A. Univ Tehran Coll Agr & Nat Resources Fac Agr Engn & Technol Dept Irrigat & Reclamat Engn Tehran *** Iran Univ Calif Santa Barbara Dept Geog Santa Barbara CA 93016 USA

This study applies a recently developed evolutionary algorithm (EA) called state of matter search (SMS) to minimize the total energy deficit in the Karun4 reservoir, Iran. The operation of the Karun4 reservoir is influenced by several factors, which requires a multiple criteria framework for selecting the most suitable solution EA. Five EAs, in addition to the SMS, were evaluated for the reservoir operation problem on the basis of four performance criteria and the fitness function (FF) value. The priority assessment on the basis of FF value revealed that the SMS outperformed the other EAs in converging to the optimal solution. However, judged by the other four performance criteria, based on weighted aggregates sum product assessment (WASPAS) technique, particle swarm optimization (PSO) proved superior to the other EAs. This paper's results show that the selection of a solution EA for solving complex reservoir optimization problem requires a multicriteria decision-making process. Multiobjective evolutionary algorithms (MOEAs) are well-suited for the task. (C) 2016 American Society of Civil Engineers.

关键词： Optimal reservoir operation algorithm benchmarking States of matter search algorithm Performance criteria Weighted aggregates sum product assessment (WASPAS) technique

来源：评论

学校读者我要写书评

暂无评论

Towards improved benchmarking of black-box optimization algorithms using clustering problems

引用

SOFT COMPUTING 2016年第10期20卷 3835-3849页

作者： Gallagher, Marcus Univ Queensland Sch Informat Technol & Elect Engn Brisbane Qld 4072 Australia

The field of Metaheuristics has produced a large number of algorithms for continuous, black-box optimization. In contrast, there are few standard benchmark problem sets, limiting our ability to gain insight into the empirical performance of these algorithms. Clustering problems have been used many times in the literature to evaluate optimization algorithms. However, much of this work has occurred independently on different problem instances and the various experimental methodologies used have produced results which are frequently incomparable and provide little knowledge regarding the difficulty of the problems used, or any platform for comparing and evaluating the performance of algorithms. This paper discusses sum of squares clustering problems from the optimization viewpoint. Properties of the fitness landscape are analysed and it is proposed that these problems are highly suitable for algorithm benchmarking. A set of 27 problem instances (from 4-D to 40-D), based on three well-known datasets, is specified. Baseline experimental results are presented for the Covariance Matrix Adaptation-Evolution Strategy and several other standard algorithms. A web-repository has also been created for this problem set to facilitate future use for algorithm evaluation and comparison.

关键词： algorithm benchmarking Continuous black-box optimization Clustering Fitness landscape analysis

来源：评论

学校读者我要写书评

暂无评论

Can modern multi-objective evolutionary algorithms discover high-dimensional financial risk portfolio tradeoffs for snow-dominated water-energy systems?

引用

ADVANCES IN WATER RESOURCES 2020年 145卷 103718-103718页

作者： Gupta, Rohini S. Hamilton, Andrew L. Reed, Patrick M. Characklis, Gregory W. Cornell Univ Dept Civil & Environm Engn Ithaca NY 14853 USA Univ North Carolina Chapel Hill Gillings Sch Global Publ Hlth Dept Environm Sci & Engn Chapel Hill NC USA Univ North Carolina Chapel Hill UNC Inst Environm Ctr Financial Risk Environm Syst Gillings Sch Global Publ Hlth Chapel Hill NC USA

Hydropower generation in the Hetch Hetchy Power System is strongly tied to snowmelt dynamics in the central Sierra Nevada and consequently is particularly financially vulnerable to changes in snowpack availability and timing. This study explores the Hetchy Hetchy Power System as a representative example from the broader class of financial risk management problems that hold promise in helping utilities such as SFPUC to understand the tradeoffs across portfolios of risk mitigation instruments given uncertainties in snowmelt dynamics. An evolution-ary multi-objective direct policy search (EMODPS) framework is implemented to identify time adaptive stochastic rules that map utility state information and exogenous inputs to optimal annual financial decisions. The resulting financial risk mitigation portfolio planning problem is mathematically difficult due to its high dimensionality and mixture of nonlinear, nonconvex, and discrete objectives. These features add to the difficulty of the problem by yielding a Pareto front of solutions that has a highly disjoint and complex geometry. In this study, we contribute a diagnostic assessment of state-of-the-art multi-objective evolutionary algorithms' (MOEAs') abilities to support a DPS framework for managing financial risk. We perform comprehensive diagnostics on five algorithms: the Borg multi-objective evolutionary algorithm, Non-dominated Sorting Genetic algorithm II (NSGA-II), Non dominated Sorting Genetic algorithm III (NSGA-III), Reference Vector Guided Evolutionary algorithm (RVEA), and the Multi-objective Evolutionary algorithm Based on Decomposition (MOEA/D). The MOEAs are evaluated to characterize their controllability (ease-of-use), reliability (probability of success), efficiency (minimizing model evaluations), and effectiveness (high quality tradeoff representations). Our results show that newer decomposition, reference point, and reference vector algorithms are highly sensitive to their parameterizations (difficult

关键词： Financial risk management Direct policy search Many objective optimization Evolutionary algorithms Hydropower algorithm benchmarking

来源：评论

学校读者我要写书评

暂无评论

Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images

引用

MEDICAL IMAGE ANALYSIS 2016年 30卷 95-107页

作者： Karim, Rashed Bhagirath, Pranav Claus, Piet Housden, R. James Chen, Zhong Karimaghaloo, Zahra Sohn, Hyon-Mok Lara Rodriguez, Laura Vera, Sergio Alba, Xenia Hennemuth, Anja Peitgen, Heinz-Otto Arbel, Tal Gonzalez Ballester, Miguel A. Frangi, Alejandro F. Gotte, Marco Razavi, Reza Schaeffter, Tobias Rhode, Kawal Kings Coll London Dept Imaging Sci & Biomed Engn London WC2R 2LS England Haga Teaching Hosp Dept Cardiol The Hague Netherlands Univ Leuven Dept Cardiovasc Sci Cardiovasc Imaging & Dynam Louvain Belgium McGill Univ Ctr Intelligence Machines Montreal PQ H3A 2T5 Canada Alma IT Syst Barcelona Spain Univ Pompeu Fabra Dept Informat & Commun Technol Ctr Computat Imaging & Simulat Technol Biomed CIS Barcelona Spain Fraunhofer MEVIS Fraunhofer Inst Med Image Comp Lubeck Germany Univ Sheffield Dept Elect & Elect Engn Ctr Computat Imaging & Simulat Technol Biomed CIS Mappin St Sheffield S1 3JD S Yorkshire England ICREA Barcelona Spain Univ Pompeu Fabra SIMBIOsys Res Grp Barcelona Spain

Studies have demonstrated the feasibility of late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging for guiding the management of patients with sequelae to myocardial infarction, such as ventricular tachycardia and heart failure. Clinical implementation of these developments necessitates a reproducible and reliable segmentation of the infarcted regions. It is challenging to compare new algorithms for infarct segmentation in the left ventricle (LV) with existing algorithms. benchmarking datasets with evaluation strategies are much needed to facilitate comparison. This manuscript presents a benchmarking evaluation framework for future algorithms that segment infarct from LGE CMR of the LV. The image database consists of 30 LGE CMR images of both humans and pigs that were acquired from two separate imaging centres. A consensus ground truth was obtained for all data using maximum likelihood estimation. Six widely-used fixed-thresholding methods and five recently developed algorithms are tested on the benchmarking framework, Results demonstrate that the algorithms have better overlap with the consensus ground truth than most of the n-SD fixed-thresholding methods, with the exception of the Full Width -at-Half-Maximum (FWHM) fixed-thresholding method. Some of the pitfalls of fixed thresholding methods are demonstrated in this work. The benchmarking evaluation framework, which is a contribution of this work, can be used to test and benchmark future algorithms that detect and quantify infarct in LGE CMR images of the LV. The datasets, ground truth and evaluation code have been made publicly available through the website: https://***/web/guest/challenges. (C) 2016 The Authors. Published by Elsevier B.V.

关键词： Late Gadolinium enhancement Segmentation algorithm benchmarking

来源：评论

学校读者我要写书评

暂无评论

Food Recognition: A New Dataset, Experiments, and Results

引用

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2017年第3期21卷 588-598页

作者： Ciocca, Gianluigi Napoletano, Paolo Schettini, Raimondo Univ Milano Bicocca Dept Informat Syst & Commun I-20126 Milan Italy DISCo Comp Sci Milan Italy

We propose a new dataset for the evaluation of food recognition algorithms that can be used in dietary monitoring applications. Each image depicts a real canteen tray with dishes and foods arranged in different ways. Each tray contains multiple instances of food classes. The dataset contains 1027 canteen trays for a total of 3616 food instances belonging to 73 food classes. The food on the tray images has been manually segmented using carefully drawn polygonal boundaries. We have benchmarked the dataset by designing an automatic tray analysis pipeline that takes a tray image as input, finds the regions of interest, and predicts for each region the corresponding food class. We have experimented with three different classification strategies using also several visual descriptors. We achieve about 79% of food and tray recognition accuracy using convolutional-neural-networks-based features. The dataset, as well as the benchmark framework, are available to the research community.

关键词： algorithm benchmarking convolutional neural networks (CNN) food dataset food recognition

来源：评论

学校读者我要写书评

暂无评论

Confronting tipping points: Can multi-objective evolutionary algorithms discover pollution control tradeoffs given environmental thresholds?

引用

ENVIRONMENTAL MODELLING & SOFTWARE 2015年 73卷 27-43页

作者： Ward, Victoria L. Singh, Riddhi Reed, Patrick M. Keller, Klaus Cornell Univ Sch Civil & Environm Engn Ithaca NY 14853 USA Indian Inst Technol Hyderabad Dept Civil Engn Yeddumailaram India Penn State Univ Dept Geosci University Pk PA 16802 USA Carnegie Mellon Univ Dept Engn & Publ Policy Pittsburgh PA 15213 USA Penn State Univ Earth & Environm Syst Inst University Pk PA 16802 USA

This study contributes a stochastic, multi-objective adaptation of the classic environmental economics Lake Problem as a computationally simple but mathematically challenging benchmarking problem. The Lake Problem considers a hypothetical town by a lake, which hopes to maximize its economic benefit without crossing a nonlinear, and potentially irreversible, pollution threshold. Optimization objectives are maximize economic benefit, minimize phosphorus in the lake, maximize the probability of avoiding the pollution threshold, and minimize the probability of drastic phosphorus loading reductions in a given year. Uncertainty is introduced through a stochastic natural phosphorus inflow. We performed comprehensive diagnostics using six algorithms: the Borg multi-objective evolutionary algorithm (MOEA), MOEA/D, epsilon-MOEA, the Non-dominated Sorting Genetic algorithm II (NSGAII), epsilon-NSGAII, and Generalized Differential Evolution 3 (GDE3) to evaluate their controllability, reliability, efficiency, and effectiveness. Our results show only the self-adaptive search of the Borg MOEA was capable of performing well on this nontrivial benchmarking problem. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Risk management Environmental thresholds Tipping points Multi-objective decision making algorithm benchmarking Lake problem benchmark

来源：评论

学校读者我要写书评

暂无评论

Evaluation of current algorithms for segmentation of scar tissue from late Gadolinium enhancement cardiovascular magnetic resonance of the left atrium: an open-access grand challenge

引用

JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE 2013年第1期15卷 1-17页

作者： Karim, Rashed Housden, R. James Balasubramaniam, Mayuragoban Chen, Zhong Perry, Daniel Uddin, Ayesha Al-Beyatti, Yosra Palkhi, Ebrahim Acheampong, Prince Obom, Samantha Hennemuth, Anja Lu, YingLi Bai, Wenjia Shi, Wenzhe Gao, Yi Peitgen, Heinz-Otto Radau, Perry Razavi, Reza Tannenbaum, Allen Rueckert, Daniel Cates, Josh Schaeffter, Tobias Peters, Dana MacLeod, Rob Rhode, Kawal Kings Coll London Dept Imaging Sci & Biomed Engn London England Univ Utah Utah Ctr Adv Imaging Res Salt Lake City UT USA Yale Univ Yale Sch Med Magnet Resonance Res Ctr New Haven CT USA Univ London Imperial Coll Sci Technol & Med Dept Comp London England Boston Univ Sch Elect & Comp Engn Boston MA 02215 USA Harvard Univ Sch Med Psychiat Neuroimaging Lab Boston MA USA Sunnybrook Hlth Sci Ctr Toronto ON M4N 3M5 Canada Fraunhofer MEVIS Fraunhofer Inst Med Image Comp Bremen Germany Harvard Univ Beth Israel Deaconess Med Ctr Sch Med Boston MA 02215 USA

Background: Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging can be used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). In this paper we present a standardised evaluation benchmarking framework for algorithms segmenting fibrosis and scar from LGE CMR images. The algorithms reported are the response to an open challenge that was put to the medical imaging community through an ISBI (IEEE International Symposium on Biomedical Imaging) workshop. Methods: The image database consisted of 60 multicenter, multivendor LGE CMR image datasets from patients with AF, with 30 images taken before and 30 after RFCA for the treatment of AF. A reference standard for scar and fibrosis was established by merging manual segmentations from three observers. Furthermore, scar was also quantified using 2, 3 and 4 standard deviations (SD) and full-width-at-half-maximum (FWHM) methods. Seven institutions responded to the challenge: Imperial College (IC), Mevis Fraunhofer (MV), Sunnybrook Health Sciences (SY), Harvard/Boston University (HB), Yale School of Medicine (YL), King's College London (KCL) and Utah CARMA (UTA, UTB). There were 8 different algorithms evaluated in this study. Results: Some algorithms were able to perform significantly better than SD and FWHM methods in both pre-and post-ablation imaging. Segmentation in pre-ablation images was challenging and good correlation with the reference standard was found in post-ablation images. Overlap scores (out of 100) with the reference standard were as follows: Pre: IC = 37, MV = 22, SY = 17, YL = 48, KCL = 30, UTA = 42, UTB = 45;Post: IC = 76, MV = 85, SY = 73, HB = 76, YL = 84, KCL = 78, UTA = 78, UTB = 72. Conclusions: The study concludes that currently no algorithm is deemed clearly better than oth

关键词： Late gadolinium enhancement Cardiovascular magnetic resonance Atrial fibrillation Segmentation algorithm benchmarking

来源：评论

学校读者我要写书评

暂无评论

On Computing Optimal Linear Diagrams 13th

On Computing Optimal Linear Diagrams

引用

13th International Conference on Theory and Application of Diagrams (Diagrams)

作者： Dobler, Alexander Noellenburg, Martin TU Wien Algorithms & Complex Grp Vienna Austria

ISBN: (纸本)9783031151460;9783031151453

Linear diagrams are an effective way to visualize set-based data by representing elements as columns and sets as rows with one or more horizontal line segments, whose vertical overlaps with other rows indicate set intersections and their contained elements. The efficacy of linear diagrams heavily depends on having few line segments. The underlying minimization problem has already been explored heuristically, but its computational complexity has yet to be classified. In this paper, we show that minimizing line segments in linear diagrams is equivalent to a well-studied NP-hard problem, and extend the NP-hardness to a restricted setting. We develop new algorithms for computing linear diagrams with minimum number of line segments that build on a traveling salesperson (TSP) formulation and allow constraints on the element orders, namely, forcing two sets to be drawn as single line segments, giving weights to sets, and allowing hierarchical constraints via PQ-trees. We conduct an experimental evaluation and compare previous algorithms for minimizing line segments with our TSP formulation, showing that a state-of-the art TSP-solver can solve all considered instances optimally, most of them within few milliseconds.

关键词： Linear diagrams Consecutive ones TSP NP-hardness algorithm benchmarking

来源：评论

学校读者我要写书评

暂无评论

The Barrier Tree Benchmark: Many Basins and Double Funnels 23

The Barrier Tree Benchmark: Many Basins and Double Funnels

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Blackwell, Tim Goldsmiths Univ London Dept Comp London SE14 6NW England

ISBN: (纸本)9798400701191

The Barrier Tree Benchmark (BTB) is a principled generator of continuous real-valued landscapes: problems of known topography/critical point structure can be systematically designed and deployed in algorithm comparison studies. A previous BTB study focused on a single funnel and a double basin. This work demonstrates algorithm performance on BTB instances with many basins, and on double funnels. A methodology for principled algorithm comparison on families of problems of similar complexity and structure is proposed. It is hoped that the BTB will address a parameter tuning pathology of current problem benchmarks, namely, that common optimisation algorithms require widely different control parameter settings for optimal performance on differing problem classes. This pathology is traced to the irregular and arbitrary composition of standard benchmarks.

关键词： optimisation algorithm benchmarking swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：