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Efficient Methods and Parallel Execution for Algorithm Sensitivity Analysis with Parameter Tuning on Microscopy Imaging Datasets [article]

George Teodoro, Tahsin Kurc, Luis F. R. Taveira, Alba C. M. A. Melo, Jun Kong, Joel Saltz
2016 arXiv   pre-print
We describe an informatics framework for researchers and clinical investigators to efficiently perform parameter sensitivity analysis and auto-tuning for algorithms that segment and classify image features  ...  Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies, and auto-tuning with large datasets with the use of high-performance systems and techniques.  ...  This work was supported in part by 1U24CA180924-01A1 from the NCI, R01LM011119-01 and R01LM009239 from the NLM, CNPq, and NIH K25CA181503.  ... 
arXiv:1612.03413v1 fatcat:iny3igenvncgxoe7paike7f36e

Tuning for Tissue Image Segmentation Workflows for Accuracy and Performance [article]

Luis F. R. Taveira, Tahsin Kurc, Alba C. M. A. Melo, Jun Kong, Erich Bremer, Joel H. Saltz, George Teodoro
2018 arXiv   pre-print
We propose a software platform that integrates methods and tools for multi-objective parameter auto- tuning in tissue image segmentation workflows.  ...  output quality; and (3) effectively use parallel systems to accelerate parameter tuning and segmentation phases.  ...  Another related work proposed the use of parameter auto-tuning and efficient parameter sensitivity analysis [47] in microscopy image with single objective optimization.  ... 
arXiv:1810.02911v1 fatcat:vrdg5hxzvbds5cslcplm5rto5y

Sensitivity analysis in digital pathology: Handling large number of parameters with compute expensive workflows

Jeremias Gomes, Willian Barreiros, Tahsin Kurc, Alba C.M.A. Melo, Jun Kong, Joel H. Saltz, George Teodoro
2019 Computers in Biology and Medicine  
Our work investigates the use of Surrogate Models (SMs) along with parallel execution to speed up parameter sensitivity analysis (SA).  ...  While there is a growing set of methods for analysis of whole slide tissue images, many of them are sensitive to changes in input parameters.  ...  Acknowledgment This work was supported in part by U24CA180924, U24CA215109, 1UG3CA225021 from the NCI, R01LM011119-01 and R01LM009239 from the NLM, CNPq, and NIH K25CA181503.  ... 
doi:10.1016/j.compbiomed.2019.03.006 pmid:31054503 pmcid:PMC7363453 fatcat:2xcm3ch5szawvlzvdeba2rteve

KiT: a MATLAB package for kinetochore tracking

Jonathan W. Armond, Elina Vladimirou, Andrew D. McAinsh, Nigel J. Burroughs
2016 Bioinformatics  
KiT supports 2D, 3D and multi-colour movies, quantification of fluorescence, integrated deconvolution, parallel execution and multiple algorithms for particle localization.  ...  Availability and implementation: KiT is free, open-source software implemented in MATLAB and runs on all MATLAB supported platforms.  ...  Acknowledgements We thank Edward Harry and Chris Smith for contributions to the code.  ... 
doi:10.1093/bioinformatics/btw087 pmid:27153705 pmcid:PMC4908324 fatcat:elhtunm3a5fkhjvag2z6v456te

Parameterized specification, configuration and execution of data-intensive scientific workflows

Vijay S. Kumar, Tahsin Kurc, Varun Ratnakar, Jihie Kim, Gaurang Mehta, Karan Vahi, Yoonju Lee Nelson, P. Sadayappan, Ewa Deelman, Yolanda Gil, Mary Hall, Joel Saltz
2010 Cluster Computing  
components (and of the whole workflow) for performance.  ...  While some performance parameters such as grouping of workflow components and their mapping to machines do not affect the accuracy of the analysis, others may dictate trading the output quality of individual  ...  Ohio Board of Regents BRTTC #BRTT02-0003 and AGMT TECH-04049 and NIH grants #R24 HL085343, #R01 LM009239, and #79077CBS10.  ... 
doi:10.1007/s10586-010-0133-8 pmid:22623878 pmcid:PMC3356923 fatcat:otnq42fe2nf7rge64b4j3cvaw4

Performance Analysis and Efficient Execution on Systems with multi-core CPUs, GPUs and MICs [article]

George Teodoro, Tahsin Kurc, Guilherme Andrade, Jun Kong, Renato Ferreira, Joel Saltz
2015 arXiv   pre-print
We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core - MIC) with a microscopy image analysis application.  ...  We correlate the observed performance with the characteristics of computing devices and data access patterns, computation complexities, and parallelization forms of the operations.  ...  of Health (NIH) K25CA181503 and by CNPq, CAPES, FINEP, Fapemig, and INWEB.  ... 
arXiv:1505.03819v1 fatcat:g5x5gwaubrc5bbfl7pmlbepzb4

Application performance analysis and efficient execution on systems with multi-core CPUs, GPUs and MICs: a case study with microscopy image analysis

George Teodoro, Tahsin Kurc, Guilherme Andrade, Jun Kong, Renato Ferreira, Joel Saltz
2016 The international journal of high performance computing applications  
We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core-MIC) with a microscopy image analysis application.  ...  We correlate the observed performance with the characteristics of computing devices and data access patterns, computation complexities, and parallelization forms of the operations.  ...  , National Institutes of Health (NIH) K25CA181503 and by CNPq, CAPES, FINEP, Fapemig, and INWEB.  ... 
doi:10.1177/1094342015594519 pmid:28239253 pmcid:PMC5319667 fatcat:tchtmfozwfc57hosfna43behoy

High-throughput label-free cell detection and counting from diffraction patterns with deep fully convolutional neural networks

Faliu Yi, Seonghwan Park, Inkyu Moon
2021 Journal of Biomedical Optics  
However, the biological cell analysis based on phase information of images is inefficient due to the complexity of numerical phase reconstruction algorithm applied to raw hologram images.  ...  Deep fully convolutional networks (FCNs) were developed on raw hologram images directly for high-throughput label-free cell detection and counting to assist the biological cell analysis in the future.  ...  purpose of hyper-parameter tuning and algorithm evaluation. 125 hologram images are used as training and 25 hologram images are taken as validation dataset.  ... 
doi:10.1117/1.jbo.26.3.036001 pmid:33686845 pmcid:PMC7939515 fatcat:aickjkllhvd7nmfrdwefhk3omq

FLIMJ: an open-source ImageJ toolkit for fluorescence lifetime image data analysis [article]

Dasong W Gao, Paul R Barber, Jenu V Chacko, Abdul Kader Sagar, Curtis T Rueden, Aivar R Grislis, Mark Hiner, Kevin W. Eliceiri
2020 bioRxiv   pre-print
One imaging technique with proven ability for yielding additional information from fluorescence imaging is Fluorescence Lifetime Imaging Microscopy (FLIM).  ...  The increased use of FLIM has necessitated the development of computational tools for integrating FLIM analysis with image and data processing.  ...  bench biologist; and 3. the integration of FLIM analysis with versatile microscopy image analysis.  ... 
doi:10.1101/2020.08.17.253625 fatcat:ajsbosh6pnafzontybejndq7gu

FLIMJ: An open-source ImageJ toolkit for fluorescence lifetime image data analysis

Dasong Gao, Paul R. Barber, Jenu V. Chacko, Md. Abdul Kader Sagar, Curtis T. Rueden, Aivar R. Grislis, Mark C. Hiner, Kevin W. Eliceiri, Kristen C. Maitland
2020 PLoS ONE  
One imaging technique with proven ability for yielding additional information from fluorescence imaging is Fluorescence Lifetime Imaging Microscopy (FLIM).  ...  The increased use of FLIM has necessitated the development of computational tools for integrating FLIM analysis with image and data processing.  ...  Coolen for the development of the Bayesian fitting algorithms. We also thank T. Gregg, M. Merrins and B DeZonia for their useful input on the original version of the program.  ... 
doi:10.1371/journal.pone.0238327 pmid:33378370 fatcat:elbj4bpqqvcndeljmxyp5czr2a

COMBImage: a modular parallel processing framework for pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies

Efthymia Chantzi, Malin Jarvius, Mia Niklasson, Anna Segerman, Mats G Gustafsson
2018 BMC Bioinformatics  
The image processing algorithms are parallelized using Google's MapReduce programming model and optimized with respect to method-specific tuning parameters.  ...  COMBImage is a fast, modular and instrument independent computational framework for in vitro pairwise drug combination analysis that quantifies temporal changes in label-free video microscopy movies.  ...  Funding This study was partly supported by grants from: Availability of data and materials  ... 
doi:10.1186/s12859-018-2458-x pmid:30477419 pmcid:PMC6257977 fatcat:u5je525mubdj7hen4qqucoj5gm

ACDC: Automated Cell Detection and Counting for Time-Lapse Fluorescence Microscopy

Leonardo Rundo, Andrea Tangherloni, Darren R. Tyson, Riccardo Betta, Carmelo Militello, Simone Spolaor, Marco S. Nobile, Daniela Besozzi, Alexander L. R. Lubbock, Vito Quaranta, Giancarlo Mauri, Carlos F. Lopez (+1 others)
2020 Applied Sciences  
ACDC was tested on two distinct cell imaging datasets to assess its accuracy and effectiveness on images with different characteristics.  ...  Moreover, ACDC represents a feasible solution for the laboratory practice, as it can leverage multi-core architectures in computer clusters to efficiently handle large-scale imaging datasets.  ...  Acknowledgments: The authors would like to thank Margarita Gamarra for her help with the analysis performed on the SNP HEp-2 Cell Dataset.  ... 
doi:10.3390/app10186187 fatcat:rkxqfewqzzfbxhqedsdebwz5im

A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy

Yanan Zhu, Qi Ouyang, Youdong Mao
2017 BMC Bioinformatics  
Our approach exhibits improved performance and high precision when tested on the standard KLH dataset.  ...  It is critical to develop a highly efficient template-free method to automatically recognize particle images from cryo-EM micrographs.  ...  Wu and S. Chen for helpful discussions, as well as S. Zhang for assistance in the code adaptation for GPU-based acceleration.  ... 
doi:10.1186/s12859-017-1757-y pmid:28732461 pmcid:PMC5521087 fatcat:pso7zfj7qbdrxexb5xtbr2lvka

Comparative Performance Analysis of Intel (R) Xeon Phi (TM), GPU, and CPU: A Case Study from Microscopy Image Analysis

George Teodoro, Tahsin Kurc, Jun Kong, Lee Cooper, Joel Saltz
2014 2014 IEEE 28th International Parallel and Distributed Processing Symposium  
We systematically implement and evaluate the performance of these operations on modern CPUs, GPUs, and MIC systems for a microscopy image analysis application.  ...  Our work is motivated by applications that analyze low-dimensional spatial datasets captured by high resolution sensors, such as image datasets obtained from whole slide tissue specimens using microscopy  ...  NHLBI, by R01LM011119-01 and R01LM009239 from the NLM, and RC4MD005964 from the NIH, and CNPq (including projects 151346/2013-5 and 313931/2013-5).  ... 
doi:10.1109/ipdps.2014.111 pmid:25419088 pmcid:PMC4240026 fatcat:nyqwqlx5mjdjdhq365w6uig3ti

fairDMS: Rapid Model Training by Data and Model Reuse [article]

Ahsan Ali, Hemant Sharma, Rajkumar Kettimuthu, Peter Kenesei, Dennis Trujillo, Antonino Miceli, Ian Foster, Ryan Coffee, Jana Thayer, Zhengchun Liu
2022 arXiv   pre-print
and/or data can be queried rapidly and a more suitable model retrieved and fine-tuned for new conditions.  ...  Conventional physics-based information retrieval methods are hard-pressed to detect interesting events fast enough to enable timely focusing on a rare event or correction of an error.  ...  We thank the three anonymous referees for their detailed and constructive comments and suggestions, which have helped us clarifying lots of confusing statements.  ... 
arXiv:2204.09805v3 fatcat:qcb3dfy5w5bplapx6xvy7ey5xu
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