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ImageJ2: ImageJ for the next generation of scientific image data [article]

Curtis T. Rueden, Johannes Schindelin, Mark C. Hiner, Barry E. DeZonia, Alison E. Walter, Ellen T. Arena, Kevin W. Eliceiri
2017 arXiv   pre-print
Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality.  ...  ImageJ is an image analysis program extensively used in the biological sciences and beyond.  ...  A special thanks to Wayne Rasband for his tireless work on, and continuing maintenance of, ImageJ 1.x for these many years.  ... 
arXiv:1701.05940v4 fatcat:4ttvwx5dh5e4vjmcd3gmy33ohe

ImageJ2: ImageJ for the next generation of scientific image data

Curtis T. Rueden, Johannes Schindelin, Mark C. Hiner, Barry E. DeZonia, Alison E. Walter, Ellen T. Arena, Kevin W. Eliceiri
2017 BMC Bioinformatics  
This next-generation ImageJ, called "ImageJ2" in places where the distinction matters, provides a host of new functionality.  ...  ImageJ is an image analysis program extensively used in the biological sciences and beyond.  ...  Key motivations for the development of ImageJ2 include: Supporting the next generation of image data. Over time, the infrastructure of image acquisition has grown in sophistication and complexity.  ... 
doi:10.1186/s12859-017-1934-z pmid:29187165 pmcid:PMC5708080 fatcat:micm7kue5jcxjk372tagjgskuu

ImageJ for the Next Generation of Scientific Image Data

Curtis T. Rueden, Kevin W. Eliceiri
2019 Microscopy and Microanalysis  
Meeting current and future needs of scientific image analysis requires a flexible and extensible data model, supporting arbitrary dimensions, data types and image sizes.  ...  We also overview the two major development efforts of the ImageJ [1, 2] family of image analysis, FIJI [3] and ImageJ2 [4] .  ... 
doi:10.1017/s1431927619001442 fatcat:jmp5n56ndbdarkhgkahdhzywbm

ImageJ: Image Analysis Interoperability for the Next Generation of Biological Image Data

Curtis T. Rueden, Mark C. Hiner, Kevin W. Eliceiri
2016 Microscopy and Microanalysis  
Meeting current and future needs of scientific image analysis requires a flexible and extensible data model, supporting arbitrary dimensions, data types and image sizes.  ...  We also overview the two major development efforts of the ImageJ [1] family of image analysis, FIJI [2] and ImageJ2 [3] .  ... 
doi:10.1017/s143192761601117x fatcat:qdvaj3fnkbeptl2kenwszizlyy

The ImageJ ecosystem: An open platform for biomedical image analysis

Johannes Schindelin, Curtis T. Rueden, Mark C. Hiner, Kevin W. Eliceiri
2015 Molecular Reproduction and Development  
Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis.  ...  In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific  ...  sample image; and Christian Dietz for his work on the ImageJ KNIME node.  ... 
doi:10.1002/mrd.22489 pmid:26153368 pmcid:PMC5428984 fatcat:lxho2lvzqvevvfj4rmnprhlvjm

ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability

Mark C. Hiner, Curtis T. Rueden, Kevin W. Eliceiri
2016 Bioinformatics  
By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks.  ...  ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ.  ...  Acknowledgements This work would not have been possible without development of the robust SciJava plugin framework, driven by its application in ImageJ.  ... 
doi:10.1093/bioinformatics/btw681 pmid:27797782 pmcid:PMC6041959 fatcat:ylxricb7jzgfvoijrfnacfmyqq

NIH Image to ImageJ: 25 years of image analysis

Caroline A Schneider, Wayne S Rasband, Kevin W Eliceiri
2012 Nature Methods  
For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis.  ...  The scientific image analysis program, ImageJ 1, 2 , known in previous incarnations as NIH Image 3 , is an early pioneer in image analysis.  ...  Acknowledgments The authors thank members of their research groups and software projects for helpful feedback on the article, in particular Curtis Rueden, Jimmy Fong and Johannes Schindelin for input on  ... 
doi:10.1038/nmeth.2089 pmid:22930834 pmcid:PMC5554542 fatcat:4vy47z777nawhcpuwzbf6mcosi

A Hitchhiker`s Guide through the Bio-image Analysis Software Universe [article]

Robert Haase, Elnaz Fazeli, David Legland, Michael Doube, Siân Culley, Ilya Belevich, Eija Jokitalo, Martin Schorb, Anna Klemm, Christian Tischer
2022 arXiv   pre-print
Modern research in the life sciences is unthinkable without computational methods for extracting, quantifying and visualizing information derived from biological microscopy imaging data.  ...  We give guidance on which aspects to consider when choosing the right platform, including aspects such as image data type, skills of the team, infrastructure and community at the institute and availability  ...  Acknowledgements We would like to thank Mafalda Sousa (I3S, Porto), Ignacio Arganda-Carreras (Universidad del Pais Vasco, Donostia-San Sebastian), Martin Jones (The Francis Crick Institute, London) for  ... 
arXiv:2204.07547v1 fatcat:np4c4gkclnaczckpwp3wp3xuqi

Easing batch image processing from OMERO: a new toolbox for ImageJ

Pierre Pouchin, Rayan Zoghlami, Rémi Valarcher, Maxence Delannoy, Manon Carvalho, Clémence Belle, Marc Mongy, Sophie Desset, Frédéric Brau
2022 F1000Research  
However, there is a lack of an easy-to-use generic tool to run a workflow on a batch of images without having to download them to local computers; and to automatically organize the results in OMERO.  ...  The Open Microscopy Environment Remote Objects (OMERO) is an open source image manager used by many biologists to store, organize, view and share microscopy images, while the open source software ImageJ  ...  Acknowledgements We thank Carole Rovere for providing the initial use case of this project in the context of a co-mentored internship.  ... 
doi:10.12688/f1000research.110385.1 pmid:35685190 pmcid:PMC9171289 fatcat:dsreuu5qm5ghlewq7k3xlg32fu

Integration of the ImageJ Ecosystem in KNIME Analytics Platform

Christian Dietz, Curtis T. Rueden, Stefan Helfrich, Ellen T. A. Dobson, Martin Horn, Jan Eglinger, Edward L. Evans, Dalton T. McLean, Tatiana Novitskaya, William A. Ricke, Nathan M. Sherer, Andries Zijlstra (+2 others)
2020 Frontiers in Computer Science  
Open-source software tools are often used for analysis of scientific image data due to their flexibility and transparency in dealing with rapidly evolving imaging technologies.  ...  ImageJ is a popular open-source image analysis platform, with contributions from a global community resulting in hundreds of specialized routines for a wide array of scientific tasks.  ...  For biological use case no. 3, we thank Tania Distler, Marco Michalski, and Luca Giorgetti for providing image and tracking data.  ... 
doi:10.3389/fcomp.2020.00008 pmid:32905440 pmcid:PMC7469687 fatcat:swuw4yfkpbd4hoplfbybs5beji

Dual-color dSTORM imaging and ThunderSTORM image reconstruction and analysis to study the spatial organization of the nuclear phosphatidylinositol phosphates

Peter Hoboth, Ondřej Šebesta, Martin Sztacho, Enrique Castano, Pavel Hozák
2021 MethodsX  
analysis using ImageJ2 plug-in ThunderSTORM to quantitatively evaluate the spatial distribution of nuclear PIP2. • Developed an ImageJ2 tool for the visualization of the Nearest Neighbor Distance analysis  ...  Therefore, here we provide the SMLM-based approach for the quantitative evaluation of the nuclear PIPs distribution while preserving the context of nuclear architecture.  ...  , to Iva Jelínková for her assistance with the cell cultures, to Pavel K říž for the lab management and to reviewers for helping us to improve our manuscript.  ... 
doi:10.1016/j.mex.2021.101372 fatcat:lcdvbijftnhphhbgcbgn3ukkgy

KNIME for reproducible cross-domain analysis of life science data

Alexander Fillbrunn, Christian Dietz, Julianus Pfeuffer, René Rahn, Gregory A. Landrum, Michael R. Berthold
2017 Journal of Biotechnology  
Experiments in the life sciences often involve tools from a variety of domains such as mass spectrometry, next generation sequencing, or image processing.  ...  Passing the data between those tools often involves complex scripts for controlling data flow, data transformation, and statistical analysis.  ...  ImageJ-Ops allows image processing algorithms to be used within a wide range of scientific applications, particularly KNIME and ImageJ and consequently, users need not choose between those applications  ... 
doi:10.1016/j.jbiotec.2017.07.028 pmid:28757290 fatcat:ia4aykx7ifdanhwvlpktijtps4

QuickFigures: A toolkit and ImageJ PlugIn to quickly transform microscope images into scientific figures

Gregory Mazo, Thomas Martin Deserno
2021 PLoS ONE  
Publications involving fluorescent microscopy images generally contain many panels with split channels, merged images, scale bars and label text.  ...  QuickFigures includes many helpful features that streamline the process of creating, aligning, and editing scientific figures.  ...  Images used for the demonstration videos and testing were taken using the microscopes within the Tsou Lab. I also acknowledge Dr. Brian O'Rourke, Avital Shulman and Dr.  ... 
doi:10.1371/journal.pone.0240280 pmid:34752463 pmcid:PMC8577749 fatcat:7g674v44sve5vnheyqs4vij6lu

Interactive design of GPU-accelerated Image Data Flow Graphs and cross-platform deployment using multi-lingual code generation [article]

Robert Haase, Akanskha Jain, Stephane Rigaud, Daniela Vorkel, Pradeep Rajasekhar, Theresa Suckert, Talley J Lambert, Juan Nunez-Iglesias, Daniel P Poole, Pavel Tomancak, Eugene W Myers
2020 bioRxiv   pre-print
We demonstrate the CLIJ-assistant for processing image data in multiple scenarios to highlight its general applicability.  ...  The current rise of graphics processing units (GPUs) in the context of image processing enables batch processing large amounts of image data at unprecedented speed.  ...  for demonstrating the potential of the CLIJ-assistant.  ... 
doi:10.1101/2020.11.19.386565 fatcat:qp6plzdskrbuzpgmywajpenu6q

Measurements of the Capillary Density and Diameter in the Choriocapillaris Using Optical Coherence Tomography Angiography

Yukari Fukazu, Ami Watanabe, Hideki Sekimukai, Yutaka Kato, Hiroaki Shintake, Kimihiro Imaizumi, Tetsuju Sekiryu
2018 JAPANESE ORTHOPTIC JOURNAL  
あたらしい眼科 34: 771-779, 2017. 11) Rueden CT, Schindelin J, Hiner MC, DeZonia BE, Walter AE, Arena ET, et al: ImageJ2: ImageJ for the next generation of scientific image data.  ...  Using SPECTRALIS ® OCT angiography module, the CC images were taken within 3x3 mm with a focus on the center of the fovea and exported at a range of 20-50 µm from the subretinal pigment epithelial border  ... 
doi:10.4263/jorthoptic.048f111 fatcat:shrssaiyufbkjas67uhdc7syd4
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