The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F21%3A10246055" target="_blank" >RIV/61989100:27740/21:10246055 - isvavai.cz</a>

Result on the web

<a href="https://onlinelibrary.wiley.com/doi/10.1002/pro.3993" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/pro.3993</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/pro.3993" target="_blank" >10.1002/pro.3993</a>

Result language

angličtina

Original language name

The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis

Original language description

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open-source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ&apos;s diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user-centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem. (C) 2020 The Protein Society

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10608 - Biochemistry and molecular biology

Project

<a href="/en/project/EF16_013%2F0001791" target="_blank" >EF16_013/0001791: IT4Innovations national supercomputing center - path to exascale</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Protein Science

ISSN

0961-8368

e-ISSN

—

Volume of the periodical

Volume 30

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

16

Pages from-to

234-249

UT code for WoS article

000590643800001

EID of the result in the Scopus database

2-s2.0-85096810136