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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

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

Popis výsledku anglicky

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

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10608 - Biochemistry and molecular biology

Projekt

<a href="/cs/project/EF16_013%2F0001791" target="_blank" >EF16_013/0001791: IT4Innovations národní superpočítačové centrum - cesta k exascale</a><br>

Návaznosti

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

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Protein Science

ISSN

0961-8368

e-ISSN

—

Svazek periodika

Volume 30

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

16

Strana od-do

234-249

Kód UT WoS článku

000590643800001

EID výsledku v databázi Scopus

2-s2.0-85096810136