M
Mark Hiner
Researcher at University of Wisconsin-Madison
Publications - 21
Citations - 8557
Mark Hiner is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Interoperability & Image processing. The author has an hindex of 8, co-authored 19 publications receiving 6959 citations.
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ImageJ2: ImageJ for the next generation of scientific image data
Curtis Rueden,Johannes Schindelin,Johannes Schindelin,Mark Hiner,Barry E. DeZonia,Alison E. Walter,Alison E. Walter,Ellen T. Arena,Ellen T. Arena,Kevin W. Eliceiri,Kevin W. Eliceiri +10 more
TL;DR: ImageJ2 as mentioned in this paper is the next generation of ImageJ, which provides a host of new functionality and separates concerns, fully decoupling the data model from the user interface.
Posted Content
ImageJ2: ImageJ for the next generation of scientific image data
Curtis Rueden,Johannes Schindelin,Johannes Schindelin,Mark Hiner,Barry E. DeZonia,Alison E. Walter,Alison E. Walter,Ellen T. Arena,Ellen T. Arena,Kevin W. Eliceiri,Kevin W. Eliceiri +10 more
TL;DR: The entire ImageJ codebase was rewrote, engineering a redesigned plugin mechanism intended to facilitate extensibility at every level, with the goal of creating a more powerful tool that continues to serve the existing community while addressing a wider range of scientific requirements.
Journal ArticleDOI
The ImageJ ecosystem: An open platform for biomedical image analysis
TL;DR: The ImageJ project is used 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 community.
Journal ArticleDOI
Quantitating the cell: turning images into numbers with ImageJ.
Ellen T. Arena,Ellen T. Arena,Curtis Rueden,Mark Hiner,Shulei Wang,Ming Yuan,Ming Yuan,Kevin W. Eliceiri,Kevin W. Eliceiri +8 more
TL;DR: An overview of prominent imaging processing approaches in ImageJ is given that are of particular interest for biological imaging and that illustrate the functionality of ImageJ and other open source image analysis software.
Journal ArticleDOI
SCIFIO: an extensible framework to support scientific image formats.
TL;DR: The core of SCIFIO is its modular definition of formats, the design of which clearly outlines the components of image I/O to encourage extensibility, facilitated by the dynamic discovery of the SciJava plugin framework.