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Before the release of ImageJ in 1997, a similar freeware image analysis program known as NIH Image had been developed in Object Pascal for Macintosh computers running pre-OS X operating systems. Further development of this code continues in the form of Image SXM , a variant tailored for physical research of scanning microscope images.
Initiated in 2006 and currently funded by NIH Grant number: 1R24EB029173, [1] [2] NITRC's mission is to provide a user-friendly knowledge environment that enables the distribution, enhancement, and adoption of neuroimaging tools and resources and has expanded from MR to Imaging Genomics, EEG/MEG, PET/SPECT, CT, optical imaging, clinical neuroinformatics, and computational neuroscience.
One of Fiji's principal aims is to make the installation of ImageJ, Java, Java 3D, the plugins, and further convenient components, as easy as possible. As a consequence, Fiji enjoys more and more active users.
Neuroimaging software is used to study the structure and function of the brain. To see an NIH Blueprint for Neuroscience Research funded clearinghouse of many of these software applications, as well as hardware, etc. go to the NITRC web site. 3D Slicer Extensible, free open source multi-purpose software for visualization and analysis.
Image SXM is an image analysis software specialized in scanning microscope images. It is based on the public domain software NIH Image (now ImageJ from the National Institutes of Health) and extended to handle scanning microscope images, especially of the SxM formats (SAM, SCM, SEM, SFM, SLM, SNOM, SPM, STM), hence its name.
Conda is an open source, [16] cross-platform, [17] language-agnostic [18] package manager and environment management system [19] [20] [50] that installs, runs, and updates packages and their dependencies. [16] It was created for Python programs, but it can package and distribute software for any language (e.g., R), including multi-language ...
pip (also known by Python 3's alias pip3) is a package-management system written in Python and is used to install and manage software packages. [4] The Python Software Foundation recommends using pip for installing Python applications and its dependencies during deployment. [5] Pip connects to an online repository of public packages, called the ...
This makes it possible for multiple users on multiple machines to share files and storage resources. Distributed file systems differ in their performance, mutability of content, handling of concurrent writes, handling of permanent or temporary loss of nodes or storage, and their policy of storing content.