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ImageJ is a public domain Java image processing program inspired by NIH Image for the Macintosh. It runs, either as an online applet or as a downloadable application, on any computer with a Java 1.4 or later virtual machine. Downloadable distributions are available for Windows, Mac OS, Mac OS X and Linux.
MRmap is a flexible software tool that enables T1, T2, and T2* mapping from source images of multiple types of pulse sequences (IR-prepared multi-image T1 mapping, Look-Locker/ TOMROP T1 mapping, MOLLI T1 mapping; single- and multi-echo T2/ T2* mapping).
MRmap is a pure research tool and is not intended for any diagnostic or clinical use.
Snofyre is an open source, service oriented API for creating SNOMED CT enabled applications in Java. It provides a number of SNOMED CT related services out of the box. These services can be used:
Snofyre API aims to
A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
A C++ package for low-frequency bio-electromagnetism solving forward problems in the field of EEG and MEG.
The complexity of cellular networks is an outstanding challenge for documentation, visualisation and mathematical modelling. In this project, we develop a new way to describe these networks that minimises the combinatorial complexity and allows an automatic visualisation and export of mathematical (ODE/rulebased) models.
Features:
ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.
ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.
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posted by holger on openCDMS 6 years 8 months
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posted by demski on Glucosio 8 years 6 days
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posted by demski on Free D Path 9 years 1 month
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posted by dreaswar on AuShadha 9 years 4 months