Search Results for "big data visualization"

PyVE is image analysis and Visualization Environment focused at clinical use. At the core of it there is a powerful viewer for displaying 3D datasets (MRI, PET, CT) based on VTK. It all comes precompiled allowing painless access to Python (2.x), the ITK toolkit for image analysis, numpy/scipy for numerical calculations, Qt and PyQt4 for the development Graphical User Interfaces. It is what you need for fast prototyping and development of more complex projects.

...The application was developed in Python and uses Blender (an open source program) to produce detailed 3D representations of raw and processed data. Py3DN is described in the paper: Aguiar P et al, "Versatile morphometric analysis and visualization of the three-dimensional structure of neurons", Neuroinformatics, 2013, 11(4):393-403 doi: 10.1007/s12021-013-9188-z

The MeVisLab Community project provides add-on modules that extend the functionality of the MeVisLab software. The modules are provided and maintained by the MeVisLab developer community and can be compiled with the public MeVisLab SDK.

This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...

A python class and GUI for visualization of data generated by the medical treatment planning software TRiP. Project has been moved to http://github.com/pytrip/pytrip on 15.06.2016

BioImageXD - free open source software for analysis, processing and 3D rendering of multi dimensional, multi data channel, time series image data from microscopy and other sources.

The OpenCMISS-Zinc Library (opencmiss.org/zinc), or Zinc, is a software library for building interactive graphical modelling and visualisation applications. Models are represented in Zinc as mathematical fields defined over domains, including finite elements with support for high-order basis functions, complex parameter mappings and time variation, and image-based fields. Further fields can be defined by mathematical expressions and algorithms on existing fields, including image...

This toolkit allows complete control of a microscopy setup from Labview, Matlab, Scilab, Python, .Net, VB, IgorPro, Mathematica and more. Included is a standalone program for image acquisition and scripting control of a scientific microscope.

Inter University Multi-Modal Imaging

MIVF - Medical Imaging and Visualization Factory, is a framework for medical applications. It supplies a platform, in which image processing and 3D visualization algorithms can be employed as reusable components (functional modules or plugins).

QuickDicom is an easy to use dicom medical imaging package for Mac OSX, providing QuickLook, Spotlight, Quartz Composer, Window/Level and a dicom file analyzer. Also included is the iiDicom Framework for image/dictionary usage in Objective C and Python.

Mainly a browser for medical patients documents. For now, it works for displaying radiology images in DICOM format. It supports Query/Retrieve. Build on Python, wxPython and ZODB.

BLIX is a cross-platform set of Python extension modules and Python scripts for Blender (www.blender.org). These scripts add camera calibration, 3D reconstruction and rigid body orientation to Blender.

Computer Controlled Optical Microscopy is a package to enable camera equipped microscopes to generate multi-modal time-lapse image sequences of 3D volumes. This is achieved by periodically changing optical settings, xyz positions and acquiring images.

A set of components based upon the PyGTK architecture for interactively displaying time-sampled data in the form of "strip charts".

This is a collection of different little tools written in MATLAB, JAVA, Python. They all have to to do with Imaging & Microscopy for life science research and related topics or problems. Some of them are meant to be used with ImageJ and MicroManager.

The 3D Slicer is freely available, open-source software for visualization, registration, segmentation, and quantification of medical image data. Follow the link for more info: http://slicer.org