Search Results for "document management c"

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 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...

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...

Modern Open Source LIMS (Laboratory Information Management System) · Professionally supported by experts The Bika code was migrated to https://github.com/bikalims Getting Started: https://github.com/bikalims/bika.lims/blob/main/README.md Modern Bika releases are built on the Senaite LIMS core, the LIMS that originated as a Bika fork. It is therefore as new and modern as Senaite, frequently upgraded and has many very useful add-ons. Bika expands on Senaite's lean design by adding...

PROJECT MOVED: see http://www.vmtk.org for up-to-date information. Libraries and tools for 3D reconstruction, geometric analysis, mesh generation and surface data analysis in image-based blood vessel modeling.

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.

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