Open Source Mac Medical Software

A simple yet powerful mesh generator based on MATLAB/GNU Octave language, creating finite-element mesh from surfaces or arbitrary 3D volumetric images (such as MRI/CT scans) with fully automatic workflows.

Plastimatch is an open source software for image computation. Our main focus is high-performance volumetric registration of medical images, such as X-ray computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET).

An application written in C#, which will assist you in calculating your Body Mass Index.

[2015-06-12] Orthanc has left SourceForge. All the downloads are now available directly from our official Website: http://www.orthanc-server.com/browse.php

Users load multiecho MRI data and draw ROIs. AnalyzeNNLS creates a T2 distribution from the averaged decay data. Regional fractions and geometric T2 times can be determined. Please reference: Bjarnason TA, Mitchell JR. JMR 206:200-4 (2010). Temporal Phase Correction included in version 2.5. If you use this functionality, please reference: Bjarnason TA, Laule C, Bluman J, Kozlowski P. JMR 232:22-31 (2013).

CUDA-SPHERE-FWD-MEEG is a CUDA C based toolkit which provides a GPU based implementation of the spherical model forward solution for the 306 channel Elekta Neuromag MEG system and the EEG. The 1-Sphere forward solution for the MEG and the 4-Sphere forward solution for the EEG is implemented in CUDA C and an accelerated solution is obtained using the NVIDIA GPU when the solution is calculated for a large number of dipoles (on the order of 15000 and above) and sensor locations. Speedup by a factor of 22 and 32 is obtained for the EEG and MEG solution respectively when compared to the fastest CPU implementation available in the public domain. The complete source code and pre-compiled binaries are also made available via an open source license (GPL Version 3). A CUDA enabled NVIDIA graphics card is required to use the software.

Moved to http://parkermills.github.io/MRI-PDQ/

This project, developed at UCL London, provides code for tomographic reconstruction. NiftyRec is written in C and has Python and Matlab extensions. Computationally intensive functions have a GPU accelerated version based on CUDA.

SimPET (http://www.sim-pet.org) is an open, efficient, and user‐friendly online platform for the generation of synthetic brain PET datasets. The platform offers the ability to generate realistic activity and attenuation maps from patient's PET/CT and MRI images. These maps can then be simulated, and sinograms and simulated images can be downloaded. More advanced features can be obtained by using the SimPET scripts: https://github.com/txusser/brainviset_simset https://github.com/txusser/simpet (New version pre-alpha) You can also upload your own phantoms to simulate. Currently the platform incorporates MC models for the GE Advance, GE Discovery ST and Siemens mCT. More models are on the way. You can also access all the previously simulated datasets from the dev team to test your quantification pipeline (Files section in this page). This project is an open collaboration between IDIS (www.idisantiago.es), Qubiotech (www.qubiotech.es), and FGUMA (www.fguma.es).