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The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with...

gVirtualXRay is a C++ library to simulate X-ray imaging. It is based on the Beer-Lambert law to compute the absorption of light (i.e. photons) by 3D objects (here polygon meshes). It is implemented on the graphics processing unit (GPU) using the OpenGL Shading Language (GLSL). SimpleGVXR is a smaller library build on the top of gVirtualXRay. It provides wrappers to Python, R, Ruby, Tcl, C#, Java, and GNU Octave.

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...

The OpenVCT project is designed to provide a common platform for performing Virtual Clinical Trials of medical imaging. OpenVCT provides tools for simulation of patient accrual and reader studies of medical imaging devices, simulating by simulating cohorts of patients and readers. OpenVCT uses common data standards, such as DICOM, to ensure inter-compatibility.

Copenhagen Computed Tomography Toolbox is a collection of applications and libraries for flexible and efficient CT reconstruction. The toolbox apps generally take a set of projections (X-ray intensity measurements) and filter and back project them in order to recreate the image or volume that the projections represent. The project includes both mostly informative CPU implementations and highly efficient GPU implementations. Regular releases are hosted at the Python Package Index.

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.