Open Source Python Medical Physics Software

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 graphical user interfaces and/or via the command-line. See our YouTube channel for tutorial videos via the homepage. The applications are all built out of a uniform user-interface framework that provides a very high level (Qt) interface to powerful image processing and scientific visualisation algorithms from the Insight Toolkit (ITK) and Visualisation Toolkit (VTK). The framework allows one to build stand-alone medical imaging applications quickly and easily.

Objective: The program is being developed for three main purposes: A. Dose assessment after acute whole body exposure. B. Dose assessment in partial body exposure C. Dose assessment after protracted and fractioned exposure 2. Applicability The following DNA lesions can be investigated with the help of the program: A. Dicentrics B. γ-H2AX foci C. Micronuclei D. PCC fragments It is planned to include Comet assays as well RICA assays in the future.

This is Python based program for analysis of radiochromic films. Similar to filmQAPro, but free. It can be used to study Gafchromic EBTX films.

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.