Open Source Unix Shell Medical Physics Software

DRAMMS is a software package designed for 2D-to-2D and 3D-to-3D deformable medical image registration tasks. Released by Section of Biomedical Image Analysis (SBIA) at the University of Pennsylvania. Some typical applications of DRAMMS include, -- Cross-subject registration of the same organ (can be brain, breast, cardiac, etc); -- Mono- and Multi-modality registration (MRI, CT, histology); -- Longitudinal registration (pediatric brain growth, cancer development, mouse brain development, etc); -- Registration under missing correspondences (e.g., vascular lesions, tumors, histological cuts). DRAMMS runs in command line in UNIX/Mac OS, It accepts Nifti/ANALYZE/MetaImage image formats. It is fully-automatic --- takes two input images, and generates a registered image and (optionally) the deformation field. More information (installation, tutorial, manual, demonstration, FAQ, etc) can be found at http://www.rad.upenn.edu/sbia/software/dramms/ .

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).

Various utilities useful for handling PET data esp. of stationary planar PEM, including fully 3D ML-EM based image reconstruction, real time viewing of scanning image and the KDE based GUI for scanning, viewing and image reconstruction.