ANKAphase processes X-ray inline phase-contrast radiographs by reconstructing the projected thickness of the object(s) imaged. The tool uses a single-distance non-iterative phase-retrieval algorithm described in a paper by D. Paganin et al. J. Microsc. vol. 206 (2002). It has an easy-to-use graphical user interface and can be run either as a standalone application or as a plugin to ImageJ. It works on powerful clusters but also on your office laptop.
3D analysis software for scientific and industrial data. Different application areas: Materials Science, Quality Assurance in Industrial Environments, Electronics, Digital Rock Analysis etc. It enables users to perform interactive visualization and computation on 3D data sets. The Avizo interface is modelled on the visual programming. Users manipulate data and module components, organized in an interactive graph representation (called Pool), or in a Tree view. Data and modules can be interactively connected together, and controlled with several parameters, creating a visual processing network whose output is displayed in a 3D viewer. With this interface, complex data can be interactively explored and analyzed by applying a controlled sequence of computation and display processes resulting in a meaningful visual representation and associated derived data.
GATE is an opensource software package developed by the international OpenGATE collaboration and dedicated to numerical simulations in medical imaging and radiotherapy. It currently supports simulations of Emission Tomography (Positron Emission Tomography - PET and Single Photon Emission Computed Tomography - SPECT), Computed Tomography (CT), Optical Imaging (Bioluminescence and Fluorescence) and Radiotherapy experiments.
Hybrid distributed code for high speed tomographic reconstruction with iterative reconstruction and a priori knowledge capabilities. PyHST2 (formerly known as PyHST) has been engineered to sustain the high data flow typical of the third generation synchrotron facilities (10 terabytes per experiment) by adopting a distributed and pipelined architecture. The code implements, beside a default filtered backprojection reconstruction, iterative reconstruction techniques with a-priori knowledge. The latter are used to improve the reconstruction quality or in order to reduce the required data volume and reach a given quality goal. The implemented a-priori knowledge techniques are based on the total variation penalisation and a new recently found convex functional which is based on overlapping patches.
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