CONRAD--a software framework for cone-beam imaging in radiology.

Purpose: In the community of x-ray imaging, there is a multitude of tools and applications that are used in scientific practice. Many of these tools are proprietary and can only be used within a certain lab. Often the same algorithm is implemented multiple times by different groups in order to enable comparison.

Respiratory Motion Compensation Using Diaphragm Tracking for Cone-Beam C-Arm CT: A Simulation and a Phantom Study.

Long acquisition times lead to image artifacts in thoracic C-arm CT. Motion blur caused by respiratory motion leads to decreased image quality in many clinical applications. We introduce an image-based method to estimate and compensate respiratory motion in C-arm CT based on diaphragm motion.

Prior-based automatic segmentation of the carotid artery lumen in TOF MRA (PASCAL).

In current clinical practice, examinations of the carotid artery bifurcation are commonly carried out with Computed Tomography Angiography (CTA) or contrast-enhanced Magnetic Resonance Angiography (ceMRA). Quantitative information about vessel morphology, extracted from segmentations, is promising for diagnosis of vessel pathologies. However, both above-mentioned techniques require the administration of contrast media.

Fast simulation of x-ray projections of spline-based surfaces using an append buffer.

Many scientists in the field of x-ray imaging rely on the simulation of x-ray images. As the phantom models become more and more realistic, their projection requires high computational effort. Since x-ray images are based on transmission, many standard graphics acceleration algorithms cannot be applied to this task.

Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT.

Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring.

Comparing performance of many-core CPUs and GPUs for static and motion compensated reconstruction of C-arm CT data.

Purpose: Interventional reconstruction of 3-D volumetric data from C-arm CT projections is a computationally demanding task. Hardware optimization is not an option but mandatory for interventional image processing and, in particular, for image reconstruction due to the high demands on performance. Several groups have published fast analytical 3-D reconstruction on highly parallel hardware such as GPUs to mitigate this issue.