The focal spot size of x-ray tubes as well as the pixel size and scintillator thickness limit the spatial resolution of projection images as they result in blurring and degradation of the system’s point spread function. Deblurring of those images has been a topic of research for several decades. However, it is not solved in general. In this manuscript the application of a convolutional neural network for the deblurring of x-ray projection images is presented and compared to a standard deblurrig technique. The advantages of the neural network in terms of image quality and applicability are demonstrated with simulations and measurements originating from table top and gantry based micro-CT systems.
X-ray scatter leads to one of the major artifacts limiting the image quality in cone-beam CT (CBCT). Hence the interest to perform an accurate scatter correction is very high. A particularly large amount of scatter is created in CBCT, due to the large cone-angle and the small distance between the rotation axis and the detector. Even if an anti-scatter grid is used, a scatter correction is necessary. The performance of an accurate scatter correction is difficult, especially when the data are additionally truncated due to a small field of measurement (FOM) (e.g. dental CT systems or C-Arm CT systems). In addition to the image degradation due to scatter artifacts, numerous CBCT artifacts like beam-hardening artifacts and cone-beam artifacts contribute to a further reduction in image quality. In this paper different detruncation methods are compared with respect to scatter to find a quantitative scatter correction approach for truncated CBCT data. The evaluation shows that a precise detruncation is crucial for an appropriate scatter correction. Additionally, the general image quality limit is enhanced by performing further artifact correction methods to reconstruct a nearly artifact-free CBCT volume.
Mobile and compact C-arm systems are routinely used in interventional procedures for fluoroscopic CT imaging. The mechanical requirements guarantee for a maximum of flexibility and mobility but restrict the mechanical rotation range (e.g. 165°) and the lateral size of the field of measurement (FOM), typically about 160 mm. Recently, the rotate-plus-shift trajectory for the acquisition of complete datasets from 180° minus fan-angle has been published.1, 2 Here, we combine the rotate-plus-shift trajectory with a shifted detector approach for a fully motorized C-arm system. As the isocenter in non-centric C-arms can be freely chosen, the shifted detector can be equally well absorbed with an offset of the C parallel to the transaxial detector direction. The typical rotation range of 360° used in shifted detector trajectories is replaced by a double rotate-plus-shift scan requiring a rotation range of at least 180° minus fan-angle. The trajectory increasing the diameter of the FOM by up to a factor of two is presented and the practical application of variations with an asymmetric FOM is shown. For image reconstruction we use our modified FDK algorithm that is equipped with a generalized redundancy weight. The presented trajectory can increase the applicability and flexibility of C-arm systems and has the potential to perform intra-operative large volume control or overview scans and thus reduce the patient’s risk.
KEYWORDS: Sensors, Fluctuations and noise, Stereoscopy, Image quality, Data acquisition, Computed tomography, Prototyping, 3D image processing, Physics, Cancer
In the last decade C–arm–based cone–beam CT became a widely used modality for intraoperative imaging. Typically a C–arm scan is performed using a circle–like trajectory around a region of interest. Therefor an angular range of at least 180° plus fan–angle must be covered to ensure a completely sampled data set. This fact defines some constraints on the geometry and technical specifications of a C–arm system, for example a larger C radius or a smaller C opening respectively. These technical modifications are usually not beneficial in terms of handling and usability of the C–arm during classical 2D applications like fluoroscopy. The method proposed in this paper relaxes the constraint of 180◦ plus fan–angle rotation to acquire a complete data set. The proposed C–arm trajectory requires a motorization of the orbital axis of the C and of ideally two orthogonal axis in the C plane. The trajectory consists of three parts: A rotation of the C around a defined iso–center and two translational movements parallel to the detector plane at the begin and at the end of the rotation. Combining these three parts to one trajectory enables for the acquisition of a completely sampled dataset using only 180° minus fan–angle of rotation. To evaluate the method we show animal and cadaver scans acquired with a mobile C-arm prototype. We expect that the transition of this method into clinical routine will lead to a much broader use of intraoperative 3D imaging in a wide field of clinical applications.
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