Simulation of PIXSCAN, a photon counting micro-CT for small animal imaging

A geometrical calibration method for the PIXSCAN micro-CT scanner

Reconstruction in Cone-Beam Tomography can suffer from artifacts due to geometrical misalignments of the source-detector system. They can be avoided by a complete and precise description of the system. We present a high precision method for the geometric calibration for the PIXSCAN, a small animal X-ray CT scanner demonstrator based on hybrid pixel detectors (XPAD2). The specificities of the XP...

Single Photon Counting X-Ray Micro-Imaging of Biological Samples

Development of Ultrafast Laser-based Micro-ct System for Small Animal Imaging

We investigated performance of ultrafast (30 fs –200 fs) laser-based x-ray source as an alternative to a microfocal x-ray tube used in micro-CT systems. A number of solid targets including Ge, Mo, Rh, Ag, Sn, Ba, La, Nd with matching filters was used. We optimized conditions for x-rays generation, measured x-ray spectra and obtained images of small animals using various characteristic x-ray lin...

Cone Beam Micro-CT System for Small Animal Imaging and Performance Evaluation

A prototype cone-beam micro-CT system for small animal imaging has been developed by our group recently, which consists of a microfocus X-ray source, a three-dimensional programmable stage with object holder, and a flat-panel X-ray detector. It has a large field of view (FOV), which can acquire the whole body imaging of a normal-size mouse in a single scan which usually takes about several minu...

A Ring Artifact Correction Method: Validation by Micro-CT Imaging with Flat-Panel Detectors and a 2D Photon-Counting Detector

We introduce an efficient ring artifact correction method for a cone-beam computed tomography (CT). In the first step, we correct the defective pixels whose values are close to zero or saturated in the projection domain. In the second step, we compute the mean value at each detector element along the view angle in the sinogram to obtain the one-dimensional (1D) mean vector, and we then compute ...