Geometry calibration and image reconstruction for carbon-nanotube-based multisource and multidetector CT

Carbon nanotube-based multiple source C-arm CT system: feasibility study with prototype system

To extend the field of view while reducing dimensions of the C-arm, we propose a carbon nanotube (CNT)-based C-arm computed tomography (CT) system with multiple X-ray sources. A prototype system was developed using three CNT X-ray sources, enabling a feasibility study. Geometry calibration and image reconstruction were performed to improve the quality of image acquisition. However, the geometry of the prototype system led to projection truncation for each source and an overlap region of object area covered by each source in the two-dimensional Radon space, necessitating specific corrective measures. We addressed these problems by implementing truncation correction and applying weighting techniques to the overlap region during the image reconstruction phase. Furthermore, to enable image reconstruction with a scan angle less than 360°, we designed a weighting function to solve data redundancy caused by the short scan angle. The accuracy of the geometry calibration method was evaluated via computer simulations. We also quantified the improvements in reconstructed image quality using mean-squared error and structural similarity. Moreover, detector lag correction was applied to address the afterglow observed in the experimental data obtained from the prototype system. Our evaluation of image quality involved comparing reconstructed images obtained with and without incorporating the geometry calibration results and images with and without lag correction. The outcomes of our simulation study and experimental investigation demonstrated the efficacy of our proposed geometry calibration, image reconstruction method, and lag correction in reducing image artifacts.

Online Calibration of a Linear Micro Tomosynthesis Scanner

In a linear tomosynthesis scanner designed for imaging histologic samples of several centimeters size at 10 µm resolution, the mechanical instability of the scanning stage (±10 µm) exceeded the resolution of the image system, making it necessary to determine the trajectory of the stage for each scan to avoid blurring and artifacts in the images that would arise from the errors in the geometric information used in 3D reconstruction. We present a method for online calibration by attaching a layer of randomly dispersed micro glass beads or calcium particles to the bottom of the sample stage. The method was based on a parametric representation of the rigid body motion of the sample stage-marker layer assembly. The marker layer was easy to produce and proven effective in the calibration procedure.

Online Geometric Calibration of a Hybrid CT System for Ultrahigh-Resolution Imaging

A hybrid imaging system consisting of a standard computed tomography (CT) scanner and a low-profile photon-counting detector insert in contact with the patient's body has been used to produce ultrahigh-resolution images in a limited volume in chest scans of patients. The detector insert is placed on the patient bed as needed and not attached. Thus, its position and orientation in the scanner is dependent on the patient's position and scan settings. To allow accurate image reconstruction, we devised a method of determining the relative geometry of the detector insert and the CT scanner for each scan using fiducial markers. This method uses an iterative registration algorithm to align the markers in the reconstructed volume from the detector insert to that of the concurrent CT scan. After obtaining precise geometric information of the detector insert relative to the CT scanner, the two complementary sets of images are summed together to create a detailed image with reduced artifacts.