As low-dose computed tomography becomes a hot issue in the field of clinical x-ray imaging, photon counting detectors
have drawn great attention as alternative x-ray image sensors. Even though photon-counting image sensors have several
advantages over the integration-type sensors, such as low noise and high DQE, they are known to be more sensitive to
the various experimental conditions like temperature and electric drift. Particularly, time-varying detector response
during the CT scan is troublesome in photon-counting-detector-based CTs. To overcome the time-varying behavior of
the image sensor during the CT scan, we developed a flat-field correction method together with an automated scanning
mechanism. We acquired the flat-field images and projection data every view alternatively. When we took the flat-field
image, we moved down the imaging sample away from the field-of-view with aid of computer controlled linear
positioning stage. Then, we corrected the flat-field effects view-by-view with the flat-field image taken at given view.
With a CdTe photon-counting image sensor (XRI-UNO, IMATEK), we took CT images of small bugs. The CT images
reconstructed with the proposed flat-field correction method were much superior to the ones reconstructed with the
conventional flat-field correction method.
Computed Tomography (CT) using Carbon Nanotube (CNT) x-ray source is a technique of generating reconstruction
images of the structure of teeth sample. A proto type CNT x-ray CT was designed for medical imaging to examine
whether it could be used to analysis the equipment of medical and industrial application. The CNT field emitter array was grown on silicon substrate through a resist-assisted patterning (RAP) process. The field emission properties showed a gate turn-on field of 3.8 V/μm at an anode emission current of 0.5 mA. The author demonstrated the x-ray source with four electrode structures utilizing the CNT emitter. The acquisitioned images were reconstructed by filtered back projection (FBP) method.
Scan time of spectral-CTs is much longer than conventional CTs due to limited number of x-ray photons detectable by
photon-counting detectors. However, the spectral pixel information in spectral-CT has much richer information on
physiological and pathological status of the tissues than the
CT-number in conventional CT, which makes the spectral-
CT one of the promising future imaging modalities. One simple way to reduce the scan time in spectral-CT imaging is to
reduce the number of views in the acquisition of projection data. But, this may result in poorer SNR and strong streak
artifacts which can severely compromise the image quality. In this work, spectral-CT projection data were obtained from
a lab-built spectral-CT consisting of a single CdTe photon counting detector, a micro-focus x-ray tube and scan
mechanics. For the image reconstruction, we used two iterative image reconstruction methods, the simultaneous iterative
reconstruction technique (SIRT) and the total variation minimization based on conjugate gradient method (CG-TV),
along with the filtered back-projection (FBP) to compare the image quality. From the imaging of the iodine containing
phantoms, we have observed that SIRT and CG-TV are superior to the FBP method in terms of SNR and streak artifacts.
The use of flat-panel detectors (FPDs) is becoming increasingly popular in the cone beam volume and multi-slice
CT imaging. But due to the deficient semiconductor array processing, the diagnostic quality of the FPD-based CT
images in both CT systems is degraded by different types of artifacts known as the ring and radiant artifacts. Several
techniques have been already published in eliminating the stripe artifacts from the projection data of the multi-slice
CT system or in other words, from the sinogram image with a view to suppress the ring and radiant artifacts from
the 2-D reconstructed CT images. On the other hand, till now a few articles have been reported to remove the
artifacts from the cone beam CT images. In this paper, an effective approach is presented to eliminate the artifacts
from the cone beam projection data using the sinogram based stripe artifact removal methods. The improvement in
the required diagnostic quality is achieved by applying them both in horizontal and vertical sinograms constituted
sequentially from the stacked cone beam projections. Finally, some real CT images have been used to demonstrate
the effectiveness of the proposed technique in eliminating the ring and radiant artifacts from the cone beam volume
CT images. A comparative study with the conventional sinogram based approaches is also presented to see the
effectiveness of the proposed technique.
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