Computerized Tomography (CT) is a powerful radiographic imaging technology but the health risk due to the exposure of x-ray radiation has drawn wide concern. In this study, we propose to use kVp modulation to reduce the radiation dose and achieve the personalized low dose CT. Two sets of simulation are performed to demonstrate the effectiveness of kVp modulation and the corresponding calibration. The first simulation used the helical body phantom (HBP) that is an elliptical water cylinder with high density bone inserts. The second simulation uses the NCAT phantom to emulate the practical use of kVp modulation approach with region of interest (ROI) selected in the cardiac region. The kVp modulation profile could be optimized view by view based on the knowledge of patient attenuation. A second order correction is applied to eliminate the beam hardening artifacts. To simplify the calibration process, we first generate the calibration vectors for a few representative spectra and then acquire other calibration vectors with interpolation. The simulation results demonstrate the beam hardening artifacts in the images with kVp modulation can be eliminated with proper beam hardening correction. The results also show that the simplification of calibration did not impair the image quality: the calibration with the simplified and the complete vectors both eliminate the artifacts effectively and the results are comparable. In summary, this study demonstrates the feasibility of kVp modulation and gives a practical way to calibrate the high order beam hardening artifacts.
The utility of digital tomosynthesis has been shown for many clinical scenarios including post orthopedic surgery applications. However, two kinds of metal artifacts can influence diagnosis: undershooting and ripple. In this paper, we describe a novel metal artifact reduction (MAR) algorithm to reduce both of these artifacts within the filtered backprojection framework. First, metal areas that are prone to cause artifacts are identified in the raw projection images. These areas are filled with values similar to those in the local neighborhood. During the filtering step, the filled projection is free of undershooting due to the resulting smooth transition near the metal edge. Finally, the filled area is fused with the filtered raw projection data to recover the metal. Since the metal areas are recognized during the back projection step, anatomy and metal can be distinguished - reducing ripple artifacts. Phantom and clinical experiments were designed to quantitatively and qualitatively evaluate the algorithms. Based on phantom images with and without metal implants, the Artifact Spread Function (ASF) was used to quantify image quality in the ripple artifact area. The tail of the ASF with MAR decreases from in-plane to out-of-plane, implying a good artifact reduction, while the ASF without MAR remains high over a wider range. An intensity plot was utilized to analyze the edge of undershooting areas. The results illustrate that MAR reduces undershooting while preserving the edge and size of the metal. Clinical images evaluated by physicists and technologists agree with these quantitative results to further demonstrate the algorithm’s effectiveness.
KEYWORDS: Monte Carlo methods, Modulation transfer functions, X-rays, Collimators, Computer simulations, Scintillators, X-ray imaging, Sensors, Computed tomography, Photon transport
Ray-tracing based simulation methods are widely used in modeling X-ray propagation, detection and imaging. While
most of the existing simulation methods rely on analytical modeling, a novel hybrid approach comprising of statistical
modeling and analytical approaches, is proposed here.
Our hybrid simulator is a unique combination of analytical modeling for evoking the fundamentals of X-ray transport
through ray-tracing, and a look-up-table (LUT) based approach for integrating it with the Monte Carlo simulations that
model optical photon-transport within scintillator. The LUT approach for scintillation-based X-ray detection invokes
depth-dependent gain factors to account for intra-pixel absorption and light-transport, together with incident-angle
dependent effects for inter-pixel X-ray absorption (parallax effect). The model simulates the post-patient collimator for
scatter-rejection, as an X-ray shadow on scintillator, while handling its position with respect to the pixel boundary, by a
smart over-sampling strategy for high efficiency.
We have validated this simulator for computed tomography system-simulations, by using real data from GE Brivo
CT385. The level of accuracy of image noise and spatial resolution is better than 98%. We have used the simulator for
designing the post-patient collimator, and measured modulation transfer function (MTF) for different widths of the
collimator plate.
Validation and simulation study clearly demonstrates that the hybrid simulator is an accurate, reliable, efficient tool for
realistic system-level simulations. It could be deployed for research, design and development purposes to model any
scintillator-based X-ray imaging-system (2-dimensional and 3-dimensional), while being equally applicable for medical
and industrial imaging.
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