The short-scan trajectory in cone-beam CT (CBCT) imaging effectively decreases the scan time and the patient dose by excluding the redundant measurements. Also, the offset scan geometry improves the efficacy of the detector utilization by achieving the larger field-of-view (FOV) than the normal use. However, the asymmetric HU value recovery in the sinus of the patient has been consistently observed whenever we use the short-scan trajectory with offset detector. Typically, the reconstruction of short-scan CBCT with an offset detector may lead to inaccuracies in the CT attenuation values within the reconstructed image. This is particularly noticeable away from the beam center due to insufficient data consistency. Also, other physical factors (ex) beam-hardening, scattering effect) and truncation artifact due to the small FOV may contribute to asymmetric sinus representation. In this study, we investigate the potential causes of the asymmetric sinus representation through the artifact study. We used a Monte-Carlo (MC) simulation to reproduce asymmetric HU value for the ease artifact study.
KEYWORDS: Computed tomography, Medical imaging, Denoising, Image sharpness, Education and training, Image quality, Tunable filters, Image restoration, Image filtering, Signal to noise ratio
Self-supervised learning for CT image denoising is a promising technique because it does not require clean target data that are usually unavailable in the clinic. Noise2void (N2V) is one of the famous methods to denoise the image without paired target data and it has been used to denoise optical images and also medical images such as MRI, and CT. However, the performance of the N2V is still limited due to the restricted receptive field of the network and it decreases the prediction performance for CT images that have complex image context and non-uniform Poisson random noise. Thus, we proposed enhanced N2V that utilizes penalty-driven network optimization to further denoise the images while preserving the important details. We used the total variation term to further denoise the image and also the laplacian pyramids term to preserve the important edges of the image. The degree of the influence of each penalty term is controlled by the hyperparameter value and they are optimized to achieve the best image quality in terms of noise level and structure sharpness. For the experiment, the real dental CBCT projection data were used to train the network in the projection domain. After the network training, the test results were reconstructed and compared at each different dose level. Meanwhile, PSNR, SNR, and a line profile were also evaluated to quantitatively compare the original FDK images, and proposed method. In conclusion, the proposed method achieved further denoises the image than N2V even preserving the details. By penalty-driven optimization, the network was able to learn the spectral features of the image while still the receptive field is limited to avoid identity mapping. We hope that our method would increase the practical utility of network-based CT images denoising that usually the target data are unavailable.
KEYWORDS: Collimators, Cameras, Sensors, 3D image processing, Gamma radiation, Reconstruction algorithms, Monte Carlo methods, Gamma ray imaging, Contamination, Cesium
Assessment of the distribution of radioactive contamination is an essential process for safe decommissioning. Gamma cameras are widely used to investigate the hot spots of radioactive materials. The 3D information of the radioactive contamination is required to reduce the occupational exposure and the radioactive waste. The purpose of this study is to design a multi-pinhole collimator for the 3D gamma ray imaging. The collimator was designed by Monte Carlo simulation and the performance was evaluated by lab test. The collimator consists of four cone-shaped pinholes, tungsten aperture, and lead septa. The acceptance angle and the source to detector distance were 40° and 15 cm, respectively. A number of 2D images were obtained by the linear motion of the gamma camera and the 3D images were reconstructed by filtered back-projection algorithm. As a result, the experimental results were within 2% of the expected values.
A large-area X-ray CMOS image sensor (LXCIS) is widely used in mammography, non-destructive inspection, and animal CT. For LXCIS, in spite of weakness such as low spatial and energy resolution, a Indirect method using scintillator like CsI(Tl) or Gd2O2S is still well-used because of low cost and easy manufacture. A photo-diode for X-ray imaging has large area about 50 ~ 200 um as compared with vision image sensors. That is because X-ray has feature of straight and very small light emission of a scintillator. Moreover, notwithstanding several structure like columnar, the scintillator still emit a diffusible light. This diffusible light from scintillator can make spatial crosstalk in X-ray photodiode array because of a large incidence angle. Moreover, comparing with vision image sensors, X-ray sensor doesn’t have micro lens for gathering the photons to photo-diode. In this study, we simulated the affection of spatial crosstalk in X-ray sensor by comparing optical sensor. Additionally, the chip, which was fabricated in 0.18 um 1P5M process by Hynix in Korea, was tested to know the effect of spatial crosstalk by changing design parameters. From these works, we found out that spatial crosstalk is affected by pixel pitch, incident angle of photons, and micro lens on each pixels.
Dual-energy cone-beam CT is an important imaging modality in diagnostic applications, and may also find its use
in other applications such as therapeutic image guidance. Despite of its clinical values, relatively high radiation dose of
dual-energy scan may pose a challenge to its wide use. In this work, we investigated a low-dose, pre-reconstruction type of
dual-energy cone-beam CT (CBCT) using a total-variation minimization algorithm for image reconstruction. An empirical
dual-energy calibration method was used to prepare material-specific projection data. Raw data acquired at high and low
tube voltages are converted into a set of basis functions which can be linearly combined to produce material-specific data
using the coefficients obtained through the calibration process. From much fewer views than are conventionally used,
material specific images are reconstructed by use of the total-variation minimization algorithm. An experimental study
was performed to demonstrate the feasibility of the proposed method using a micro-CT system. We have reconstructed
images of the phantoms from only 90 projections acquired at tube voltages of 40 kVp and 90 kVp each. Aluminum-only
and acryl-only images were successfully decomposed. A low-dose dual-energy CBCT can be realized via the proposed
method by greatly reducing the number of projections.
In this work, we proposed a novel scatter correction method for a circular cone-beam computed tomography (CBCT)
using a hardware-based approach that completes both data acquisition and scatter correction in a single rotation. We
utilized (quasi-)redundancy in the circular cone-beam data, and applied the chord-based backprojection-filtration (BPF)
algorithm to avoid the problem of filtering discontinuous data that would occur if conventional filtered-backprojection
(FBP) algorithms were used. A single scan was performed on a cylindrical uniform phantom with beam-block strips
between the source and the phantom, and the scatter was estimated for each projection from the data under the blocked
regions. The beam-block strips (BBSs) were aligned parallel to the rotation axis, and the spacing between the strips was
determined so that the data within the spaces constitute at least slightly more than the minimum data required for image
reconstruction. The results showed that the image error due to scatter (about 30 % of the attenuation coefficient value) has
been successfully corrected by the proposed algorithm.
The solid-state detector(SSD) for X-CT consists of photodiode coupled to CdWO4$(CWO. It is important to maximize the light collection in respect of a patient's dose, radiation effect and X-ray efficiency. The factors affecting the light collection efficiency are analyzed and optimized by using experimental data and appropriate simulation code. Quantum nomogram is used to investigate the signal propagation characteristics of optimally designed solid-state detector and to ensure at which stage quantum sink occurs. This paper shows that the part of SSD, the CWO of treatment with ground top/ground side yields higher quanta than that of ground top/polish side, which is different from the result of previous studies. We also shows that optimum thickness of SiN passivation and p-layer is 0.12mm and 0.1mm, respectively. From the quantum nomogram calculated for optimal design, it is predicted that the most serious signal degradation occurs at the photodiode.
Wide-band-gap semiconductor detectors are recently in spotlight for various applications because of their good performances, such as the high energy resolution, the compactness in array geometry, and the room temperature operation. The performance of these detectors, for example, CdZnTe, is mainly limited by the charge transport properties. Especially, the dispersive nature of trapping and detrapping process affects on the detector performance resulting in random fluctuations in the current flowing. Based on the spectroscopic measurement, in this study, a simple analytical model is developed to investigate the charge transport characteristics for planar semiconductor detectors, especially for CdZnTe of m-i-m (metal-intrinsic-metal) diode structure. The model can take the input variables of material properties, as well as the operation parameters, such as the applied bias voltage, the pulse shaping time, the incident direction and the energy of gamma-rays. The measured gamma spectra from CdZnTe for Co57 showed excellent agreement with the simulation results from our model, and the parameters governing detector performance were analyzed. We expect that this model will be very useful to understand the charge transport mechanism in the wide-band-gap semiconductor detectors, and to optimally design the detector geometry for various applications.
The new LED structure suitable for high power and narrow beam pattern is proposed composed of microlens and LED layer. The microlens is fabricated by the meltback etching and regrowth technique in LPE. To control the shape of microlens, meltback etching and regrowth technique is studied and nearly ideal hemisphere is obtained. The characteristics of the proposed LED structure is calculated based upon ray-tracing method. And the fabricated result is discussed.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.