Pairash Thajchayapong

Radiation dose and accuracy analysis of newly developed cone-beam CT for dental and maxillofacial imaging

Cone-beam computed tomography (CBCT) has become increasingly popular in dental and maxillofacial imaging due to its accurate 3D information, minimal radiation dose, and low machine cost. In this paper, we have proposed the newly developed CBCT scanner, called DentiiScan. Our gantry system consisting of a cone-beam X-ray source and an amorphous silicon flat panel detector is rotated around a patients head. With the large area detector, only a single rotation is needed to reconstruct the field-of-view area from chin to eyes and our reconstructed algorithm based on GPU calculation is about 30 times faster than the CPU-based algorithm. The radiation dose was measured and compared to other dental and medical CT machines. The absorbed radiation dose from our proposed CBCT machine is significantly low. In addition, geometric accuracy was analyzed when the test object was scanned at the normal position as well as the inclined position. The results from three observers repeated for five times confirm that the machine can produce reconstructed images with high accuracy.

Experiment-based scatter correction for cone-beam computed tomography using the statistical method

Scatter signals in cone-beam computed tomography (CBCT) cause a significant problem that degrades image quality of reconstructed images, such as inaccuracy of CT numbers and cupping artifacts. In this paper, we will present an experiment-based scatter correction method by pre-processing projection images using a statistical model combined with experimental kernels. The convolution kernels are estimated by using different thickness of PMMA plates attached to a beam stop lead sheet such that the scatter signal values can be measure in the shadow area of the projection images caused by the lead sheet. The scatter signal values of different thickness levels can be measured in the shadow area of projection images caused by the lead sheet. Then, the projection images are convolved with the kernels that are derived from the actual measurement of scatter signals in PMMA plates. Finally, the primary signals can be estimated using the maximum likelihood expectation maximization method. Experimental results by using the proposed method show that the quality of the reconstruction images is significantly improved. The CT numbers become more accurate and the cupping artifact is reduced.

X-Ray Scatter Correction on Soft Tissue Images for Portable Cone Beam CT

Soft tissue images from portable cone beam computed tomography (CBCT) scanners can be used for diagnosis and detection of tumor, cancer, intracerebral hemorrhage, and so forth. Due to large field of view, X-ray scattering which is the main cause of artifacts degrades image quality, such as cupping artifacts, CT number inaccuracy, and low contrast, especially on soft tissue images. In this work, we propose the X-ray scatter correction method for improving soft tissue images. The X-ray scatter correction scheme to estimate X-ray scatter signals is based on the deconvolution technique using the maximum likelihood estimation maximization (MLEM) method. The scatter kernels are obtained by simulating the PMMA sheet on the Monte Carlo simulation (MCS) software. In the experiment, we used the QRM phantom to quantitatively compare with fan-beam CT (FBCT) data in terms of CT number values, contrast to noise ratio, cupping artifacts, and low contrast detectability. Moreover, the PH3 angiography phantom was also used to mimic human soft tissues in the brain. The reconstructed images with our proposed scatter correction show significant improvement on image quality. Thus the proposed scatter correction technique has high potential to detect soft tissues in the brain.

Fast scatter correction for cone-beam computed tomography using the statistical method

X-ray scatter signals acquired from a large flat panel detector in cone-beam computed tomography (CBCT) can degrade image quality of cross-section images. In this paper, we propose a new fast scatter correction method in CBCT using the statistical method in combination with the downsampling technique in projection images to reduce the computation time. The downsampled primary signal is estimated using the MLEM algorithm and then upsampled to obtain the original size. To reduce the upsampling effect, we deconvolve one more time to obtain the final estimated primary signal. The experimental results show that the proposed method with downsampling by two can reduce the computation time by a factor of more than four. In addition, the quality of reconstructed images is improved in terms of higher CT number accuracy and smaller cupping artifacts in comparison with the results obtained from fan-beam computed tomography.

Quantitative Performance Evaluation of Mobile Cone-Beam CT for Head and Neck Imaging

Cone-beam computed tomography (CBCT) has become increasingly popular in dental and maxillofacial imaging due to its accurate 3D information, minimal radiation dose, and low machine cost. In this paper, we propose the newly developed mobile CBCT scanner which combines the benefits of CBCT and mobility to extend its applications to head and neck imaging and allow faster access to a patient at various clinical sites. With the large area detector, only a single rotation is needed to reconstruct the field-of-view of almost the entire head. Our filtered back-projection reconstruction and artifact reduction algorithms were based on a graphics processing unit to speed up the calculations. The quantitative performance was evaluated in terms of radiation doses and image quality. The radiation doses were measured using both CT dose index and dose area product (DAP) and compared with other CBCT and multi-slice CT (MSCT) machines. Then, we analyzed image quality using the standard cone-beam phantom. The effective doses radiated from the proposed mobile CBCT machine were within the range of 0.1–0.2 mSv, while the normalized DAP measurements were within the range of 46–144 mGy cm2, which are significantly below the achievable dose of 250 mGy cm2. The overall image quality of the proposed scanner was mostly comparable to other MSCT and CBCT scanners. Geometric accuracy of the reconstructed images provided the errors less than 0.16 mm or 0.12%. Due to low radiation dose, high accuracy and adequate image quality as compared to others, the proposed mobile CBCT has high potential for diagnosis and treatment planning in head and neck applications.

A Simple Scatter Reduction Method in Cone-Beam Computed Tomography for Dental and Maxillofacial Applications Based on Monte Carlo Simulation

The quality of images obtained from cone-beam computed tomography (CBCT) is important in diagnosis and treatment planning for dental and maxillofacial applications. However, X-ray scattering inside a human head is one of the main factors that cause a drop in image quality, especially in the CBCT system with a wide-angle cone-beam X-ray source and a large area detector. In this study, the X-ray scattering distribution within a standard head phantom was estimated using the Monte Carlo method based on Geant4. Due to small variation of low-frequency scattering signals, the scattering signals from the head phantom can be represented as the simple predetermined scattering signals from a patients head and subtracted the projection data for scatter reduction. The results showed higher contrast and less cupping artifacts on the reconstructed images of the head phantom and real patients. Furthermore, the same simulated scattering signals can also be applied to process with higher-resolution projection data.

Acceleration of filtered back-projection algorithm for 3D cone-beam CT reconstruction using parallel computation

Filtered back-projection (FBP) is the most commonly used reconstruction method for computed tomographic image reconstruction due to its practicality in comparison with other computationally demanding methods. However, the FBP is still a very computationally expensive algorithm to implement, given that real world data obtained from CT machine are relatively large. Memory management and arithmetic computation of the FBP algorithm on conventional PC-based sequential executions still pose challenges in terms of computation time required for demanding diagnostic requirements. In this work, we propose and develop an approach for GPU-based implementation of the FBP algorithm that fully utilizes the parallel computing power of the graphic processing unit (GPU). We confirmed that the computation performance is significantly improved by applying our proposed approach with actual data obtained from our in-house dental CBCT machine called DentiiScan. The experiments show that we are able to achieve up to 80 times of computation time reduction.

DentiiScan: The first cone-beam CT scanner for dental and maxillofacial imaging developed in Thailand

Due to accurate 3D information, minimal radiation dose, and low machine cost, cone-beam computed tomography (CBCT) has become increasingly popular in dental and maxillofacial imaging. In this paper, we propose the first development of the CBCT scanner in Thailand, called DentiiScan. The gantry system uses a cone-beam X-ray source and a large amorphous silicon flat panel detector to rotate around a patients head and capture raw data. Our reconstructed algorithm based on GPU calculation can produce 3D image data in approximately 5 seconds. Image quality of reconstructed images was evaluated through a standard phantom as well as visual analysis on real clinical data. The results show that our system is suitable for diagnosis and treatment planning in dental and maxillofacial applications.