Sorapong Aootaphao

Penalized-likelihood reconstruction for metal artifact reduction in cone-beam CT

CT reconstruction from metal-embedded data usually produces streak artifacts that reduce the quality of the reconstructed images. In this paper, we propose a new technique for metal artifact reduction in cone-beam CT based on statistical reconstruction. First, the metal objects are segmented in the reconstructed images and then reprojected to obtain the measurement data of the metal objects using cone-beam reconstruction. The original measurement data in the metal area are corrected through cubic interpolation. y, the corrected measurement data are reconstructed with the penalized likelihood using the modified convex algorithm. The simulation results show that the reconstructed images of the metal object using the proposed metal artifact reduction technique are superior to conventional filtered backprojection reconstruction.

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.

Acclerate a Dlt Motion Capture System With Quad-Tree Searching Scheme

This paper describes a 3D motion capture system to generate a skeleton model representing the human body. The system consists of a number of digital cameras placed at arbitrary position around the subject. The subjects joints to be measured are attached with illuminated landmarks. The 3D dynamic information of these landmarks is then detected using the direct linear transform (DLT) technique. In order to establish corresponding point of the landmarks across individual camera as required in the DLT procedure, the quad-tree searching scheme has been adopted which can speed up the dynamic 3D modelling process of up to 70 percent. The 3D motion capture system has been performed to visualize the motion of various subjects. The result is very promising

A Computational Investigation for Metal Artifact Reduction in Cone-beam X-Ray Computed Tomography

Due to low radiation dose, cone-beam computed tomography is growing in importance. In image reconstruction, a stack of cross-sectional images can be reconstructed from a series of X-ray radiographs, served as projections. The presence of metals in the object, however, has deteriorated the quality of the reconstructed image as well as the 3D modeling results. The consequence of metal artifact can be demonstrated through the occurrence of streak effects on the reconstruction volume. In this paper, the attempt has been conducted to solve the problem of metal artifacts. The proposed technique is achieved by segmenting the metal shadowgram and filling it with the averaged intensity prior to reconstruction. The result of computer simulation shows the potential of such method for clinical use

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.

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.

Metal artifact reduction in cone-beam X-ray computed tomography using statistical iterative reconstruction

In general, image reconstruction from metal-embedded data causes streak artifacts that reduce the quality of the reconstructed image. In this paper, the attempt has been conducted to solve the problem of metal artifacts in cone-beam X-ray CT. The proposed method is applied directly to CT measurement data. First, the metal objects in the reconstructed image are detected and then reprojected to obtain the raw data using cone-beam reconstruction. The missing projections caused by the metal objects are replaced with their surrounding unaffected area through interpolation. Finally, the corrected raw data are reconstructed with the convex algorithm, which is the iterative algorithm for maximizing the likelihood function. The reconstructed images of metal artifact data using statistical reconstruction tends to be superior to conventional filtered backprojection (FBP) reconstruction.