Journal of X-Ray Science and Technology - Volume 26, issue 3

Authors: Polat, Adem | Yildirim, Isa

Article Type: Research Article

Abstract: BACKGROUND: Iterative image reconstruction in Digital Breast Tomosynthesis (DBT) is a developing modality that produces three-dimensional (3D) reconstructed images of a breast to detect suspicious lesions. Algebraic reconstruction technique (ART), one of the iterative image reconstruction methods, was applied to reconstruct 3D data of breast and is becoming as one alternative method for the conventional image reconstruction techniques such as filtered back projection (FBP) in DBT imaging. OBJECTIVE: A new majorization-minimization (MM) algorithm was presented for TV denoising of signals. In the field of DBT, however, the algorithm has not yet been applied. In this study, we proposed …a new method of “ART+TV3D +MM,” which applies (MM) algorithm to the images reconstructed by ART+TV3D for different imaging dose levels to investigate a possible reduction of radiation dose. METHODS: Projections of a real breast phantom (CD Pasmam 1054) were acquired with a Siemens MAMMOMAT DBT system. The proposed new method was repeated and tested with 3 different radiation dose levels. The quality of the images reconstructed using the proposed new method were compared with those generated by the commonly used FBP method using both qualitative and quantitative assessments. RESULTS: The new method showed superior results in terms of visual assessment, contrast to noise ratios (CNR), full width at half maximum (FWHM) values and 1D profiles compared with FBP of the Siemens MAMMOMAT. CNR values were evaluated for two different region of interests (ROIs). For instance, CNR values of ROI-2 of FBP and of new method were 1.670 and 1.978 at 100 mAs, respectively. Moreover, while CNR value of ROI-1 of FBP at 100 mAs was 0.955, CNR value of ROI-1 of using new method at 100 mAs was 48.163. FWHM values for FBP and the new method were 2.328 and 1.765 at 56 mAs, 2.032 and 1.661 at 100 mAs, and 2.111 and 1.736 at 199 mAs, respectively. CONCLUSIONS: The results support that using the new method of “ART+TV3D +MM” could help decrease the radiation dose level, which is one of the most critical limitations of DBT imaging. Show more

Keywords: Digital breast tomosynthesis, iterative reconstruction, algebraic reconstruction technique, 3D total variation, majorization-minimization, real DBT image

DOI: 10.3233/XST-17320

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 347-360, 2018

Authors: Xu, Yifu | Yan, Bin | Chen, Jian | Zeng, Lei | Li, Lei

Article Type: Research Article

Abstract: BACKGROUND: Dual-energy computed tomography (DECT) has been widely used to improve identification of substances from different spectral information. Decomposition of the mixed test samples into two materials relies on a well-calibrated material decomposition function. OBJECTIVE: This work aims to establish and validate a data-driven algorithm for estimation of the decomposition function. METHODS: A deep neural network (DNN) consisting of two sub-nets is proposed to solve the projection decomposition problem. The compressing sub-net, substantially a stack auto-encoder (SAE), learns a compact representation of energy spectrum. The decomposing sub-net with a two-layer structure fits the nonlinear transform between …energy projection and basic material thickness. RESULTS: The proposed DNN not only delivers image with lower standard deviation and higher quality in both simulated and real data, and also yields the best performance in cases mixed with photon noise. Moreover, DNN costs only 0.4 s to generate a decomposition solution of 360 × 512 size scale, which is about 200 times faster than the competing algorithms. CONCLUSIONS: The DNN model is applicable to the decomposition tasks with different dual energies. Experimental results demonstrated the strong function fitting ability of DNN. Thus, the Deep learning paradigm provides a promising approach to solve the nonlinear problem in DECT. Show more

Keywords: Dual-energy computed tomography, material decomposition, deep learning, stack auto-encoder

DOI: 10.3233/XST-17349

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 361-377, 2018

Authors: Cui, Xuelin | Mili, Lamine | Wang, Ge | Yu, Hengyong

Article Type: Research Article

Abstract: Since their inceptions, the multimodal imaging techniques have received a great deal of attention for achieving enhanced imaging performance. In this work, a novel joint reconstruction framework using sparse computed tomography (CT) and magnetic resonance imaging (MRI) data is developed and evaluated. CT and MRI images are synchronously acquired and registered from a hybrid CT-MRI platform. Because image data are highly undersampled, analytic methods are unable to generate decent image quality. To overcome this drawback, we resort to the compressed sensing (CS) techniques, which employ sparse priors that result from an application of a wavelet transform. To utilize multimodal information, …projection distance is introduced and is tuned to tailor the texture and pattern of the final images. Specifically, CT and MRI images are alternately reconstructed using the updated multimodal results that are calculated at the latest step of the iterative optimization algorithm. The method exploits the structural similarities shared by the CT and MRI images to achieve better reconstruction quality. The good performance of the proposed approach is demonstrated on a pair of undersampled CT and MRI body images. Clinical CT and MRI images are tested with the joint reconstruction, the analytic reconstruction, and the independent reconstruction which does not uses multimodal imaging information. Results show that the proposed method improves about 5dB in signal to noise ratio (SNR) and nearly 10% in structural similarity measure comparing to independent reconstruction. It offers similar quality with fully sampled analytic reconstruction with only 20% sampling rate for CT and 40% for MRI. Structural similarities and correlations residing in images from different modalities are useful to mutually promote the quality of image reconstruction. Show more

Keywords: Multimodal imaging, Image reconstruction, Compressed sensing

DOI: 10.3233/XST-17324

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 379-393, 2018

Authors: Al-antari, Mugahed A. | Al-masni, Mohammed A. | Metwally, Mohamed K. | Hussain, Dildar | Park, Se-Je | Shin, Jeong-Sik | Han, Seung-Moo | Kim, Tae-Seong

Article Type: Research Article

Abstract: BACKGROUND: In general, the image quality of high and low energy images of dual energy X-ray absorptiometry (DXA) suffers from noise due to the use of a small amount of X-rays. Denoising of DXA images could be a key process to improve a bone mineral density map, which is derived from a pair of high and low energy images. This could further improve the accuracy of diagnosis of bone fractures and osteoporosis. OBJECTIVE: This study aims to develop and test a new technology to improve the quality, remove the noise, and preserve the edges and fine details of …real DXA images. METHODS: In this study, a denoising technique for high and low energy DXA images using a non-local mean filter (NLM) was presented. The source and detector noises of a DXA system were modeled for both high and low DXA images. Then, the optimized parameters of the NLM filter were derived utilizing the experimental data from CIRS-BFP phantoms. After that, the optimized NLM was tested and verified using the DXA images of the phantoms and real human spine and femur. RESULTS: Quantitative evaluation of the results showed average 24.22% and 34.43% improvement of the signal-to-noise ratio for real high and low spine images, respectively, while the improvements were about 15.26% and 13.55% for the high and low images of the femur. The qualitative visual observations of both phantom and real structures also showed significantly improved quality and reduced noise while preserving the edges in both high and low energy images. Our results demonstrate that the proposed NLM outperforms the conventional method using an anisotropic diffusion filter (ADF) and median techniques for all phantom and real human DXA images. CONCLUSIONS: Our work suggests that denoising via NLM could be a key preprocessing method for clinical DXA imaging. Show more

Keywords: DXA images, radiography dual-energy scanned projection, DXA noise modelling, non-local means filter (NLM), image denoising

DOI: 10.3233/XST-17341

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 395-412, 2018

Authors: Jeon, Soomin | Lee, Chang-Ock

Article Type: Research Article

Abstract: BACKGROUND: Streak artifacts in computed tomography (CT) images caused by metallic objects limit the wider use of CT imaging technologies. There have been various attempts to improve CT images containing streak artifacts; however, most of them generate additional artifacts or do not completely eradicate existing artifacts. OBJECTIVE: In this paper, we propose a novel algorithm which reduces streak artifacts in CT images. METHODS: Using CT numbers reconstructed from a given sinogram, we extract the metal part M and the surrounding area C with similar CT numbers. By filling in the area C  ∪ M …with the evaluated average CT number of C , we obtain a modified CT image. Using forward projection of the modified CT image, we generate a sinogram containing information about the anatomical structure. We undertake sinogram surgery to remove the metallic effects from the sinogram, after which we repeat the procedure. RESULTS: We perform numerical experiments using various simulated phantoms and patient images. For a quantitative analysis, we use the relative l ∞ error and the relative l 2 error. In simulated phantom experiments, all l ∞ errors and l 2 errors approach 10% and 1% of the initial errors, respectively. Moreover, for the patient image simulations, all l ∞ errors are decreased by a factor of 20 while the l 2 errors are decreased less than 5%. We observe that the proposed algorithm effectively reduces the metal artifacts. CONCLUSIONS: In this paper, we propose a metal artifact reduction algorithm based on sinogram surgery to reduce metal artifacts without additional artifacts. We also provide empirical convergence of our algorithm. Show more

Keywords: Computed tomography (CT), metal artifact reduction, sinogram surgery, iterative algorithm

DOI: 10.3233/XST-17336

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 413-434, 2018

Authors: Qiao, Zhiwei | Redler, Gage | Qian, Yuhua | Tang, Shaojie | Epel, Boris | Halpern, Howard

Article Type: Research Article

Abstract: The optimization-based image reconstruction methods have been thoroughly investigated in the field of medical imaging. The Chambolle-Pock (CP) algorithm may be employed to solve these convex optimization image reconstruction programs. The preconditioned CP (PCP) algorithm has been shown to have much higher convergence rate than the ordinary CP (OCP) algorithm. This algorithm utilizes a preconditioner-parameter to tune the implementation of the algorithm to the specific application, which ranges from 0 and 2, but is often set to 1. In this work, we investigated the impact of the preconditioner-parameter on the convergence rate of the PCP algorithm when it is applied …to the TV constrained, data-divergence minimization (TVDM) optimization based image reconstruction. We performed the investigations in the context of 2D computed tomography (CT) and 3D electron paramagnetic resonance imaging (EPRI). For 2D CT, we used the Shepp-Logan and two FORBILD phantoms. For 3D EPRI, we used a simulated 6-spheres phantom and a physical phantom. Study results showed that the optimal preconditioner-parameter depends on the specific imaging conditions. Simply setting the parameter equal to 1 cannot guarantee a fast convergence rate. Thus, this study suggests that one should adaptively tune the preconditioner-parameter to obtain the optimal convergence rate of the PCP algorithm. Show more

Keywords: Optimization-based image reconstruction, total variation minimization, Chambolle-Pock algorithm, preconditioner, convergence rate

DOI: 10.3233/XST-17337

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 435-448, 2018

Authors: Yu, Jinfeng | Hu, Yun | Huang, Mingna | Chen, Jun | Ding, Xiaoqian | Zheng, Leilei

Article Type: Research Article

Abstract: OBJECTIVE: To evaluate the skeletal and dental characteristics in skeletal class III patients with facial asymmetry and to analyse the relationships among various parts of the stomatognathic system to provide a theoretical basis for clinical practice. METHODS: Asymmetric cone-beam computed tomography data acquired from 56 patients were evaluated using Mimics 10.0 and 3-Matic software. Skeletal and dental measurements were performed to assess the three-dimensional differences between two sides. Pearson correlation analysis was used to determine the correlations among measurements. RESULTS: Linear measurements, such as ramal height, mandible body length, ramal height above the sigmoid notch (RHASN), …maxillary height, condylar height, buccal and total cancellous bone thickness, and measurements of condylar size, were significantly larger on the nondeviated side than on the deviated side (P  < 0.05). Crown root ratio and buccolingual angle of mandibular first molar were found to be significantly smaller on the nondeviated side than on the deviated side (P  < 0.05). A negative correlation was also discovered between the buccolingual angle of mandibular first molar and the ramal height (P  < 0.01). CONCLUSIONS: In patients with facial asymmetry, asymmetries in the mandible, maxilla and condylar morphology, and skeletal canting served as major components of skeletal asymmetry. Furthermore, a reduced thickness of buccal cancellous bone and a larger crown root ratio were found on the deviated side, indicating that orthodontic camouflage has limitations and potential risks. A combination of orthodontics and orthognathic surgery may be the advisable choice in patients with a menton deviation greater than 4 mm. An important association between vertical skeletal disharmony and dental compensation was also observed. Show more

Keywords: Facial asymmetry, skeletal and dental characteristics, cone-beam computed tomography

DOI: 10.3233/XST-17333

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 449-462, 2018

Authors: Liu, Shihe | Fu, Qing | Yu, Hualong | Zhang, Chuanyu | Yang, Qing | Hu, Yabin | Xu, Wenjian

Article Type: Research Article

Abstract: BACKGROUND: 640-slice coronary CT angiography is becoming an accurate and reliable method of diagnosing coronary heart disease. However, how to reduce the radiation dosage while ensuring the clinically acceptable image quality remains a quite challenging issue. OBJECTIVE: To evaluate the effect of low tube voltage on radiation dosage under 640-slice coronary CT angiography (CCTA). METHODS: Four hundred patients (236 males, 164 females) with coronary heart disease and underwent CCTA using DCVT were classified into A1 (tube voltage: 120 kV; exposure phase window: 30–80%), B1 (120 kV; 70–80%), A2 (100 kV; 30–80%) and B2 group (100 kV; 70–80%), respectively. Image qualities …and effective dose (ED) were assessed and compared. RESULTS: No significant differences were observed among the groups in terms of age, height, weight and body mass index (BMI) (P  > 0.05). ED were significantly lower in 100 kV group (P  < 0.05). CT values of coronary artery in 100 kV groups were 13.5% and 17.3% higher than 120 kV group. ED in B1 group were 64.5% and 67.0% lower than A1 group. ED in B2 group were 65.4% and 65.2% lower than A2 group. CONCLUSION: When using a 640-slice CCTA prospective ECG-gating scanning mode, it is preferable to use a 100 kV tube voltage setting because compared to 120 kV tube voltage protocol, it seems to significantly decrease the mean effective radiation dose, without significantly lowering both the subjective and objective image quality. Show more

Keywords: 640-slices CT, coronary CT angiography, radiation dosage, tube voltage, image quality

DOI: 10.3233/XST-17332

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 463-471, 2018

Authors: Hatanaka, Shogo | Shimbo, Munefumi | Hariu, Masatsugu | Nakajima, Go | Todoroki, Keisuke | Hosaka, Katsuhito | Watanabe, Tetsuya | Washizu, Kana | Utsumi, Nobuko | Yamano, Takafumi | Nishimura, Keiichiro | Takahashi, Takeo

Article Type: Brief Report

Abstract: PURPOSE: Based on a retrospective analysis, this study aims to develop a simple index for validity of the evaluation point for the dosimetric verification of intensity-modulated radiation therapy (IMRT). METHODS: The results for the dosimetric verifications of a total of 69 IMRT plans were analyzed in this study. A Farmer-type ion chamber was used as a dose detector, and a solid water-equivalent phantom was used. Index values were obtained by dividing the difference between the maximum and minimum dosages by the mean dosage of the 69 plans, and the values were classified into five groups with index value …<4, 4–8, 8–12, 12–16, and >16. A t -test was used to assess the statistical significance of the mean differences of the absolute values of the relative errors among these groups. RESULTS: We found that there was no significant difference between the groups with index value <4 and 4–8 (p  = 0.152); however, there were significant differences between the other groups (p  < 0.01). In addition, when the index values were smaller than 8, the pass ratio of 3% tolerance was 96.2% and the pass ratio of 5% tolerance was 99.9%. We observed that the smaller the index value, the smaller the uncertainty of the dose measurement. CONCLUSIONS: The results obtained in this study may prove to be useful for accurate dosimetric verifications of IMRTs when ion chambers are used. Show more

Keywords: Dosimetric verification, ionization chamber, intensity-modulated radiation therapy, dose flatness, retrospective analysis

DOI: 10.3233/XST-17339

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 473-480, 2018

Authors: Zhang, Lingli | Zeng, Li | Guo, Yumeng

Article Type: Research Article

Abstract: PURPOSES: Restricted by the scanning environment in some CT imaging modalities, the acquired projection data are usually incomplete, which may lead to a limited-angle reconstruction problem. Thus, image quality usually suffers from the slope artifacts. The objective of this study is to first investigate the distorted domains of the reconstructed images which encounter the slope artifacts and then present a new iterative reconstruction method to address the limited-angle X-ray CT reconstruction problem. METHODS: The presented framework of new method exploits the structural similarity between the prior image and the reconstructed image aiming to compensate the distorted edges. Specifically, …the new method utilizes l0 regularization and wavelet tight framelets to suppress the slope artifacts and pursue the sparsity. New method includes following 4 steps to (1) address the data fidelity using SART; (2) compensate for the slope artifacts due to the missed projection data using the prior image and modified nonlocal means (PNLM); (3) utilize l0 regularization to suppress the slope artifacts and pursue the sparsity of wavelet coefficients of the transformed image by using iterative hard thresholding (l0 W); and (4) apply an inverse wavelet transform to reconstruct image. In summary, this method is referred to as “l0 W-PNLM”. RESULTS: Numerical implementations showed that the presented l0 W-PNLM was superior to suppress the slope artifacts while preserving the edges of some features as compared to the commercial and other popular investigative algorithms. When the image to be reconstructed is inconsistent with the prior image, the new method can avoid or minimize the distorted edges in the reconstructed images. Quantitative assessments also showed that applying the new method obtained the highest image quality comparing to the existing algorithms. CONCLUSIONS: This study demonstrated that the presented l0 W-PNLM yielded higher image quality due to a number of unique characteristics, which include that (1) it utilizes the structural similarity between the reconstructed image and prior image to modify the distorted edges by slope artifacts; (2) it adopts wavelet tight frames to obtain the first and high derivative in several directions and levels; and (3) it takes advantage of l0 regularization to promote the sparsity of wavelet coefficients, which is effective for the inhibition of the slope artifacts. Therefore, the new method can address the limited-angle CT reconstruction problem effectively and have practical significance. Show more

Keywords: Computed tomography, image reconstruction, l0 regularization, nonlocal means, wavelet tight framelet, prior image

DOI: 10.3233/XST-17334

Citation: Journal of X-Ray Science and Technology, vol. 26, no. 3, pp. 481-498, 2018