Journal of X-Ray Science and Technology - Volume 32, issue 5

Authors: He, Yu | Wang, Chengxiang | Yu, Wei | Wang, Jiaxi

Article Type: Research Article

Abstract: BACKGROUND: Due to the incomplete projection data collected by limited-angle computed tomography (CT), severe artifacts are present in the reconstructed image. Classical regularization methods such as total variation (TV) minimization, ℓ0 minimization, are unable to suppress artifacts at the edges perfectly. Most existing regularization methods are single-objective optimization approaches, stemming from scalarization methods for multiobjective optimization problems (MOP). OBJECTIVE: To further suppress the artifacts and effectively preserve the edge structures of the reconstructed image. METHOD: This study presents a multiobjective optimization model incorporates both data fidelity term and ℓ0 -norm of the image gradient as …objective functions. It employs an iterative approach different from traditional scalarization methods, using the maximization of structural similarity (SSIM) values to guide optimization rather than minimizing the objective function.The iterative method involves two steps, firstly, simultaneous algebraic reconstruction technique (SART) optimizes the data fidelity term using SSIM and the Simulated Annealing (SA) algorithm for guidance. The degradation solution is accepted in the form of probability, and guided image filtering (GIF) is introduced to further preserve the image edge when the degradation solution is rejected. Secondly, the result from the first step is integrated into the second objective function as a constraint, we use ℓ0 minimization to optimize ℓ0 -norm of the image gradient, and the SSIM, SA algorithm and GIF are introduced to guide optimization process by improving SSIM value like the first step. RESULTS: With visual inspection, the peak signal-to-noise ratio (PSNR), root mean square error (RMSE), and SSIM values indicate that our approach outperforms other traditional methods. CONCLUSIONS: The experiments demonstrate the effectiveness of our method and its superiority over other classical methods in artifact suppression and edge detail restoration. Show more

Keywords: CT reconstruction, limited-angle CT, image quality assessment, multiobjective optimization

DOI: 10.3233/XST-240111

Citation: Journal of X-Ray Science and Technology, vol. 32, no. 5, pp. 1209-1237, 2024

Authors: Zhou, Xuan | Liu, Yuedong | Wei, Cunfeng | Xu, Qiong

Article Type: Research Article

Abstract: BACKGROUND: Geometry calibration for robotic CT system is necessary for obtaining acceptable images under the asynchrony of two manipulators. OBJECTIVE: We aim to evaluate the impact of different types of asynchrony on images and propose a reference-free calibration method based on a simplified geometry model. METHODS: We evaluate the impact of different types of asynchrony on images and propose a novel calibration method focused on asynchronous rotation of robotic CT. The proposed method is initialized with reconstructions under default uncalibrated geometry and uses grid sampling of estimated geometry to determine the direction of optimization. Difference between …the re-projections of sampling points and the original projection is used to guide the optimization direction. Images and estimated geometry are optimized alternatively in an iteration, and it stops when the difference of residual projections is close enough, or when the maximum iteration number is reached. RESULTS: In our simulation experiments, proposed method shows better performance, with the PSNR increasing by 2%, and the SSIM increasing by 13.6% after calibration. The experiments reveal fewer artifacts and higher image quality. CONCLUSION: We find that asynchronous rotation has a more significant impact on reconstruction, and the proposed method offers a feasible solution for correcting asynchronous rotation. Show more

Keywords: Robotic CT, reference-free, geometry calibration

DOI: 10.3233/XST-240023

Citation: Journal of X-Ray Science and Technology, vol. 32, no. 5, pp. 1239-1252, 2024

Authors: Xue, Xiying | Ji, Dongjiang | Xu, Chunyu | Zhao, Yuqing | Li, Yimin | Hu, Chunhong

Article Type: Research Article

Abstract: BACKGROUND: Low-dose computed tomography (CT) has been successful in reducing radiation exposure for patients. However, the use of reconstructions from sparse angle sampling in low-dose CT often leads to severe streak artifacts in the reconstructed images. OBJECTIVE: In order to address this issue and preserve image edge details, this study proposes an adaptive orthogonal directional total variation method with kernel regression. METHODS: The CT reconstructed images are initially processed through kernel regression to obtain the N-term Taylor series, which serves as a local representation of the regression function. By expanding the series to the second order, …we obtain the desired estimate of the regression function and localized information on the first and second derivatives. To mitigate the noise impact on these derivatives, kernel regression is performed again to update the first and second derivatives. Subsequently, the original reconstructed image, its local approximation, and the updated derivatives are summed using a weighting scheme to derive the image used for calculating orientation information. For further removal of stripe artifacts, the study introduces the adaptive orthogonal directional total variation (AODTV) method, which denoises along both the edge direction and the normal direction, guided by the previously obtained orientation. RESULTS: Both simulation and real experiments have obtained good results. The results of two real experiments show that the proposed method has obtained PSNR values of 34.5408 dB and 29.4634 dB, which are 1.2392–5.9333 dB and 2.828–6.7995 dB higher than the contrast denoising algorithm, respectively, indicating that the proposed method has good denoising performance. CONCLUSIONS: The study demonstrates the effectiveness of the method in eliminating strip artifacts and preserving the fine details of the images. Show more

Keywords: CT reconstruction denoising, orthogonal direction, kernel regression, edge adaptive directional total variation

DOI: 10.3233/XST-230416

Citation: Journal of X-Ray Science and Technology, vol. 32, no. 5, pp. 1253-1271, 2024

Authors: Yang, Yingjian | Zheng, Jie | Guo, Peng | Wu, Tianqi | Gao, Qi | Zeng, Xueqiang | Chen, Ziran | Zeng, Nanrong | Ouyang, Zhanglei | Guo, Yingwei | Chen, Huai

Article Type: Research Article

Abstract: BACKGROUND: Chest X-rays (CXR) are widely used to facilitate the diagnosis and treatment of critically ill and emergency patients in clinical practice. Accurate hemi-diaphragm detection based on postero-anterior (P-A) CXR images is crucial for the diaphragm function assessment of critically ill and emergency patients to provide precision healthcare for these vulnerable populations. OBJECTIVE: Therefore, an effective and accurate hemi-diaphragm detection method for P-A CXR images is urgently developed to assess these vulnerable populations’ diaphragm function. METHODS: Based on the above, this paper proposes an effective hemi-diaphragm detection method for P-A CXR images based on the convolutional …neural network (CNN) and graphics. First, we develop a robust and standard CNN model of pathological lungs trained by human P-A CXR images of normal and abnormal cases with multiple lung diseases to extract lung fields from P-A CXR images. Second, we propose a novel localization method of the cardiophrenic angle based on the two-dimensional projection morphology of the left and right lungs by graphics for detecting the hemi-diaphragm. RESULTS: The mean errors of the four key hemi-diaphragm points in the lung field mask images abstracted from static P-A CXR images based on five different segmentation models are 9.05, 7.19, 7.92, 7.27, and 6.73 pixels, respectively. Besides, the results also show that the mean errors of these four key hemi-diaphragm points in the lung field mask images abstracted from dynamic P-A CXR images based on these segmentation models are 5.50, 7.07, 4.43, 4.74, and 6.24 pixels,respectively. CONCLUSION: Our proposed hemi-diaphragm detection method can effectively perform hemi-diaphragm detection and may become an effective tool to assess these vulnerable populations’ diaphragm function for precision healthcare. Show more

Keywords: Chest X-ray images, hemi-diaphragm, morphology, lung filed segmentation, convolutional neural network, graphics

DOI: 10.3233/XST-240108

Citation: Journal of X-Ray Science and Technology, vol. 32, no. 5, pp. 1273-1295, 2024

Authors: Zhi, Lijia | Duan, Shaoyong | Zhang, Shaomin

Article Type: Research Article

Abstract: OBJECTIVE: Content-based medical image retrieval (CBMIR) has become an important part of computer-aided diagnostics (CAD) systems. The complex medical semantic information inherent in medical images is the most difficult part to improve the accuracy of image retrieval. Highly expressive feature vectors play a crucial role in the search process. In this paper, we propose an effective deep convolutional neural network (CNN) model to extract concise feature vectors for multiple semantic X-ray medical image retrieval. METHODS: We build a feature pyramid based CNN model with ResNet50V2 backbone to extract multi-level semantic information. And we use the well-known public multiple …semantic annotated X-ray medical image data set IRMA to train and test the proposed model. RESULTS: Our method achieves an IRMA error of 32.2, which is the best score compared to the existing literature on this dataset. CONCLUSIONS: The proposed CNN model can effectively extract multi-level semantic information from X-ray medical images. The concise feature vectors can improve the retrieval accuracy of multi-semantic and unevenly distributed X-ray medical images. Show more

Keywords: CBMIR, multiple semantic, retrieval, X-Ray image, IRMA

DOI: 10.3233/XST-240069

Citation: Journal of X-Ray Science and Technology, vol. 32, no. 5, pp. 1297-1313, 2024

Authors: Gao, Youtao | Wu, Yixiang | Li, Shijia | Hei, Daqian | Tang, Yajun

Article Type: Research Article

Abstract: X-ray communication is a kind of space communication technology which uses X-ray as information carrier. In order to improve the information transmission capacity, communication rate and anti-interference ability of X-ray communication, we proposes to design a novel multi-target X-ray source. The source is composed of a fast switching module of light channels based on FPGA technology and four photoelectric X-ray tubes with different target materials: Cr, Fe, Ni, and Cu. Using Geant4 software, we determined the optimal target thickness for each material, which enabled us to fully leverage the characteristic X-rays for multi-channel signal modulation transmission. Moreover, using CST software …for particle trajectory simulation and optimization of the electron beam revealed that at a tube voltage of 20 kV, the focus area measures approximately 1.2 mm×1.2 mm. The simulations show that four kinds of spectra with high distinctiveness can be generated from the Cr, Fe, Ni, and Cu targets. Within a single modulation period, these spectra can be combined in various ways to create 16 different X-ray spectra signals, thereby increasing the number of communication elements and enhancing the information transmission rate. Show more

Keywords: X-ray communication, X-ray tube, multi-target, CST simulation, characteristic spectrum

DOI: 10.3233/XST-240094

Citation: Journal of X-Ray Science and Technology, vol. 32, no. 5, pp. 1315-1329, 2024

Authors: Abdulameer, Mohammed S. | Pallathadka, Harikumar | Menon, Soumya V. | Rab, Safia Obaidur | Hjazi, Ahmed | Kaur, Mandeep | Sivaprasad, G.V. | Husseen, Beneen | Al-Mualm, Mahmood | Banaei, Amin

Article Type: Research Article

Abstract: INTRODUCTION: Intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) are the main radiotherapy techniques for treating and managing rectal cancer. Collimator rotation is one of the crucial parameters in radiotherapy planning, and its alteration can cause dosimetric variations. This study assessed the effect of collimator rotation on the dosimetric results of various IMRT and VMAT plans for rectal cancer. MATERIALS AND METHODS: Computed tomography (CT) images of 20 male patients with rectal cancer were utilized for IMRT and VMAT treatment planning with various collimator angles. Nine different IMRT techniques (5, 7, and 9 coplanar fields with …collimator angles of 0°, 45°, and 90°) and six different VMAT techniques (1 and 2 full coplanar arcs with collimator angles of 0°, 45°, and 90°) were planned for each patient. The dosimetric results of various treatment techniques for target tissue (conformity index [CI] and homogeneity index [HI]) and organs at risk (OARs) sparing (parameters obtained from OARs dose–volume histograms [DVH]) as well as radiobiological findings were analyzed and compared. RESULTS: The 7-fields IMRT technique demonstrated lower bladder doses (V40Gy , V45Gy ), unaffected by collimator rotation. The 9-fields IMRT and 2-arcs VMAT (excluding the 90-degree collimator) had the lowest V35Gy and V45Gy . A 90-degree collimator rotation in 2-arcs VMAT significantly increased small bowel and bladder V45Gy , femoral head doses, and HI values. Radiobiologically, the 90-degree rotation had adverse effects on small bowel NTCP (normal tissue complication probability). No superiority was found for a 45-degree collimator rotation over 0 or 30 degrees in VMAT techniques. CONCLUSION: Collimator rotation had minimal impact on dosimetric parameters in IMRT planning but is significant in VMAT techniques. A 90-degree rotation in VMAT, particularly in a 2-full arc technique, adversely affects PTV homogeneity index, bladder dose, and small bowel NTCP. Other evaluated collimator angles did not significantly affect VMAT dosimetrical or radiobiological outcomes. Show more

Keywords: Rectal cancer, intensity modulated radiotherapy, volumetric modulated arc therapy, collimator, radiobiologic parameters, dosimetric parameters

DOI: 10.3233/XST-240172

Citation: Journal of X-Ray Science and Technology, vol. 32, no. 5, pp. 1331-1348, 2024

Authors: Shankarlal, B. | Dhivya, S. | Rajesh, K. | Ashok, S.

Article Type: Correction

DOI: 10.3233/XST-200002

Citation: Journal of X-Ray Science and Technology, vol. 32, no. 5, pp. 1349-1349, 2024