Journal of X-Ray Science and Technology - Volume 28, issue 5

Authors: Nazia Fathima, S.M. | Tamilselvi, R. | Parisa Beham, M. | Sabarinathan, D.

Article Type: Research Article

Abstract: BACKGROUND: Osteoporosis, a silent killing disease of fracture risk, is normally determined based on the bone mineral density (BMD) and T-score values measured in bone. However, development of standard algorithms for accurate segmentation and BMD measurement from X-ray images is a challenge in the medical field. OBJECTIVE: The purpose of this work is to more accurately measure BMD from X-ray images, which can overcome the limitations of the current standard technique to measure BMD using Dual Energy X-ray Absorptiometry (DEXA) such as non-availability and inaccessibility of DEXA machines in developing countries. In addition, this work also attempts to …analyze the DEXA scan images for better segmentation and measurement of BMD. METHODS: This work employs a modified U-Net with Attention unit for accurate segmentation of bone region from X-Ray and DEXA images. A linear regression model is developed to compute BMD and T-score. Based on the value of T-score, the images are then classified as normal, osteopenia or osteoporosis. RESULTS: The proposed network is experimented with the two internally collected datasets namely, DEXSIT and XSITRAY, comprised of DEXA and X-ray images, respectively. The proposed method achieved an accuracy of 88% on both datasets. The Dice score on DEXSIT and XSITRAY is 0.94 and 0.92, respectively. CONCLUSION: Our modified U-Net with attention unit achieves significantly higher results in terms of Dice score and classification accuracy. The computed BMD and T-score values of the proposed method are also compared with the respective clinical reports for validation. Hence, using the digitized X-Ray images can be used to detect osteoporosis efficiently and accurately. Show more

Keywords: Osteoporosis, bone mineral density (BMD), dual-energy X-ray absorptiometry (DEXA), deep learning, attention unit, U-net, Dice value, and T-Score

DOI: 10.3233/XST-200692

Citation: Journal of X-Ray Science and Technology, vol. 28, no. 5, pp. 953-973, 2020

Authors: Vellakani, Sivamurugan | Pushbam, Indumathi

Article Type: Research Article

Abstract: Human eye is affected by the different eye diseases including choroidal neovascularization (CNV), diabetic macular edema (DME) and age-related macular degeneration (AMD). This work aims to design an artificial intelligence (AI) based clinical decision support system for eye disease detection and classification to assist the ophthalmologists more effectively detecting and classifying CNV, DME and drusen by using the Optical Coherence Tomography (OCT) images depicting different tissues. The methodology used for designing this system involves different deep learning convolutional neural network (CNN) models and long short-term memory networks (LSTM). The best image captioning model is selected after performance analysis by comparing …nine different image captioning systems for assisting ophthalmologists to detect and classify eye diseases. The quantitative data analysis results obtained for the image captioning models designed using DenseNet201 with LSTM have superior performance in terms of overall accuracy of 0.969, positive predictive value of 0.972 and true-positive rate of 0.969using OCT images enhanced by the generative adversarial network (GAN). The corresponding performance values for the Xception with LSTM image captioning models are 0.969, 0.969 and 0.938, respectively. Thus, these two models yield superior performance and have potential to assist ophthalmologists in making optimal diagnostic decision. Show more

Keywords: Age-related macular degeneration (AMD), connective tissue, choroidal neovascularization (CNV), light sensitive tissue, Optical Coherence Tomography (OCT), deep learning, convolution neural network (CNN), long short term memory (LSTM), neovascular tissue, surrounding tissue

DOI: 10.3233/XST-200697

Citation: Journal of X-Ray Science and Technology, vol. 28, no. 5, pp. 975-988, 2020

Authors: Lu, Nan-Han | Liu, Yi-Shan | Liu, Ko-In | Hsu, Shih-Yen | Huang, Yung-Hui | Sun, Cheuk-Kwan | Chen, Tai-Been

Article Type: Research Article

Abstract: OBJECTIVE: This study aims to analyze and compare the diagnostic effectiveness of 320-row multi-detector computed tomography for coronary artery angiography (MDCTA) in subjects with and without sublingual vasodilator (nitroglycerin). MATERIALS AND METHODS: From September 2015 to September 2016, 70 individuals without history of major cardiovascular diseases who underwent MDCTA for health examination were retrospectively categorized into sublingual nitroglycerin (NTG) and non-NTG groups. Medical history, CT dose index (CTDI), and multi-slice CT images were compared between two groups. A diameter of coronary artery (DA, mm) was computed and analyzed. RESULTS: A total of 41 males and 29 …females (mean age: 55.43±8.84 years, range: 34– 76) were reviewed. Normal and abnormal MDCTA findings were noted in 54 and 16 participants, respectively, with the detection rate of coronary artery disease being 23%. There was no significant difference in inter-observer variability of coronary CTA image quality and diagnosis between the NTG and non-NTG groups among three experienced radiologists. Although the percentage dilatation of left anterior descending branch (LAD), right coronary artery (RCA) and left circumflex branch (LCX) following in the NTG group were 12.4%, 12.8% and 25.3%, respectively (p  < 0.01), there was no significant difference in image quality and diagnosis between the two groups. CONCLUSIONS: Despite the recommendation of routine nitroglycerin use for subjects undergoing computed tomography for coronary artery angiography, our results showed no significant advantage of its use in improving image quality and rate of diagnosis accuracy. Show more

Keywords: Multi-detector computed tomography for coronary artery angiography (MDCTA), coronary artery disease, nitroglycerin

DOI: 10.3233/XST-200652

Citation: Journal of X-Ray Science and Technology, vol. 28, no. 5, pp. 989-999, 2020

Authors: Wang, Yu | Wang, Yuanjun

Article Type: Research Article

Abstract: BACKGROUND: Multi-modal medical image fusion plays a crucial role in many areas of modern medicine like diagnosis and therapy planning. OBJECTIVE: Due to the factor that the structure tensor has the property of preserving the image geometry, we utilized it to construct the directional structure tensor and further proposed an improved 3-D medical image fusion method. METHOD: The local entropy metrics were used to construct the gradient weights of different source images, and the eigenvectors of traditional structure tensor were combined with the second-order derivatives of image to construct the directional structure tensor. In addition, the …guided filtering was employed to obtain detail components of the source images and construct a fused gradient field with the enhanced detail. Finally, the fusion image was generated by solving the functional minimization problem. RESULTS AND CONCLUSION: Experimental results demonstrated that this new method is superior to the traditional structure tensor and multi-scale analysis in both visual effect and quantitative assessment. Show more

Keywords: 3-D medical image, multi-modal image fusion, directional structure tensor, local entropy, detail component

DOI: 10.3233/XST-200684

Citation: Journal of X-Ray Science and Technology, vol. 28, no. 5, pp. 1001-1016, 2020

Authors: Hu, Pengfei | Wang, Xing

Article Type: Research Article

Abstract: It is of great importance to study the alignment of atoms in collision process in elementary analysis with a Particle Induced X-ray Emission (PIXE) technique. The measurement of alignment can also offer an effective testing ground for developing theory models in ionization process. The typical L X-ray spectra are measured for Ag thin target by 15 keV electron impact at emission angles from 0° to 25°. Angular dependence of intensity ratios Lα /Lβ 1 , Lβ 2 /Lβ 1 and Lγ /Lβ 1 are investigated as a function of the second-order Legendre polynomial P 2 (cosθ ). …This study found that Lβ 2 line exhibits anisotropic emission spatially, while the emission of Lα , Lβ 1 and Lγ 1 lines is isotropic. The results are interpreted by the influence of the Coster-Kronig (CK) transitions on the spatial distribution of X-ray emission. The anisotropy parameter β for Lβ 2 lines is obtained experimentally and consequently the alignment degree A 20 for L3 subshell is determined by taking CK transition into account. Namely, the alignment does exist in L3 -subshell for atomic ionization by electron impact. The measurements offer an evidence to the existence of alignment for atomic ionization in electron-impact process. Show more

Keywords: X-ray, angular distribution, particle induced X-ray emission (PIXE), electron impact, alignment of atoms

DOI: 10.3233/XST-200701

Citation: Journal of X-Ray Science and Technology, vol. 28, no. 5, pp. 1017-1023, 2020