Journal of X-Ray Science and Technology - Volume 25, issue 6

Authors: Li, Mengfei | Zhao, Yunsong | Zhang, Peng

Article Type: Research Article

Abstract: Computed tomography (CT) plays an important role in digital rock analysis, which is a new prospective technique for oil and gas industry. But the artifacts in CT images will influence the accuracy of the digital rock model. In this study, we proposed and demonstrated a novel method to restore detector-unit-dependent functions for polychromatic projection calibration by scanning some simple shaped reference samples. As long as the attenuation coefficients of the reference samples are similar to the scanned object, the size or position is not needed to be exactly known. Both simulated and real data were used to verify the proposed …method. The results showed that the new method reduced both beam hardening artifacts and ring artifacts effectively. Moreover, the method appeared to be quite robust. Show more

Keywords: Computed tomography, beam hardening artifacts, ring artifacts, polychromatic projection, calibration

DOI: 10.3233/XST-17263

Citation: Journal of X-Ray Science and Technology, vol. 25, no. 6, pp. 1019-1031, 2017

Authors: Yang, Quan-Xin | Ji, Xing | Feng, Lin-Lin | Zheng, Long | Zhou, Xiao-Qian | Wu, Qian | Chen, Xin

Article Type: Research Article

Abstract: OBJECTIVE: To explore and evaluate new malignant predictors of breast non-mass enhancement lesions using the new BI-RADS MRI lexicon. METHODS: A dataset involving 422 consecutive women underwent breast 3.0 T MRI between January 2014 and July 2016 was assembled for this study. Each case was retrospectively reviewed by 3 radiologists. Eighty-four lesions that present non-mass enhancement in 79 patients were identified in the study. Dynamic contrast-enhanced MRI features were analyzed using univariate and multivariate analyses to identify significant indicators of malignancy. RESULTS: Of 84 non-mass enhancement lesions, 52 (61.9%) were malignant and 32 (38.1%) were benign. …Segmental distribution (P  = 0.015 from univariate analysis; OR = 4.739, P  = 0.008 from multivariate analysis), cluster ring enhancement (P  = 0.017 from univariate analysis; OR = 3.601, P  = 0.032 from multivariate analysis), time-intensity curve of plateau (P  = 0.002 from univariate analysis; OR = 3.525, P  = 0.027 from multivariate analysis) and phase to peak (P  = 0.06 from univariate analysis; OR = 6.327, P  = 0.015 from multivariate analysis) were significantly different between malignant and benign lesions. CONCLUSIONS: This study demonstrated that segmental distribution, clustered ring enhancement, and short time to peak could act as new malignant predictors for breast non-mass enhancement detected on 3.0 T MRI. Show more

Keywords: Breast, non-mass enhancement, magnetic resonance imaging, breast imaging reporting and data system

DOI: 10.3233/XST-17311

Citation: Journal of X-Ray Science and Technology, vol. 25, no. 6, pp. 1033-1044, 2017