scholarly journals Dual Energy Method for Breast Imaging: A Simulation Study

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
V. Koukou ◽  
N. Martini ◽  
C. Michail ◽  
P. Sotiropoulou ◽  
C. Fountzoula ◽  
...  
Keyword(s):  
Energy Method ◽  
Breast Imaging ◽  
Analytical Modeling ◽  
High Energy ◽  
Dual Energy ◽  
Pixel Size ◽  
X Ray ◽  
Mean Glandular Dose ◽  
Filter Materials ◽  
Cmos Sensor

Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNRtc) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels.

scholarly journals Combination of Dual-Energy X-ray Transmission and Variable Gas-Ejection for the In-Line Automatic Sorting of Many Types of Scrap in One Measurement

2021 ◽  
Vol 11 (10) ◽  
pp. 4349
Author(s):  
Tianzhong Xiong ◽  
Wenhua Ye ◽  
Xiang Xu
Keyword(s):  
High Efficiency ◽  
Nearest Neighbor ◽  
High Energy ◽  
Dual Energy ◽  
Center Of Gravity ◽  
Low Energy ◽  
Identification Accuracy ◽  
Flow Process ◽  
X Ray ◽  
Automatic Sorting

As an important part of pretreatment before recycling, sorting has a great impact on the quality, efficiency, cost and difficulty of recycling. In this paper, dual-energy X-ray transmission (DE-XRT) combined with variable gas-ejection is used to improve the quality and efficiency of in-line automatic sorting of waste non-ferrous metals. A method was proposed to judge the sorting ability, identify the types, and calculate the mass and center-of-gravity coordinates according to the shading of low-energy, the line scan direction coordinate and transparency natural logarithm ratio of low energy to high energy (R_value). The material identification was satisfied by the nearest neighbor algorithm of effective points in the material range to the R_value calibration surface. The flow-process of identification was also presented. Based on the thickness of the calibration surface, the material mass and center-of-gravity coordinates were calculated. The feasibility of controlling material falling points by variable gas-ejection was analyzed. The experimental verification of self-made materials showed that identification accuracy by count basis was 85%, mass and center-of-gravity coordinates calculation errors were both below 5%. The method proposed features high accuracy, high efficiency, and low operation cost and is of great application value even to other solid waste sorting, such as plastics, glass and ceramics.

scholarly journals Exploring silver as a contrast agent for contrast-enhanced dual-energy X-ray breast imaging

2014 ◽  
Vol 87 (1041) ◽  
pp. 20140081 ◽  
Author(s):  
R Karunamuni ◽  
A Tsourkas ◽  
A D A Maidment
Keyword(s):  
Contrast Agent ◽  
Breast Imaging ◽  
Dual Energy ◽  
X Ray ◽  
Contrast Enhanced

Identification of materials in X-Ray inspections of objects by the dual-energy method

2017 ◽  
Vol 53 (8) ◽  
pp. 568-587 ◽  
Author(s):  
S. P. Osipov ◽  
V. A. Udod ◽  
Y. Wang
Keyword(s):  
Energy Method ◽  
Dual Energy ◽  
X Ray

scholarly journals Optimum filter selection for Dual Energy X-ray Applications through Analytical Modeling

2015 ◽  
Vol 633 ◽  
pp. 012093
Author(s):  
V Koukou ◽  
N Martini ◽  
C Michail ◽  
P Sotiropoulou ◽  
N Kalyvas ◽  
...  
Keyword(s):  
Analytical Modeling ◽  
Dual Energy ◽  
X Ray ◽  
Optimum Filter ◽  
Selection For ◽  
Filter Selection

scholarly journals Contrast-enhanced mammography: what the radiologist needs to know

BJR|Open ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 20210034
Author(s):  
Lidewij M.F.H. Neeter ◽  
H.P.J. (Frank) Raat ◽  
Rodrigo Alcantara ◽  
Quirien Robbe ◽  
Marjolein L. Smidt ◽  
...  
Keyword(s):  
Breast Imaging ◽  
Contrast Material ◽  
High Energy ◽  
Dual Energy ◽  
Everyday Clinical Practice ◽  
Future Developments ◽  
Imaging Protocols ◽  
Iodinated Contrast ◽  
Contrast Enhanced ◽  
The Subject

Contrast-enhanced mammography (CEM) is a combination of standard mammography and iodinated contrast material administration. During the last decade, CEM has found its place in breast imaging protocols: after i.v. administration of iodinated contrast material, low-energy and high-energy images are retrieved in one acquisition using a dual-energy technique, and a recombined image is constructed enabling visualisation of areas of contrast uptake. The increased incorporation of CEM into everyday clinical practice is reflected in the installation of dedicated equipment worldwide, the (commercial) availability of systems from different vendors, the number of CEM examinations performed, and the number of scientific articles published on the subject. It follows that ever more radiologists will be confronted with this technique, and thus be required to keep up to date with the latest developments in the field. Most importantly, radiologists must have sufficient knowledge on how to interpret CEM images and be acquainted with common artefacts and pitfalls. This comprehensive review provides a practical overview of CEM technique, including CEM-guided biopsy; reading, interpretation and structured reporting of CEM images, including the accompanying learning curve, CEM artefacts and interpretation pitfalls; indications for CEM; disadvantages of CEM; and future developments.

scholarly journals Modified kernel MLAA using autoencoder for PET-enabled dual-energy CT

2021 ◽  
Vol 379 (2204) ◽  
pp. 20200204 ◽  
Author(s):  
Siqi Li ◽  
Guobao Wang
Keyword(s):  
Image Reconstruction ◽  
Kernel Method ◽  
High Energy ◽  
Dual Energy ◽  
Feature Representation ◽  
Dual Energy Ct ◽  
Ct Image ◽  
Material Decomposition ◽  
X Ray ◽  
Image Prior

Combined use of PET and dual-energy CT provides complementary information for multi-parametric imaging. PET-enabled dual-energy CT combines a low-energy X-ray CT image with a high-energy γ -ray CT (GCT) image reconstructed from time-of-flight PET emission data to enable dual-energy CT material decomposition on a PET/CT scanner. The maximum-likelihood attenuation and activity (MLAA) algorithm has been used for GCT reconstruction but suffers from noise. Kernel MLAA exploits an X-ray CT image prior through the kernel framework to guide GCT reconstruction and has demonstrated substantial improvements in noise suppression. However, similar to other kernel methods for image reconstruction, the existing kernel MLAA uses image intensity-based features to construct the kernel representation, which is not always robust and may lead to suboptimal reconstruction with artefacts. In this paper, we propose a modified kernel method by using an autoencoder convolutional neural network (CNN) to extract an intrinsic feature set from the X-ray CT image prior. A computer simulation study was conducted to compare the autoencoder CNN-derived feature representation with raw image patches for evaluation of kernel MLAA for GCT image reconstruction and dual-energy multi-material decomposition. The results show that the autoencoder kernel MLAA method can achieve a significant image quality improvement for GCT and material decomposition as compared to the existing kernel MLAA algorithm. A weakness of the proposed method is its potential over-smoothness in a bone region, indicating the importance of further optimization in future work. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.

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