Jamin Schaefer, Steffen Kappler, Ferdinand Lueck, Ludwig Ritschl, Thomas Weber, Georg Rose
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引用次数: 0
Abstract
Purpose: The combination of multi-layer flat panel detector (FPDT) X-ray imaging and physics-based material decomposition algorithms allows for the removal of anatomical structures. However, the reliability of these algorithms may be compromised by unaccounted materials or scattered radiation.
Approach: We investigated the two-material decomposition performance of a multi-layer FPDT in the context of 2D chest radiography without and with a 13:1 anti-scatter grid employed. A matrix-based material decomposition (MBMD) (equivalent to weighted logarithmic subtraction), a matrix-based material decomposition with polynomial beam hardening pre-correction (MBMD-PBC), and a projection domain decomposition were evaluated. The decomposition accuracy of simulated data was evaluated by comparing the bone and soft tissue images to the ground truth using the structural similarity index measure (SSIM). Simulation results were supported by experiments using a commercially available triple-layer FPDT retrofitted to a digital X-ray system.
Results: Independent of the selected decomposition algorithm, uncorrected scatter leads to negative bone estimates, resulting in small SSIM values and bone structures to remain visible in soft tissue images. Even with a 13:1 anti-scatter grid employed, bone images continue to show negative bone estimates, and bone structures appear in soft tissue images. Adipose tissue on the contrary has an almost negligible effect.
Conclusions: In a contact scan, scattered radiation leads to negative bone contrast estimates in the bone images and remaining bone contrast in the soft tissue images. Therefore, accurate scatter estimation and correction algorithms are essential when aiming for material decomposition using image data obtained with a multi-layer FPDT.
期刊介绍:
JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.