ArticleMedical physics2025
Improving decomposition image quality in dual-energy chest radiography using two-dimensional crisscrossed anti-scatter grid.
Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Scatter Removal in Photon-Counting Dual-Energy Chest X-Ray Imaging Using a Moving Block Method: A Simulation Phantom Study.Sensors (Basel, Switzerland) · 2025Article
- Improving decomposition image quality in dual-energy chest radiography using two-dimensional crisscrossed anti-scatter grid.Medical physics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundChest radiography is a widely used medical imaging modality for diagnosing chest-related diseases. However, anatomical structure overlap hinders accurate lesion detection. While the dual-energy x-ray imaging technique addresses this issue by separating soft-tissue and bone images from an original chest radiograph, scattered radiation remains a significant challenge in decomposition image quality. PURPOSE: This work aims to conduct dual-energy material decomposition (DEMD) in chest radiography using a two-dimensional (2D) crisscrossed anti-scatter grid to improve decomposition image quality by effectively removing scattered radiation.
methodsA 2D graphite-interspaced grid with a strip density of N = 1.724 lines/mm and grid ratio r = 6:1 was fabricated using a high-precision sawing process. The grid characteristics were evaluated using the IEC standard fixture. A 2D-grid-based DEMD process, which involves the acquisition of low- and high-kV radiographs with a 2D grid, generation of a pairwise decomposition function using a calibration wedge phantom, and decomposition of soft-tissue and bone images using the decomposition function, was implemented, followed by software-based grid artifact reduction. Experiments were conducted on a commercially available chest phantom using an x-ray imaging system operating at two tube voltages of 70 and 120 kVp. The decomposition image quality of the proposed DEMD and conventional dual-energy subtraction methods was compared for the cases of no grid, software-based scatter correction, 1D grid (N = 8.475 lines/mm and r = 12:1), and 2D grid.
resultsThe 2D grid demonstrated superior scatter radiation removal ability with scatter radiation transmission of 6.34% and grid selectivity of 9.67, representing a 2.6-fold decrease and a 2.7-fold improvement over the 1D grid, respectively. Compared to other competitive methods, the 2D-grid-based DEMD method considerably improved decomposition image quality, with improved lung structure visibility in selective soft-tissue images.
conclusionsThe proposed DEMD method yielded high-quality dual-energy chest radiographs by effectively removing scattered radiation, demonstrating significant potential for improving lesion detection in clinical practice.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.