ArticleMedical physics2017
Technical Note: Insertion of digital lesions in the projection domain for dual-source, dual-energy CT.
Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Insertion of hepatic lesions into clinical photon-counting-detector CT projection data.Physics in medicine and biology · 2025Article
- A Generalizable Framework for Kidney Stone Composition Characterization Using Dual-Energy CT.Academic radiology · 2025Article
- Image quality evaluation in deep-learning-based CT noise reduction using virtual imaging trial methods: Contrast-dependent spatial resolution.Medical physics · 2024Article
- Framework of metal insertion in the projection domain for image quality optimization in interventional computed tomography.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Dual-energy CT imaging of nasopharyngeal cancer cells using multifunctional gold nanoparticles.IET nanobiotechnology · 2019Article
- A deep learning- and partial least square regression-based model observer for a low-contrast lesion detection task in CT.Medical physics · 2019Article
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Authors and funding
5 authors.
Funding
Abstract
purposeTo compare algorithms performing material decomposition and classification in dual-energy CT, it is desirable to know the ground truth of the lesion to be analyzed in real patient data. In this work, we developed and validated a framework to insert digital lesions of arbitrary chemical composition into patient projection data acquired on a dual-source, dual-energy CT system.
methodsA model that takes into account beam-hardening effects was developed to predict the CT number of objects with known chemical composition. The model utilizes information about the x-ray energy spectra, the patient/phantom attenuation, and the x-ray detector energy response. The beam-hardening model was validated on samples of iodine (I) and calcium (Ca) for a second-generation dual-source, dual-energy CT scanner for all tube potentials available and a wide range of patient sizes. The seven most prevalent mineral components of renal stones were modeled and digital stones were created with CT numbers computed for each patient/phantom size and x-ray energy spectra using the developed beam-hardening model. Each digital stone was inserted in the dual-energy projection data of a water phantom scanned on a dual-source scanner and reconstructed with the routine algorithms in use in our practice. The geometry of the forward projection for dual-energy data was validated by comparing CT number accuracy and high-contrast resolution of simulated dual-energy CT data of the ACR phantom with experimentally acquired data.
resultsThe beam-hardening model and forward projection method accurately predicted the CT number of I and Ca over a wide range of tube potentials and phantom sizes. The images reconstructed after the insertion of digital kidney stones were consistent with the images reconstructed from the scanner, and the CT number ratios for different kidney stone types were consistent with data in the literature. A sample application of the proposed tool was also demonstrated.
conclusionA framework was developed and validated for the creation of digital objects of known mineral composition, and for inserting the digital objects into projection data from a commercial dual-source, dual-energy CT scanner. Among other applications, it will allow a systematic investigation of the impact of scan and reconstruction parameters on kidney stone dual-energy properties under rigorously controlled conditions.
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