Energy-sensitive scatter estimation and correction for spectral x-ray imaging with photon-counting detectors. (1st December 2022)

• Record Type: Journal Article
• Authors: Lewis, Cale E.; Das, Mini
• Is Part Of: Journal of instrumentation. Volume 17:Number 12(2022)
• Publication Date: 2022-12-01
• Subjects: Computerized Tomography (CT) and Computed Radiography (CR) -- Inspection with x-rays -- X-ray detectors -- X-ray radiography and digital radiography (DR); Scientific apparatus and instruments -- Periodicals; 502.84
• DOI: 10.1088/1748-0221/17/12/P12004
• Languages: English
• ISSNs: 1748-0221

Abstract

Abstract: As photon counting detectors are being explored for medical and industrial imaging applications, there is a critical need to understand spectral characteristics of scattered x-ray photons. Scattered radiation is detrimental to x-ray imaging by reducing image quality and quantitative accuracy. While various scatter correction techniques have been proposed for x-ray imaging with conventional energy-integrating detectors, additional efforts are required to develop approaches for spectral x-ray imaging with energy-resolving PCDs. We show the benefits of accurate scatter estimation and correction for each energy bin when using a photon counting detector. We propose a scatter estimation model that accounts for the energy-dependent scatter characteristics in projection imaging. This can then be used to restore quantitative accuracy for spectral x-ray imaging with PCDs. Results are shown in the context of contrast-enhanced spectral mammography using dual-energy subtraction to digitally isolate iodine targets (2.5–40 mg/ml). In the presence of scatter, the projected iodine densities are increasingly underestimated as the object thickness increases. The energy-sensitive scatter correction improves the iodine density estimation up to 46%. These results suggest that our scatter estimation model can accurately account for the energy-dependent scatter distribution, which can be an effective tool for scatter compensation in spectral x-ray imaging. Implementing this scatter estimation model does not require any modifications to the acquisition parameters and is transferable to other x-ray imaging applications such as tomosynthesis and CT.