Spectral Signatures of X-ray Scatter Using Energy-Resolving Photon-Counting Detectors

Abstract

Energy-resolving photon-counting detectors (PCDs) separate photons from a polychromatic X-ray source into a number of separate energy bins. This spectral information from PCDs would allow advancements in X-ray imaging, such as improving image contrast, quantitative imaging, and material identification and characterization. However, aspects like detector spectral distortions and scattered photons from the object can impede these advantages if left unaccounted for. Scattered X-ray photons act as noise in an image and reduce image contrast, thereby significantly hindering PCD utility. In this paper, we explore and outline several important characteristics of spectral X-ray scatter with examples of soft-material imaging (such as cancer imaging in mammography or explosives detection in airport security). Our results showed critical spectral signatures of scattered photons that depend on a few adjustable experimental factors. Additionally, energy bins over a large portion of the spectrum exhibit lower scatter-to-primary ratio in comparison to what would be expected when using a conventional energy-integrating detector. These important findings allow flexible choice of scatter-correction methods and energy-bin utilization when using PCDs. Our findings also propel the development of efficient spectral X-ray scatter correction methods for a wide range of PCD-based applications.

Energy-sensitive scatter estimation and correction for spectral x-ray imaging with photon-counting detectors

“…The attenuation coefficient of the low-Z background reduces as the energy increases, meaning µ b (E 1 ) > µ b (E 2 ). Similarly, our previous work [17] has shown that the scatter fraction reduces as the energy increases, meaning SF (E 1 ) > SF (E 2 ). However, it can be determined that the underestimation due to the µ b (E 1 ) and SF (E 2 ) term has a larger impact than the overestimation due to the µ b (E 2 ) and SF (E 1 ) term.…”

“…Rather, this method relies on physically modeling the scatter interactions and an off-line scatter database of homogeneous PMMA slabs. Unlike [40] who prepared the database through beam-stop array, we used Monte Carlo simulation to accurately account for the spectrally-varying scatter fractions [17]. Although we considered constant thickness objects (as relevant to the breast compression in clinical mammography), this method may be expanded to prepare a scatter database of non-uniform thickness objects.…”

“…In review, this estimation relies on a few measurable quantities, depicted in Figure 2. As shown in our recent work [17], the required spectrally-varying scatter fraction values of homogeneous PMMA slabs (SF P M M A (x x x, E)) can be determined through measurement-based methods or Monte Carlo simulation [17] using equivalent acquisition parameters as with the unknown object. The PMMA slabs are chosen with a thickness t pmma equivalent to the object to produce similar amount of scattered radiation.…”

“…We have previously characterized the spectral behavior of scattered radiation for energy-resolved x-ray imaging with PCDs [17]. Here, we present methods to apply these spectral scatter signatures to develop an energy-sensitive scatter estimation technique using a kernel-based approach.…”

Enhanced Tomographic Sensing Multimodality with a Crystal Analyzer

“…Various types of sensors and detectors exist. In the X-ray range, examples include ionization chambers (gas discharge counters) [1,2], scintillation counters (chambers) [3] in which X-ray radiation is converted into visible light, or solid-state detectors [4][5][6][7], in which X-ray photons generate electron-hole pairs and the corresponding current is recorded. Improvement of existing detector types or the creation of new detectors (using new physical principles) equates to progress in sensing.…”