Wavefront Engineering for Scintillation-Based Imaging

TL;DR

This work reframes scintillation-based X-ray imaging as a wavefront-engineering problem, showing that depth integration across scintillator planes fundamentally constrains conventional wavefront coding but also reveals new design opportunities. By modeling the scintillator as a stack of depth-resolved PSFs and analyzing the system transfer function $H_{ ext{sys}}(oldsymbol{k})$, the authors identify when extended depth of field is advantageous and how inverse-design of pupil phase using Zernike modes can place an effective focal plane near the average emission depth $x_{ ext{optimal}}=rac{ times 0 \,dx}{ times 0 \,dx}$ to maximize the integrated MTF. They demonstrate that energy-dependent imaging, via energy-specific depth weightings $s(x)$, yields energy-band–dependent optimal planes and can selectively emphasize features tied to different X-ray energies. Collectively, the results provide a roadmap for end-to-end wavefront-engineered scintillation systems—via nanophotonic scintillators, metasurfaces, and co-design with detection and reconstruction—that could enhance resolution, enable spectral/material discrimination, and tailor imaging to specific diagnostic tasks.

Abstract

Recent research in nanophotonics for scintillation-based imaging has demonstrated promising improvements in scintillator performance. In parallel, advances in nanophotonics have enabled wavefront control through metasurfaces, a capability that has transformed fields such as microscopy by allowing tailored control of optical propagation. This naturally raises the following question, which we address in this perspective: can wavefront-control strategies be leveraged to improve scintillation-based imaging? To answer this question, we explore nanophotonic- and metasurface-enabled wavefront control in scintillators to mitigate image blurring arising from their intrinsically diffuse light emission. While depth-of-field extension in scintillation faces fundamental limitations absent in microscopy, this approach reveals promising avenues, including stacked scintillators, selective spatial-frequency enhancement, and X-ray energy-dependent imaging. These results clarify the key distinctions in adapting wavefront engineering to scintillation and its potential to enable tailored detection strategies.

Figures (5)

• Figure 1: Wavefront engineering in scintillation-based X-ray imaging. Schematic highlighting wavefront control in scintillation: tailoring X-ray sources with dedicated optics (here we show a zone plate common for X-ray focusing), designing custom scintillators (e.g., multicolor stacks), and integrating end-to-end computational design. On the detection side, aperiodic, free-form, and 3D nanostructures together with arbitrary pupil-phase control provide further degrees of freedom for shaping scintillation light. Insets for "Custom Scintillator Stacks" and "3D Nanostructures" are adapted from Refs. min2025end and roques2022toward.
• Figure 2: Similarities between scintillation-based imaging and microscopy. (a) In scintillators imaged by, for example, free-space optics, light emission from the scintillator is collected and focused to the detector. (b) In microscopy, detection optics similarly image a biological specimen, and wavefront engineering can be used to enhance certain functionalities. (c) A cubic phase profile can be inserted to modify the system point spread function to be depth-invariant. (d) Without a phase profile the PSF results in standard image defocus, but (e) with a cubic phase profile the PSF is altered to be invariant to defocus, allowing extended depth of field (EDOF) to be achieved through computational reconstruction. The ground truth image can be found in (b).
• Figure 3: Extended depth of field (EDOF) for scintillation-based imaging. (a) Comparison between scintillation using standard detection optics versus scintillation with extended depth of field (EDOF) capabilities. (b) The point spread functions along discrete scintillator planes for standard detection (top) and EDOF detection (bottom). The depth-dependent energy deposition in the scintillator is modeled using the source X-ray spectrum and the energy-dependent scintillator mass attenuation coefficients. (c) Comparison between discrete planar standard and EDOF modulation transfer functions (MTF). Different color lines in the MTF plots correspond to the various discrete planes in the scintillator. Despite the apparent advantage of the discrete planar MTFs in the EDOF case, the system MTF of the standard system lies above the system MTF of the EDOF system at all spatial frequencies.
• Figure 4: Use cases for EDOF in scintillation-based imaging. (a) When the desired focal plane lies outside the scintillator volume, extended depth of field becomes beneficial, as seen in the system MTFs comparing the standard and cubic phase mask designs. (b) The same principle extends to stacked multicolor scintillator systems, where, without EDOF, the scintillator layers away from the chosen focal plane are severely out of focus.
• Figure 5: (a) Inverse design using the Zernike basis can optimize for certain spatial frequencies above the in-focus optimal MTF. (b) A toy model demonstrates energy-dependent scintillation imaging, where some features of the Shepp-Logan phantom are contained by high energy X-rays and some features are contained by low energy X-rays. The X-ray energy deposited for each portion of the Shepp-Logan phantom is plotted on the yellow rectangular prism representing the scintillator. The detected image thus varies according to the plane of focus in the scintillator.