High-resolution sub-sampling incoherent x-ray imaging with a single-pixel detector

Abstract

X-ray “ghost” imaging has drawn great attention for its potential to obtain images with a high resolution and lower radiation dose in medical diagnosis, even with only a single-pixel detector. However, it is hard to realize with a portable x-ray source due to its low flux. Here, we demonstrate a computational x-ray ghost imaging scheme where a real bucket detector and specially designed high-efficiency modulation masks are used, together with a robust deep learning algorithm in which a compressed set of Hadamard matrices is incorporated into a multi-level wavelet convolutional neural network. With a portable incoherent x-ray source of ∼37 µm diameter, we have obtained an image of a real object from only 18.75% of the Nyquist sampling rate. A high imaging resolution of ∼10 µm has been achieved, which is required for cancer detection and so represents a concrete step toward the realization of a practical low cost x-ray ghost imaging camera for applications in biomedicine, archeology, material science, and so forth.

Single-pixel imaging with neutrons

“…Moreover, compared with the first three completed neutron scattering instruments at CSNS, the space and cable interface near the worktable were more suitable for optical devices and detector layout. For the spatial modulation, the scheme of computational ghost imaging that has been successfully exploited for both high-energy electromagnetic radiation and particles [13][14][15]32,33] was used to realize SPIN. The setup of our experiment is shown in Fig.…”

Megapixel X-ray ghost imaging with a binned detector in the object arm

“…Theoretically, the resolution limit of real-space XGI through the CSA can surpass the Rayleigh diffraction limit [15,29] . According to Fig.…”

“…As a result, GI has been investigated for application in various fields such as remote sensing [8] , three-dimensional imaging [9] , and quantum lithography [10,11] . In principle, lensless GI [12][13][14] is applicable to any wavelength, which has been demonstrated experimentally with X-rays [1,2,[15][16][17][18][19][20] , electrons [21] , atoms [22] , and neutrons [23] in addition to visible [24,25] and infrared light [26] .…”

“…Up to now, X-ray GI (XGI) has attracted extensive attention and has been investigated theoretically and experimentally in recent years with pseudo-thermal [1,15,17,20] , true-thermal [18] , and entangled X-ray sources [19] and in many diverse strategies including real-space XGI [1,15,17,18,20] , Fourier-transform XGI [2] , phase contrast XGI [27] , and X-ray ghost tomography [16] . In 2016, Yu et al experimentally demonstrated the Fourier-transform XGI method using X-rays of the Shanghai Synchrotron Radiation Facility (SSRF) and successfully reconstructed the amplitude and phase images of a multi-slit sample with an image size of 300 × 300 pixels from 284 measurements [2] .…”

“…Ceddia et al proposed an experimental scheme for phase contrast XGI and demonstrated it by numerical simulation [27] . Two years later, He et al [15] applied the scheme of computational GI to restore a structured metal sample of 64 × 64 pixels through a deep learning algorithm from 768 frames, in which speckle patterns were generated by a designed orthogonal Hadamard matrix instead of silicon carbide sandpaper. Up to now, the image size achieved by XGI has been limited to 300 × 300 pixels or less, which prevents the practical application of XGI to high-fidelity and megapixel imaging in biomedicine and material science.…”