Enhancing the X-ray differential phase contrast image quality with deep learning technique
Objective: The purpose of this work is to investigate the feasibility of using deep
convolutional neural network (CNN) to improve the image quality of a grating-based X-ray …
convolutional neural network (CNN) to improve the image quality of a grating-based X-ray …
Sampling grating approach for X-ray differential phase contrast imaging
Y Du, X Liu, J Huang, Y Lei, Z Zhao, D Lin, J Guo… - Optics …, 2015 - opg.optica.org
Grating-based X-ray differential phase contrast imaging (GDPCI) typically employs the
phase-stepping technique to extract an object's phase information. This method requires …
phase-stepping technique to extract an object's phase information. This method requires …
Evaluation of differential phase contrast cone beam CT imaging system
Grating-based differential phase contrast (DPC) imaging enables the use of a hospital-grade
X-ray tube, but compromises the image quality due to insufficiently coherent illumination. In …
X-ray tube, but compromises the image quality due to insufficiently coherent illumination. In …
Improving radiation dose efficiency of x-ray differential phase contrast imaging using an energy-resolving grating interferometer and a novel rank constraint
In this paper, a novel method was developed to improve the radiation dose efficiency, viz.,
contrast to noise ratio normalized by dose (CNRD), of the grating-based X-ray differential …
contrast to noise ratio normalized by dose (CNRD), of the grating-based X-ray differential …
Enhanced phase retrieval via deep concatenation networks for in-line X-ray phase contrast imaging
Purpose In-line X-ray phase contrast imaging offers considerable additional information
beyond that acquired from conventional absorption contrast X-ray imaging, showing …
beyond that acquired from conventional absorption contrast X-ray imaging, showing …
DeepPhase: learning phase contrast signal from dual energy X-ray absorption images
Due to the high hardware complexity and low dose efficiency of existing X-ray phase
contrast imaging, the biomedical and clinical applications of this novel imaging technique …
contrast imaging, the biomedical and clinical applications of this novel imaging technique …
Dual-path deep learning reconstruction framework for propagation-based X-ray phase–contrast computed tomography with sparse-view projections
Propagation-based X-ray phase–contrast computed tomography (PB-PCCT) can serve as
an effective tool for studying organ function and pathologies. However, it usually suffers from …
an effective tool for studying organ function and pathologies. However, it usually suffers from …
Model-driven phase retrieval network for single-shot x-ray Talbot–Lau interferometer imaging
P Liu, J Yang, J Chen, T Su, J Guo, H Zheng, D Liang… - Optics Letters, 2020 - opg.optica.org
The single-shot x-ray Talbot–Lau interferometer-based differential phase contrast (DPC)
imaging is able to accelerate time-consuming data acquisition; however, the extracted …
imaging is able to accelerate time-consuming data acquisition; however, the extracted …
Mixed scale dense convolutional networks for x-ray phase contrast imaging
X-ray in-line phase contrast imaging relies on the measurement of Fresnel diffraction
intensity patterns due to the phase shift and the attenuation induced by the object. The …
intensity patterns due to the phase shift and the attenuation induced by the object. The …
Single-shot grating-based X-ray phase contrast imaging via generative adversarial network
Talbot-Lau interferometry obtains X-ray differential phase contrast (DPC) signals of object by
subtracting multiple moiré patterns acquired by phase-stepping (PS) procedure. Due to the …
subtracting multiple moiré patterns acquired by phase-stepping (PS) procedure. Due to the …