A5004120576- Advanced X-ray and CT Imaging
- Medical Imaging Techniques and Applications
- Radiation Dose and Imaging
- Photoacoustic and Ultrasonic Imaging
- Nuclear Physics and Applications
- Advanced Image Processing Techniques
- Electrical and Bioimpedance Tomography
- Advanced X-ray Imaging Techniques
- Image Processing Techniques and Applications
- Image and Signal Denoising Methods
- Welding Techniques and Residual Stresses
PLA Information Engineering University
2022-2024
Compared with conventional single-energy computed tomography (CT), dual-energy CT (DECT) provides better material differentiation but most DECT imaging systems require dual full-angle projection data at different X-ray spectra. Relaxing the requirement of acquisition is an attractive research to promote applications in wide range areas and reduce radiation dose as low reasonably achievable. In this work, we design a novel scheme quarter scans propose efficient method reconstruct desired...
The guideline of "as low as reasonably achievable" (ALARA) for radiation dose has attracted attention to sparse-view spectral computed tomography (CT) imaging. Any missing scanning view in any energy will reduce the quality image reconstruction and material decomposition. Recently, a series achievements have been made optimizing CT imaging based on traditional iterative models or deep learning methods. However, these works are independent simply coupled, often neglecting dependency...
Dual-energy computed tomography (DECT) is a promising technique, which can provide unique capability for material quantification. The iterative reconstruction of maps requires spectral information and its accuracy affected by mismatch. Simultaneously estimating the spectra reconstructing avoids extra workload on spectrum estimation negative impact However, existing methods are not satisfactory in image detail preservation, edge retention, convergence rate. purpose this paper was to mine...
Due to the hardware constraints of Computed Tomography (CT) imaging, acquiring high-resolution (HR) CT images in clinical settings poses a significant challenge. In recent years, convolutional neural networks have shown great potential super-resolution (SR) problems. However, reconstruction results many deep learning-based SR methods structural distortion and detail ambiguity. this paper, new network based on generative adversarial learning is proposed. The consists gradient branch branch....
Purpose: Low-dose computed tomography (LDCT) has promising potential for dose reduction in medical applications, while suffering from low image quality caused by noise. Therefore, it is urgent need developing new algorithms to obtain high-quality images LDCT. Methods: This study tries exploit the sparse and low-rank properties of proposes a algorithm based on subspace identification. The collection transmission data sparsely represented singular value decomposition eigen-images are then...
Photon counting detector (PCD) is a hot topic at present. Compared with traditional energy integral detector, it has the potential of high spatial resolution, sensitivity and low dose, which can effectively promote medical imaging diagnosis. However, when PCD X-ray photons, photon number each bin relatively small. Additionally, charge-sharing response pulse superposition effect will also affect count rate, resulting in serious noise affecting quality. In this paper, photon-counting denoising...
Spectral computed tomography based on photon-counting detector (PCCT) is a promising technique with high spatial and energy resolution. Multi-material decomposition typical application of PCCT, which can provide accurate material identification. However, due to the finite photons in each bin, number bins cannot grow without limit while image quality suffers from serious noise. Despite quantitative capability for multi-material, existing methods require adequate corresponding materials. In...
Spectral computed tomography (CT) utilizing photon counting detector (PCD) has advanced quickly in recent years, and its utilization clinics been gradually increasing. Compared with traditional CT, PCD-CT the advantages of multi substances quantification, can significantly reduce image noise scanning dose while maintaining quality. However, due to limitation hardware, PCD is affected by starving, charge sharing effect pulse superposition effect, leading statistical fluctuation spectral CT...