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Monochromatic CT Image Reconstruction from Current-Integrating Data via Deep Learning
Wenxiang Cong, Ge Wang
In clinical CT, the x-ray source emits polychromatic x-rays, which are detected in the current-integrating mode. This physical process is accurately described by an energy-dependen…
Development of a focused-X-ray luminescence tomography (FXLT) system
Michael C Lun, Wei Zhang, Yue Zhao +4
Biophotonics is an active research area in molecular imaging, genetic diagnosis and prognosis, with direct applicability in precision medicine. However, long-standing challenges of…
General Backpropagation Algorithm for Training Second-order Neural Networks
Fenglei Fan, Wenxiang Cong, Ge Wang
The artificial neural network is a popular framework in machine learning. To empower individual neurons, we recently suggested that the current type of neurons could be upgraded to…
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss
Qingsong Yang, Pingkun Yan, Yanbo Zhang +5
In this paper, we introduce a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity. The Wasserstein d…
Reconstruction of optical parameters for molecular tomographic imaging
Wenxiang Cong, Xavier Intes, Ge Wang
Optical molecular tomographic imaging is to reconstruct the concentration distribution of photon-molecular probes in a small animal from measured photon fluence rates. The localiza…
LEARN: Learned Experts' Assessment-based Reconstruction Network for Sparse-data CT
Hu Chen, Yi Zhang, Yunjin Chen +7
Compressive sensing (CS) has proved effective for tomographic reconstruction from sparsely collected data or under-sampled measurements, which are practically important for few-vie…