activity
20162022
most citedConvolutional Sparse Coding for Compressed Sensing CT Reconstruction

133 citations · 271 across the 15 of their papers we have counts for

collaborators
Showing 2018Show all

7 papers · 1 filter

cs.CV2018

Three-dimensional Optical Coherence Tomography Image Denoising through Multi-input Fully-Convolutional Networks

Ashkan Abbasi, Amirhassan Monadjemi, Leyuan Fang +2

In recent years, there has been a growing interest in applying convolutional neural networks (CNNs) to low-level vision tasks such as denoising and super-resolution. Due to the coh…

physics.med-ph2018

Sparse-View CT Reconstruction via Convolutional Sparse Coding

Peng Bao, Wenjun Xia, Kang Yang +2

Traditional dictionary learning based CT reconstruction methods are patch-based and the features learned with these methods often contain shifted versions of the same features. To…

physics.med-ph2018

Visual Attention Network for Low Dose CT

Wenchao Du, Hu Chen, Peixi Liao +3

Noise and artifacts are intrinsic to low dose CT (LDCT) data acquisition, and will significantly affect the imaging performance. Perfect noise removal and image restoration is intr…

math.AP2018

Asymptotic dynamic for dipolar Quantum Gases below the ground state energy threshold

Jacopo Bellazzini, Luigi Forcella

We consider the Gross-Pitaevskii equation describing a dipolar Bose-Einstein condensate without external confinement. We first consider the unstable regime, where the nonlocal nonl…

cs.CV2018

Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising

Chenyu You, Qingsong Yang, Hongming Shan +8

Computed tomography (CT) is a popular medical imaging modality in clinical applications. At the same time, the x-ray radiation dose associated with CT scans raises public concerns…

physics.med-ph2018

Few-View CT Reconstruction with Group-Sparsity Regularization

Peng Bao, Jiliu Zhou, Yi Zhang

Classical total variation (TV) based iterative reconstruction algorithms assume that the signal is piecewise smooth, which causes reconstruction results to suffer from the over-smo…