37 citations · 82 across the 8 of their papers we have counts for
15 papers
Metal Artifact Reduction in 2D CT Images with Self-supervised Cross-domain Learning
Lequan Yu, Zhicheng Zhang, Xiaomeng Li +3
The presence of metallic implants often introduces severe metal artifacts in the X-ray CT images, which could adversely influence clinical diagnosis or dose calculation in radiatio…
A Geometry-Informed Deep Learning Framework for Ultra-Sparse 3D Tomographic Image Reconstruction
Liyue Shen, Wei Zhao, Dante Capaldi +2
Deep learning affords enormous opportunities to augment the armamentarium of biomedical imaging, albeit its design and implementation have potential flaws. Fundamentally, most deep…
TransCT: Dual-path Transformer for Low Dose Computed Tomography
Zhicheng Zhang, Lequan Yu, Xiaokun Liang +2
Low dose computed tomography (LDCT) has attracted more and more attention in routine clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray radia…
Dual-energy Computed Tomography Imaging from Contrast-enhanced Single-energy Computed Tomography
Wei Zhao, Tianling Lyu, Yang Chen +1
In a standard computed tomography (CT) image, pixels having the same Hounsfield Units (HU) can correspond to different materials and it is therefore challenging to differentiate an…
Beam data modeling of linear accelerators (linacs) through machine learning and its potential applications in fast and robust linac commissioning and quality assurance
Wei Zhao, Ishan Patil, Bin Han +3
Background and purpose: To propose a novel machine learning-based method for reliable and accurate modeling of linac beam data applicable to the processes of linac commissioning an…
Dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network
Tianling Lyu, Zhan Wu, Yikun Zhang +3
Dual-energy computed tomography (DECT) is of great significance for clinical practice due to its huge potential to provide material-specific information. However, DECT scanners are…