67 citations · 279 across the 19 of their papers we have counts for
5 papers · 1 filter
Noise2Context: Context-assisted Learning 3D Thin-layer Low Dose CT Without Clean Data
Zhicheng Zhang, Xiaokun Liang, Wei Zhao +1
Computed tomography (CT) has played a vital role in medical diagnosis, assessment, and therapy planning, etc. In clinical practice, concerns about the increase of X-ray radiation e…
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…
A deep learning approach for virtual monochromatic spectral CT imaging with a standard single energy CT scanner
Wei Zhao, Tianling Lyu, Yang Chen +1
Purpose/Objectives: To develop and assess a strategy of using deep learning (DL) to generate virtual monochromatic CT (VMCT) images from a single-energy CT (SECT) scan. Materials/M…