20 citations · 29 across the 9 of their papers we have counts for
9 papers
CNsEMD: An Expert-Annotated Multi-Field-Strength MRI Dataset and a Hyperspherical Manifold Network for Multimodal Cranial Nerve Parcellation
Lei Xie, Junxiong Huang, Guoqiang Xie +9
Cranial nerves (CNs) play essential roles in sensory, motor, and autonomic functions. Accurate CN parcellation from multimodal magnetic resonance imaging (MRI) is crucial for neuro…
Efficient Chambolle-Pock based algorithms for Convoltional sparse representation
Yi Liu, Junjing Li, Yang Chen +4
Recently convolutional sparse representation (CSR), as a sparse representation technique, has attracted increasing attention in the field of image processing, due to its good chara…
CC-DCNet: Dynamic Convolutional Neural Network with Contrastive Constraints for Identifying Lung Cancer Subtypes on Multi-modality Images
Yuan Jin, Gege Ma, Geng Chen +5
The accurate diagnosis of pathological subtypes of lung cancer is of paramount importance for follow-up treatments and prognosis managements. Assessment methods utilizing deep lear…
RSTAR4D: Rotational Streak Artifact Reduction in 4D CBCT using a Separable 4D CNN
Ziheng Deng, Hua Chen, Yongzheng Zhou +7
Four-dimensional cone-beam computed tomography (4D CBCT) provides respiration-resolved images and can be used for image-guided radiation therapy. However, the ability to reveal res…
Full-length-body CBCT imaging in upright position with robotic-arm system: a simulation study
Tong Lin, Tianling Lyu, Zhan Wu +3
Upright position CT scans make it possible for full-length-body imaging at conditions more relevant to daily situations, but the substantial weight of the upright CT scanners incre…
PDS-MAR: a fine-grained Projection-Domain Segmentation-based Metal Artifact Reduction method for intraoperative CBCT images with guidewires
Tianling Lyu, Zhan Wu, Gege Ma +5
Since the invention of modern CT systems, metal artifacts have been a persistent problem. Due to increased scattering, amplified noise, and insufficient data collection, it is more…
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…
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…