most citedIntensity Non-uniformity Correction in MR Imaging Using Residual Cycle Generative Adversarial Network

1 citations · 1 across the 1 of their papers we have counts for

collaborators
Showing physics.med-phShow all

3 papers · 1 filter

physics.med-ph2020

Synthetic MRI-aided Head-and-Neck Organs-at-Risk Auto-Delineation for CBCT-guided Adaptive Radiotherapy

Xianjin Dai, Yang Lei, Tonghe Wang +7

Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-va…

physics.med-ph2020★ 1 cited

Intensity Non-uniformity Correction in MR Imaging Using Residual Cycle Generative Adversarial Network

Xianjin Dai, Yang Lei, Yingzi Liu +6

Purpose: Correcting or reducing the effects of voxel intensity non-uniformity (INU) within a given tissue type is a crucial issue for quantitative MRI image analysis in daily clini…

physics.med-ph2019

Dual-energy CT imaging using a single-energy CT data is feasible via deep learning

Wei Zhao, Tianling Lv, Peng Gao +6

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…