activity
20172022
most citedDilated FCN for Multi-Agent 2D/3D Medical Image Registration

15 citations · 16 across the 4 of their papers we have counts for

collaborators

5 papers

eess.IV2022

A Metal Artifact Reduction Scheme For Accurate Iterative Dual-Energy CT Algorithms

Tao Ge, Maria Medrano, Rui Liao +4

CT images have been used to generate radiation therapy treatment plans for more than two decades. Dual-energy CT (DECT) has shown high accuracy in estimating electronic density or…

eess.IV2021

A Machine-learning Based Initialization for Joint Statistical Iterative Dual-energy CT with Application to Proton Therapy

Tao Ge, Maria Medrano, Rui Liao +3

Dual-energy CT (DECT) has been widely investigated to generate more informative and more accurate images in the past decades. For example, Dual-Energy Alternating Minimization (DEA…

cs.CV20191 cited

Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations

Chen Qin, Bibo Shi, Rui Liao +3

We propose a fully unsupervised multi-modal deformable image registration method (UMDIR), which does not require any ground truth deformation fields or any aligned multi-modal imag…

cs.CV2018

Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation

Yue Zhang, Shun Miao, Tommaso Mansi +1

Automatic parsing of anatomical objects in X-ray images is critical to many clinical applications in particular towards image-guided invention and workflow automation. Existing dee…

cs.CV201715 cited

Dilated FCN for Multi-Agent 2D/3D Medical Image Registration

Shun Miao, Sebastien Piat, Peter Fischer +4

2D/3D image registration to align a 3D volume and 2D X-ray images is a challenging problem due to its ill-posed nature and various artifacts presented in 2D X-ray images. In this p…