activity
20182022
most citedDeep Iterative 2D/3D Registration

20 citations · 23 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV20221 cited

Self-Supervised 2D/3D Registration for X-Ray to CT Image Fusion

Srikrishna Jaganathan, Maximilian Kukla, Jian Wang +2

Deep Learning-based 2D/3D registration enables fast, robust, and accurate X-ray to CT image fusion when large annotated paired datasets are available for training. However, the nee…

cs.CV202120 cited

Deep Iterative 2D/3D Registration

Srikrishna Jaganathan, Jian Wang, Anja Borsdorf +2

Deep Learning-based 2D/3D registration methods are highly robust but often lack the necessary registration accuracy for clinical application. A refinement step using the classical…

cs.CV20212 cited

Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization

Jian Wang, Miaomiao Zhang

This paper presents a novel hierarchical Bayesian model for unbiased atlas building with subject-specific regularizations of image registration. We develop an atlas construction pr…

cs.CV2021

Learning the Update Operator for 2D/3D Image Registration

Srikrishna Jaganathan, Jian Wang, Anja Borsdorf +1

Image guidance in minimally invasive interventions is usually provided using live 2D X-ray imaging. To enhance the information available during the intervention, the preoperative v…

cs.CV2018

Metric-Driven Learning of Correspondence Weighting for 2-D/3-D Image Registration

Roman Schaffert, Jian Wang, Peter Fischer +2

Registration of pre-operative 3-D volumes to intra-operative 2-D X-ray images is important in minimally invasive medical procedures. Rigid registration can be performed by estimati…