John C. Stendahl

According to our database, John C. Stendahl authored at least 12 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Segmentation-Free PVC for Cardiac SPECT Using a Densely-Connected Multi-Dimensional Dynamic Network.

Huidong Xie, Zhao Liu, Luyao Shi, Kathleen Greco, Xiongchao Chen, Bo Zhou, Attila Feher, John C. Stendahl, Nabil Boutagy, Tassos C. Kyriakides, Ge Wang, Albert J. Sinusas, Chi Liu

IEEE Trans. Medical Imaging, May, 2023

An Adaptive Correspondence Scoring Framework for Unsupervised Image Registration of Medical Images.

Xiaoran Zhang, John C. Stendahl, Lawrence H. Staib, Albert J. Sinusas, Alexandra L. N. Wong, James S. Duncan

CoRR, 2023

2021

Learning-Based Regularization for Cardiac Strain Analysis via Domain Adaptation.

Allen Lu, Shawn S. Ahn, Kevinminh Ta, Nripesh Parajuli, John C. Stendahl, Zhao Liu, Nabil Boutagy, Geng-Shi Jeng, Lawrence H. Staib, Matthew O'Donnell, Albert J. Sinusas, James S. Duncan

IEEE Trans. Medical Imaging, 2021

Simultaneous Segmentation and Motion Estimation of Left Ventricular Myocardium in 3D Echocardiography Using Multi-task Learning.

Kevinminh Ta, Shawn S. Ahn, John C. Stendahl, Jonathan Langdon, Albert J. Sinusas, James S. Duncan

Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021

Shape-Regularized Unsupervised Left Ventricular Motion Network With Segmentation Capability In 3d+ Time Echocardiography.

Kevinminh Ta, Shawn S. Ahn, John C. Stendahl, Albert J. Sinusas, James S. Duncan

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

2020

A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography.

Kevinminh Ta, Shawn S. Ahn, John C. Stendahl, Albert J. Sinusas, James S. Duncan

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

A Semi-Supervised Joint Learning Approach to Left Ventricular Segmentation and Motion Tracking in Echocardiography.

Kevinminh Ta, Shawn S. Ahn, Allen Lu, John C. Stendahl, Albert J. Sinusas, James S. Duncan

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019

Flow network tracking for spatiotemporal and periodic point matching: Applied to cardiac motion analysis.

Nripesh Parajuli, Allen Lu, Kevinminh Ta, John C. Stendahl, Nabil Boutagy, Imran Alkhalil, Melissa Eberle, Geng-Shi Jeng, Maria Zontak, Matthew O'Donnell, Albert J. Sinusas, James S. Duncan

Medical Image Anal., 2019

2018

Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation.

Allen Lu, Nripesh Parajuli, Maria Zontak, John C. Stendahl, Kevinminh Ta, Zhao Liu, Nabil Boutagy, Geng-Shi Jeng, Imran Alkhalil, Lawrence H. Staib, Matthew O'Donnell, Albert J. Sinusas, James S. Duncan

CoRR, 2018

2017

Flow Network Based Cardiac Motion Tracking Leveraging Learned Feature Matching.

Nripesh Parajuli, Allen Lu, John C. Stendahl, Maria Zontak, Nabil Boutagy, Imran Alkhalil, Melissa Eberle, Ben A. Lin, Matthew O'Donnell, Albert J. Sinusas, James S. Duncan

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Learning-Based Spatiotemporal Regularization and Integration of Tracking Methods for Regional 4D Cardiac Deformation Analysis.

Allen Lu, Maria Zontak, Nripesh Parajuli, John C. Stendahl, Nabil Boutagy, Melissa Eberle, Imran Alkhalil, Matthew O'Donnell, Albert J. Sinusas, James S. Duncan

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

2016

Integrated Dynamic Shape Tracking and RF Speckle Tracking for Cardiac Motion Analysis.

Nripesh Parajuli, Allen Lu, John C. Stendahl, Maria Zontak, Nabil Boutagy, Melissa Eberle, Imran Alkhalil, Matthew O'Donnell, Albert J. Sinusas, James S. Duncan

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016