Chen Shen

Orcid: 0000-0001-8284-9048

Affiliations:
  • Nagoya University, Graduate School of Informatics, Nagoya, Japan


According to our database1, Chen Shen authored at least 15 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Anatomical attention can help to segment the dilated pancreatic duct in abdominal CT.
Int. J. Comput. Assist. Radiol. Surg., April, 2024

2023
ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

2022
A cascaded fully convolutional network framework for dilated pancreatic duct segmentation.
Int. J. Comput. Assist. Radiol. Surg., 2022

Effective hyperparameter optimization with proxy data for multi-organ segmentation.
Proceedings of the Medical Imaging 2022: Image Processing, 2022

Joint Multi Organ and Tumor Segmentation from Partial Labels Using Federated Learning.
Proceedings of the Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health, 2022

2021
Extraction of lung and lesion regions from COVID-19 CT volumes using 3D fully convolutional networks.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

Multi-task Federated Learning for Heterogeneous Pancreas Segmentation.
Proceedings of the Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning, 2021

Attention-Guided Pancreatic Duct Segmentation from Abdominal CT Volumes.
Proceedings of the Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning, 2021

2020
Spatial information-embedded fully convolutional networks for multi-organ segmentation with improved data augmentation and instance normalization.
Proceedings of the Medical Imaging 2020: Image Processing, 2020

Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning.
Proceedings of the Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning, 2020

Usefulness of fine-tuning for deep learning based multi-organ regions segmentation method from non-contrast CT volumes using small training dataset.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
Improving V-Nets for multi-class abdominal organ segmentation.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

2018
Deep learning and its application to medical image segmentation.
CoRR, 2018

On the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks.
CoRR, 2018

A Multi-scale Pyramid of 3D Fully Convolutional Networks for Abdominal Multi-organ Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018


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