Professor | Junhua Chen | Asia Growth Partners

Name	Junhua Chen
Language ability	Chinese, English
Province	Shanghai

Name

Junhua Chen

Language ability

Chinese, English

Province

Shanghai

University/Lab Affiliation and Title	Shanghai University
Faculty	Medicine
Academic Background & Achievements	2023 PhD: Maastricht University Published 11 SCI-indexed research papers Granted 2 invention patents
Work Experience	2023 - Shanghai University Medical School - Assistant Professor

University/Lab Affiliation and Title

Shanghai University

Faculty

Medicine

Academic Background & Achievements

2023 PhD: Maastricht University
Published 11 SCI-indexed research papers
Granted 2 invention patents

Work Experience

2023 - Shanghai University Medical School - Assistant Professor

Areas of Focus	Medical Artificial Intelligence Quantitative Medical Image Analysis Generative Models in Medical Imaging
Publications	A Solution to Reconstruct Cross-Cut Shredded Text Documents Based on K-means algorithm and ant colony algorithm., Junhua Chen, Miao Tian, Wenxin Wang, Xingmin Qi and Youjun Liu, 2019 Lung cancer diagnosis using deep attention-based multiple instance learning and radiomics., Junhua Chen , Haiyan Zeng, Chong Zhang, Zhenwei Shi, Andre Dekker, Leonard Wee, and Inigo Bermejo, 2022 Using 3D Deep Features from CT scans for Cancer Prognosis based on a Video Classification Model: A Multi-Dataset Feasibility Study., Junhua Chen , Andre Dekker, Leonard Wee, Inigo Bermejo, 2023 Generative models improve radiomics reproducibility in low dose CTs: a simulation study., Junhua Chen , Chong Zhang, Alberto Traverso, Ivan Zhovannik, Andre Dekker, Leonard Wee, and Inigo Bermejo, 2021 Deep Learning Based Unpaired Image-to-Image Translation Applications for Medical Physics: A Systematic Review., Junhua Chen ,#, Shenlun Chen ,#, Andre Dekker, Leonard Wee, Inigo Bermejo, 2023 A high splicing accuracy solution to reconstruction of cross-cut shredded text document problem., Junhua Chen, Daguan Ke, Zhanghong Wang and Youjun Liu, 2018 Real-time Locating of Surgical Incision in Cataract Phacoemulsification., Junhua Chen, Xingming Qi, Wenxin Wang, Bao Li and Youjun Liu, 2020 Generative models improve radiomics performance in different tasks and different datasets: An experimental study., Junhua Chen, Andre Dekker, Leonard Wee, Inigo Bermejo, 2022 Improving reproducibility and performance of radiomics in low-dose CT using cycle GANs., Junhua Chen, Andre Dekker, Leonard Wee, Inigo Bermejo, 2022 Are all shortcuts in encoder–decoder networks beneficial for CT denoising., Junhua Chen , Chong Zhang, Leonard Wee, Andre Dekker, and Inigo Bermejo, 2023

Areas of Focus

Medical Artificial Intelligence
Quantitative Medical Image Analysis
Generative Models in Medical Imaging

Publications

A Solution to Reconstruct Cross-Cut Shredded Text Documents Based on K-means algorithm and ant colony algorithm., Junhua Chen, Miao Tian, Wenxin Wang, Xingmin Qi and Youjun Liu, 2019
Lung cancer diagnosis using deep attention-based multiple instance learning and radiomics., Junhua Chen *, Haiyan Zeng, Chong Zhang, Zhenwei Shi, Andre Dekker, Leonard Wee, and Inigo Bermejo, 2022
Using 3D Deep Features from CT scans for Cancer Prognosis based on a Video Classification Model: A Multi-Dataset Feasibility Study., Junhua Chen *, Andre Dekker, Leonard Wee, Inigo Bermejo, 2023
Generative models improve radiomics reproducibility in low dose CTs: a simulation study., Junhua Chen *, Chong Zhang, Alberto Traverso, Ivan Zhovannik, Andre Dekker, Leonard Wee, and Inigo Bermejo, 2021
Deep Learning Based Unpaired Image-to-Image Translation Applications for Medical Physics: A Systematic Review., Junhua Chen *,#, Shenlun Chen *,#, Andre Dekker, Leonard Wee, Inigo Bermejo, 2023
A high splicing accuracy solution to reconstruction of cross-cut shredded text document problem., Junhua Chen, Daguan Ke, Zhanghong Wang and Youjun Liu, 2018
Real-time Locating of Surgical Incision in Cataract Phacoemulsification., Junhua Chen, Xingming Qi, Wenxin Wang, Bao Li and Youjun Liu, 2020
Generative models improve radiomics performance in different tasks and different datasets: An experimental study., Junhua Chen*, Andre Dekker, Leonard Wee, Inigo Bermejo, 2022
Improving reproducibility and performance of radiomics in low-dose CT using cycle GANs., Junhua Chen*, Andre Dekker, Leonard Wee, Inigo Bermejo, 2022
Are all shortcuts in encoder–decoder networks beneficial for CT denoising., Junhua Chen *, Chong Zhang, Leonard Wee, Andre Dekker, and Inigo Bermejo, 2023

Ai Machine Learning Image Analysis Medical Imaging Deep Learning Radiomics Ct Scans Cancer Diagnosis Image Translation Generative Adversarial Networks

Yuemin Bian - Shanghai University

Yuanjun Wang - University of Shanghai for Science and Technology

Yuemin Bian - Shanghai University

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