World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
8553
World Ranking
9174
National Ranking
128

Overview

Yen-Wei Chen is affiliated with Ritsumeikan University in Japan and has contributed extensively to research at the intersection of computer science and medicine. Their main fields of study include Computer Science and Medicine, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Neurology, and Biomedical Engineering.

The scientist's research topics include:

  • Radiomics and Machine Learning in Medical Imaging
  • Advanced Neural Network Applications
  • AI in Cancer Detection
  • Medical Image Segmentation Techniques
  • Brain Tumor Detection and Classification
  • COVID-19 Diagnosis Using AI
  • Advanced Image Processing Techniques

Yen-Wei Chen has co-authored numerous publications with frequent collaborators including Lanfen Lin, Yutaro Iwamoto, Hongjie Hu, Xian-Hua Han, and Ruofeng Tong.

The scientist has published significant work in well-known venues such as:

  • arXiv (Cornell University)
  • IEEE Journal of Biomedical and Health Informatics
  • 2022 IEEE International Conference on Consumer Electronics (ICCE)
  • 2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)
  • Applied Sciences

Some of the recent papers authored or co-authored by Yen-Wei Chen include:

  • Mixed Transformer U-Net for Medical Image Segmentation, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Conservation and Divergence of Vulnerability and Responses to Stressors Between Human and Mouse Astrocytes, 2021, Nature Communications
  • Accuracy of CAD/CAM Digital Impressions with Different Intraoral Scanner Parameters, 2020, Sensors
  • CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation, 2022, Proceedings of the 30th ACM International Conference on Multimedia
  • Automatic Cephalometric Landmark Detection on X-ray Images Using a Deep-Learning Method, 2020, Applied Sciences

Yen-Wei Chen has also contributed to multiple book publications, predominantly with Springer Nature and Springer International Publishing. Titles include Handbook of Artificial Intelligence in Healthcare (2021), Intelligent System Design (2020, 2022), Artificial Intelligence and Machine Learning for Healthcare (2022), Innovation in Medicine and Healthcare (2020, 2021), Recent Advances in Logo Detection Using Machine Learning Paradigms (2024), and Recent Advances in Deep Learning for Medical Image Analysis (2025).

Best Publications

  • Mixed Transformer U-Net For Medical Image Segmentation.

    Hongyi Wang;Shiao Xie;Lanfen Lin;Yutaro Iwamoto

  • Automated segmentation of the liver from 3D CT images using probabilistic atlas and multilevel statistical shape model.

    Toshiyuki Okada;Ryuji Shimada;Masatoshi Hori;Masahiko Nakamoto

  • Letter: Supervised kernel locality preserving projections for face recognition

    Jian Cheng;Qingshan Liu;Hanqing Lu;Yen-Wei Chen

  • Ensemble learning for independent component analysis

    Jian Cheng;Qingshan Liu;Hanqing Lu;Yen-Wei Chen

  • VesselNet: A deep convolutional neural network with multi pathways for robust hepatic vessel segmentation

    Titinunt Kitrungrotsakul;Xian-Hua Han;Yutaro Iwamoto;Lanfen Lin

  • Medical Image Classification Using Deep Learning

    Weibin Wang;Dong Liang;Qingqing Chen;Yutaro Iwamoto

  • Automatic Cephalometric Landmark Detection on X-ray Images Using a Deep-Learning Method

    Yu Song;Xu Qiao;Yutaro Iwamoto;Yen-wei Chen

  • Automated segmentation of the liver from 3D CT images using probabilistic atlas and multi-level statistical shape model

    Toshiyuki Okada;Ryuji Shimada;Yoshinobu Sato;Masatoshi Hori

  • Robust multi-logo watermarking by RDWT and ICA

    Thai Duy Hien;Zensho Nakao;Yen-Wei Chen

  • Robust Japanese Road Sign Detection and Recognition in Complex Scenes Using Convolutional Neural Networks

    Ryo Hasegawa;Yutaro Iwamoto

  • Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level.

    Hao Sun;Jiaqing Liu;Shurong Chai;Zhaolin Qiu

  • Semi-supervised Segmentation of Liver Using Adversarial Learning with Deep Atlas Prior

    Han Zheng;Lanfen Lin;Hongjie Hu;Qiaowei Zhang

  • Sparse Codebook Model of Local Structures for Retrieval of Focal Liver Lesions Using Multiphase Medical Images

    Jian Wang;Xian-Hua Han;Yingying Xu;Lanfen Lin

  • Segmentation of Liver in Low-Contrast Images Using K-Means Clustering and Geodesic Active Contour Algorithms

    Amir Hossein Foruzan;Yen-Wei Chen;Reza Aghaeizadeh Zoroofi;Akira Furukawa

  • Improved segmentation of low-contrast lesions using sigmoid edge model

    Amir Hossein Foruzan;Yen-Wei Chen

  • K-CPD: Learning of overcomplete dictionaries for tensor sparse coding

    Guifang Duan;Hongcui Wang;Zhenyu Liu;Junping Deng

  • Combining Convolutional and Recurrent Neural Networks for Classification of Focal Liver Lesions in Multi-phase CT Images

    Dong Liang;Lanfen Lin;Hongjie Hu;Qiaowei Zhang

  • Multi-Level and Multi-Scale Spatial and Spectral Fusion CNN for Hyperspectral Image Super-Resolution

    Xian-Hua Han;YinQiang Zheng;Yen-Wei Chen

  • Feature Selection Using Recursive Feature Elimination for Handwritten Digit Recognition

    Xiangyan Zeng;Yen-Wei Chen;Caixia Tao;Deborah van Alphen

  • Automatic gender recognition based on pixel-pattern-based texture feature

    Huchuan Lu;Yingjie Huang;Yenwei Chen;Yenwei Chen;Deli Yang

  • Abdominal multi-organ segmentation of CT images based on hierarchical spatial modeling of organ interrelations

    Toshiyuki Okada;Yasuhide Yoshida;Masatoshi Hori;Ronald M. Summers

  • A novel method for gaze tracking by local pattern model and support vector regressor

    Hu-Chuan Lu;Guo-Liang Fang;Chao Wang;Yen-Wei Chen

  • Computer-Assisted Preoperative Planning for Reduction of Proximal Femoral Fracture Using 3-D-CT Data

    T. Okada;Y. Iwasaki;T. Koyama;N. Sugano

  • 2009 Fifth International Conference on Natural Computation

    Motoi Kinishi;Toshiyuki Okada;Masatoshi Hori;Yen-Wei Chen

Frequent Co-Authors

Ruofeng Tong
Ruofeng Tong Zhejiang University
Yoshinobu Sato
Yoshinobu Sato Nara Institute of Science and Technology
Huchuan Lu
Huchuan Lu Dalian University of Technology
Hanqing Lu
Hanqing Lu Chinese Academy of Sciences
Jian Cheng
Jian Cheng Chinese Academy of Sciences
Yasushi Yagi
Yasushi Yagi Osaka University
Qingshan Liu
Qingshan Liu Nanjing University of Information Science and Technology
Yinqiang Zheng
Yinqiang Zheng National Institute of Informatics

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