LI Binghua

LI Binghua

Publications

You can also find my articles on my Google Scholar profile.

Journal Articles

Are Diffusion Models Effective Good Feature Extractors for MRI Discriminative Tasks?

Published in Magnetic Resonance in Medical Sciences (MRMS), 2025

This work proposes a novel framework, termed CATS, that uses a diffusion model as a direct feature extractor for MRI-based discriminative tasks

Recommended citation: Binghua Li, Zhe Sun, Chao Li, Koji Kamagata, Christina Andica, Wataru Uchida, Kaito Takabayashi, Sen Guo, Rui Zou, Shigeki Aoki, Toshihisa Tanaka and Qibin Zhao. Are Diffusion Models Effective Good Feature Extractors for MRI Discriminative Tasks? Magnetic Resonance in Medical Sciences, 2025: mp. 2024-0206.
Download Paper | Download Code

Predicting Nasal Diseases Based on Microbiota Relationship Network

Published in Science Progress, 2025

This study proposes a graph-based machine learning framework to identify key nasal microbiome features for disease prediction, revealing keystone bacterial genera linked to nasal diseases.

Recommended citation: Yibo Liang, Jie Mao, Tianlei Qi, Binghua Li, Chenting Zhang, Kai Zhang, Zhe Sun, Guimin Zhang. Predicting Nasal Diseases Based on Microbiota Relationship Network. Science Progress, 2025, 108(1): 00368504251320832.
Download Paper | Download Code

MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor Classification

Published in arXiv, 2024

This work proposes a novel interpretable model named MAProtoNet for brain tumor classification using brain MRI data.

Recommended citation: Binghua Li, Jie Mao, Zhe Sun, Chao Li, Qibin Zhao, Toshihisa Tanaka. MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor Classification. arXiv preprint arXiv:2404.08917, 2024.
Download Paper | Download Code

Graph Empirical Mode Decomposition-Based Data Augmentation Applied to Gifted Children MRI Analysis

Published in Frontiers in Neuroscience, 2022

This paper proposes a graph-emd-based data augmentation methods for gifted children analysis using brain MRI data.

Recommended citation: Xuning Chen, Binghua Li, Hao Jia, Fan Feng, Feng Duan, Zhe Sun, Cesar F. Caiafa, Jordi Sol ́e-Casals. Graph Empirical Mode Decomposition Based Data Augmentation for Gifted Children MRI Dataset Analysis. Frontiers in Neuroscience, 2022, 16: 866735.
Download Paper

Component-mixing Strategy: A Decomposition-based Data Augmentation Algorithm for Motor Imagery Signals

Published in Neurocomputing, 2021

This paper proposes a decomposition-based component-mixing strategy for EEG augmentation using motor imagery signals.

Recommended citation: Binghua Li, Zhiwen Zhang, Feng Duana, Zhenglu Yang, Qibin Zhao, Zhe Sun, Jordi Sol ́e-Casals. Component- mixing Strategy: A Decomposition-based Data Augmentation Algorithm for Motor Imagery Signals. Neurocom- puting, 2021, 465: 325-335.
Download Paper | Download Slides

Conference Papers

Parameter-Efficient Fine-Tuning of 3D DDPM for MRI Image Generation Using Tensor Networks

Published in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), early accepted paper, 2025

This work proposes a novel method, called TenVOO, for parameter-efficient fine-tuning in 3D MRI generation tasks.

Recommended citation: Binghua Li, ZiQing Chang, Tong Liang, Chao Li, Toshihisa Tanaka, Shigeki Aoki, Qibin Zhao and Zhe Sun .Parameter-Efficient Fine-Tuning of 3D DDPM for MRI Image Generation Using Tensor Networks Parameter-Efficient Fine-Tuning of 3D DDPM for MRI Image Generation Using Tensor Networks, MICCAI 2025.
Download Paper | Download Code

The Development of a UAV Target Tracking System Based on YOLOv3-Tiny Object Detection Algorithm

Published in IEEE International Conference on Robotics and Biomimetics (ROBIO), 2021

This paper proposes the use of YOLOv3-tiny for unmanned aerial vehicle control.

Recommended citation: Gan Liu, Ying Tan, Wenchuan Kuang, Lingfeng Chen, Binghua Li, Feng Duan, Chi Zhu. The Development of a UAV Target Tracking System Based on YOLOv3-Tiny Object Detection Algorithm. 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO 2021). IEEE, 2021: 1636-1641.
Download Paper

TPFN: Applying Outer Product Along Time to Multimodal Sentiment Analysis Fusion on Incomplete Data

Published in European Conference on Computer Vision (ECCV), 2020

This paper proposes a TPFN model for multimodal sentiment analysis fusion on incomplete data.

Recommended citation: Binghua Li, Chao Li, Feng Duan, Ning Zheng and Qibin Zhao. TPFN: Applying Outer Product Along Time to Multimodal Sentiment Analysis Fusion on Incomplete Data. 16th European Conference on Computer Vision (ECCV 2020). Springer International Publishing, 2020: 431-447.
Download Paper | Download Slides | Download Code

Classification of Epileptic IEEG Signals by CNN and Data Augmentation

Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020

This paper proposes a novel 1D-cnn model and a data augmentation method for epileptic IEEG classification.

Recommended citation: Xuyang Zhao, Jordi Sol ́e-Casals, Binghua Li, Zihao Huang, Andong Wang, Jianting Cao, Qibin Zhao. Classification of Epileptic IEEG Signals by CNN and Data Augmentation. 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2020). IEEE, 2020: 926-930.
Download Paper