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Self-Supervised Neuron Segmentation with Multi-Agent Reinforcement Learning IJCAI (oral) | August 17, 2023

Chen, Yinda ; Huang, Wei ; Zhou, Shenglong ; Chen, Qi ; Xiong, Zhiwei

This paper proposes a decision - based MIM for neuron segmentation in EM data. It uses MARL to optimize masking, outperforming alternatives.

@inproceedings{chen2023self,
  title={Self-supervised neuron segmentation with multi-agent reinforcement learning},
  author={Chen, Yinda and Huang, Wei and Zhou, Shenglong and Chen, Qi and Xiong, Zhiwei},
  booktitle={Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence},
  pages={609--617},
  year={2023}
  }

Learning multiscale consistency for self-supervised electron microscopy instance segmentation ICASSP | April 13, 2024

Chen, Yinda ; Huang, Wei ; Liu, Xiaoyu ; Deng, Shiyu ; Chen, Qi ; Xiong, Zhiwei

A pretraining framework for EM volume instance segmentation is proposed. It enforces multiscale consistency and shows good performance in neuron and mitochondria segmentation.

@inproceedings{chen2024learning,
  title={Learning multiscale consistency for self-supervised electron microscopy instance segmentation},
  author={Chen, Yinda and Huang, Wei and Liu, Xiaoyu and Deng, Shiyu and Chen, Qi and Xiong, Zhiwei},
  booktitle={ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={1566--1570},
  year={2024},
  organization={IEEE}
}

Unsupervised Domain Adaptation for EM Image Denoising with Invertible Networks TMI | July 19, 2024

Deng, Shiyu ; Chen, Yinda ; Huang, Wei ; Zhang, Ruobing ; Xiong, Zhiwei

The paper proposes an unsupervised domain adaptation method for EM image denoising with invertible networks, outperforming existing methods.

@article{deng2024unsupervised,
title={Unsupervised Domain Adaptation for EM Image Denoising with Invertible Networks},
author={Deng, Shiyu and Chen, Yinda and Huang, Wei and Zhang, Ruobing and Xiong, Zhiwei},
journal={IEEE Transactions on Medical Imaging},
year={2024},
publisher={IEEE}
}

BIMCV-R: A Landmark Dataset for 3D CT Text-Image Retrieval MICCAI | October 06, 2024

Chen, Yinda ; Liu, Che ; Liu, Xiaoyu ; Arcucci, Rossella ; Xiong, Zhiwei

This paper presents BIMCV-R, a 3D CT text - image retrieval dataset, and MedFinder. Tests show MedFinder outperforms baselines in related tasks.

@inproceedings{chen2024bimcv,
  title={Bimcv-r: A landmark dataset for 3d ct text-image retrieval},
  author={Chen, Yinda and Liu, Che and Liu, Xiaoyu and Arcucci, Rossella and Xiong, Zhiwei},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={124--134},
  year={2024},
  organization={Springer}
}

MaskFactory: Towards High-quality Synthetic Data Generation for Dichotomous Image Segmentation NeurIPS | October 17, 2024

Qian, Haotian* ; Chen, Yinda* ; Lou, Shengtao ; Khan, Fahad Shahbaz ; Jin, Xiaogang ; Fan, Deng-Ping

MaskFactory proposes a two - stage method to generate high - quality synthetic datasets for DIS, outperforming existing methods in quality and efficiency.

@article{qian2024mask,
  title={MaskFactory: Towards High-quality Synthetic Data Generation for Dichotomous Image Segmentation},
  author={Qian, Haotian and Chen, YD and Lou, Shengtao and Khan, Fahad Shahbaz and Jin, Xiaogang and Fan, Deng-Ping},
  journal={arXiv preprint arXiv:2412.19080},
  year={2024}
}

Condition-generation Latent Coding with an External Dictionary for Deep Image Compression AAAI (oral) | March 06, 2025

Wu, Siqi* ; Chen, Yinda* ; Liu, Dong ; He, Zhihai

The paper proposes CLC for deep image compression. It uses a dictionary to generate references, shows good performance, and has theoretical analysis.

@article{wu2023conditional,
  title={Conditional Latent Coding with Learnable Synthesized Reference for Deep Image Compression},
  author={Wu, Siqi and Chen, Yinda and Liu, Dong and He, Zhihai},
  journal={arXiv preprint arXiv:XXXX.XXXXX},
  year={2025}
}

Talk on Medical Pretraining Using Generative Methods JD.com, Intelligent Healthcare Group | March 01, 2023

Delivered a talk on the application of generative methods in vision-language models (VLMs) for medical pretraining. The presentation focused on leveraging advanced generative techniques to enhance performance in medical AI tasks.

XMU Wiserclub–Data Mining Xiamen University, WISER Club | August 01, 2021

Responsible for designing and discussing the Data Mining course. Delivered lectures on Clustering and Feature Extraction topics.