Zhicheng He

Zhicheng He

he/him

Second-year Master of Engineering by Research student in the Department of Biomedical Engineering at the National University of Singapore (NUS).
Research interests: medical image analysis and multi-modal large language models.

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Pages

Posts

Future Blog Post

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Blog Post number 1

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notes

portfolio

progress

Week 01 — Research Progress

Published:

Goals

  • Define Q1 research focus in medical image analysis.
  • Survey recent multi-modal LLM papers relevant to clinical imaging.

publications

Transformer-based visual question answering model comparison

Published in Journal of Physics: Conference Series, 2023

A comparative analysis of LXMERT and UNITER models for visual question answering tasks.

Recommended citation: Zhicheng He, Yuanzhi Li, Dingming Zhang. (2023). "Transformer-based visual question answering model comparison." Journal of Physics: Conference Series, 2646(1), 012031.
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Deep Learning-Based Detection of Impacted Teeth on Panoramic Radiographs

Published in Biomedical Engineering and Computational Biology, 2024

Fine-tuning MedSAM for impacted tooth segmentation in X-ray images to aid dental diagnoses.

Recommended citation: He Zhicheng, Wang Yipeng, Li Xiao. (2024). "Deep Learning-Based Detection of Impacted Teeth on Panoramic Radiographs." Biomedical Engineering and Computational Biology, 15, 11795972241288319.
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Endouic: Promptable diffusion transformer for unified illumination correction in capsule endoscopy

Published in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024

A WCE unified illumination correction solution using an end-to-end promptable diffusion transformer (DiT) model.

Recommended citation: Long Bai, Tong Chen, Qiaozhi Tan, Wan Jun Nah, Yanheng Li, Zhicheng He, Sishen Yuan, Zhen Chen, Jinlin Wu, Mobarakol Islam, Zhen Li, Hongbin Liu, Hongliang Ren. (2024). "Endouic: Promptable diffusion transformer for unified illumination correction in capsule endoscopy." International Conference on Medical Image Computing and Computer-Assisted Intervention, Pages 296-306.
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Graph Matching Based Graph Self-Supervised Learning for Molecular Property Prediction

Published in 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024

A graph self-supervised learning framework utilizing graph matching for molecular property prediction.

Recommended citation: Hongxiang Lin, Yixiao Zhou, Huiying Hu, Zhicheng He, Runzhi Wu, Xiaoqing Lyu. (2024). "Graph Matching Based Graph Self-Supervised Learning for Molecular Property Prediction." 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Pages 7092-7094.
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Multimodal Content Alignment with LLM for Visual Presentation of Papers

Published in International Conference on Document Analysis and Recognition (ICDAR), 2025

Paper2PPT framework for generating visual presentations of scientific papers with cross-modal alignment.

Recommended citation: Huiying Hu, Zhicheng He, Yixiao Zhou, Tongwei Zhang, Xiaoqing Lyu. (2025). "Multimodal Content Alignment with LLM for Visual Presentation of Papers." International Conference on Document Analysis and Recognition, Pages 238-256.
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SSSI: Self-prompted Segmentation of Scientific Illustrations

Published in International Conference on Document Analysis and Recognition (ICDAR), 2025

A self-prompted segmentation framework for scientific illustrations using SAM-based methods.

Recommended citation: Tuo Wang, Yixiao Zhou, Tongwei Zhang, Zhicheng He, Yumeng Zhao, Xiaoqing Lyu. (2025). "SSSI: Self-prompted Segmentation of Scientific Illustrations." International Conference on Document Analysis and Recognition, Pages 347-361.
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Scalable next-scale autoregression for medical image generation across anatomical regions

Published in arXiv preprint arXiv:2602.14512 (v3), 2026

A next-scale autoregressive foundation model for CT and MRI generation across six anatomical regions.

Recommended citation: Zhicheng He, Yunpeng Zhao, Junde Wu, Ziwei Niu, Ziyue Wang, Bohan Li, Zijun Li, Lanfen Lin, Nan Liu, Yueming Jin. (2026). "Scalable next-scale autoregression for medical image generation across anatomical regions." arXiv preprint arXiv:2602.14512 (v3).
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Granulon: Awakening Pixel-Level Visual Encoders with Adaptive Multi-Granularity Semantics for MLLM

Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026

A multimodal model that adapts visual feature granularity to the text context.

Recommended citation: Junyuan Mao, Qiankun Li, Linghao Meng, Zhicheng He, Xinliang Zhou, Kun Wang, Yang Liu, Yueming Jin. (2026). "Granulon: Awakening Pixel-Level Visual Encoders with Adaptive Multi-Granularity Semantics for MLLM." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Pages 26317-26327.
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Morphological Decoupling-Based Skeletal Classification for Clinical Assessment of Malocclusion

Published in Biocybernetics and Biomedical Engineering, 2026

A CBCT-based graph framework for skeletal classification of malocclusion.

Recommended citation: Zhichun Jin*, Zhicheng He*, Hao Xu, Dongyang Li, Lin Wang, Hongliang Ren, Long Bai. (2026). "Morphological Decoupling-Based Skeletal Classification for Clinical Assessment of Malocclusion." Biocybernetics and Biomedical Engineering, 46(4), Pages 650-660.
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Reasoning with Memory: A Temporal Granularity-Adaptive Framework for Training-Free Long Video Understanding

Published in European Conference on Computer Vision (ECCV), 2026

A memory-guided keyframe selection framework for long-video question answering.

Recommended citation: Linghao Meng, Qiankun Li, Junyuan Mao, Pujin Liao, Zhicheng He, Enbo Zhang, Kun Wang, Yang Liu, Huazhu Fu, Yueming Jin. (2026). "Reasoning with Memory: A Temporal Granularity-Adaptive Framework for Training-Free Long Video Understanding." European Conference on Computer Vision, Pages 588-606.
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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