Luyi Han (韓路易)

I am a Lecturer in the Faculty of Applied Sciences at Macao Polytechnic University and a member of the Intelligent Medical Computing Laboratory (IMCL), where I work with Prof. Dr. Tao Tan.

I received my Ph.D. from Radboud University, with doctoral research conducted in the Breast Imaging Group (BIG), Department of Medical Imaging, Radboud University Medical Center (Radboudumc), Nijmegen, under the supervision of Prof. Dr. Ritse Mann, Prof. Dr. W.M. Prokop, and Prof. Dr. Tao Tan.

Email  /  Google Scholar  /  GitHub  /  LinkedIn  /  ResearchGate

My research focuses on artificial intelligence for medical imaging and multimodal healthcare, with an emphasis on clinically meaningful, robust, and generalizable methods. My interests include:

• Breast imaging and clinical prediction: AI-assisted diagnosis, prognosis, and treatment-response modeling using MRI, mammography, ultrasound, and clinical data.
• Tumor vascular imaging and analysis: quantitative analysis of tumor-associated vasculature and perfusion for disease characterization and treatment-response assessment.
• Medical image computing: representation learning, generative modeling, and data-efficient methods for image synthesis, segmentation, and registration, with a focus on domain adaptation and generalization.
• Multimodal healthcare and wearable sensing: integrating medical images, electronic health records, and physiological signals for personalized healthcare, and exploring wearable devices for continuous health monitoring and digital biomarker discovery.

I welcome collaborations that connect methodological advances with real-world healthcare needs. Please feel free to contact me.

I welcome inquiries year-round from motivated prospective master's and Ph.D. students interested in medical imaging, multimodal healthcare, wearable sensing, and related areas of AI. Applicants from computer science, biomedical engineering, data science, medical imaging, health informatics, and related disciplines are welcome.

For current Ph.D. opportunities and application details, please see Open Positions. Prospective master's students are welcome to email me to discuss research interests and potential opportunities.

➤ Breast Imaging

Exploring Personalized Neoadjuvant Therapy Selection Strategies in Breast Cancer: an Explainable Multi-Modal Response Model
eClinicalMedicine, 2025.

➤ Medical Image Synthesis

AsynDiff: Asynchronous-Timestep Diffusion with Noise-Aware Attention for Multi-Sequence MRI Synthesis
MICCAI, 2026.

Virtual Sequence: All in One Medical Image-to-Image Translation
Cell Reports Methods, 2025.

Non-Adversarial Learning: Vector-Quantized Common Latent Space for Multi-Sequence MRI
MICCAI, 2024.

Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRI
Medical Image Analysis, 2024.

An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis
MICCAI, 2023.

Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism
MICCAI, 2023.

GAN-based Disentanglement Learning for Chest X-ray Rib Suppression
Medical Image Analysis, 2022.

➤ Medical Image Segmentation

Multi-Annotation Adaption: A Label-Informed Dynamic Framework for Medical Segmentation and Localization
MICCAI, 2026.

Semi-supervised Segmentation of Lesion from Breast Ultrasound Images with Attentional Generative Adversarial Network
Computer Methods and Programs in Biomedicine, 2020.

➤ Medical Image Registration

Tumor-preserving Deformable Registration of Longitudinal Breast DCE MRI during Neoadjuvant Chemotherapy
Radiology: Artificial Intelligence, 2026.

Localizing the Recurrent Laryngeal Nerve via Ultrasound with a Bayesian Shape Framework
MICCAI, 2022.

➤ Challenges

Anatomy-Aware Intracranial Aneurysm Analysis with Vessel-Guided Dual-Decoder Multi-Task Learning
MICCAI Challenges, 2026.

Fine-Grained Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation
MICCAI Challenges, 2023.

Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation and Koos Grade Prediction based on Semi-Supervised Contrastive Learning
MICCAI Challenges, 2022.

Deformable Registration of Brain MR Images via a Hybrid Loss
MICCAI Challenges, 2021.

➤ More publications see my GoogleScholar

➤ Thesis

➤ Conference Proceedings

CSC Scholarships (No. 202006240065), 2020-2024

➤ Teaching

Macao Polytechnic University, 26/27(1) MATH1111: Linear Algebra

Macao Polytechnic University, 26/27(1) COMP4116: Digital Image and Multimedia Processing

➤ Editorial Activities

Editor, Deep-Breath series at MICCAI (2024–present)

➤ Program Committees

Co-chair of the Organizing Committee of the 3rd Deep Breath Workshop at MICCAI 2026

Member of the Organizing Committee of the MAMA-SYNTH at MICCAI 2026

Member of the Organizing Committee of the Universal UltraSound Image&Video analysis Challenge (UUSIVC) at MICCAI 2026

Member of the Organizing Committee of the Universal UltraSound Image Challenge (UUSIC) at MICCAI 2025

Co-chair of the Technical Committee of the 1st/2nd Deep Breath Workshop at MICCAI 2024/2025

➤ Review Service

AAAI 2026-2027

Advanced Science

Artificial Intelligence in Medicine

Artificial Intelligence Review

BME Frontiers

IEEE Journal of Biomedical and Health Informatics

IEEE Transactions on Medical Imaging

Investigative Radiology

Journal of Medical Internet Research

Medical Image Analysis

Medical Physics

MICCAI 2023-2026

Neurocomputing

The Innovation Oncology

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