๐Ÿ‘‹ About Me

Hi there! I am an AI Engineer and Researcher dedicated to bridging the gap between state-of-the-art deep learning research and real-world clinical applications. With a PhD background in medical image analysis, I specialize in building robust, interpretable models for complex diagnostic tasks.

Currently based in Amsterdam, I focus on computer vision, medical imaging, and automated deep learning pipelines that enhance clinical decision-making and improve patient outcomes.

๐ŸŽฏ Research Interests

  • ๐Ÿง  Deep Learning
  • ๐Ÿฅ Medical Imaging
  • ๐Ÿค– Computer Vision
  • ๐Ÿ”ฌ Precision Oncology
  • ๐ŸŽ—๏ธ Tumor Segmentation
  • ๐Ÿ’Š Treatment Response
  • ๐Ÿ“ท CT/PET
  • ๐Ÿงฒ MRI
  • ๐Ÿ“Š Data Analysis

๐Ÿš€ Featured Projects

๐Ÿ† HECKTOR 2025 Competition

Top-1 Solution for Segmentation and Detection of Head and Neck Cancer Tumors. Developed a multi-modal deep learning approach for robust lesion detection.

โœจ Anatomy-aware nnU-Net Open Source

Improved rectal tumor segmentation using anomaly fusion derived from anatomical inpainting. Integrates domain knowledge into automated segmentation pipelines.

๐Ÿ› ๏ธ MLNet Research Tool

An automated deep learning pipeline for EMVI classification and response prediction of rectal cancer using baseline MRI.

๐Ÿ“š Selected Publications

  • Improving rectal tumor segmentation with anomaly fusion derived from anatomical inpainting
    Lishan Cai, et al.
    Scientific Reports (2025)
  • An automated deep learning pipeline for EMVI classification and response prediction of rectal cancer
    Lishan Cai, et al.
    npj Precision Oncology (2024)

๐Ÿ’ผ Experience

๐Ÿ‘จโ€๐Ÿ’ป AI Medical Analyst 2024 โ€“ Present
Amsterdam UMC, Amsterdam
๐ŸŽ“ PhD Candidate 2020 โ€“ 2024
Netherlands Cancer Institute

๐ŸŽ“ Education

PhD in AI (Medical Image Analysis) 2020 โ€“ 2024
Netherlands Cancer Institute
M.Sc. Bioinformatics 2017 โ€“ 2019
Copenhagen University