Pak Hei (Hugo) Yeung 楊栢熙

I am a DPhil student in the Oxford Machine Learning in NeuroImaging Lab at the University of Oxford, where I am supervised by Dr. Ana Namburete and Dr. Weidi Xie, and generously supported by The R C Lee Centenary Scholarship.

I received my BEng (Medical Engineering) from the University of Hong Kong, where I was supervised by Dr. WeiNing Lee for my final year project.

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Research

I'm interested in medical image analysis, machine learning, ultrasound imaging, and computer vision.

Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images
Pak Hei Yeung, Moska Aliasi, Monique Haak, The INTERGROWTH-21st Consortium, Weidi Xie, Ana I.L. Namburete
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022
project page / paper / video / code (coming soon) / bibtex

Sensorless 3D localization of 2D freehand scans. Trained with just 3D volumes, the model can be adapted to any domains (e.g. machines) in an unsupervised manner.

ImplicitVol: Sensorless 3D Ultrasound Reconstruction with Deep Implicit Representation
Pak Hei Yeung, Linde Hesse, Moska Aliasi, Monique Haak, The INTERGROWTH-21st Consortium, Weidi Xie*, Ana I.L. Namburete*
Arxiv preprint, 2021
project page / paper / video / code (coming soon) / bibtex

Reconstructing a 3D volume from 2D freehand ultrasound images by training a deep network to implicitly represent the volume.

Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning
Pak Hei Yeung, Ana I.L. Namburete*, Weidi Xie*
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021
project page / paper / video / code / bibtex

Trained with just raw 3D volumes, a single Sli2Vol model can be used to propagate a single-slice annotation to the whole 3D volume, for any structures across different modalities.

Learning to Map 2D Ultrasound Images into 3D Space with Minimal Human Annotation
Pak Hei Yeung, Moska Aliasi, Aris T. Papageorghiou, Monique Haak, Weidi Xie, Ana I.L. Namburete
Medical Image Analysis, Volume 70, 2021 (Impact factor ∼ 11)
project page / paper / video / code / bibtex

A network, trained with just registered volumes, to predict the 3D location of 2D freehand ultrasound fetal brain images and video.


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