Pak-Hei Yeung

Orcid: 0000-0003-4778-1134

According to our database1, Pak-Hei Yeung authored at least 25 papers between 2018 and 2026.

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Bibliography

2026
Deep Fourier-Embedded Network for RGB and Thermal Salient Object Detection.
IEEE Trans. Circuits Syst. Video Technol., April, 2026

Beyond Benchmarks of IUGC: Rethinking Requirements of Deep Learning Methods for Intrapartum Ultrasound Biometry from Fetal Ultrasound Videos.
CoRR, February, 2026

Beyond benchmarks of IUGC: Rethinking requirements of deep learning method for intrapartum ultrasound biometry from fetal ultrasound videos.
Medical Image Anal., 2026

2025
Optical Flow-Enhanced Mamba U-Net for Cardiac Phase Detection in Ultrasound Videos.
IEEE Trans. Medical Imaging, July, 2025

Bridging the Inter-Domain Gap through Low-Level Features for Cross-Modal Medical Image Segmentation.
CoRR, May, 2025

Exploring Test Time Adaptation for Subcortical Segmentation of the Fetal Brain in 3D Ultrasound.
CoRR, February, 2025

Efficient Fourier Filtering Network With Contrastive Learning for AAV-Based Unaligned Bimodal Salient Object Detection.
IEEE Trans. Geosci. Remote. Sens., 2025

FedDEAP: Adaptive Dual-Prompt Tuning for Multi-Domain Federated Learning.
Proceedings of the 33rd ACM International Conference on Multimedia, 2025

Semi-supervised 3D Medical Segmentation from 2D Natural Images Pretrained Model.
Proceedings of the Machine Learning in Medical Imaging - 16th International Workshop, 2025

Subcortical Masks Generation in CT Images via Ensemble-Based Cross-Domain Label Transfer.
Proceedings of the Medical Image Understanding and Analysis - 29th Annual Conference, 2025

Exploring Test Time Adaptation for Subcortical Segmentation of the Fetal Brain in 3D Ultrasound.
Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

Rapidvol: Rapid Reconstruction of 3D Ultrasound Volumes from Sensorless 2D Scans.
Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

Unsupervised Domain Adaptation via Content Alignment for Hippocampus Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

2024
Sensorless volumetric reconstruction of fetal brain freehand ultrasound scans with deep implicit representation.
Medical Image Anal., 2024

Efficient Fourier Filtering Network with Contrastive Learning for UAV-based Unaligned Bi-modal Salient Object Detection.
CoRR, 2024

Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos.
CoRR, 2024

Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Automated Fetal Biometry Assessment with Deep Ensembles Using Sparse-Sampling of 2D Intrapartum Ultrasound Images.
Proceedings of the Intrapartum Ultrasound - MICCAI 2024 Grand Challenge, 2024

Is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing.
Proceedings of the Machine Learning in Clinical Neuroimaging - 7th International Workshop, 2024

2022
Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021
Learning to map 2D ultrasound images into 3D space with minimal human annotation.
Medical Image Anal., 2021

ImplicitVol: Sensorless 3D Ultrasound Reconstruction with Deep Implicit Representation.
CoRR, 2021

Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-supervised Learning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020
A Multi-Organ Nucleus Segmentation Challenge.
IEEE Trans. Medical Imaging, 2020

2018
Automated synovium segmentation in doppler ultrasound images for rheumatoid arthritis assessment.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018


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