Nan Meng

Principle Scientist of CONOVA

Senior Researcher and Engineer

Department of Orthopaedics and Traumatology, Medicine School, the University of Hong Kong.

Nan Meng received his B.S. degree (with distinction) in 2015 in Computer Science from the University of Electronic Science and Technology of China (UESTC), and his Ph.D. degree in 2020 in Electric and Electronic Engineering from The University of Hong Kong. At HKU, he conducted research for image-based cancer diagnosis and released the first large-scale dataset for human somatic bright-field cells. He also conducted research for Light Field Reconstruction in Imaging Systems Laboratory supervised by Prof. Edmund Y. Lam. During his Ph.D., he has consulted for an AI company in the areas of multi-view imaging systems and HKU Medicine School about medical image processing and analysis. After graduation, Dr. Meng joined the Digital Health Laboratory in HKU as a research engineer.

Talk

Datasets

His research interests include computational optics and imag-ing, from algorithms to applications and medical imaging. His research direction includes light-field reconstruction, view synthesis, depth estimation and medical imaging.

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Projects

AlignPro

TM

TM

AlignPro     is a medical AI platform that supports automatic spine malalignment analysis. It Integrates customers'  radiographic spinal images for analysis and carries out personalized visualization results for doctors' reference.

LRCIS System

Light-based radiograph-comparable image synthesis (LRCIS) system produces accurate spine alignment radiographs based on optical images with depth information.

 

Clinical

Computer Science

Bioinformatics

Select Publication

[J] Meng, Nan and Cheung, Jason Pui Yin and Wong, Kwan-Yee Kenneth and Dokos, Socrates and Li, Sofia Pik Hung and Choy, Richard W. and To, Samuel Ching Hang and Li, Ricardo J. and Zhang, Teng, "An Artificial Intelligence Powered Platform for Auto-Analyses of Spine Alignment Irrespective of Image Quality with Prospective Validation", Lancet: EclinicalMedicine, January 2022.

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[J] Nan Meng, Kai Li, Jianzhuang Liu, and Edmund Y. Lam, “Light Field View Synthesis via Aperture Disparity and Warping Confidence Map”, IEEE Transactions on Image Processing, March 2021.

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[J] Nan Meng, Hayden K.-H. So, Xing Sun, and Edmund Y. Lam, “High-Dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 3, pp. 873-886, March 2020.

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[J] Nan Meng, Edmund Y. Lam, Kevin K.-M. Tsia and Hayden K.-H. So, “Large-Scale Multi-Class Image-Based Cell Classification with Deep Learning”, IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 5, pp. 2091-2098, 2019.

 

Review Service

2022

          IEEE: IEEE JBHI / IEEE TIP / IEEE TCI

    Springer: SIVP

           OSA: JOSA A

2021