Mingyuan Meng/蒙明远

Mingyuan Meng/蒙明远

He/His

PhD candidate at the University of Sydney && Visiting scholar at Shanghai Jiao Tong University

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

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Blog Post number 4

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Blog Post number 3

less than 1 minute read

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Blog Post number 2

less than 1 minute read

Published:

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Blog Post number 1

less than 1 minute read

Published:

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portfolio

publications

DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CT

Published in IEEE Journal of Biomedical and Health Informatics, 2022

Recommended citation: Mingyuan Meng, Bingxin Gu, Lei Bi, Shaoli Song, David Dagan Feng, and Jinman Kim. DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CT. IEEE Journal of Biomedical and Health Informatics, 26(9):4497-4507, 2022.
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Multi-task Deep Learning-based Radiomic Nomogram for Prognostic Prediction in Locoregionally Advanced Nasopharyngeal Carcinoma

Published in European Journal of Nuclear Medicine and Molecular Imaging , 2023

Recommended citation: Bingxin Gu*, Mingyuan Meng*, Mingzhen Xu*, David Dagan Feng, Lei Bi, Jinman Kim, and Shaoli Song. Multi-task Deep Learning-based Radiomic Nomogram for Prognostic Prediction in Locoregionally Advanced Nasopharyngeal Carcinoma. European Journal of Nuclear Medicine and Molecular Imaging, 50:3996-4009, 2023.
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Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer

Published in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023

Recommended citation: Mingyuan Meng, Lei Bi, Michael Fulham, Dagan Feng, and Jinman Kim. Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pages 400-410, 2023.
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Non-iterative Coarse-to-Fine Transformer Networks for Joint Affine and Deformable Image Registration

Published in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023

Recommended citation: Mingyuan Meng, Lei Bi, Michael Fulham, Dagan Feng, and Jinman Kim. Non-iterative Coarse-to-Fine Transformer Networks for Joint Affine and Deformable Image Registration. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pages 750-760, 2023.
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3DPX: Progressive 2D-to-3D Oral Image Reconstruction with Hybrid MLP-CNN Networks

Published in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024

Recommended citation: Xiaoshuang Li, Mingyuan Meng, Lei Bi, Eduardo Delamare, Zimo Huang, Dagan Feng, Bin Sheng, and Jinman Kim. 3DPX: Progressive 2D-to-3D Oral Image Reconstruction with Hybrid MLP-CNN Networks. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pages 25-34, 2024.
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Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance

Published in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024

Recommended citation: Shuchang Ye, Mingyuan Meng, Mingjian Li, Dagan Feng, and Jinman Kim. Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pages 242-252, 2024.
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Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image Registration

Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

Presented as oral presentation and selected as best paper award candidate (Top 24) at CVPR 2024

Recommended citation: Mingyuan Meng, Dagan Feng, Lei Bi, and Jinman Kim. Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image Registration. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9645-9654, 2024.
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.