Yuanhan Mo

According to our database, Yuanhan Mo authored at least 19 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Spinal Osteophyte Detection via Robust Patch Extraction on minimally annotated X-rays.

Soumya Snigdha Kundu, Yuanhan Mo, Nicharee Srikijkasemwat, Bartlomiej W. Papiez

CoRR, 2024

2023

Towards Automatic Scoring of Spinal X-ray for Ankylosing Spondylitis.

Yuanhan Mo, Yao Chen, Aimee Readie, Gregory Ligozio, Thibaud Coroller, Bartlomiej W. Papiez

CoRR, 2023

VertXNet: An Ensemble Method for Vertebrae Segmentation and Identification of Spinal X-Ray.

Yao Chen, Yuanhan Mo, Aimee Readie, Gregory Ligozio, Indrajeet Mandal, Faiz Jabbar, Thibaud Coroller, Bartlomiej W. Papiez

CoRR, 2023

Multi-task Cooperative Learning via Searching for Flat Minima.

Fuping Wu, Le Zhang, Yang Sun, Yuanhan Mo, Thomas Nichols, Bartlomiej W. Papiez

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

2022

Suggestive annotation of brain MR images with gradient-guided sampling.

Chengliang Dai, Shuo Wang, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai

Medical Image Anal., 2022

The Extreme Cardiac MRI Analysis Challenge under Respiratory Motion (CMRxMotion).

Shuo Wang, Chen Qin, Chengyan Wang, Kang Wang, Haoran Wang, Chen Chen, Cheng Ouyang, Xutong Kuang, Chengliang Dai, Yuanhan Mo, Zhang Shi, Chenchen Dai, Xinrong Chen, He Wang, Wenjia Bai

CoRR, 2022

VertXNet: Automatic Segmentation and Identification of Lumbar and Cervical Vertebrae from Spinal X-ray Images.

Yao Chen, Yuanhan Mo, Aimee Readie, Gregory Ligozio, Thibaud Coroller, Bartlomiej W. Papiez

CoRR, 2022

2021

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.

Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil S. Nalawade, Chandan Ganesh, Benjamin C. Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Alexandra Daza, Catalina Gómez Caballero, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Linmin Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Verónica Vilaplana, Hugh McHugh, Gonzalo D. Maso Talou, Alan Wang, Jay B. Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Thumbavanam Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicolas Boutry, Alexis Huard, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Élodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Lladó, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas J. Tustison, Craig H. Meyer, Nisarg A. Shah, Sanjay N. Talbar, Marc-André Weber, Abhishek Mahajan, András Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko, Daniel S. Marcus, Aikaterini Kotrotsou, Rivka Colen, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Bjoern H. Menze, Spyridon Bakas, Yarin Gal, Tal Arbel

CoRR, 2021

2020

Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling.

Chengliang Dai, Shuo Wang, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai

CoRR, 2020

Efficient Deep Representation Learning by Adaptive Latent Space Sampling.

Yuanhan Mo, Shuo Wang, Chengliang Dai, Rui Zhou, Zhongzhao Teng, Wenjia Bai, Yike Guo

CoRR, 2020

Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation.

Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Suggestive Annotation of Brain Tumour Images with Gradient-Guided Sampling.

Chengliang Dai, Shuo Wang, Yuanhan Mo, Kaichen Zhou, Elsa D. Angelini, Yike Guo, Wenjia Bai

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Self-training for Brain Tumour Segmentation with Uncertainty Estimation and Biophysics-Guided Survival Prediction.

Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019

Transfer Learning from Partial Annotations for Whole Brain Segmentation.

Chengliang Dai, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai

Proceedings of the Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data, 2019

SIMGAN: Photo-Realistic Semantic Image Manipulation Using Generative Adversarial Networks.

Simiao Yu, Hao Dong, Felix Liang, Yuanhan Mo, Chao Wu, Yike Guo

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction.

Shuo Wang, Chengliang Dai, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018

The Deep Poincaré Map: A Novel Approach for Left Ventricle Segmentation.

Yuanhan Mo, Fangde Liu, Douglas McIlwraith, Guang Yang, Jingqing Zhang, Taigang He, Yike Guo

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017

Deep Poincare Map For Robust Medical Image Segmentation.

Yuanhan Mo, Fangde Liu, Jingqing Zhang, Guang Yang, Taigang He, Yike Guo

CoRR, 2017

Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks.

Hao Dong, Guang Yang, Fangde Liu, Yuanhan Mo, Yike Guo

Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017