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2020 – today
- 2025
[i12]Ethan Dack, Chengliang Dai:
Understanding Dataset Bias in Medical Imaging: A Case Study on Chest X-rays. CoRR abs/2507.07722 (2025)- [i11]Kang Wang, Chen Qin, Zhang Shi, Haoran Wang, Xiwen Zhang, Chen Chen, Cheng Ouyang, Chengliang Dai, Yuanhan Mo, Chenchen Dai, Xutong Kuang, Ruizhe Li, Xin Chen, Xiuzheng Yue, Song Tian, Alejandro Mora-Rubio, Kumaradevan Punithakumar, Shizhan Gong, Qi Dou, Sina Amirrajab, Yasmina Al Khalil, Cian M. Scannell, Lexiaozi Fan, Huili Yang, Xiaowu Sun, Rob J. van der Geest, Tewodros Weldebirhan Arega, Fabrice Mériaudeau, Caner Özer, Amin Ranem, John Kalkhof, Ilkay Öksüz, Anirban Mukhopadhyay, Abdul Qayyum, Moona Mazher, Steven A. Niederer, Carles García-Cabrera, Eric Arazo, Michal K. Grzeszczyk, Szymon Plotka, Wanqin Ma, Xiaomeng Li, Rongjun Ge, Yongqing Kou, Xinrong Chen, He Wang, Chengyan Wang, Wenjia Bai, Shuo Wang:
Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge. CoRR abs/2507.19165 (2025) - 2024
- [j3]Jinge Wu, Hang Dong
, Zexi Li, Haowei Wang, Runci Li, Arijit Patra, Chengliang Dai, Waqar Ali, Phil Scordis, Honghan Wu:
A hybrid framework with large language models for rare disease phenotyping. BMC Medical Informatics Decis. Mak. 24(1): 289 (2024) - 2022
- [j2]Chengliang Dai, Shuo Wang, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Suggestive annotation of brain MR images with gradient-guided sampling. Medical Image Anal. 77: 102373 (2022) - [i10]Chengliang Dai, Shuo Wang, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Suggestive Annotation of Brain MR Images with Gradient-guided Sampling. CoRR abs/2206.01014 (2022) - [i9]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:
The Extreme Cardiac MRI Analysis Challenge under Respiratory Motion (CMRxMotion). CoRR abs/2210.06385 (2022) - 2021
- [i8]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:
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. CoRR abs/2112.10074 (2021) - 2020
- [c8]Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Self-training for Brain Tumour Segmentation with Uncertainty Estimation and Biophysics-Guided Survival Prediction. BrainLes@MICCAI (1) 2020: 514-523 - [c7]Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai:
Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation. MICCAI (4) 2020: 88-97 - [c6]Chengliang Dai, Shuo Wang, Yuanhan Mo, Kaichen Zhou, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Suggestive Annotation of Brain Tumour Images with Gradient-Guided Sampling. MICCAI (4) 2020: 156-165 - [i7]Yuanhan Mo, Shuo Wang, Chengliang Dai, Rui Zhou, Zhongzhao Teng, Wenjia Bai, Yike Guo:
Efficient Deep Representation Learning by Adaptive Latent Space Sampling. CoRR abs/2004.02757 (2020) - [i6]Shuo Wang, Giacomo Tarroni, Chen Qin, Yuanhan Mo, Chengliang Dai, Chen Chen, Ben Glocker, Yike Guo, Daniel Rueckert, Wenjia Bai:
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation. CoRR abs/2006.13379 (2020) - [i5]Chengliang Dai, Shuo Wang, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling. CoRR abs/2006.14984 (2020)
2010 – 2019
- 2019
- [j1]Christopher Crispin-Bailey, Chengliang Dai, Jim Austin:
A 65-nm CMOS Lossless Bio-Signal Compression Circuit With 250 FemtoJoule Performance Per Bit. IEEE Trans. Biomed. Circuits Syst. 13(5): 1087-1100 (2019) - [c5]Jingqing Zhang, Xiaoyu Zhang, Kai Sun, Xian Yang, Chengliang Dai, Yike Guo:
Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records. BIBM 2019: 598-603 - [c4]Xiaoyu Zhang, Jingqing Zhang, Kai Sun, Xian Yang, Chengliang Dai, Yike Guo:
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification. BIBM 2019: 765-769 - [c3]Shuo Wang, Chengliang Dai, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction. BrainLes@MICCAI (2) 2019: 61-72 - [c2]Chengliang Dai, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Transfer Learning from Partial Annotations for Whole Brain Segmentation. DART/MIL3ID@MICCAI 2019: 199-206 - [i4]Xiaoyu Zhang, Jingqing Zhang, Kai Sun, Xian Yang, Chengliang Dai, Yike Guo:
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification. CoRR abs/1908.06278 (2019) - [i3]Chengliang Dai, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Transfer Learning from Partial Annotations for Whole Brain Segmentation. CoRR abs/1908.10851 (2019) - [i2]Jingqing Zhang, Xiaoyu Zhang, Kai Sun, Xian Yang, Chengliang Dai, Yike Guo:
Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records. CoRR abs/1911.03862 (2019) - [i1]Shuo Wang, Chengliang Dai, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai:
Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction. CoRR abs/1911.08483 (2019) - 2015
- [c1]Chengliang Dai, Christopher Bailey:
A lossless data reduction technique for wireless EEG recorders and its use in selective data filtering for seizure monitoring. EMBC 2015: 6186-6189
Coauthor Index
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