Author

Hui Qiao

Tsinghua UniversityORCID 0000-0002-4896-8657Unclaimed ORCID profile · follow to get notified of new preprints

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Hui Qiao2 papers · Fudan University

Biology Disciplines

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Bioinformatics· 1 Biophysics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Assay:imaging· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:contrastive learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Qionghai DaiiD· 3 shared Guoxun ZhangiD· 2 shared Hao XieiD· 2 shared Haoqian WangiD· 2 shared Jiamin WuiD· 2 shared Xing LiniD· 2 shared Xinyang LiiD· 2 shared Chang Fu QiaoiD· 1 shared

Activity by Year

2021-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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3 shared papersBiophysics

Qionghai DaiORCID

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3 papers

Recent·Most cited

Time-lapse Image Super-resolution Neural Network with Reliable Confidence Quantification for Optical Microscopy

Chang Fu Qiao, Shuran Liu, Yuwang Wang, Wencong Xu, Xiaohan Geng, Tao Jiang, Jingyu Zhang, Quan Meng, Hui Qiao, Dong Li, Qionghai Dai

This paper introduces a time-lapse image super-resolution neural network with confidence quantification for optical microscopy, improving temporal consistency and reliability.

Nature Biotechnology · Jan 29, 2025Peer-reviewedBiophysics

Reinforcing neuron extraction and spike inference in calcium imaging using deep self-supervised learning

Xinyang Li, Guoxun Zhang, Jiamin Wu, Yuanlong Zhang, Zhifeng Zhao, Xing Lin, Hui Qiao, Hao Xie, Haoqian Wang, Lu Fang, Qionghai Dai

This paper introduces DeepCAD, a self-supervised learning method to enhance calcium imaging by reducing noise and improving SNR, leading to better neuron extraction and spike inference.

Nature Methods · Aug 16, 2021Peer-reviewedNeuroscience

Unsupervised content-preserving transformation for optical microscopy

Xinyang Li, Guoxun Zhang, Hui Qiao, Feng Bao, Yue Cheng Deng, Jiamin Wu, Yangfan He, Jing‐Ping Yun, Xing Lin, Hao Xie, Haoqian Wang, Qionghai Dai

This paper introduces an unsupervised image transformation method for optical microscopy that avoids data annotation and achieves high-fidelity image transformations across modalities.

Light Science & Applications · Mar 1, 2021Peer-reviewedBioinformatics