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In this study, we evaluate the performance of the Segment Anything Model (SAM) in clinical radiotherapy.
Active contours without edges
Tony F. Chan and Luminita A. Vese · 2001
Earlier work this paper cites.
Segmentation of brain mr images through a hidden markov random field model and the expectation-maximization algorithm
Yongyue Zhang, Michael Brady, and Stephen Smith · 2001
Earlier work this paper cites.
A multiphase level set framework for image segmentation using the mumford and shah model
Luminita A. Vese and Tony F. Chan · 2002
Earlier work this paper cites.
Pet/ct: fundamental principles
Marcus D Seemann · 2004
Earlier work this paper cites.
The role of radiotherapy in cancer treatment: estimating optimal utilization from a review of evidence-based clinical guidelines
Geoff Delaney, Susannah Jacob, Carolyn Featherstone, and Michael Barton · 2005
Earlier work this paper cites.
The relationship between waiting time for radiotherapy and clinical outcomes: a systematic review of the literature
Zheng Chen, Will King, Robert Pearcey, Marc Kerba, and William J Mackillop · 2008
Earlier work this paper cites.
Neural network for graphs: A contextual constructive approach
Alessio Micheli · 2009
Earlier work this paper cites.
Emphasizing conformal avoidance versus target definition for imrt planning in head-and-neck cancer
Paul M Harari, Shiyu Song, and Wolfgang A Tomé · 2010
Earlier work this paper cites.
A review of methods of analysis in contouring studies for radiation oncology
Michael G Jameson, Lois C Holloway, Philip J Vial, Shalini K Vinod, and Peter E Metcalfe · 2010
Earlier work this paper cites.
Robust optimization of intensity modulated proton therapy
Wei Liu, Xiaodong Zhang, Yupeng Li, and Radhe Mohan · 2012
Earlier work this paper cites.
Influence of robust optimization in intensity-modulated proton therapy with different dose delivery techniques
Wei Liu, Yupeng Li, Xiaoqiang Li, Wenhua Cao, and Xiaodong Zhang · 2012
Earlier work this paper cites.
Effectiveness of robust optimization in intensity-modulated proton therapy planning for head and neck cancers
Wei Liu, Steven J Frank, Xiaoqiang Li, Yupeng Li, Peter C Park, Lei Dong, X Ronald Zhu, and Radhe Mohan · 2013
Earlier work this paper cites.
Ptv-based impt optimization incorporating planning risk volumes vs robust optimization
Wei Liu, Steven J Frank, Xiaoqiang Li, Yupeng Li, Ron X Zhu, and Radhe Mohan · 2013
Earlier work this paper cites.
Proton beam therapy for locally advanced lung cancer: A review
Steven E Schild, William G Rule, Jonathan B Ashman, Sujay A Vora, Sameer Keole, Aman Anand, Wei Liu, and Martin Bues · 2014
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An automatic approach for satisfying dose-volume constraints in linear fluence map optimization for impt
Maryam Zaghian, Gino Lim, Wei Liu, and Radhe Mohan · 2014
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Dosimetric benefits of robust treatment planning for intensity modulated proton therapy for base-of-skull cancers
Wei Liu, Radhe Mohan, Peter Park, Zhong Liu, Heng Li, Xiaoqiang Li, Yupeng Li, Richard Wu, Narayan Sahoo, Lei Dong, et al · 2014
Earlier work this paper cites.
Robustness quantification and robust optimization in intensity-modulated proton therapy
W Liu · 2015
Earlier work this paper cites.
Impact of respiratory motion on worst-case scenario optimized intensity modulated proton therapy for lung cancers
Wei Liu, Zhongxing Liao, Steven E Schild, Zhong Liu, Heng Li, Yupeng Li, Peter C Park, Xiaoqiang Li, Joshua Stoker, Jiajian Shen, et al · 2015
Earlier work this paper cites.
Robust optimization in intensity-modulated proton therapy to account for anatomy changes in lung cancer patients
Heng Li, Xiaodong Zhang, Peter Park, Wei Liu, Joe Chang, Zhongxing Liao, Steve Frank, Yupeng Li, Falk Poenisch, Radhe Mohan, et al · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Bayesian convolutional neural networks with bernoulli approximate variational inference
Yarin Gal and Zoubin Ghahramani · 2015
Earlier work this paper cites.
Robustness quantification methods comparison in volumetric modulated arc therapy to treat head and neck cancer
Wei Liu, Samir H Patel, Jiajian Jason Shen, Yanle Hu, Daniel P Harrington, Xiaoning Ding, Michele Y Halyard, Steven E Schild, William W Wong, Gary A Ezzell, et al · 2016
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Exploratory study of 4d versus 3d robust optimization in intensity modulated proton therapy for lung cancer
Wei Liu, Steven E Schild, Joe Y Chang, Zhongxing Liao, Yu-Hui Chang, Zhifei Wen, Jiajian Shen, Joshua B Stoker, Xiaoning Ding, Yanle Hu, et al · 2016
Earlier work this paper cites.
Uncertainties in volume delineation in radiation oncology: a systematic review and recommendations for future studies
Shalini K Vinod, Michael G Jameson, Myo Min, and Lois C Holloway · 2016
Earlier work this paper cites.
A review of interventions to reduce inter-observer variability in volume delineation in radiation oncology
Shalini K Vinod, Myo Min, Michael G Jameson, and Lois C Holloway · 2016
Earlier work this paper cites.
Comparison of linear and nonlinear programming approaches for “worst case dose” and “minmax” robust optimization of intensity-modulated proton therapy dose distributions
Maryam Zaghian, Wenhua Cao, Wei Liu, Laleh Kardar, Sharmalee Randeniya, Radhe Mohan, and Gino Lim · 2017
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Robust treatment planning with conditional value at risk chance constraints in intensity-modulated proton therapy
Yu An, Jianming Liang, Steven E Schild, Martin Bues, and Wei Liu · 2017
Earlier work this paper cites.
A survey on deep learning in medical image analysis
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen Awm Van Der Laak, Bram Van Ginneken, and Clara I. Sánchez · 2017
Earlier work this paper cites.
Robust optimization in impt using quadratic objective functions to account for the minimum mu constraint
Jie Shan, Yu An, Martin Bues, Steven E Schild, and Wei Liu · 2018
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Small-spot intensity-modulated proton therapy and volumetric-modulated arc therapies for patients with locally advanced non-small-cell lung cancer: a dosimetric comparative study
Chenbin Liu, Terence T Sio, Wei Deng, Jie Shan, Thomas B Daniels, William G Rule, Pedro R Lara, Shawn M Korte, Jiajian Shen, Xiaoning Ding, et al · 2018
Earlier work this paper cites.
Deep generative models in the real-world: An open challenge from medical imaging
Xiaoran Chen, Nick Pawlowski, Martin Rajchl, Ben Glocker, and Ender Konukoglu · 2018
Earlier work this paper cites.
Robust radiotherapy planning
Jan Unkelbach, Markus Alber, Mark Bangert, Rasmus Bokrantz, Timothy CY Chan, Joseph O Deasy, Albin Fredriksson, Bram L Gorissen, Marcel Van Herk, Wei Liu, et al · 2018
Earlier work this paper cites.
Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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System and method for robust intensity-modulated proton therapy planning, August 2019
Wei Liu · 2019
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Dosimetric comparison of distal esophageal carcinoma plans for patients treated with small-spot intensity-modulated proton versus volumetric-modulated arc therapies
Chenbin Liu, Ronik S Bhangoo, Terence T Sio, Nathan Y Yu, Jie Shan, Jennifer S Chiang, Julia X Ding, William G Rule, Shawn Korte, Pedro Lara, et al · 2019
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Treatment planning system (tps) approximations matter—comparing intensity-modulated proton therapy (impt) plan quality and robustness between a commercial and an in-house developed tps for nonsmall cell lung cancer (nsclc)
Chenbin Liu, Nathan Y Yu, Jie Shan, Ronik S Bhangoo, Thomas B Daniels, Jennifer S Chiang, Xiaoning Ding, Pedro Lara, Christopher L Patrick, James P Archuleta, et al · 2019
Earlier work this paper cites.
Rapid advances in auto-segmentation of organs at risk and target volumes in head and neck cancer
M Kosmin, J Ledsam, B Romera-Paredes, R Mendes, S Moinuddin, D de Souza, L Gunn, C Kelly, CO Hughes, A Karthikesalingam, et al · 2019
Earlier work this paper cites.
Clinical evaluation of commercial atlas-based auto-segmentation in the head and neck region
Hyothaek Lee, Eungman Lee, Nalee Kim, Joo Ho Kim, Kwangwoo Park, Ho Lee, Jaehee Chun, Jae-ik Shin, Jee Suk Chang, and Jin Sung Kim · 2019
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Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer
Sang Hee Ahn, Adam Unjin Yeo, Kwang Hyeon Kim, Chankyu Kim, Youngmoon Goh, Shinhaeng Cho, Se Byeong Lee, Young Kyung Lim, Haksoo Kim, Dongho Shin, et al · 2019
Cited alongside, same era.
Deep learning-based auto-segmentation of targets and organs-at-risk for magnetic resonance imaging only planning of prostate radiotherapy
Sharif Elguindi, Michael J Zelefsky, Jue Jiang, Harini Veeraraghavan, Joseph O Deasy, Margie A Hunt, and Neelam Tyagi · 2019
Cited alongside, same era.
Anatomynet: deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy
Wentao Zhu, Yufang Huang, Liang Zeng, Xuming Chen, Yong Liu, Zhen Qian, Nan Du, Wei Fan, and Xiaohui Xie · 2019
Cited alongside, same era.
Applications and limitations of machine learning in radiation oncology
Daniel Jarrett, Eleanor Stride, Katherine Vallis, and Mark J Gooding · 2019
Cited alongside, same era.
End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
Radiology-gpt: A large language model for radiology
Zhengliang Liu, Aoxiao Zhong, Yiwei Li, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Peng Shu, Cheng Chen, Sekeun Kim, et al · 2023
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Impressiongpt: An iterative optimizing framework for radiology report summarization with chatgpt
Chong Ma, Zihao Wu, Jiaqi Wang, Shaochen Xu, Yaonai Wei, Zhengliang Liu, Lei Guo, Xiaoyan Cai, Shu Zhang, Tuo Zhang, et al · 2023
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Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Haixing Dai, Chong Ma, Zhengliang Liu, Lin Zhao, Gang Li, Wei Liu, et al · 2023
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Chatabl: Abductive learning via natural language interaction with chatgpt
Tianyang Zhong, Yaonai Wei, Li Yang, Zihao Wu, Zhengliang Liu, Xiaozheng Wei, Wenjun Li, Junjie Yao, Chong Ma, Xiang Li, et al · 2023
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Diego Ardila, Atilla P. Kiraly, Sujeeth Bharadwaj, Bokyung Choi, Joshua J. Reicher, Lily Peng, and Daniel et al. Tse · 2019
Cited alongside, same era.
A review of cone-beam ct applications for adaptive radiotherapy of prostate cancer
M Posiewnik and T Piotrowski · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Cited alongside, same era.
Beam angle comparison for distal esophageal carcinoma patients treated with intensity-modulated proton therapy
Hongying Feng, Terence T Sio, William G Rule, Ronik S Bhangoo, Pedro Lara, Christopher L Patrick, Shawn Korte, Mirek Fatyga, William W Wong, Steven E Schild, et al · 2020
Cited alongside, same era.
Improving automatic delineation for head and neck organs at risk by deep learning contouring
Lisanne V Van Dijk, Lisa Van den Bosch, Paul Aljabar, Devis Peressutti, Stefan Both, Roel JHM Steenbakkers, Johannes A Langendijk, Mark J Gooding, and Charlotte L Brouwer · 2020
Cited alongside, same era.
Acute toxicities and short-term patient outcomes after intensity-modulated proton beam radiation therapy or intensity-modulated photon radiation therapy for esophageal carcinoma: a mayo clinic experience
Ronik S Bhangoo, Todd A DeWees, Y Yu Nathan, Julia X Ding, Chenbin Liu, Michael A Golafshar, William G Rule, Sujay A Vora, Helen J Ross, Daniel H Ahn, et al · 2020
Cited alongside, same era.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy
Xuming Chen, Shanlin Sun, Narisu Bai, Kun Han, Qianqian Liu, Shengyu Yao, Hao Tang, Chupeng Zhang, Zhipeng Lu, Qian Huang, et al · 2021
Cited alongside, same era.
Deid-gpt: Zero-shot medical text de-identification by gpt-4
Zhengliang Liu, Xiaowei Yu, Lu Zhang, Zihao Wu, Chao Cao, Haixing Dai, Lin Zhao, Wei Liu, Dinggang Shen, Quanzheng Li, et al · 2023
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Chataug: Leveraging chatgpt for text data augmentation
Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Zihao Wu, Lin Zhao, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, et al · 2023
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Differentiate chatgpt-generated and human-written medical texts
Wenxiong Liao, Zhengliang Liu, Haixing Dai, Shaochen Xu, Zihao Wu, Yiyang Zhang, Xiaoke Huang, Dajiang Zhu, Hongmin Cai, Tianming Liu, et al · 2023
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Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, Tianming Liu, et al · 2023
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Ad-autogpt: An autonomous gpt for alzheimer’s disease infodemiology
Haixing Dai, Yiwei Li, Zhengliang Liu, Lin Zhao, Zihao Wu, Suhang Song, Ye Shen, Dajiang Zhu, Xiang Li, Sheng Li, et al · 2023
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Artificial general intelligence for medical imaging
Xiang Li, Lu Zhang, Zihao Wu, Zhengliang Liu, Lin Zhao, Yixuan Yuan, Jun Liu, Gang Li, Dajiang Zhu, Pingkuan Yan, et al · 2023
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Segment anything model for medical images?
Yuhao Huang, Xin Yang, Lian Liu, Han Zhou, Ao Chang, Xinrui Zhou, Rusi Chen, Junxuan Yu, Jiongquan Chen, Chaoyu Chen, et al · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, and Laura et al. Gustafson · 2023
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Inpaint anything: Segment anything meets image inpainting
Tao Yu, Runseng Feng, Ruoyu Feng, Jinming Liu, Xin Jin, Wenjun Zeng, and Zhibo Chen · 2023
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Edit everything: A text-guided generative system for images editing
Defeng Xie, Ruichen Wang, Jian Ma, Chen Chen, Haonan Lu, Dong Yang, Fobo Shi, and Xiaodong Lin · 2023
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Any-to-any style transfer: Making picasso and da vinci collaborate
Songhua Liu, Jingwen Ye, and Xinchao Wang · 2023
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Deep learning universal crater detection using segment anything model (sam)
Iraklis Giannakis, Anshuman Bhardwaj, Lydia Sam, and Georgios Leontidis · 2023
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Segment anything is not always perfect: An investigation of sam on different real-world applications
Wei Ji, Jingjing Li, Qi Bi, Wenbo Li, and Li Cheng · 2023
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Deep-learning based fast and accurate 3d ct deformable image registration in lung cancer
Yuzhen Ding, Hongying Feng, Yunze Yang, Jason Holmes, Zhengliang Liu, David Liu, William W Wong, Nathan Y Yu, Terence T Sio, Steven E Schild, et al · 2023
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Florian Putz, Johanna Grigo, Thomas Weissmann, Philipp Schubert, Daniel Hoefler, Ahmed Gomaa, Hassen Ben Tkhayat, Amr Hagag, Sebastian Lettmaier, Benjamin Frey, et al · 2023
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Segment anything model for medical image analysis: an experimental study
Maciej A. Mazurowski, Haoyu Dong, Hanxue Gu, and Yixin Zhang · 2023
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Inpaint anything: Segment anything meets image inpainting
Tao Yu, Runseng Feng, Ruoyu Feng, Jinming Liu, Xin Jin, Wenjun Zeng, and Chen Zhibo · 2023
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Segment anything is not always perfect: An investigation of sam on different real-world applications
Wei Ji, Li Cheng, Qi Bi, Wenbo Li, and Li Cheng · 2023
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Sam struggles in concealed scenes–empirical study on" segment anything"
Ge-Peng Ji, Deng-Ping Fan, Peng Xu, Ming-Ming Cheng, Bowen Zhou, and Luc Van Gool · 2023
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Brain extraction comparing segment anything model (sam) and fsl brain extraction tool
Sovesh Mohapatra, Advait Gosai, and Gottfried Schlaug · 2023
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Ruining Deng, Can Cui, Quan Liu, Tianyuan Yao, Lucas W. Remedios, et al · 2023
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Tao Zhou, Yizhe Zhang, Yi Zhou, and Ye Wu · 2023
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Accuracy of segment-anything model (sam) in medical image segmentation tasks
Sheng He, Rina Bao, Jingpeng Li, P. Ellen Grant, and Yangming Ou · 2023
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Community graph convolution neural network for alzheimer’s disease classification and pathogenetic factors identification
Xia-An Bi, Ke Chen, Siyu Jiang, Sheng Luo, Wenyan Zhou, Zhaoxu Xing, Luyun Xu, Zhengliang Liu, and Tianming Liu · 2023
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Lian Zhang, Jason M Holmes, Zhengliang Liu, Sujay A Vora, Terence T Sio, Carlos E Vargas, Nathan Y Yu, Sameer R Keole, Steven E Schild, Martin Bues, et al · 2023
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Chuanfei Hu and Xinde Li · 2023
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Breastsam: A study of segment anything model for breast tumor detection in ultrasound images
Mingzhe Hu, Yuheng Li, and Xiaofeng Yang · 2023
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Polyp-sam: Transfer sam for polyp segmentation
Yuheng Li, Mingzhe Hu, and Xiaofeng Yang · 2023
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Skinsam: Empowering skin cancer segmentation with segment anything model
Mingzhe Hu, Yuheng Li, and Xiaofeng Yang · 2023
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Medical sam adapter: Adapting segment anything model for medical image segmentation
Junde Wu, Rao Fu, Huihui Fang, Yuanpei Liu, Zhaowei Wang, Yanwu Xu, Yueming Jin, and Tal Arbel · 2023
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Benchmd: A benchmark for modality-agnostic learning on medical images and sensors
Kathryn Wantlin, Chenwei Wu, Shih-Cheng Huang, Oishi Banerjee, Farah Dadabhoy, Veeral Vipin Mehta, Ryan Wonhee Han, Fang Cao, Raja R Narayan, Errol Colak, et al · 2023
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Context matters: A strategy to pre-train language model for science education
Zhengliang Liu, Xinyu He, Lei Liu, Tianming Liu, and Xiaoming Zhai · 2023
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Mask-guided bert for few shot text classification
Wenxiong Liao, Zhengliang Liu, Haixing Dai, Zihao Wu, Yiyang Zhang, Xiaoke Huang, Yuzhong Chen, Xi Jiang, Dajiang Zhu, Tianming Liu, et al · 2023
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