Hongliang Ren

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Hongliang Ren
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Hongliang Ren (67)
Mobarakol Islam (24)
Long Bai (11)
An Wang (10)
Mengya Xu (9)
Max Qing Hu Meng (7)
Nitish V Thakor (5)
Beilei Cui (4)
Godwin Ponraj (4)
Lalithkumar Seenivasan (4)
Sunil L Kukreja (4)
Wenjun Xu (4)
Xiao Xiao (4)
Keyu Wu (3)
Liao Wu (3)
Lisheng Xu (2)
Max Qinghu H Meng (2)
Shuang Song (2)
Shuzhi Sam Ge (2)
Weian Guo (2)

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Publication

Journal/Magazine Names

Information Fusion (2)
Journal of Intelligent and Robotic Systems (2)
Procedia Computer Science (2)
Artificial Intelligence in Medicine (1)
Complexity (1)
Computers in Biology and Medicine (1)
IEEE Transactions on Intelligent Transportation Systems (1)
IEEE Transactions on Robotics (1)
International Journal of Robotics Research (1)
Knowledge-Based Systems (1)
Microsystem Technologies (1)
Neural Computing and Applications (1)
Neurocomputing (1)
Soft Computing - A Fusion of Foundations, Methodologies and Applications (1)

Proceedings/Book Names

2021 IEEE International Conference on Robotics and Automation (ICRA) (5)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 (4)
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (3)
2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob) (3)
2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) (3)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 (3)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 (3)
2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) (2)
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (2)
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (1)
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (1)
ICBCB 2018: Proceedings of the 2018 6th International Conference on Bioinformatics and Computational Biology (1)
Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 (1)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops (1)
Simulation and Synthesis in Medical Imaging (1)

Publisher

IEEE Press (27)
Springer-Verlag (26)
Elsevier Science Publishers B. V. (6)
Kluwer Academic Publishers (2)
Association for Computing Machinery (1)
Elsevier Science Publishers Ltd. (1)
IEEE Computer Society (1)
John Wiley & Sons, Inc. (1)
Pergamon Press, Inc. (1)
Sage Publications, Inc. (1)

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Publications

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research-article
Surgical-VQLA++: Adversarial contrastive learning for calibrated robust visual question-localized answering in robotic surgery
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
  ,
- Guankun Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
  ,
- Mobarakol Islam
  Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK
  ,
- Lalithkumar Seenivasan
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Department of Biomedical Engineering, National University of Singapore, Singapore
  ,
- An Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
  Department of Biomedical Engineering, National University of Singapore, Singapore
Information Fusion, Volume 113, Issue C•Jan 2025 • https://doi.org/10.1016/j.inffus.2024.102602
Abstract
Medical visual question answering (VQA) bridges the gap between visual information and clinical decision-making, enabling doctors to extract understanding from clinical images and videos. In particular, surgical VQA can enhance the interpretation ...
Highlights

We propose a Surgical-VQLA++ framework to connect answering and localization.
We incorporate feature calibration and adversarial contrastive training techniques.
We expand our datasets by including additional queries related to ...
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Benchmarking Robustness of Endoscopic Depth Estimation with Synthetically Corrupted Data
- An Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Haochen Yin
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Beilei Cui
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Mengya Xu
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
Simulation and Synthesis in Medical Imaging•October 2024, pp 45-57• https://doi.org/10.1007/978-3-031-73281-2_5
Abstract
Accurate depth perception is crucial for patient outcomes in endoscopic surgery, yet it is compromised by image distortions common in surgical settings. To tackle this issue, our study presents a benchmark for assessing the robustness of ...
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LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-Diffusion
- Tong Chen
  https://ror.org/0384j8v12Faculty of Electrical Engineering, The University of Sydney, Sydney, Australia
  ,
- Qingcheng Lyu
  https://ror.org/0384j8v12Faculty of Electrical Engineering, The University of Sydney, Sydney, Australia
  ,
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong, SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
  ,
- Erjian Guo
  https://ror.org/0384j8v12Faculty of Electrical Engineering, The University of Sydney, Sydney, Australia
  ,
- Huxin Gao
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong, SAR, China
  ,
- Xiaoxiao Yang
  https://ror.org/056ef9489Qilu Hospital of Shandong University, Jinan, China
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong, SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
  ,
- Luping Zhou
  https://ror.org/0384j8v12Faculty of Electrical Engineering, The University of Sydney, Sydney, Australia
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024•October 2024, pp 369-379• https://doi.org/10.1007/978-3-031-72089-5_35
Abstract
Advances in endoscopy use in surgeries face challenges like inadequate lighting. Deep learning, notably the Denoising Diffusion Probabilistic Model (DDPM), holds promise for low-light image enhancement in the medical field. However, DDPMs are ...
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EndoDAC: Efficient Adapting Foundation Model for Self-Supervised Depth Estimation from Any Endoscopic Camera
- Beilei Cui
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
  ,
- Mobarakol Islam
  https://ror.org/02jx3x895Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) and Department of Medical Physics and Biomedical Engineering, University College London, London, UK
  ,
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
  ,
- An Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024•October 2024, pp 208-218• https://doi.org/10.1007/978-3-031-72089-5_20
Abstract
Depth estimation plays a crucial role in various tasks within endoscopic surgery, including navigation, surface reconstruction, and augmented reality visualization. Despite the significant achievements of foundation models in vision tasks, ...
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Endo-4DGS: Endoscopic Monocular Scene Reconstruction with 4D Gaussian Splatting
- Yiming Huang
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Sha Tin, Hong Kong SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
  ,
- Beilei Cui
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Sha Tin, Hong Kong SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
  ,
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Sha Tin, Hong Kong SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
  ,
- Ziqi Guo
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Sha Tin, Hong Kong SAR, China
  ,
- Mengya Xu
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Sha Tin, Hong Kong SAR, China
  ,
- Mobarakol Islam
  Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Sha Tin, Hong Kong SAR, China
  Shun Hing Institute of Advanced Engineering, CUHK, Sha Tin, Hong Kong SAR, China
  https://ror.org/00sz56h79Shenzhen Research Institute, CUHK, Shenzhen, China
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024•October 2024, pp 197-207• https://doi.org/10.1007/978-3-031-72089-5_19
Abstract
In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance Fields (NeRF)-based methods have recently risen to prominence for ...
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Landmark Detection using Transformer Toward Robot-assisted Nasal Airway Intubation
- Tianhang Liu
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Hechen Li
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Yanan Wu
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China
  ,
- An Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Mobarakol Islam
  Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Department of Biomedical Engineering, National University of Singapore, Singapore
  Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
Procedia Computer Science, Volume 226, Issue C•2023, pp 36-42 • https://doi.org/10.1016/j.procs.2023.10.633
Abstract
Robot-assisted airway intubation application needs high accuracy in locating targets and organs. Two vital landmarks, nostrils and glottis, can be detected during the intubation to accommodate the stages of nasal intubation. Automated landmark ...
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Semi-supervised Learning for Segmentation of Bleeding Regions in Video Capsule Endoscopy
- Hechen Li
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Yanan Wu
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- An Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Tong Chen
  School of Electrical and Information Engineering, The University of Sydney, Sydney, Australia
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Department of Biomedical Engineering, National University of Singapore, Singapore
  Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
Procedia Computer Science, Volume 226, Issue C•2023, pp 29-35 • https://doi.org/10.1016/j.procs.2023.10.632
Abstract
In the realm of modern diagnostic technology, video capsule endoscopy (VCE) is a standout for its high efficacy and non-invasive nature in diagnosing various gastrointestinal (GI) conditions, including obscure bleeding. Importantly, for the ...
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Transendoscopic flexible parallel continuum robotic mechanism for bimanual endoscopic submucosal dissection
- Huxin Gao
  The Department of Electronic Engineering, 26451The Chinese University of Hong Kong (CUHK), Hong Kong, China
  The Department of Biomedical Engineering, 37580National University of Singapore, Singapore
  Shun Hing Institute of Advanced Engineering (SHIAE), 26451The Chinese University of Hong Kong (CUHK), Hong Kong, China
  NUS (Suzhou) Research Institute (NUSRI), Suzhou, China
  ,
- Xiaoxiao Yang
  The Department of Gastroenterology, 91623Qilu Hospital of Shandong University, Jinan, China
  ,
- Xiao Xiao
  The Department of Electronic and Electrical Engineering, 255310Southern University of Science and Technology, Shenzhen, China
  ,
- Xiaolong Zhu
  The Department of Electronic and Electrical Engineering, 255310Southern University of Science and Technology, Shenzhen, China
  ,
- Tao Zhang
  The Department of Biomedical Engineering, 37580National University of Singapore, Singapore
  Shun Hing Institute of Advanced Engineering (SHIAE), 26451The Chinese University of Hong Kong (CUHK), Hong Kong, China
  ,
- Cheng Hou
  School of Mechanical and Electric Engineering, 12582Soochow University, Suzhou, China
  ,
- Huicong Liu
  School of Mechanical and Electric Engineering, 12582Soochow University, Suzhou, China
  ,
- Max Q.-H. Meng
  The Department of Biomedical Engineering, 37580National University of Singapore, Singapore
  The Department of Electronic and Electrical Engineering, 255310Southern University of Science and Technology, Shenzhen, China
  ,
- Lining Sun
  School of Mechanical and Electric Engineering, 12582Soochow University, Suzhou, China
  ,
- Xiuli Zuo
  The Department of Gastroenterology, 91623Qilu Hospital of Shandong University, Jinan, China
  ,
- Yanqing Li
  The Department of Gastroenterology, 91623Qilu Hospital of Shandong University, Jinan, China
  ,
- Hongliang Ren
  The Department of Electronic Engineering, 26451The Chinese University of Hong Kong (CUHK), Hong Kong, China
  The Department of Biomedical Engineering, 37580National University of Singapore, Singapore
  Shun Hing Institute of Advanced Engineering (SHIAE), 26451The Chinese University of Hong Kong (CUHK), Hong Kong, China
  NUS (Suzhou) Research Institute (NUSRI), Suzhou, China
International Journal of Robotics Research, Volume 43, Issue 3•Mar 2024, pp 281-304 • https://doi.org/10.1177/02783649231209338

In endoscopic submucosal dissection (ESD), the gastrointestinal (GI) tract warrants the surgical instruments to navigate through a long, narrow and tortuous endoscope. This poses a great challenge in developing ESD instruments with small dimensions, ...
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SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation
- An Wang
  https://ror.org/00t33hh48Department of Electronic Engineering, Shun Hing Institute of Advanced Engineering (SHIAE), The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Mobarakol Islam
  Department of Medical Physics and Biomedical Engineering, Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK
  ,
- Mengya Xu
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
  ,
- Yang Zhang
  https://ror.org/02d3fj342School of Mechanical Engineering, Hubei University of Technology, Wuhan, China
  ,
- Hongliang Ren
  https://ror.org/00t33hh48Department of Electronic Engineering, Shun Hing Institute of Advanced Engineering (SHIAE), The Chinese University of Hong Kong, Hong Kong SAR, China
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops •October 2023, pp 234-244• https://doi.org/10.1007/978-3-031-47401-9_23
Abstract
The Segment Anything Model (SAM) serves as a fundamental model for semantic segmentation and demonstrates remarkable generalization capabilities across a wide range of downstream scenarios. In this empirical study, we examine SAM’s robustness and ...
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LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China
  ,
- Tong Chen
  https://ror.org/0384j8v12The University of Sydney, Sydney, NSW, Australia
  ,
- Yanan Wu
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China
  https://ror.org/03awzbc87Northeastern University, Shenyang, China
  ,
- An Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China
  ,
- Mobarakol Islam
  Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China
  Shun Hing Institute of Advanced Engineering, CUHK, Hong Kong SAR, China
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 34-44• https://doi.org/10.1007/978-3-031-43999-5_4
Abstract
Wireless capsule endoscopy (WCE) is a painless and non-invasive diagnostic tool for gastrointestinal (GI) diseases. However, due to GI anatomical constraints and hardware manufacturing limitations, WCE vision signals may suffer from insufficient ...
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Rectifying Noisy Labels with Sequential Prior: Multi-scale Temporal Feature Affinity Learning for Robust Video Segmentation
- Beilei Cui
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Minqing Zhang
  Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Mengya Xu
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
  ,
- An Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Wu Yuan
  Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 90-100• https://doi.org/10.1007/978-3-031-43996-4_9
Abstract
Noisy label problems are inevitably in existence within medical image segmentation causing severe performance degradation. Previous segmentation methods for noisy label problems only utilize a single image while the potential of leveraging the ...
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Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China
  ,
- Mobarakol Islam
  Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China
  Shun Hing Institute of Advanced Engineering, CUHK, Hong Kong SAR, China
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 68-78• https://doi.org/10.1007/978-3-031-43996-4_7
Abstract
The visual-question localized-answering (VQLA) system can serve as a knowledgeable assistant in surgical education. Except for providing text-based answers, the VQLA system can highlight the interested region for better surgical scene ...
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CAT-ViL: Co-attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China
  ,
- Mobarakol Islam
  Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), Hong Kong SAR, China
  Shun Hing Institute of Advanced Engineering, CUHK, Hong Kong SAR, China
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 397-407• https://doi.org/10.1007/978-3-031-43996-4_38
Abstract
Medical students and junior surgeons often rely on senior surgeons and specialists to answer their questions when learning surgery. However, experts are often busy with clinical and academic work, and have little time to give guidance. Meanwhile, ...
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SurgicalGPT: End-to-End Language-Vision GPT for Visual Question Answering in Surgery
- Lalithkumar Seenivasan
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
  ,
- Mobarakol Islam
  https://ror.org/02jx3x895WEISS, University College London, London, UK
  ,
- Gokul Kannan
  https://ror.org/047x65e68Department of Production Engineering, National Institute of Technology, Tiruchirappalli, India
  ,
- Hongliang Ren
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
  Department of Electronic Engineering, Chinese University of Hong Kong, Shatin, Hong Kong
  Shun Hing Institute of Advanced Engineering, Chinese University of Hong Kong, Shatin, Hong Kong
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 281-290• https://doi.org/10.1007/978-3-031-43996-4_27
Abstract
Advances in GPT-based large language models (LLMs) are revolutionizing natural language processing, exponentially increasing its use across various domains. Incorporating uni-directional attention, these autoregressive LLMs can generate long and ...
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S $^{2}$ ME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-Supervised Polyp Segmentation
- An Wang
  Department of Electronic Engineering, Shun Hing Institute of Advanced Engineering (SHIAE), The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
  ,
- Mengya Xu
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
  ,
- Yang Zhang
  Department of Electronic Engineering, Shun Hing Institute of Advanced Engineering (SHIAE), The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
  https://ror.org/02d3fj342School of Mechanical Engineering, Hubei University of Technology, Wuhan, China
  ,
- Mobarakol Islam
  Department of Medical Physics and Biomedical Engineering, Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK
  ,
- Hongliang Ren
  Department of Electronic Engineering, Shun Hing Institute of Advanced Engineering (SHIAE), The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
  https://ror.org/01tgyzw49Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 35-45• https://doi.org/10.1007/978-3-031-43907-0_4
Abstract
Fully-supervised polyp segmentation has accomplished significant triumphs over the years in advancing the early diagnosis of colorectal cancer. However, label-efficient solutions from weak supervision like scribbles are rarely explored yet ... $^{}$
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Rethinking exemplars for continual semantic segmentation in endoscopy scenes: Entropy-based mini-batch pseudo-replay
- Guankun Wang
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Yanan Wu
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China
  ,
- Tong Chen
  School of Electrical and Information Engineering, The University of Sydney, Sydney, Australia
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Department of Biomedical Engineering, National University of Singapore, Singapore
  Suzhou Research Institute, National University of Singapore, Suzhou, China
  Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Hong Kong, China
  Shenzhen Research Institute, The Chinese University of, Hong Kong, Shenzhen, China
Computers in Biology and Medicine, Volume 165, Issue C•Oct 2023 • https://doi.org/10.1016/j.compbiomed.2023.107412
Abstract
Endoscopy is a widely used technique for the early detection of diseases or robotic-assisted minimally invasive surgery (RMIS). Numerous deep learning (DL)-based research works have been developed for automated diagnosis or processing of ...
Highlights

A class-incremental segmentation framework for endoscopic images is established.
Mini-batch pseudo-replay is employed to mitigate catastrophic forgetting.
Self-adaptive noisy cross-entropy loss is adopted based on sample ...
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research-article
Two-stage contextual transformer-based convolutional neural network for airway extraction from CT images
- Yanan Wu
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Shuiqing Zhao
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  ,
- Shouliang Qi
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China
  ,
- Jie Feng
  School of Chemical Equipment, Shenyang University of Technology, Liaoyang, China
  ,
- Haowen Pang
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  ,
- Runsheng Chang
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  ,
- Long Bai
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Mengqi Li
  Department of Respiratory, the Second Affiliated Hospital of Dalian Medical University, Dalian, China
  ,
- Shuyue Xia
  Respiratory Department, Central Hospital Affiliated to Shenyang Medical College, Shenyang, China
  ,
- Wei Qian
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
Artificial Intelligence in Medicine, Volume 143, Issue C•Sep 2023 • https://doi.org/10.1016/j.artmed.2023.102637
Abstract
Accurate airway segmentation from computed tomography (CT) images is critical for planning navigation bronchoscopy and realizing a quantitative assessment of airway-related chronic obstructive pulmonary disease (COPD). Existing methods face ...
Highlights

A two-stage framework using a transformer-based 3D U-Net for accurate airway segmentation is proposed.
A novel 3D contextual transformer effectively captures the contextual and long-range information in CT images.
Multiple datasets,...
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research-article
Magnetic Tracking With Real-Time Geomagnetic Vector Separation for Robotic Dockable Charging
- Shijian Su
  Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang, China
  ,
- Houde Dai
  Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang, China
  ,
- Yuanchao Zhang
  Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang, China
  ,
- Sishen Yuan
  Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong
  ,
- Shuang Song
  Harbin Institute of Technology, Shenzhen, China
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong
IEEE Transactions on Intelligent Transportation Systems, Volume 24, Issue 12•Dec. 2023, pp 13830-13840 • https://doi.org/10.1109/TITS.2023.3304298
High-precision pose adjustment for the self-charging of mobile robots remains a significant challenge. Permanent magnet (PM)-based magnetic tracking technique is a promising technical solution, with occlusion-free and simultaneous positioning and ...
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research-article
Information loss challenges in surgical navigation systems: From information fusion to AI-based approaches
- Lisheng Xu
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China
  Key Laboratory of Medical Image Computing, Ministry of Education, Shenyang 110169, China
  Engineering Research Center of Medical Imaging and Intelligent Analysis, Ministry of Education, Shenyang 110169, China
  Neusoft Research of Intelligent Healthcare Technology, Co. Ltd. Shenyang 110169, China
  ,
- Haoran Zhang
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China
  ,
- Jiaole Wang
  School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China
  ,
- Ang Li
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Shuang Song
  School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China
  ,
- Hongliang Ren
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
  ,
- Lin Qi
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China
  Key Laboratory of Medical Image Computing, Ministry of Education, Shenyang 110169, China
  Engineering Research Center of Medical Imaging and Intelligent Analysis, Ministry of Education, Shenyang 110169, China
  ,
- Jason J. Gu
  Department of Electrical and Computer Engineering, Dalhousie University, Canada
  ,
- Max Q.-H. Meng
  Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China
Information Fusion, Volume 92, Issue C•Apr 2023, pp 13-36 • https://doi.org/10.1016/j.inffus.2022.11.015
Highlights

Focus on the information loss problem in tracking technologies for surgical navigation systems.
Survey the existing solutions to information loss in tracking surgical instruments.
Information fusion technology to improve accuracy, ...
Abstract
Surgical navigation technology provides minimally invasive surgery (MIS) with the relative pose relationships amongst medical images, surgical instruments, and lesions. On the other hand, traditional operation procedures depend heavily on direct ...
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Article
Surgical-VQA: Visual Question Answering in Surgical Scenes Using Transformer
- Lalithkumar Seenivasan
  Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
  ,
- Mobarakol Islam
  Biomedical Image Analysis Group, Imperial College London, London, UK
  ,
- Adithya K Krishna
  Department of ECE, National Institute of Technology, Tiruchirappalli, India
  ,
- Hongliang Ren
  Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
  Department of Electronic Engineering, Chinese University of Hong Kong, Hong Kong, Hong Kong
  Shun Hing Institute of Advanced Engineering, Chinese University of Hong Kong, Hong Kong, Hong Kong
Medical Image Computing and Computer Assisted Intervention – MICCAI 2022•September 2022, pp 33-43• https://doi.org/10.1007/978-3-031-16449-1_4
Abstract
Visual question answering (VQA) in surgery is largely unexplored. Expert surgeons are scarce and are often overloaded with clinical and academic workloads. This overload often limits their time answering questionnaires from patients, medical ...
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Author Profile Pages

Description: The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM bibliographic database, the Guide. Coverage of ACM publications is comprehensive from the 1950's. Coverage of other publishers generally starts in the mid 1980's. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community.
Please see the following 2007 Turing Award winners' profiles as examples:
History: Disambiguation of author names is of course required for precise identification of all the works, and only those works, by a unique individual. Of equal importance to ACM, author name normalization is also one critical prerequisite to building accurate citation and download statistics. For the past several years, ACM has worked to normalize author names, expand reference capture, and gather detailed usage statistics, all intended to provide the community with a robust set of publication metrics. The Author Profile Pages reveal the first result of these efforts.
Normalization: ACM uses normalization algorithms to weigh several types of evidence for merging and splitting names.
These include:
- co-authors: if we have two names and cannot disambiguate them based on name alone, then we see if they have a co-author in common. If so, this weighs towards the two names being the same person.
- affiliations: names in common with same affiliation weighs toward the two names being the same person.
- publication title: names in common whose works are published in same journal weighs toward the two names being the same person.
- keywords: names in common whose works address the same subject matter as determined from title and keywords, weigh toward being the same person.
The more conservative the merging algorithms, the more bits of evidence are required before a merge is made, resulting in greater precision but lower recall of works for a given Author Profile. Many bibliographic records have only author initials. Many names lack affiliations. With very common family names, typical in Asia, more liberal algorithms result in mistaken merges.

Automatic normalization of author names is not exact. Hence it is clear that manual intervention based on human knowledge is required to perfect algorithmic results. ACM is meeting this challenge, continuing to work to improve the automated merges by tweaking the weighting of the evidence in light of experience.
Bibliometrics: In 1926, Alfred Lotka formulated his power law (known as Lotka's Law) describing the frequency of publication by authors in a given field. According to this bibliometric law of scientific productivity, only a very small percentage (~6%) of authors in a field will produce more than 10 articles while the majority (perhaps 60%) will have but a single article published. With ACM's first cut at author name normalization in place, the distribution of our authors with 1, 2, 3..n publications does not match Lotka's Law precisely, but neither is the distribution curve far off. For a definition of ACM's first set of publication statistics, see Bibliometrics
Future Direction: The initial release of the Author Edit Screen is open to anyone in the community with an ACM account, but it is limited to personal information. An author's photograph, a Home Page URL, and an email may be added, deleted or edited. Changes are reviewed before they are made available on the live site.
ACM will expand this edit facility to accommodate more types of data and facilitate ease of community participation with appropriate safeguards. In particular, authors or members of the community will be able to indicate works in their profile that do not belong there and merge others that do belong but are currently missing.

A direct search interface for Author Profiles will be built.

An institutional view of works emerging from their faculty and researchers will be provided along with a relevant set of metrics.

It is possible, too, that the Author Profile page may evolve to allow interested authors to upload unpublished professional materials to an area available for search and free educational use, but distinct from the ACM Digital Library proper. It is hard to predict what shape such an area for user-generated content may take, but it carries interesting potential for input from the community.

Bibliometrics

The ACM DL is a comprehensive repository of publications from the entire field of computing.

It is ACM's intention to make the derivation of any publication statistics it generates clear to the user.

Average citations per article = The total Citation Count divided by the total Publication Count.
Citation Count = cumulative total number of times all authored works by this author were cited by other works within ACM's bibliographic database. Almost all reference lists in articles published by ACM have been captured. References lists from other publishers are less well-represented in the database. Unresolved references are not included in the Citation Count. The Citation Count is citations TO any type of work, but the references counted are only FROM journal and proceedings articles. Reference lists from books, dissertations, and technical reports have not generally been captured in the database. (Citation Counts for individual works are displayed with the individual record listed on the Author Page.)
Publication Count = all works of any genre within the universe of ACM's bibliographic database of computing literature of which this person was an author. Works where the person has role as editor, advisor, chair, etc. are listed on the page but are not part of the Publication Count.
Publication Years = the span from the earliest year of publication on a work by this author to the most recent year of publication of a work by this author captured within the ACM bibliographic database of computing literature (The ACM Guide to Computing Literature, also known as "the Guide".
Available for download = the total number of works by this author whose full texts may be downloaded from an ACM full-text article server. Downloads from external full-text sources linked to from within the ACM bibliographic space are not counted as 'available for download'.
Average downloads per article = The total number of cumulative downloads divided by the number of articles (including multimedia objects) available for download from ACM's servers.
Downloads (cumulative) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server since the downloads were first counted in May 2003. The counts displayed are updated monthly and are therefore 0-31 days behind the current date. Robotic activity is scrubbed from the download statistics.
Downloads (12 months) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 12-month period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (12-month download counts for individual works are displayed with the individual record.)
Downloads (6 weeks) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 6-week period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (6-week download counts for individual works are displayed with the individual record.)

ACM Author-Izer Service

Summary Description

ACM Author-Izer is a unique service that enables ACM authors to generate and post links on both their homepage and institutional repository for visitors to download the definitive version of their articles from the ACM Digital Library at no charge.

Downloads from these sites are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to definitive version of ACM articles should reduce user confusion over article versioning.

ACM Author-Izer also extends ACM’s reputation as an innovative “Green Path” publisher, making ACM one of the first publishers of scholarly works to offer this model to its authors.

To access ACM Author-Izer, authors need to establish a free ACM web account. Should authors change institutions or sites, they can utilize the new ACM service to disable old links and re-authorize new links for free downloads from a different site.

How ACM Author-Izer Works

Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.

The Service can be applied to all the articles you have ever published with ACM.

Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.

For authors who do not have a free ACM Web Account:

Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.

For authors who have an ACM web account, but have not edited their ACM Author Profile page:

Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.

For authors who have an account and have already edited their Profile Page:

Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"

ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.

Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.

FAQ

Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
Q. What articles are eligible for ACM Author-Izer?
A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.

Q. Are there any restrictions on authors to use this service?
A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.

Q. What are the requirements to use this service?
A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.

Q. What is an ACM Author Profile Page?
A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.

Q. How do I find my Author Profile page and take ownership?
A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours

Q. Why does my photo not appear?
A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters

Q. What if I cannot find the Add Personal Information function on my author page?
A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.

Q. What happens if an author changes the location of his bibliography or moves to a new institution?
A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.

Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.

However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.

Q. What happens if the author’s bibliography lives on a page with several aliases?
A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.

Q. Why should authors use ACM Author-Izer?
A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.

Q. Does ACM Author-Izer provide benefits for authors?
A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.

Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.

Q. How does ACM Author-Izer benefit the computing community?
A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.

In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.

Q. How do authors access ACM Author-Izer?
A. See How to Use

Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.

Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner

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Applied Filters

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Surgical-VQLA++: Adversarial contrastive learning for calibrated robust visual question-localized answering in robotic surgery

Benchmarking Robustness of Endoscopic Depth Estimation with Synthetically Corrupted Data

LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-Diffusion

EndoDAC: Efficient Adapting Foundation Model for Self-Supervised Depth Estimation from Any Endoscopic Camera

Endo-4DGS: Endoscopic Monocular Scene Reconstruction with 4D Gaussian Splatting

Landmark Detection using Transformer Toward Robot-assisted Nasal Airway Intubation

Semi-supervised Learning for Segmentation of Bleeding Regions in Video Capsule Endoscopy

Transendoscopic flexible parallel continuum robotic mechanism for bimanual endoscopic submucosal dissection

SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation

LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion

Rectifying Noisy Labels with Sequential Prior: Multi-scale Temporal Feature Affinity Learning for Robust Video Segmentation

Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery

CAT-ViL: Co-attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery

SurgicalGPT: End-to-End Language-Vision GPT for Visual Question Answering in Surgery

S $^{2}$ ME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-Supervised Polyp Segmentation

Rethinking exemplars for continual semantic segmentation in endoscopy scenes: Entropy-based mini-batch pseudo-replay

Two-stage contextual transformer-based convolutional neural network for airway extraction from CT images

Magnetic Tracking With Real-Time Geomagnetic Vector Separation for Robotic Dockable Charging

Information loss challenges in surgical navigation systems: From information fusion to AI-based approaches

Surgical-VQA: Visual Question Answering in Surgical Scenes Using Transformer