238 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Capital Medical UniversityCN10 papers
- Sun Yat-sen UniversityCN4 papers
- Chinese University of Hong KongHK3 papers
- Tsinghua UniversityCN3 papers
- University of Hong KongHK3 papers
- Beihang UniversityCN2 papers
- Beijing Tsinghua Chang Gung HospitalCN2 papers
- Hong Kong Polytechnic UniversityHK2 papers
- Imperial College LondonGB2 papers
- Rehab-Robotics (China)CN2 papers
- Shanxi Medical UniversityCN2 papers
- Tencent Healthcare (China)CN2 papers
14 papers
Full end-to-end diagnostic workflow automation of 3D OCT via foundation model-driven AI for retinal diseases
Jinze Zhang, Jian Zhong, Li Lin +18
Optical coherence tomography (OCT) has revolutionized retinal disease diagnosis with its high-resolution and three-dimensional imaging nature, yet its full diagnostic automation in…
DiffCamera: Arbitrary Refocusing on Images
Yiyang Wang, Xi Chen, Xiaogang Xu +2
The depth-of-field (DoF) effect, which introduces aesthetically pleasing blur, enhances photographic quality but is fixed and difficult to modify once the image has been created. T…
Versatile Cataract Fundus Image Restoration Model Utilizing Unpaired Cataract and High-quality Images
Zheng Gong, Zhuo Deng, Weihao Gao +7
Cataract is one of the most common blinding eye diseases and can be treated by surgery. However, because cataract patients may also suffer from other blinding eye diseases, ophthal…
An AI-Driven Multimodal Smart Home Platform for Continuous Monitoring and Assistance in Post-Stroke Motor Impairment
Chenyu Tang, Ruizhi Zhang, Shuo Gao +21
At-home rehabilitation for post-stroke patients presents significant challenges, as continuous, personalized care is often limited outside clinical settings. Moreover, the lack of…
A deep learning-enabled smart garment for accurate and versatile sleep conditions monitoring in daily life
Chenyu Tang, Wentian Yi, Muzi Xu +6
In wearable smart systems, continuous monitoring and accurate classification of different sleep-related conditions are critical for enhancing sleep quality and preventing sleep-rel…
VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence
Jianing Qiu, Jian Wu, Hao Wei +39
We present VisionFM, a foundation model pre-trained with 3.4 million ophthalmic images from 560,457 individuals, covering a broad range of ophthalmic diseases, modalities, imaging…
Large AI Models in Health Informatics: Applications, Challenges, and the Future
Jianing Qiu, Lin Li, Jiankai Sun +11
Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions. Once p…
Augmenting Pathologists with NaviPath: Design and Evaluation of a Human-AI Collaborative Navigation System
Hongyan Gu, Chunxu Yang, Mohammad Haeri +7
Artificial Intelligence (AI) brings advancements to support pathologists in navigating high-resolution tumor images to search for pathology patterns of interest. However, existing…
OMSN and FAROS: OCTA Microstructure Segmentation Network and Fully Annotated Retinal OCTA Segmentation Dataset
Peng Xiao, Xiaodong Hu, Ke Ma +4
The lack of efficient segmentation methods and fully-labeled datasets limits the comprehensive assessment of optical coherence tomography angiography (OCTA) microstructures like re…
Analysing Wideband Absorbance Immittance in Normal and Ears with Otitis Media with Effusion Using Machine Learning
Emad M. Grais, Xiaoya Wang, Jie Wang +6
Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation…
Difficulty-aware Glaucoma Classification with Multi-Rater Consensus Modeling
Shuang Yu, Hong-Yu Zhou, Kai Ma +4
Medical images are generally labeled by multiple experts before the final ground-truth labels are determined. Consensus or disagreement among experts regarding individual images re…
Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student Learning
Junde Wu, Shuang Yu, Wenting Chen +5
Recently, deep learning has been adopted to the glaucoma classification task with performance comparable to that of human experts. However, a well trained deep learning model deman…
Learn to Segment Retinal Lesions and Beyond
Qijie Wei, Xirong Li, Weihong Yu +8
Towards automated retinal screening, this paper makes an endeavor to simultaneously achieve pixel-level retinal lesion segmentation and image-level disease classification. Such a m…
Performance assessment of the deep learning technologies in grading glaucoma severity
Yi Zhen, Lei Wang, Han Liu +2
Objective: To validate and compare the performance of eight available deep learning architectures in grading the severity of glaucoma based on color fundus images. Materials and Me…