72 citations · 105 across the 9 of their papers we have counts for
9 papers
Native Intelligence Emerges from Large-Scale Clinical Practice: A Retinal Foundation Model with Deployment Efficiency
Jia Guo, Jiawei Du, Shengzhu Yang +21
Current retinal foundation models remain constrained by curated research datasets that lack authentic clinical context, and require extensive task-specific optimization for each ap…
RetSTA: An LLM-Based Approach for Standardizing Clinical Fundus Image Reports
Jiushen Cai, Weihang Zhang, Hanruo Liu +2
Standardization of clinical reports is crucial for improving the quality of healthcare and facilitating data integration. The lack of unified standards, including format, terminolo…
ViLReF: An Expert Knowledge Enabled Vision-Language Retinal Foundation Model
Shengzhu Yang, Jiawei Du, Jia Guo +4
Subtle semantic differences in retinal image and text data present great challenges for pre-training visual-language models. Moreover, false negative samples, i.e., image-text pair…
RET-CLIP: A Retinal Image Foundation Model Pre-trained with Clinical Diagnostic Reports
Jiawei Du, Jia Guo, Weihang Zhang +4
The Vision-Language Foundation model is increasingly investigated in the fields of computer vision and natural language processing, yet its exploration in ophthalmology and broader…
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…
Applications of Deep Learning in Fundus Images: A Review
Tao Li, Wang Bo, Chunyu Hu +4
The use of fundus images for the early screening of eye diseases is of great clinical importance. Due to its powerful performance, deep learning is becoming more and more popular i…
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…
Attention Based Glaucoma Detection: A Large-scale Database and CNN Model
Liu Li, Mai Xu, Xiaofei Wang +2
Recently, the attention mechanism has been successfully applied in convolutional neural networks (CNNs), significantly boosting the performance of many computer vision tasks. Unfor…