17 citations · 23 across the 10 of their papers we have counts for
10 papers
Polygon-mamba: Retinal vessel segmentation using polygon scanning mamba and space-frequency collaborative attention
Yuanyuan Peng, Wen Li
Retinal vessel segmentation is crucial for diagnosis and assessment of ocular diseases. Notably, segmentation of small retinal vessels has been consistently recognized as a challen…
Beyond Classification Accuracy: Neural-MedBench and the Need for Deeper Reasoning Benchmarks
Miao Jing, Mengting Jia, Junling Lin +4
Recent advances in vision-language models (VLMs) have achieved remarkable performance on standard medical benchmarks, yet their true clinical reasoning ability remains unclear. Exi…
Clinician-Friendly Foundation Models for Ophthalmic Image Diagnostics without Fine-Tuning or Technical Barriers
Meng Wang, Tian Lin, Qingshan Hou +69
Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, yet most current models require retraining when applied across different clinical settings,…
Enhancing Diagnostic Reliability of Foundation Model with Uncertainty Estimation in OCT Images
Yuanyuan Peng, Aidi Lin, Meng Wang +10
Inability to express the confidence level and detect unseen classes has limited the clinical implementation of artificial intelligence in the real-world. We developed a foundation…
Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model
Meng Wang, Tian Lin, Aidi Lin +46
Previous foundation models for fundus images were pre-trained with limited disease categories and knowledge base. Here we introduce a knowledge-rich vision-language model (RetiZero…
MAF-Net: Multiple attention-guided fusion network for fundus vascular image segmentation
Yuanyuan Peng, Pengpeng Luan, Zixu Zhang
Accurately segmenting blood vessels in retinal fundus images is crucial in the early screening, diagnosing, and evaluating some ocular diseases, yet it poses a nontrivial uncertain…
Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification
Meng Wang, Tian Lin, Lianyu Wang +21
Failure to recognize samples from the classes unseen during training is a major limitation of artificial intelligence in the real-world implementation for recognition and classific…
Curvilinear object segmentation in medical images based on ODoS filter and deep learning network
Yuanyuan Peng, Lin Pan, Pengpeng Luan +2
Automatic segmentation of curvilinear objects in medical images plays an important role in the diagnosis and evaluation of human diseases, yet it is a challenging uncertainty in th…
Pulmonary Fissure Segmentation in CT Images Based on ODoS Filter and Shape Features
Yuanyuan Peng, Pengpeng Luan, Hongbin Tu +2
Priori knowledge of pulmonary anatomy plays a vital role in diagnosis of lung diseases. In CT images, pulmonary fissure segmentation is a formidable mission due to various of facto…
Novel coronavirus pneumonia lesion segmentation in CT images
Yuanyuan Peng, Zixu Zhang, Hongbin Tu +1
Background: The 2019 novel coronavirus disease (COVID-19) has been spread widely in the world, causing a huge threat to people's living environment. Objective: Under computed tomog…