39 citations · 56 across the 8 of their papers we have counts for
8 papers
DeLightMono: Enhancing Self-Supervised Monocular Depth Estimation in Endoscopy by Decoupling Uneven Illumination
Mingyang Ou, Haojin Li, Yifeng Zhang +4
Self-supervised monocular depth estimation serves as a key task in the development of endoscopic navigation systems. However, performance degradation persists due to uneven illumin…
Open-Medical-R1: How to Choose Data for RLVR Training at Medicine Domain
Zhongxi Qiu, Zhang Zhang, Yan Hu +2
This paper explores optimal data selection strategies for Reinforcement Learning with Verified Rewards (RLVR) training in the medical domain. While RLVR has shown exceptional poten…
COph100: A comprehensive fundus image registration dataset from infants constituting the "RIDIRP" database
Yan Hu, Mingdao Gong, Zhongxi Qiu +7
Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with…
RaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image Segmentation
Heng Li, Haojin Li, Jianyu Chen +3
Deep learning models often encounter challenges in making accurate inferences when there are domain shifts between the source and target data. This issue is particularly pronounced…
Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image Enhancement
Heng Li, Ziqin Lin, Zhongxi Qiu +4
Medical imaging provides many valuable clues involving anatomical structure and pathological characteristics. However, image degradation is a common issue in clinical practice, whi…
Learnable Ophthalmology SAM
Zhongxi Qiu, Yan Hu, Heng Li +1
Segmentation is vital for ophthalmology image analysis. But its various modal images hinder most of the existing segmentation algorithms applications, as they rely on training base…
Hard Exudate Segmentation Supplemented by Super-Resolution with Multi-scale Attention Fusion Module
Jiayi Zhang, Xiaoshan Chen, Zhongxi Qiu +3
Hard exudates (HE) is the most specific biomarker for retina edema. Precise HE segmentation is vital for disease diagnosis and treatment, but automatic segmentation is challenged b…
SuperVessel: Segmenting High-resolution Vessel from Low-resolution Retinal Image
Yan Hu, Zhongxi Qiu, Dan Zeng +3
Vascular segmentation extracts blood vessels from images and serves as the basis for diagnosing various diseases, like ophthalmic diseases. Ophthalmologists often require high-reso…