11 citations · 35 across the 14 of their papers we have counts for
18 papers
DS3-Net: Difficulty-perceived Common-to-T1ce Semi-Supervised Multimodal MRI Synthesis Network
Ziqi Huang, Li Lin, Pujin Cheng +2
Contrast-enhanced T1 (T1ce) is one of the most essential magnetic resonance imaging (MRI) modalities for diagnosing and analyzing brain tumors, especially gliomas. In clinical prac…
LesionPaste: One-Shot Anomaly Detection for Medical Images
Weikai Huang, Yijin Huang, Xiaoying Tang
Due to the high cost of manually annotating medical images, especially for large-scale datasets, anomaly detection has been explored through training models with only normal data.…
Uni4Eye: Unified 2D and 3D Self-supervised Pre-training via Masked Image Modeling Transformer for Ophthalmic Image Classification
Zhiyuan Cai, Li Lin, Huaqing He +1
A large-scale labeled dataset is a key factor for the success of supervised deep learning in computer vision. However, a limited number of annotated data is very common, especially…
Multi-modal Brain Tumor Segmentation via Missing Modality Synthesis and Modality-level Attention Fusion
Ziqi Huang, Li Lin, Pujin Cheng +2
Multi-modal magnetic resonance (MR) imaging provides great potential for diagnosing and analyzing brain gliomas. In clinical scenarios, common MR sequences such as T1, T2 and FLAIR…
JOINED : Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection
Huaqing He, Li Lin, Zhiyuan Cai +1
Fundus photography has been routinely used to document the presence and severity of various retinal degenerative diseases such as age-related macula degeneration, glaucoma, and dia…
COROLLA: An Efficient Multi-Modality Fusion Framework with Supervised Contrastive Learning for Glaucoma Grading
Zhiyuan Cai, Li Lin, Huaqing He +1
Glaucoma is one of the ophthalmic diseases that may cause blindness, for which early detection and treatment are very important. Fundus images and optical coherence tomography (OCT…