4 papers
MGML: A Plug-and-Play Meta-Guided Multi-Modal Learning Framework for Incomplete Multimodal Brain Tumor Segmentation
Yulong Zou, Bo Liu, Cun-Jing Zheng +6
Leveraging multimodal information from Magnetic Resonance Imaging (MRI) plays a vital role in lesion segmentation, especially for brain tumors. However, in clinical practice, multi…
ERANet: Edge Replacement Augmentation for Semi-Supervised Meniscus Segmentation with Prototype Consistency Alignment and Conditional Self-Training
Siyue Li, Yongcheng Yao, Junru Zhong +9
Manual segmentation is labor-intensive, and automatic segmentation remains challenging due to the inherent variability in meniscal morphology, partial volume effects, and low contr…
WaveNet-SF: A Hybrid Network for Retinal Disease Detection Based on Wavelet Transform in Spatial-Frequency Domain
Jilan Cheng, Guoli Long, Zeyu Zhang +6
Retinal diseases are a leading cause of vision impairment and blindness, with timely diagnosis being critical for effective treatment. Optical Coherence Tomography (OCT) has become…
DGSSA: Domain generalization with structural and stylistic augmentation for retinal vessel segmentation
Bo Liu, Yudong Zhang, Shuihua Wang +2
Retinal vascular morphology is crucial for diagnosing diseases such as diabetes, glaucoma, and hypertension, making accurate segmentation of retinal vessels essential for early int…