3 citations · 3 across the 12 of their papers we have counts for
10 papers · 1 filter
CS-MUNet: A Channel-Spatial Dual-Stream Mamba Network for Multi-Organ Segmentation
Yuyang Zheng, Mingda Zhang, Jianglong Qin +4
Recently Mamba-based methods have shown promise in abdominal organ segmentation. However, existing approaches neglect cross-channel anatomical semantic collaboration and lack expli…
Unified Multimodal Coherent Field: Synchronous Semantic-Spatial-Vision Fusion for Brain Tumor Segmentation
Mingda Zhang, Yuyang Zheng, Ruixiang Tang +2
Brain tumor segmentation requires accurate identification of hierarchical regions including whole tumor (WT), tumor core (TC), and enhancing tumor (ET) from multi-sequence magnetic…
A Semantic Segmentation Algorithm for Pleural Effusion Based on DBIF-AUNet
Ruixiang Tang, Mingda Zhang, Jianglong Qin +3
Pleural effusion semantic segmentation can significantly enhance the accuracy and timeliness of clinical diagnosis and treatment by precisely identifying disease severity and lesio…
DCFFSNet: Deep Connectivity Feature Fusion Separation Network for Medical Image Segmentation
Mingda Zhang, Xun Ye, Ruixiang Tang +1
Medical image segmentation leverages topological connectivity theory to enhance edge precision and regional consistency. However, existing deep networks integrating connectivity of…
Knowledge-Guided Brain Tumor Segmentation via Synchronized Visual-Semantic-Topological Prior Fusion
Mingda Zhang, Kaiwen Pan
Background: Brain tumor segmentation requires precise delineation of hierarchical structures from multi-sequence MRI. However, existing deep learning methods primarily rely on visu…
Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps
Nanye Ma, Shangyuan Tong, Haolin Jia +8
Generative models have made significant impacts across various domains, largely due to their ability to scale during training by increasing data, computational resources, and model…