6 papers
MSNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentation
Xiaoqi Zhao, Hongpeng Jia, Youwei Pang +5
Accurate medical image segmentation is critical for early medical diagnosis. Most existing methods are based on U-shape structure and use element-wise addition or concatenation to…
HFP-SAM: Hierarchical Frequency Prompted SAM for Efficient Marine Animal Segmentation
Pingping Zhang, Tianyu Yan, Yuhao Wang +7
Marine Animal Segmentation (MAS) aims at identifying and segmenting marine animals from complex marine environments. Most of previous deep learning-based MAS methods struggle with…
Interactive Spatial-Frequency Fusion Mamba for Multi-Modal Image Fusion
Yixin Zhu, Long Lv, Pingping Zhang +5
Multi-Modal Image Fusion (MMIF) aims to combine images from different modalities to produce fused images, retaining texture details and preserving significant information. Recently…
Spatial-Frequency Enhanced Mamba for Multi-Modal Image Fusion
Hui Sun, Long Lv, Pingping Zhang +4
Multi-Modal Image Fusion (MMIF) aims to integrate complementary image information from different modalities to produce informative images. Previous deep learning-based MMIF methods…
UniSegDiff: Boosting Unified Lesion Segmentation via a Staged Diffusion Model
Yilong Hu, Shijie Chang, Lihe Zhang +3
The Diffusion Probabilistic Model (DPM) has demonstrated remarkable performance across a variety of generative tasks. The inherent randomness in diffusion models helps address issu…
P3Net: Progressive and Periodic Perturbation for Semi-Supervised Medical Image Segmentation
Zhenyan Yao, Miao Zhang, Lanhu Wu +4
Perturbation with diverse unlabeled data has proven beneficial for semi-supervised medical image segmentation (SSMIS). While many works have successfully used various perturbation…