11 papers
GR-FM: Geometrically Regularized Flow Matching for SDF-Based Medical Image Segmentation
Yuxin Ai, Zhichang Guo, Fanghui Song +1
Medical image segmentation remains challenging in terms of accurate boundary localization and complex-structure preservation, as target regions often exhibit weak boundaries, fine-…
From level set evolution to threshold optimization: A grayscale level set framework for image segmentation
Xingkai Li, Jiebao Sun, Fanghui Song +1
The segmentation of multiple degradations has been a challenging problem in the field of image segmentation. Existing level set approaches commonly adopt a length regularization te…
A Smooth Phase-Separation Model for Weak-Boundary Segmentation of Homogeneous Structures
Zihan Li, Jiebao Sun, Fanghui Song +1
Segmentation of adjacent structures with similar intensity distributions remains a challenging problem in image analysis, particularly when object boundaries are weak or ambiguous.…
SILSM: A Sustainable Interactive Level Set Method for Progressive Refinement
Jiachen Song, Dazhi Zhang, Fanghui Song +2
Interactive segmentation aims to precisely isolate target objects using sparse user guidance. However, traditional methods often suffer from heavy interaction burdens and parameter…
An ICTM-RMSAV Framework for Bias-Field Aware Image Segmentation under Poisson and Multiplicative Noise
Xinyu Wang, Wenjun Yao, Fanghui Song +1
Image segmentation is a core task in image processing, yet many methods degrade when images are heavily corrupted by noise and exhibit intensity inhomogeneity. Within the iterative…
TA-LSDiff:Topology-Aware Diffusion Guided by a Level Set Energy for Pancreas Segmentation
Yue Gou, Fanghui Song, Yuming Xing +3
Pancreas segmentation in medical image processing is a persistent challenge due to its small size, low contrast against adjacent tissues, and significant topological variations. Tr…
COFM: Consistent Optimal Transport Flow Matching via Partially Input Convex Neural Networks
Fanghui Song, Zhongjian Wang, Jiebao Sun
Optimal transport (OT) provides a principled framework for learning mappings between probability distributions, and has found broad applications in generative modeling, inverse pro…
Progressive Alignment Degradation Learning for Pansharpening
Enzhe Zhao, Zhichang Guo, Yao Li +2
Deep learning-based pansharpening has been shown to effectively generate high-resolution multispectral (HRMS) images. To create supervised ground-truth HRMS images, synthetic data…
A class of thin-film equations with space-time dependent gradient nonlinearity and its application to image sharpening
Yuhang Li, Zhichang Guo, Fanghui Song +2
We introduce a class of thin-film equations with space-time dependent gradient nonlinearity and apply them to image sharpening. By modifying the potential well method, we overcome…
Mixed geometry information regularization for image multiplicative denoising
Shengkun Yang, Zhichang Guo, Jia Li +2
This paper focuses on solving the multiplicative gamma denoising problem via a variation model. Variation-based regularization models have been extensively employed in a variety of…
Re-initialization-free Level Set Method via Molecular Beam Epitaxy Equation Regularization for Image Segmentation
Fanghui Song, Jiebao Sun, Shengzhu Shi +2
Variational level set method has become a powerful tool in image segmentation due to its ability to handle complex topological changes and maintain continuity and smoothness in the…