2 citations · 5 across the 12 of their papers we have counts for
6 papers · 1 filter
A Unified Variational Framework for Deep Weakly Supervised Image Segmentation
Yin King Chu, Lingfeng Li, Sung Ha Kang +2
We propose a unified variational framework for image segmentation under sparse pixel-level supervision. Our method is based on a simplex-constrained Potts model with a smooth perim…
Topology-Guaranteed Image Segmentation: Enforcing Connectivity, Genus, and Width Constraints
Wenxiao Li, Xue-Cheng Tai, Jun Liu
Existing research highlights the crucial role of topological priors in image segmentation, particularly in preserving essential structures such as connectivity and genus. Accuratel…
A Registration-Based Star-Shape Segmentation Model and Fast Algorithms
Daoping Zhang, Xue-Cheng Tai, Lok Ming Lui
Image segmentation plays a crucial role in extracting objects of interest and identifying their boundaries within an image. However, accurate segmentation becomes challenging when…
A Mathematical Explanation of UNet
Xue-Cheng Tai, Hao Liu, Raymond H. Chan +1
The UNet architecture has transformed image segmentation. UNet's versatility and accuracy have driven its widespread adoption, significantly advancing fields reliant on machine lea…
Deep Convolutional Neural Networks Meet Variational Shape Compactness Priors for Image Segmentation
Kehui Zhang, Lingfeng Li, Hao Liu +2
Shape compactness is a key geometrical property to describe interesting regions in many image segmentation tasks. In this paper, we propose two novel algorithms to solve the introd…
Double-well Net for Image Segmentation
Hao Liu, Jun Liu, Raymond H. Chan +1
In this study, our goal is to integrate classical mathematical models with deep neural networks by introducing two novel deep neural network models for image segmentation known as…