7 citations · 23 across the 7 of their papers we have counts for
7 papers
Interpretable Small Training Set Image Segmentation Network Originated from Multi-Grid Variational Model
Junying Meng, Weihong Guo, Jun Liu +1
The main objective of image segmentation is to divide an image into homogeneous regions for further analysis. This is a significant and crucial task in many applications such as me…
Image Segmentation with Adaptive Spatial Priors from Joint Registration
Haifeng Li, Weihong Guo, Jun Liu +2
Image segmentation is a crucial but challenging task that has many applications. In medical imaging for instance, intensity inhomogeneity and noise are common. In thigh muscle imag…
Convex Shape Prior for Deep Neural Convolution Network based Eye Fundus Images Segmentation
Jun Liu, Xue-Cheng Tai, Shousheng Luo
Convex Shapes (CS) are common priors for optic disc and cup segmentation in eye fundus images. It is important to design proper techniques to represent convex shapes. So far, it is…
Deep Convolutional Neural Networks with Spatial Regularization, Volume and Star-shape Priori for Image Segmentation
Jun Liu, Xiangyue Wang, Xue-cheng Tai
We use Deep Convolutional Neural Networks (DCNNs) for image segmentation problems. DCNNs can well extract the features from natural images. However, the classification functions in…
Nonlocal Patches based Gaussian Mixture Model for Image Inpainting
Wei Wan, Jun Liu
We consider the inpainting problem for noisy images. It is very challenge to suppress noise when image inpainting is processed. An image patches based nonlocal variational method i…
Volume Preserving Image Segmentation with Entropic Regularization Optimal Transport and Its Applications in Deep Learning
Haifeng Li, Jun Liu, Li Cui +2
Image segmentation with a volume constraint is an important prior for many real applications. In this work, we present a novel volume preserving image segmentation algorithm, which…