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Hyperparameter selection for Discrete Mumford–Shah
This work focuses on a parameter-free joint piecewise smooth image denoising and contour detection. Formulated as the minimization of a discrete...
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Automated Image Restoration and Segmentation Using Mumford–Shah-Like Regularization and Topological Asymptotic Expansion
In this paper, we propose an approach to the problem of automated image restoration and segmentation. To solve these tasks simultaneously, we...
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Uncertainty Quantification in Image Segmentation Using the Ambrosio–Tortorelli Approximation of the Mumford–Shah Energy
The quantification of uncertainties in image segmentation based on the Mumford–Shah model is studied. The aim is to address the error propagation of...
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Piece-wise Constant Image Segmentation with a Deep Image Prior Approach
Image segmentation is a key topic in image processing and computer vision and several approaches have been proposed in the literature to address it....
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GAN-Based Bi-Modal Segmentation Using Mumford-Shah Loss: Application to Head and Neck Tumors in PET-CT Images
A deep model based on SegAN, a generative adversarial network (GAN) for medical image segmentation, is proposed for PET-CT image segmentation,...
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Blake–Zisserman Model of Segmentation Method for Low-Contrast and Piecewise Smooth Image
Although extensively investigated, image segmentation is still a challenging topic, particularly for new and develo** imaging modalities with...
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Enforcing Geometrical Priors in Deep Networks for Semantic Segmentation Applied to Radiotherapy Planning
Incorporating prior knowledge into a segmentation process, whether it is geometrical constraints such as volume penalisation, (partial) convexity...
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An entropy-weighted local intensity clustering-based model for segmenting intensity inhomogeneous images
This paper proposes an entropy-weighted local intensity clustering-based model for segmenting intensity inhomogeneous images caused by the bias...
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An adaptive multi-level-sets active contour model based on block search
In order to better handle images with intensity inhomogeneity and noise, an adaptive multi-level set active contour model based on block search is...
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A novel dual-based ADMM to the Chan-Vese model
The level set method is a classical method to solve the Chan-Vese model for the binary image segmentation problem. Some efficient methods such as the...
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An image segmentation method based on Mumford–Shah model with mask factor and neighborhood factor
A novel image segmentation model is proposed to improve the stability of existing segmentation methods. In the proposed model, we introduce two...
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Segmentation and Risk Score Prediction of Head and Neck Cancers in PET/CT Volumes with 3D U-Net and Cox Proportional Hazard Neural Networks
We utilized a 3D nnU-Net model with residual layers supplemented by squeeze and excitation (SE) normalization for tumor segmentation from PET/CT...
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Local image segmentation model via Hellinger distance
Highly accurate active contour models are widely used in various image segmentation methods. In this paper, we propose an image segmentation model...
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Medical image segmentation model based on caputo fractional differential
Medical image segmentation technology, as a key work of modern medical such as intelligent medical diagnosis, has attracted a lot of attention....
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Model Fitting and Optimization
In the previous chapter, we covered a large number of image processing operators that take as input one or more images and produce some filtered or...
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Efficient and robust level set model for extracting regions of interest in X-ray welding images and MRI brain images
Extraction of the region of interest (ROI) from the X-ray welding images and MRI brain images is extremely challenging due to their poor quality, low...
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A Retinex-Based Selective Segmentation Model for Inhomogeneous Images
It is often challenging to selectively segment the images with intensity inhomogeneity for the existing region-based variational models. This article...
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Image Segmentation via Mean Curvature Regularized Mumford-Shah Model and Thresholding
Due to the limitations in imaging devices and subject-induced susceptibility effect, general image segmentation is still an open problem. Typical...
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An Elastica-Driven Digital Curve Evolution Model for Image Segmentation
Geometric priors have been shown to be useful in image segmentation to regularize the results. For example, the classical Mumford–Shah functional...
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Shape Prior Based Myocardial Segmentation with Anatomically Motivated Pose Model
We extend the shape-prior based geometric approach developed for myocardial segmentation in cardiac CT imagery by incorporating minimal user input in...