State-of-the-art methods for brain tissue segmentation: A review
Brain tissue segmentation is one of the most sought after research areas in medical image
processing. It provides detailed quantitative brain analysis for accurate disease diagnosis …
processing. It provides detailed quantitative brain analysis for accurate disease diagnosis …
Deformable models for image segmentation: A critical review of achievements and future challenges
Image segmentation is a fundamental and tedious task of computer vision. Because of
inherent noise and intensity inhomogeneity in real-world images, it remains a difficult …
inherent noise and intensity inhomogeneity in real-world images, it remains a difficult …
An active contour model based on local fitted images for image segmentation
Active contour models are popular and widely used for a variety of image segmentation
applications with promising accuracy, but they may suffer from limited segmentation …
applications with promising accuracy, but they may suffer from limited segmentation …
Attractive deep morphology-aware active contour network for vertebral body contour extraction with extensions to heterogeneous and semi-supervised scenarios
Automatic vertebral body contour extraction (AVBCE) from heterogeneous spinal MRI is
indispensable for the comprehensive diagnosis and treatment of spinal diseases. However …
indispensable for the comprehensive diagnosis and treatment of spinal diseases. However …
Automatic initialization of active contours and level set method in ultrasound images of breast abnormalities
A Rodtook, K Kirimasthong, W Lohitvisate… - Pattern Recognition, 2018 - Elsevier
We propose a novel initialization method designed for active contours (AC) and the level set
method (LSM), based on walking particles. The algorithm defines the seeds at converging …
method (LSM), based on walking particles. The algorithm defines the seeds at converging …
GVFOM: a novel external force for active contour based image segmentation
Z Zhang, C Duan, T Lin, S Zhou, Y Wang, X Gao - Information Sciences, 2020 - Elsevier
The GVF snake is effective on converging into concave areas and being insensitive to
initialization. However, it fails to converge to areas with deep and narrow concavities or …
initialization. However, it fails to converge to areas with deep and narrow concavities or …
[图书][B] Variational methods in image processing
LA Vese, C Le Guyader - 2016 - api.taylorfrancis.com
This manuscript is devoted to variational models, their corresponding Euler–Lagrange
equations and numerical implementations for image processing. Such techniques allow us …
equations and numerical implementations for image processing. Such techniques allow us …
Adaptive diffusion flow active contours for image segmentation
Gradient vector flow (GVF) active contour model shows good performance at concavity
convergence and initialization insensitivity, yet it is susceptible to weak edges as well as …
convergence and initialization insensitivity, yet it is susceptible to weak edges as well as …
Segmentation of the left ventricle in cardiac cine MRI using a shape-constrained snake model
Segmentation of the left ventricle (LV) is a hot topic in cardiac magnetic resonance (MR)
images analysis. In this paper, we present an automatic LV myocardial boundary …
images analysis. In this paper, we present an automatic LV myocardial boundary …
Image segmentation using active contours with normally biased GVF external force
Y Wang, L Liu, H Zhang, Z Cao… - IEEE Signal Processing …, 2010 - ieeexplore.ieee.org
Gradient vector flow (GVF) is an effective external force for active contours, but its isotropic
nature handicaps its performance. The recently proposed NGVF model is anisotropic since it …
nature handicaps its performance. The recently proposed NGVF model is anisotropic since it …