Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
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A quantitative method to measure biofilm removal efficiency from complex biomaterial surfaces using SEM and image analysisMRI segmentation of the human brain: challenges, methods, and applications.A novel dictionary based computer vision method for the detection of cell nuclei.Semi-supervised segmentation of ultrasound images based on patch representation and continuous min cut.A Method for Lung Boundary Correction Using Split Bregman Method and Geometric Active Contour ModelLow Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method.Energy minimization in medical image analysis: Methodologies and applications.Spine labeling in MRI via regularized distribution matching.Automatic measurement of volume percentage stroma in endometrial images using texture segmentation.Toward accurate tooth segmentation from computed tomography images using a hybrid level set model.Discontinuity Preserving Image Registration through Motion Segmentation: A Primal-Dual ApproachBrain MR image segmentation based on an improved active contour model.Deterministic direct aperture optimization using multiphase piecewise constant segmentation.Anatomical pulmonary magnetic resonance imaging segmentation for regional structure-function measurements of asthma.Automatic segmentation method for bone and blood vessel in murine hindlimb.Active Contour with a Tangential ComponentFast marching over the 2D Gabor magnitude domain for tongue body segmentationImage Segmentation Using Euler’s Elastica as the RegularizationCompletely Convex Formulation of the Chan-Vese Image Segmentation ModelEntropy-Scale Profiles for Texture SegmentationA New Variational Model for Segmenting Objects of Interest from Color ImagesOn the Application of the Spectral Projected Gradient Method in Image SegmentationConvex Image Segmentation Model Based on Local and Global Intensity Fitting Energy and Split Bregman MethodAdaptively Active Contours Based on Variable ExponentLp(|∇I|)Norm for Image SegmentationA New and Fast Multiphase Image Segmentation Model for Color ImagesLocal- and Global-Statistics-Based Active Contour Model for Image SegmentationA New Multiphase Soft Segmentation with Adaptive VariantsSplit Bregman Iteration Algorithm for Image Deblurring Using Fourth-Order Total Bounded Variation Regularization ModelUnsupervised Texture Segmentation Using Active Contour Model and Oscillating InformationActive Contour Model for Ultrasound Images with Rayleigh DistributionCoupling Image Restoration and Segmentation: A Generalized Linear Model/Bregman Perspective
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P2860
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
description
article
@en
wetenschappelijk artikel
@nl
наукова стаття, опублікована в січні 2006
@uk
name
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
@en
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
@nl
type
label
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
@en
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
@nl
prefLabel
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
@en
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
@nl
P356
P1476
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
@en
P2093
Mila Nikolova
Selim Esedoglu
P304
P356
10.1137/040615286
P50
P577
2006-01-01T00:00:00Z