8.7.3 Level Set Segmentation, Level Set Methods

Chapter Contents (Back)
Level Set.
See also Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision and Materials Science.
See also Level Sets, Shape Models, Prior Shape Models.
See also Level Set Models for Volumes.

Sumengen, B.[Baris],
Matlab toolbox for Level Set Methods,
Online2008.
HTML Version. Code, Segmentation. Code, Segmentation, Matlab. The code follows Osher and Fedkiw book. BibRef 0800

Sussman, M., Smereka, P., and Osher, S.J.,
A Level Set Approach for Computing Solutions to Incompressible Two-Phase Flow,
CompPhys(114), 1994, pp. 146-159. BibRef 9400

Osher, S.J.[Stanley J.],
A Level Set Formulation for the Solution of the Dirichlet Problem for Hamilton-Jacobi Equations,
NumAnal(24), Vol. 24, No. 5, 1993, pp. 1145-1152
DOI Link BibRef 9300

Samson, C.[Christophe], Blanc-Féraud, L.[Laure], Aubert, G.[Gilles], Zerubia, J.B.[Josiane B.],
A Variational Model for Image Classification and Restoration,
PAMI(22), No. 5, May 2000, pp. 460-472.
IEEE DOI 0008
BibRef

Bect, J.[Julien], Blanc-Féraud, L.[Laure], Aubert, G.[Gilles], Chambolle, A.[Antonin],
A/1-Unified Variational Framework for Image Restoration,
ECCV04(Vol IV: 1-13).
Springer DOI 0405
BibRef

Samson, C.[Christophe], Blanc-Féraud, L.[Laure], Aubert, G.[Gilles], Zerubia, J.B.[Josiane B.],
A Level Set Model for Image Classification,
IJCV(40), No. 3, December 2000, pp. 187-197.
DOI Link 0102
BibRef
Earlier: ScaleSpace99(306-317). BibRef
And:
Two Variational Models for Multispectral Image Classification,
EMMCVPR01(344-356).
Springer DOI 0205
BibRef
And: A1, A2, A4, A3:
Simultaneous Image Classification and Restoration Using a Variational Approach,
CVPR99(II: 618-623).
IEEE DOI variational model, level set model, active regions, image classification, labelling BibRef

Teboul, S., Blanc-Feraud, L.[Laure], Aubert, G., and Barlaud, M.,
Segmentation and Edge-Preserving Restoration,
ICIP97(II: 470-473).
IEEE DOI BibRef 9700
Earlier: A2, A1, A3, A4:
Nonlinear Regularization Using Constrained Edges in Image Reconstruction,
ICIP96(II: 449-452).
IEEE DOI BibRef

Sifakis, E.[Eftichis], Garcia, C.[Christophe], Tziritas, G.[Georgios],
Bayesian Level Sets for Image Segmentation,
JVCIR(13), No. 1/2, March/June 2002, pp. 44-64.
DOI Link 0204
BibRef

Sifakis, E.[Eftychis], Tziritas, G.[Georgios],
Robust object boundary determination using a locally adaptive level set algorithm,
ICIP03(I: 141-144).
IEEE DOI 0312
BibRef

Vese, L.A.[Luminita A.], Chan, T.F.[Tony F.],
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model,
IJCV(50), No. 3, December 2002, pp. 271-293.
DOI Link 0211
BibRef
Earlier: A2, A1:
A Level Set Algorithm for minimizing the Mumford-Shah functional in Image Processing,
LevelSet01(xx-yy). 0106

See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems.
See also Active contours without edges. BibRef

Chan, T.F.[Tony F.], Zhu, W.[Wei],
Level Set Based Shape Prior Segmentation,
CVPR05(II: 1164-1170).
IEEE DOI 0507
BibRef

Chung, G.[Ginmo], Vese, L.A.[Luminita A.],
Energy Minimization Based Segmentation and Denoising Using a Multilayer Level Set Approach,
EMMCVPR05(439-455).
Springer DOI 0601
BibRef

Wang, D.J.[De-Jun], Soatto, S.[Stefano], Prados, E.[Emmanuel],
Towards Robust and Physically Plausible Shaded Stereoscopic Segmentation,
3DCINE06(171).
IEEE DOI 0609
BibRef

Hong, B.W.[Byung-Woo], Soatto, S.[Stefano],
Shape Matching Using Multiscale Integral Invariants,
PAMI(37), No. 1, January 2015, pp. 151-160.
IEEE DOI 1412
Indexes BibRef

Hong, B.W.[Byung-Woo], Prados, E.[Emmanuel], Soatto, S.[Stefano], Vese, L.A.[Luminita A.],
Shape Representation based on Integral Kernels: Application to Image Matching and Segmentation,
CVPR06(I: 833-840).
IEEE DOI 0606
BibRef

Kervrann, C.[Charles], Trubuil, A.[Alain],
Optimal Level Curves and Global Minimizers of Cost Functionals in Image Segmentation,
JMIV(17), No. 2, September 2002, pp. 153-174.
DOI Link 0211
BibRef

Kervrann, C.[Charles], Hoebeke, M.[Mark], Trubuil, A.[Alain],
Isophotes Selection and Reaction-Diffusion Model for Object Boundaries Estimation,
IJCV(50), No. 1, October 2002, pp. 63-94.
DOI Link 0210
BibRef
Earlier:
A Level Line Selection Approach for Object Boundary Estimation,
ICCV99(963-968).
IEEE DOI BibRef
Earlier:
Level Lines as Global Minimizers of Energy Functionals in Image Segmentation,
ECCV00(II: 241-256).
Springer DOI 0003
BibRef

Combettes, P.L., Luo, J.[Jian],
An adaptive level set method for nondifferentiable constrained image recovery,
IP(11), No. 11, November 2002, pp. 1295-1304.
IEEE DOI 0301
BibRef

Nilsson, B.[Björn], Heyden, A.[Anders],
A fast algorithm for level set-like active contours,
PRL(24), No. 9-10, June 2003, pp. 1331-1337.
Elsevier DOI 0304
BibRef
Earlier:
Fast Approximation of Level Set Computations: Application to Image Segmentation,
SCIA01(P-W3A). 0206
BibRef

Han, X.[Xiao], Xu, C.Y.[Chen-Yang], Prince, J.L.,
Topology Preserving Level Set Method for Geometric Deformable Models,
PAMI(25), No. 6, June 2003, pp. 755-768.
IEEE Abstract. 0306
BibRef
Earlier:
A Topology Preserving Deformable Model Using Level Sets,
CVPR01(II:765-770).
IEEE DOI 0110
For cases where topology must be preserved. Uses local computations. Active contour model.
See also Reconstruction of the human cerebral cortex from magnetic resonance images. BibRef

Han, X.[Xiao], Xu, C.Y.[Chen-Yang], Prince, J.L.[Jerry L.],
A Moving Grid Framework for Geometric Deformable Models,
IJCV(84), No. 1, August 2009, pp. xx-yy.
Springer DOI 0905
BibRef
Earlier:
A 2D moving grid geometric deformable model,
CVPR03(I: 153-160).
IEEE DOI 0307

See also Digital Topology on Adaptive Octree Grids. BibRef

Martin, P.[Pascal], Refregier, P.[Philippe], Goudail, F.[Francois], Guerault, F.[Federic],
Influence of the Noise Model on Level Set Active Contour Segmentation,
PAMI(26), No. 6, June 2004, pp. 799-803.
IEEE Abstract. 0404
Improve segmentation. Derive the regularization terms using the MDL. BibRef

Martin, P.[Pascal], Refregier, P.[Philippe], Galland, F., Guerault, F.[Federic],
Nonparametric Statistical Snake Based on the Minimum Stochastic Complexity,
IP(15), No. 9, August 2006, pp. 2762-2770.
IEEE DOI 0608
BibRef

Galland, F.[Frederic], Jaegler, A.[Arnaud], Allain, M.[Marc], Savery, D.[David], Refregier, P.[Philippe],
Smooth contour coding with minimal description length active grid segmentation techniques,
PRL(32), No. 5, 1 April 2011, pp. 721-730.
Elsevier DOI 1103
Image segmentation; Statistical image processing; Minimum description length (MDL); Stochastic complexity BibRef

Jeon, M., Alexander, M., Pedrycz, W., Pizzi, N.,
Unsupervised hierarchical image segmentation with level set and additive operator splitting,
PRL(26), No. 10, 15 July 2005, pp. 1461-1469.
Elsevier DOI 0506
multi-phase images. BibRef

Gao, H.[Hai], Lin, W.S.[Wei-Si], Xue, P.[Ping], Siu, W.C.[Wan-Chi],
Marker-based image segmentation relying on disjoint set union,
SP:IC(21), No. 2, February 2006, pp. 100-112.
Elsevier DOI 0512
Pixel sorting, set union, pixel resolving. Compare to Meyer (
See also Levelings, Image Simplification Filters for Segmentation. ?) BibRef

Mansouri, A.R.[Abdol-Reza], Mitiche, A.[Amar], Vázquez, C.[Carlos],
Multiregion competition: A level set extension of region competition to multiple region image partitioning,
CVIU(101), No. 3, March 2006, pp. 137-150.
Elsevier DOI 0601
BibRef
Earlier:
Image partioning by level set multiregion competition,
ICIP04(IV: 2721-2724).
IEEE DOI 0505
BibRef
And: A3, A1, A2:
Approximation of Images by Basis Functions for Multiple Region Segmentation with Level Sets,
ICIP04(I: 549-552).
IEEE DOI 0505

See also Multiple Motion Segmentation with Level Sets. BibRef

Vazquez, C., Mitiche, A., Ben Ayed, I.[Ismail],
Image Segmentation as Regularized Clustering: A Fully Global Curve Evolution Method,
ICIP04(V: 3467-3470).
IEEE DOI 0505
BibRef

Mitiche, A.[Amar], Ben Ayed, I.[Ismail],
Variational and Level Set Methods in Image Segmentation,
Springer2011, ISBN: 978-3-642-15351-8
WWW Link. Survey, Level Set Segmentation. Buy this book: Variational and Level Set Methods in Image Segmentation (Springer Topics in Signal Processing) 1011
Code, Level Set Segmentation. Code:
WWW Link. BibRef

Mathlouthi, Y.[Yosra], Mitiche, A.[Amar], Ben Ayed, I.[Ismail],
Boundary Preserving Variational Image Differentiation,
GCPR16(355-364).
Springer DOI 1611
BibRef

Dejnožková, E.[Eva], Dokládal, P.[Petr],
Embedded Real-Time Architecture for Level-Set-Based Active Contours,
JASP(2005), No. 17, 2005, pp. 2788-2803.
WWW Link. 0603
BibRef
Earlier:
Modelling of Overlapping Circular Objects Based on Level Set Approach,
ICIAR04(I: 416-423).
Springer DOI 0409
BibRef

Chabardès, T.[Théodore], Dokládal, P.[Petr], Faessel, M.[Matthieu], Bilodeau, M.[Michel],
An Affinity Score for Grains Merging and Touching Grains Separation,
ISMM17(423-434).
Springer DOI 1706
overlapping objects. BibRef

Borocco, A.[Albane], Fellah, C.[Clémentine], Braun, J.[James], Berger, M.H.[Marie-Hélène], Dokládal, P.[Petr],
Morphological Characterization of Graphene Plans Stacking,
ISMM17(435-446).
Springer DOI 1706
BibRef

Lie, J.[Johan], Lysaker, M.[Marius], Tai, X.C.[Xue-Cheng],
A Binary Level Set Model and Some Applications to Mumford-Shah Image Segmentation,
IP(15), No. 5, May 2006, pp. 1171-1181.
IEEE DOI 0605
BibRef
Earlier:
Piecewise Constant Level Set Methods and Image Segmentation,
ScaleSpace05(573-584).
Springer DOI 0505

See also Graph Cuts for Curvature Based Image Denoising. BibRef

Tai, X.C.[Xue-Cheng], Christiansen, O.[Oddvar], Lin, P.[Ping], SkjÆlaaen, I.[Inge],
Image Segmentation Using Some Piecewise Constant Level Set Methods with MBO Type of Projection,
IJCV(73), No. 1, June 2007, pp. 61-76.
Springer DOI 0702
BibRef

Han, S., Tao, W., Wang, D., Tai, X.C., Wu, X.,
Image Segmentation Based on GrabCut Framework Integrating Multiscale Nonlinear Structure Tensor,
IP(18), No. 10, October 2009, pp. 2289-2302.
IEEE DOI 0909
BibRef

Yan, S.[Shi], Tai, X.C.[Xue-Cheng], Liu, J.[Jun], Huang, H.Y.[Hai-Yang],
Convexity Shape Prior for Level Set-Based Image Segmentation Method,
IP(29), 2020, pp. 7141-7152.
IEEE DOI 2007
Shape, Level set, Image segmentation, Mathematical model, Computational modeling, Numerical models, Minimization, Chan-Vese model BibRef

Shu, X.[Xiu], Yang, Y.Y.[Yun-Yun], Liu, J.[Jun], Chang, X.J.[Xiao-Jun], Wu, B.Y.[Bo-Ying],
ALVLS: Adaptive local variances-Based levelset framework for medical images segmentation,
PR(136), 2023, pp. 109257.
Elsevier DOI 2301
Image segmentation, Local fitting variance, Edge-based information, Level set framework BibRef

Luo, S.S.[Shou-Sheng], Tai, X.C.[Xue-Cheng], Huo, L.M.[Li-Mei], Wang, Y.[Yang], Glowinski, R.[Roland],
Convex Shape Prior for Multi-Object Segmentation Using a Single Level Set Function,
ICCV19(613-621)
IEEE DOI 2004
Gaussian processes, image segmentation, partial differential equations, convex shape, Computational efficiency BibRef

Losnegård, A.[Are], Christiansen, O.[Oddvar], Tai, X.C.[Xue-Cheng],
Piecewise Constant Level Set Method for 3D Image Segmentation,
SSVM07(687-696).
Springer DOI 0705
BibRef

de Cezaro, A.[Adriano], Leitão, A.[Antonio], Tai, X.C.[Xue-Cheng],
On Level-Set Type Methods for Recovering Piecewise Constant Solutions of Ill-Posed Problems,
SSVM09(50-62).
Springer DOI 0906
BibRef

Hodneland, E.[Erlend], Tai, X.C.[Xue-Cheng], Gerdes, H.H.[Hans-Hermann],
Four-Color Theorem and Level Set Methods for Watershed Segmentation,
IJCV(82), No. 3, May 2009, pp. xx-yy.
Springer DOI 0903
BibRef

Tai, X.C.[Xue-Cheng], Hodneland, E.[Erlend], Weickert, J.[Joachim], Bukoreshtliev, N.V.[Nickolay V.], Lundervold, A.[Arvid], Gerdes, H.H.[Hans-Hermann],
Level Set Methods for Watershed Image Segmentation,
SSVM07(178-190).
Springer DOI 0705
BibRef

Groisser, D.[David],
Some Differential-Geometric Remarks on a Method for Minimizing Constrained Functionals of Matrix-Valued Functions,
JMIV(24), No. 3, May 2006, pp. 349-358.
Springer DOI 0605
BibRef

Lee, S.H., Seo, J.K.,
Level Set-Based Bimodal Segmentation With Stationary Global Minimum,
IP(15), No. 9, August 2006, pp. 2843-2852.
IEEE DOI 0608
BibRef

Lee, S.H., Woo, H., Gi-Kang, M.G.,
Global Illumination Invariant Object Detection With Level Set Based Bimodal Segmentation,
CirSysVideo(20), No. 4, April 2010, pp. 616-620.
IEEE DOI 1003
BibRef

Brox, T.[Thomas], Weickert, J.[Joachim],
Level Set Segmentation With Multiple Regions,
IP(15), No. 10, October 2006, pp. 3213-3218.
IEEE DOI 0609
BibRef
Earlier:
Level Set Based Image Segmentation with Multiple Regions,
DAGM04(415-423).
Springer DOI 0505
BibRef

Brox, T.[Thomas], Bruhn, A.[Andrés], Weickert, J.[Joachim],
Variational Motion Segmentation with Level Sets,
ECCV06(I: 471-483).
Springer DOI 0608
BibRef

Brox, T.[Thomas], Cremers, D.[Daniel],
On Local Region Models and a Statistical Interpretation of the Piecewise Smooth Mumford-Shah Functional,
IJCV(84), No. 2, August 2009, pp. xx-yy.
Springer DOI 0906
BibRef
Earlier:
On the Statistical Interpretation of the Piecewise Smooth Mumford-Shah Functional,
SSVM07(203-213).
Springer DOI Or:
PDF File. 0705
BibRef

Strekalovskiy, E.[Evgeny], Cremers, D.[Daniel],
Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional,
ECCV14(II: 127-141).
Springer DOI 1408
BibRef

Brox, T.[Thomas], Rousson, M.[Mikael], Deriche, R.[Rachid], Weickert, J.[Joachim],
Colour, texture, and motion in level set based segmentation and tracking,
IVC(28), No. 3, March 2010, pp. 376-390.
Elsevier DOI 1001
Image segmentation; Tracking; Level set methods; Nonlinear diffusion; Texture; Motion BibRef

Kim, Y.J., Brox, T.[Thomas], Feiden, W., Weickert, J.[Joachim],
Fully automated segmentation and morphometrical analysis of muscle fibre images,
Cytometry(A, 71), January 2007, pp. 8-15. BibRef 0701
And: TRPreprint No. 177, July 2006. Department of Mathematics, Saarland University, Saarbrücken, Germany. BibRef

Kolev, K.[Kalin], Brox, T.[Thomas], Cremers, D.[Daniel],
Robust Variational Segmentation of 3D Objects from Multiple Views,
DAGM06(688-697).
Springer DOI 0610
BibRef

Hanning, T.[Tobias], Schöne, R.[René], Pisinger, G.[Georg],
Vector Image Segmentation by Piecewise Continuous Approximation,
JMIV(25), No. 1, July 2006, pp. 5-23.
Springer DOI 0610
BibRef

Hanning, T.[Tobias], Farr, H., Kellner, M., Lauren, V.,
Segmentation of Vector Images by N-level-set-fitting,
ICIP01(II: 793-796).
IEEE DOI 0108
BibRef

Aujol, J.F.[Jean-Francois], Chan, T.F.[Tony F.],
Combining geometrical and textured information to perform image classification,
JVCIR(17), No. 5, October 2006, pp. 1004-1023.
Elsevier DOI 0711
Classification; Texture; Geometrical image; Decomposition; Logic model; Level-set; Active contour; PDE; Wavelets BibRef

Lam, B.S.Y., Yan, H.,
A curve tracing algorithm using level set based affine transform,
PRL(28), No. 2, 15 January 2007, pp. 181-196.
Elsevier DOI 0611
Fuzzy curve-tracing (FCT) algorithm; Level set method; Affine transform; Pattern thinning; Skeletonization BibRef

Juan, O.[Olivier], Keriven, R.[Renaud], Postelnicu, G.[Gheorghe],
Stochastic Motion and the Level Set Method in Computer Vision: Stochastic Active Contours,
IJCV(69), No. 1, August 2006, pp. 7-25.
Springer DOI 0606
BibRef

Allene, C.[Cedric], Audibert, J.Y.[Jean-Yves], Couprie, M.[Michel], Keriven, R.[Renaud],
Some links between extremum spanning forests, watersheds and min-cuts,
IVC(28), No. 10, October 2010, pp. 1460-1471.
Elsevier DOI 1007
Min-cuts; Extremum spanning forests; Watersheds; Segmentation BibRef

Duchenne, O.[Olivier], Audibert, J.Y.[Jean-Yves], Keriven, R.[Renaud], Ponce, J.[Jean], Segonne, F.[Florent],
Segmentation by transduction,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Maurel, P.[Pierre], Keriven, R.[Renaud], Faugeras, O.D.[Olivier D.],
Reconciling Landmarks and Level Sets,
ICPR06(IV: 69-72).
IEEE DOI 0609
BibRef

Pons, J.P.[Jean-Philippe], Hermosillo, G.[Gerardo], Keriven, R.[Renaud], Faugeras, O.D.[Olivier D.],
How to deal with point correspondences and tangential velocities in the level set framework,
ICCV03(894-899).
IEEE DOI 0311
BibRef
Earlier: INRIARR-4857, 2003.
HTML Version. BibRef

Ballester, C.[Coloma], Caselles, V.[Vicent], Igual, L.[Laura], Garrido, L.[Luis],
Level Lines Selection with Variational Models for Segmentation and Encoding,
JMIV(27), No. 1, January 2007, pp. 5-27.
Springer DOI 0702
BibRef

Cremers, D.[Daniel], Rousson, M.[Mikael], Deriche, R.[Rachid],
A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape,
IJCV(72), No. 2, April 2007, pp. 195-215.
Springer DOI Or:
PDF File. 0702
BibRef

Chaudhury, K.N.[Kunal N.], Ramakrishnan, K.R.,
Stability and convergence of the level set method in computer vision,
PRL(28), No. 7, May 2007, pp. 884-893.
Elsevier DOI 0703
Level-set method; Tracking; Curve evolution; Difference equation; Numerical stability; Courant-Friedrichs-Levy condition BibRef

Gelas, A., Bernard, O., Friboulet, D., Prost, R.,
Compactly Supported Radial Basis Functions Based Collocation Method for Level-Set Evolution in Image Segmentation,
IP(16), No. 7, July 2007, pp. 1873-1887.
IEEE DOI 0707

See also Variational B-Spline Level-Set: A Linear Filtering Approach for Fast Deformable Model Evolution. BibRef

Fredj, S.B.[Sarra Ben], Glatard, T.[Tristan], Casta, C.[Christopher], Clarysse, P.[Patrick],
An exploration framework for segmentation parameter spaces,
ICIP11(2257-2260).
IEEE DOI 1201
BibRef

Gelas, A., Schaerer, J., Bernard, O., Friboulet, D., Clarysse, P., Magnin, I.E., Prost, R.,
Radial Basis Functions Collocation Methods for Model Based Level-Set Segmentation,
ICIP07(II: 237-240).
IEEE DOI 0709
BibRef

de Santis, A.[Alberto], Iacoviello, D.[Daniela],
A discrete level set approach to image segmentation,
SIViP(1), No. 4, October 2007, pp. 303-320.
Springer DOI 0711
BibRef

de Santis, A.[Alberto], Iacoviello, D.[Daniela],
Discrete image modelling for piecewise constant segmentation by artificial neural networks,
IET-IPR(2), No. 1, February 2008, pp. 37-47.
DOI Link 0905
BibRef

Fan, D.,
Level-set image segmenation software,
Online2002.
WWW Link. Code, Segmentation. BibRef 0200

Chen, Q.A.[Qi-Ang], Luo, J.[Jian], Heng, P.A.[Pheng Ann], Xia, D.S.[De-Shen],
Fast and active texture segmentation based on orientation and local variance,
JVCIR(18), No. 2, April 2007, pp. 119-129.
Elsevier DOI 0711
Texture segmentation; Orientation and local variance; Separability; Nonlinear diffusion; Level set; Active image segmentation
See also Two-Stage Object Tracking Method Based on Kernel and Active Contour. BibRef

Cao, G.[Guo], Mao, Z.H.[Zhi-Hong], Yang, X.[Xin], Xia, D.S.[De-Shen],
Optical aerial image partitioning using level sets based on modified Chan-Vese model,
PRL(29), No. 4, 1 March 2008, pp. 457-464.
Elsevier DOI 0711
Optical aerial image; Image partitioning; Level sets; Chan-Vese model
See also Active contours without edges. BibRef

Hsu, C.Y.[Chih-Yu], Yang, C.H.[Chih-Hung], Wang, H.C.[Hui-Ching],
Topological control of level set method depending on topology constraints,
PRL(29), No. 4, 1 March 2008, pp. 537-546.
Elsevier DOI 0711
Image processing; Segmentation; Geometric active contour; Level set method BibRef

Shi, Y.G.[Yong-Gang], Karl, W.C.[W. Clem],
A Real-Time Algorithm for the Approximation of Level-Set-Based Curve Evolution,
IP(17), No. 5, May 2008, pp. 645-656.
IEEE DOI 0804
BibRef
Earlier:
Real-Time Tracking Using Level Sets,
CVPR05(II: 34-41).
IEEE DOI 0507
BibRef

Ségonne, F.[Florent],
Active Contours Under Topology Control: Genus Preserving Level Sets,
IJCV(79), No. 2, August 2008, pp. xx-yy.
Springer DOI 0711
BibRef

Ségonne, F.[Florent], Pons, J.P.[Jean-Philippe], Grimson, W.E.L.[W. Eric L.], Fischl, B.[Bruce],
Active Contours Under Topology Control Genus Preserving Level Sets,
CVBIA05(135-145).
Springer DOI 0601
BibRef
And: A1, A2, A4, A3:
A Novel Active Contour Framework. Multi-component Level Set Evolution under Topology Control,
CSAIL-2005-038, June 2005.
WWW Link. BibRef

Fablet, R., Pujolle, S., Chessel, A., Benzinou, A., Cao, F.,
2D Image-based reconstruction of shape deformation of biological structures using a level-set representation,
CVIU(111), No. 3, September 2008, pp. 295-306.
Elsevier DOI 0809
BibRef
Earlier:
Variational Level-Set Reconstruction of Accretionary Morphogenesis from Images,
ICIP06(221-224).
IEEE DOI 0610
Shape matching; Accretionary morphogenesis; Level-set representation; Inverse problem BibRef

Yip, A.M., Ding, C., Chan, T.F.,
Dynamic Cluster Formation Using Level Set Methods,
PAMI(28), No. 6, June 2006, pp. 877-889.
IEEE DOI 0605
Density based clustering. BibRef

Law, Y.N., Lee, H.K., Yip, A.M.,
A Multiresolution Stochastic Level Set Method for Mumford-Shah Image Segmentation,
IP(17), No. 12, December 2008, pp. 2289-2300.
IEEE DOI 0811
BibRef

Law, Y.N.[Yan Nei], Lee, H.K.[Hwee Kuan], Yip, A.M.[Andy M.],
Learning Dynamical Shape Prior for Level Set based Cell Tracking,
BMVA(2013), No. 1, 2013, pp. 6, 1-14.
PDF File. 1304
BibRef

Law, Y.N., Lee, H.K., Liu, C., Yip, A.M.,
A Variational Model for Segmentation of Overlapping Objects With Additive Intensity Value,
IP(20), No. 6, June 2011, pp. 1495-1503.
IEEE DOI 1106
BibRef

Law, Y.N., Lee, H.K., Ng, M.K., Yip, A.M.,
A Semisupervised Segmentation Model for Collections of Images,
IP(21), No. 6, June 2012, pp. 2955-2968.
IEEE DOI 1202
BibRef

Lau, T.S.[Tze Siong], Yip, A.M.[Andy M.],
A Fast Method for Segmenting Images with Additive Intensity Value,
SIIMS(5), No. 3 2012, pp. 993-1021.
DOI Link 1209
BibRef

Ni, K.Y.[Kang-Yu], Hong, B.W.[Byung-Woo], Soatto, S.[Stefano], Chan, T.F.[Tony F.],
Unsupervised multiphase segmentation: A recursive approach,
CVIU(113), No. 4, April 2009, pp. 502-510.
Elsevier DOI 0903
Segmentation; Scale-Space; Multiphase; Active contour; Mumford-Shah; Chan-Vese
See also Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model, A. BibRef

Badshah, N., Chen, K.[Ke],
On Two Multigrid Algorithms for Modeling Variational Multiphase Image Segmentation,
IP(18), No. 5, May 2009, pp. 1097-1106.
IEEE DOI 0904
Repeated use of Vese-Chan (
See also Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model, A. ) And a variation on multigrid. BibRef

Ali, H.[Haider], Badshah, N.[Noor], Chen, K.[Ke], Khan, G.A.[Gulzar Ali],
A variational model with hybrid images data fitting energies for segmentation of images with intensity inhomogeneity,
PR(51), No. 1, 2016, pp. 27-42.
Elsevier DOI 1601
Image segmentation BibRef

Mabood, L.[Lutful], Ali, H.[Haider], Badshah, N.[Noor], Chen, K.[Ke], Khan, G.A.[Gulzar Ali],
Active contours textural and inhomogeneous object extraction,
PR(55), No. 1, 2016, pp. 87-99.
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Implicit Active Model using Radial Basis Function Interpolated Level Sets,
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Gao, X.B.[Xin-Bo], Wang, B.[Bin], Tao, D.C.[Da-Cheng], Li, X.L.[Xue-Long],
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SMC-B(41), No. 2, April 2011, pp. 518-525.
IEEE DOI 1103

See also Zernike-Moment-Based Image Super Resolution.
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Markov processes BibRef

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Bayes methods BibRef

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Balla-Arabe, S., Gao, X.B.[Xin-Bo], Wang, B.[Bin],
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fuzzy clustering method; Image edge detection BibRef

Wang, L.[Lei], Ji, H.B.[Hong-Bing], Gao, X.B.[Xin-Bo],
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Yang, X.[Xi], Gao, X.B.[Xin-Bo], Tao, D.C.[Da-Cheng], Li, X.L.[Xue-Long],
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Tao, D.P.[Da-Peng], Guo, Y.[Yanan], Li, Y.T.[Yao-Tang], Gao, X.B.[Xin-Bo],
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face recognition, feature extraction, image representation, spectral analysis, tensors, TRPDA algorithm, rank preserving BibRef

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Saliency Cut in Stereo Images,
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image segmentation BibRef

Balla-Arabe, S., Gao, X.B.[Xin-Bo], Wang, B.[Bin],
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Markov processes BibRef

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Level set; adaptive regularization; bias field; image segmentation BibRef

Andersson, T.[Thord], Läthén, G.[Gunnar], Lenz, R.[Reiner], Borga, M.[Magnus],
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A Fast Optimization Method for Level Set Segmentation,
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Active geodesics: Region-based active contour segmentation with a global edge-based constraint,
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Earlier:
Fully Isotropic Fast Marching Methods on Cartesian Grids,
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Earlier: ECCV10(VI: 71-83).
Springer DOI 1009
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Li, C., Wang, X., Eberl, S., Fulham, M., Feng, D.,
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Level set; distribution; segmentation BibRef

Kasaiezadeh, A.[Alireza], Khajepour, A.[Amir],
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Image segmentation BibRef

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Dong, F.F.[Fang-Fang], Chen, Z.S.[Zeng-Si], Wang, J.W.[Jin-Wei],
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Image segmentation BibRef

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Segmentation BibRef

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Statistical Shape Analysis of Neuroanatomical Structures via Level-Set-based Shape Morphing,
SIIMS(7), No. 3, 2014, pp. 1645-1668.
DOI Link 1410
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Statistical Shape Analysis for Population Studies via Level-Set Based Shape Morphing,
NORDIA12(I: 42-51).
Springer DOI 1210
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Wang, X.F.[Xiao-Feng], Min, H.[Hai], Zou, L.[Le], Zhang, Y.G.[Yi-Gang],
A novel level set method for image segmentation by incorporating local statistical analysis and global similarity measurement,
PR(48), No. 1, 2015, pp. 189-204.
Elsevier DOI 1410
Image segmentation BibRef

Min, H.[Hai], Jia, W.[Wei], Wang, X.F.[Xiao-Feng], Zhao, Y.[Yang], Hu, R.X.[Rong-Xiang], Luo, Y.T.[Yue-Tong], Xue, F.[Feng], Lu, J.T.[Jing-Ting],
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PR(48), No. 4, 2015, pp. 1547-1562.
Elsevier DOI 1502
Image segmentation BibRef

Xu, Z.[Zhi], Huang, T.Z.[Ting-Zhu], Wang, H.[Hui], Wang, C.L.[Chuan-Long],
Variant of the region-scalable fitting energy for image segmentation,
JOSA-A(32), No. 3, March 2015, pp. 463-470.
DOI Link 1503
Digital image processing; Image detection systems Variant of Level Set. BibRef

Wang, Y.G.[Yu-Gang], Huang, T.Z.[Ting-Zhu], Wang, H.[Hui],
Region-based active contours with cosine fitting energy for image segmentation,
JOSA-A(32), No. 11, November 2015, pp. 2237-2246.
DOI Link 1512
Digital image processing; Image detection systems BibRef

Korfiatis, V.C.[Vasileios Ch.], Asvestas, P.A.[Pantelis A.], Matsopoulos, G.K.[George K.],
Automatic local parameterization of the Chan Vese active contour model's force coefficients using edge information,
JVCIR(29), No. 1, 2015, pp. 71-78.
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Geometric active contours
See also Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model, A. BibRef

Dubrovina-Karni, A.[Anastasia], Rosman, G.[Guy], Kimmel, R.[Ron],
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PAMI(37), No. 8, August 2015, pp. 1585-1601.
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Active Contours for Multi-region Image Segmentation with a Single Level Set Function,
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Active contours BibRef

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Gaussian distribution BibRef

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Image segmentation, Nonhomogeneous media, Level set, Adaptation models, Robustness, Estimation, TV, Image segmentation, image denoising BibRef

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Segmentation-based tracking BibRef

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Zhou, X.[Xue], Li, X.[Xi], Hu, W.,
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Cyber(46), No. 7, July 2016, pp. 1498-1510.
IEEE DOI 1606
Adaptation models BibRef

Zhou, X.[Xue], Li, X.[Xi], Chin, T.J.[Tat-Jun], Suter, D.[David],
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ICIP12(409-412).
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Shahvaran, Z.[Zahra], Kazemi, K.[Kamran], Helfroush, M.S.[Mohamad Sadegh],
Simultaneous vector-valued image segmentation and intensity nonuniformity correction using variational level set combined with Markov random field modeling,
SIViP(10), No. 5, May 2016, pp. 887-893.
Springer DOI 1608
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Alarcon-Ramirez, A., Rwebangira, M.R., Chouikha, M.F., Manian, V.,
A New Methodology Based on Level Sets for Target Detection in Hyperspectral Images,
GeoRS(54), No. 9, September 2016, pp. 5385-5396.
IEEE DOI 1609
geophysical image processing BibRef

He, K.[Kun], Wang, D.[Dan], Zhang, X.[Xu],
Image segmentation using the level set and improved-variation smoothing,
CVIU(152), No. 1, 2016, pp. 29-40.
Elsevier DOI 1609
Image segmentation BibRef

Balla-Arabé, S.[Souleymane], Gao, X.B.[Xin-Bo], Ginhac, D.[Dominique], Brost, V.[Vincent], Yang, F.[Fan],
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Active contours BibRef

Abdelsamea, M.M.[Mohammed M.],
A semi-automated system based on level sets and invariant spatial interrelation shape features for Caenorhabditis elegans phenotypes,
JVCIR(41), No. 1, 2016, pp. 314-323.
Elsevier DOI 1612
Level sets BibRef

Vakili, N.[Nima], Rezghi, M.[Mansoor], Hosseini, S.M.[S. Mohammad],
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Active contour BibRef

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Active contours BibRef

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Springer DOI 1704
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Mesadi, F., Cetin, M., Tasdizen, T.,
Disjunctive Normal Parametric Level Set With Application to Image Segmentation,
IP(26), No. 6, June 2017, pp. 2618-2631.
IEEE DOI 1705
BibRef
Earlier:
Disjunctive normal level set: An efficient parametric implicit method,
ICIP16(4299-4303)
IEEE DOI 1610
image representation, image segmentation, set theory, shape recognition, Bayesian framework, DNLS, appearance model, convenient shape representation, disjunctive normal parametric level set method, energy minimization, image segmentation, irregularity formation, local region-based image segmentation, multiphase image segmentation, numerical computation, polytope union, signed distance function, topological changes, BibRef

Baxter, J.S.H.[John S. H.], Rajchl, M.[Martin], McLeod, A.J.[A. Jonathan], Yuan, J.[Jing], Peters, T.M.[Terry M.],
Directed Acyclic Graph Continuous Max-Flow Image Segmentation for Unconstrained Label Orderings,
IJCV(123), No. 3, July 2017, pp. 415-434.
Springer DOI 1706
BibRef

Rajchl, M.[Martin], Baxter, J.S.H.[John S. H.], Bae, E.[Egil], Tai, X.C.[Xue-Cheng], Fenster, A.[Aaron], Peters, T.M.[Terry M.], Yuan, J.[Jing],
Variational Time-Implicit Multiphase Level-Sets,
EMMCVPR15(278-291).
Springer DOI 1504
BibRef

Min, H.[Hai], Jia, W.[Wei], Wang, X.F.[Xiao-Feng], Zhao, Y.[Yang], Luo, Y.T.[Yue-Tong],
A polynomial piecewise constant approximation method based on dual constraint relaxation for segmenting images with intensity inhomogeneity,
PR(73), No. 1, 2018, pp. 15-32.
Elsevier DOI 1709
Level set BibRef

Wang, L.[Lei], Zhu, J.B.[Jian-Bing], Sheng, M.[Mao], Cribb, A.[Adriena], Zhu, S.C.[Shao-Cheng], Pu, J.T.[Jian-Tao],
Simultaneous Segmentation and Bias Field Estimation Using Local Fitted Images,
PR(74), No. 1, 2018, pp. 145-155.
Elsevier DOI 1711
Level set BibRef

Su, T.[Ting], She, L.H.[Li-Huang], Zhang, S.[Shi],
FBSLS model for image segmentation,
IET-IPR(12), No. 1, January 2018, pp. 126-132.
DOI Link 1712
FBSLS: fractional B-spline level set BibRef

Le, T.H.N.[T. Hoang Ngan], Quach, K.G.[Kha Gia], Luu, K.[Khoa], Duong, C.N.[Chi Nhan], Savvides, M.[Marios],
Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation,
IP(27), No. 5, May 2018, pp. 2393-2407.
IEEE DOI 1804
image segmentation, learning (artificial intelligence), least squares approximations, medical image processing, semantic segmentation BibRef

Le, T.H.N.[T. Hoang Ngan], Duong, C.N.[Chi Nhan], Han, L.[Ligong], Luu, K.[Khoa], Quach, K.G.[Kha Gia], Savvides, M.[Marios],
Deep contextual recurrent residual networks for scene labeling,
PR(80), 2018, pp. 32-41.
Elsevier DOI 1805
Recurrent network, Residual learning, Visual representation, Context modeling, Scene labeling BibRef

Ding, K.[Keyan], Xiao, L.F.[Lin-Fang], Weng, G.R.[Gui-Rong],
Active contours driven by local pre-fitting energy for fast image segmentation,
PRL(104), 2018, pp. 29-36.
Elsevier DOI 1804
Image segmentation, Active contour model, Level set method, Robust initialization, Local pre-fitting BibRef

Wang, D.W.[Deng-Wei],
Hybrid fitting energy-based fast level set model for image segmentation solving by algebraic multigrid and sparse field method,
IET-IPR(12), No. 4, April 2018, pp. 539-545.
DOI Link 1804
BibRef

Zhi, X.H.[Xu-Hao], Shen, H.B.[Hong-Bin],
Saliency driven region-edge-based top down level set evolution reveals the asynchronous focus in image segmentation,
PR(80), 2018, pp. 241-255.
Elsevier DOI 1805
Image segmentation, Level set evolution, Saliency map, Edge, SDREL BibRef

Liu, J.X.[Jia-Xing], Wen, X.B.[Xian-Bin], Meng, Q.X.[Qing-Xia], Xu, H.X.[Hai-Xia], Yuan, L.M.[Li-Ming],
Synthetic Aperture Radar Image Segmentation with Reaction Diffusion Level Set Evolution Equation in an Active Contour Model,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Wu, K.[Kan], Yu, Y.Z.[Yi-Zhou],
Automatic object extraction from images using deep neural networks and the level-set method,
IET-IPR(12), No. 7, July 2018, pp. 1131-1141.
DOI Link 1806
BibRef

Yang, T.J.[Tie-Jun], Chen, Y.W.[Yao-Wen], Fan, Z.[Zhun],
Vegetation segmentation based on variational level set using multi-channel local wavelet texture and color,
SIViP(12), No. 5, July 2018, pp. 951-958.
WWW Link. 1806
BibRef

Cheng, D.S.[Dan-Song], Tian, F.[Feng], Liu, L.[Lin], Liu, X.F.[Xiao-Fang], Jin, Y.[Ye],
Image segmentation based on multi-region multi-scale local binary fitting and Kullback-Leibler divergence,
SIViP(12), No. 5, July 2018, pp. 895-903.
Springer DOI 1806
BibRef

Liu, Y.[Yang], He, C.J.[Chuan-Jiang], Wu, Y.F.[Yong-Fei], Ren, Z.M.[Ze-Min],
The L0-regularized discrete variational level set method for image segmentation,
IVC(75), 2018, pp. 32-43.
Elsevier DOI 1807
Image segmentation, Level set, Variational model, -based regularizer BibRef

Min, H., Jia, W., Zhao, Y., Zuo, W., Ling, H., Luo, Y.,
LATE: A Level-Set Method Based on Local Approximation of Taylor Expansion for Segmenting Intensity Inhomogeneous Images,
IP(27), No. 10, October 2018, pp. 5016-5031.
IEEE DOI 1808
approximation theory, concave programming, image segmentation, intensity inhomogeneous image segmentation, nonlinear description BibRef

Wan, M.J.[Min-Jie], Gu, G.H.[Guo-Hua], Sun, J.H.[Jian-Hong], Qian, W.X.[Wei-Xian], Ren, K.[Kan], Chen, Q.[Qian], Maldague, X.[Xavier],
A Level Set Method for Infrared Image Segmentation Using Global and Local Information,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Liu, G.Q.[Guo-Qi], Zou, J.[Jian],
Level set evolution with sparsity constraint for object extraction,
IET-IPR(12), No. 8, August 2018, pp. 1413-1422.
DOI Link 1808
BibRef

Zhu, H.Q.[Hong-Qing], Xie, Q.Y.[Qun-Yi],
A multiphase level set formulation for image segmentation using a MRF-based nonsymmetric Student's-t mixture model,
SIViP(12), No. 8, November 2018, pp. 1577-1585.
WWW Link. 1809
BibRef

Rahmat, R.[Roushanak], Harris-Birtill, D.[David],
Comparison of level set models in image segmentation,
IET-IPR(12), No. 12, December 2018, pp. 2212-2221.
DOI Link 1812
BibRef

Yang, Y.Y.[Yun-Yun], Jia, W.J.[Wen-Jing], Yang, Y.[Yunna],
Multi-atlas segmentation and correction model with level set formulation for 3D brain MR images,
PR(90), 2019, pp. 450-463.
Elsevier DOI 1903
Level set formulation, Multi-atlas label fusion, Tissue segmentation, Bias correction, MR images BibRef

Liu, C.[Cheng], Liu, W.B.[Wei-Bin], Xing, W.W.[Wei-Wei],
A weighted edge-based level set method based on multi-local statistical information for noisy image segmentation,
JVCIR(59), 2019, pp. 89-107.
Elsevier DOI 1903
Noisy image segmentation, Active contour model, Level set method, Weighted coefficients, Edge stop function BibRef

Min, H.[Hai], Xia, L.[Li], Han, J.W.[Jun-Wei], Wang, X.F.[Xiao-Feng], Pan, Q.Q.[Qian-Qian], Fu, H.[Hao], Wang, H.Z.[Hong-Zhi], Wong, S.T.C.[Stephen T.C.], Li, H.[Hai],
A multi-scale level set method based on local features for segmentation of images with intensity inhomogeneity,
PR(91), 2019, pp. 69-85.
Elsevier DOI 1904
Intensity inhomogeneity, Level set, Local maximum description difference, Multi-scale BibRef

Wang, D.W.[Deng-Wei],
Efficient level-set segmentation model driven by the local GMM and split Bregman method,
IET-IPR(13), No. 5, 18 April 2019, pp. 761-770.
DOI Link 1904
BibRef

Lv, H.L.[Hong-Li], Fu, S.J.[Shu-Jun], Zhang, C.M.[Cai-Ming], Liu, X.[Xuya],
Non-local weighted fuzzy energy-based active contour model with level set evolution starting with a constant function,
IET-IPR(13), No. 7, 30 May 2019, pp. 1115-1123.
DOI Link 1906
BibRef

Yang, L.[Ling], Fu, Y.Q.[Yuan-Qi], Wang, Z.K.[Zhong-Ke], Zhen, X.Q.[Xiao-Qiong], Yang, Z.P.[Zhi-Peng], Fan, X.G.[Xin-Gang],
An Optimized Level Set Method Based on QPSO and Fuzzy Clustering,
IEICE(E102-D), No. 5, May 2019, pp. 1065-1072.
WWW Link. 1906
BibRef

Cai, Q.[Qing], Liu, H.Y.[Hui-Ying], Qian, Y.M.[Yi-Ming], Zhou, S.P.[San-Ping], Duan, X.J.[Xiao-Jun], Yang, Y.H.[Yee-Hong],
Saliency-guided level set model for automatic object segmentation,
PR(93), 2019, pp. 147-163.
Elsevier DOI 1906
Level set model, Object segmentation, Visual saliency, Graph cuts, Automatic initialization BibRef

Huang, G.P.[Guo-Peng], Ji, H.B.[Hong-Bing], Zhang, W.B.[Wen-Bo], Zhu, Z.G.[Zhi-Gang],
Adaptive multilayer level set method for segmenting images with intensity inhomogeneity,
IET-IPR(13), No. 10, 22 August 2019, pp. 1714-1724.
DOI Link 1909
BibRef

Huang, G.H.[Guang-Hui], Qian, J.L.[Jian-Liang],
Analysis of Regularized Kantorovich-Rubinstein Metric and Its Application to Inverse Gravity Problems,
SIIMS(12), No. 3, 2019, pp. 1528-1560.
DOI Link 1911
Level-set based inverse gravity problems BibRef

Huang, B.X.[Bao-Xiang], Pan, Z.K.[Zhen-Kuan], Yang, H.[Huan], Bai, L.[Li],
Variational level set method for image segmentation with simplex constraint of landmarks,
SP:IC(82), 2020, pp. 115745.
Elsevier DOI 2001
Image segmentation, Point landmarks, Simplex constraint, Alternating direction method of multipliers, Variational level set method BibRef

Wei, Z.W.[Zi-Wei], Qiao, Y.L.[Yu-Long], Lu, X.[Xiao],
Heat diffusion embedded level set evolution for infrared image segmentation,
IET-IPR(14), No. 2, February 2020, pp. 267-278.
DOI Link 2001
BibRef

Zhang, P., Liu, W., Lei, Y., Wang, H., Lu, H.,
Deep Multiphase Level Set for Scene Parsing,
IP(29), 2020, pp. 4556-4567.
IEEE DOI 2003
Level set, Semantics, Image segmentation, Feature extraction, Active contours, Machine learning, DSL, Semantic scene parsing, object boundary estimation BibRef

Falcone, M.[Maurizio], Paolucci, G.[Giulio], Tozza, S.[Silvia],
A High-Order Scheme for Image Segmentation via a Modified Level-Set Method,
SIIMS(13), No. 1, 2020, pp. 497-534.
DOI Link 2004
BibRef

Eliasof, M.[Moshe], Sharf, A.[Andrei], Treister, E.[Eran],
Multimodal 3D Shape Reconstruction under Calibration Uncertainty Using Parametric Level Set Methods,
SIIMS(13), No. 1, 2020, pp. 265-290.
DOI Link 2004
BibRef

Wang, X.H.[Xiang-Hai], Zhao, X.Y.[Xiao-Yang], Zhu, Y.H.[Yi-Huan], Su, X.[Xin],
NSST and vector-valued C-V model based image segmentation algorithm,
IET-IPR(14), No. 8, 19 June 2020, pp. 1614-1620.
DOI Link 2005
NSST: non-subsampled shearlet transform. Chan-Vese.
See also Active contours without edges. BibRef

Alves, W.A.L.[Wonder A.L.], Gobber, C.F.[Charles F.], Silva, D.J.[Dennis J.], Morimitsu, A.[Alexandre], Hashimoto, R.F.[Ronaldo F.], Marcotegui, B.[Beatriz],
Image segmentation based on ultimate levelings: From attribute filters to machine learning strategies,
PRL(133), 2020, pp. 264-271.
Elsevier DOI 2005
Residual morphological operator, Ultimate levelings, Ultimate attribute openings, Ultimate grain filters, Morphological trees BibRef

Zhang, W., Wang, X., Chen, J., You, W.,
A New Hybrid Level Set Approach,
IP(29), 2020, pp. 7032-7044.
IEEE DOI 2007
Level set, Image segmentation, Computational modeling, Image edge detection, Nonhomogeneous media, Optimization, energy weight constraint BibRef