A review on graph based segmentation techniques

With the enhancement of the technologies in medical sciences, it is becoming necessary to trace the object of interest, so need of boundary tracing techniques is increased. This paper provides a survey on graph based segmentation techniques which aim at extracting the boundary of object.

[1]  Jayaram K. Udupa,et al.  Segmentation of 3D objects using live wire , 1997, Medical Imaging.

[2]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[3]  Ghassan Hamarneh,et al.  3D live-wire-based semi-automatic segmentation of medical images , 2005, SPIE Medical Imaging.

[4]  Sheng Xu,et al.  Live-wire-based segmentation of 3D anatomical structures for image-guided lung interventions , 2012, Medical Imaging.

[5]  Swati Goel,et al.  ICA in Image Processing: A Survey , 2015, 2015 IEEE International Conference on Computational Intelligence & Communication Technology.

[6]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Alberto Martelli,et al.  An application of heuristic search methods to edge and contour detection , 1976, CACM.

[8]  Bülent Sankur,et al.  Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.

[9]  Alberto Martelli,et al.  Edge detection using heuristic search methods , 1972, Comput. Graph. Image Process..

[10]  Ugo Montanari,et al.  On the optimal detection of curves in noisy pictures , 1971, CACM.

[11]  Jerry L. Prince,et al.  A Survey of Current Methods in Medical Image Segmentation , 1999 .

[12]  Marie-Pierre Jolly,et al.  Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images , 2001, ICCV.

[13]  Vladimir Kolmogorov,et al.  An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision , 2001, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  J. B. Kneeland,et al.  Analysis of in vivo 3-D internal kinematics of the joints of the foot [MRI analysis] , 1998, IEEE Transactions on Biomedical Engineering.

[15]  M. Wertheimer.  Laws of organization in perceptual forms. , 1938 .

[16]  Jerry L Prince,et al.  Current methods in medical image segmentation. , 2000, Annual review of biomedical engineering.

[17]  Kannan,et al.  ON IMAGE SEGMENTATION TECHNIQUES , 2022 .

[18]  N. Senthilkumaran,et al.  Image Segmentation - A Survey of Soft Computing Approaches , 2009, 2009 International Conference on Advances in Recent Technologies in Communication and Computing.

[19]  Lu Xu,et al.  An Interactive Method Based on the Live Wire for Segmentation of the Breast in Mammography Images , 2014, Comput. Math. Methods Medicine.

[20]  P. N. Chatur,et al.  Survey on Medical Image Segmentation Methods , 2013 .

[21]  J K Udupa,et al.  New method of studying joint kinematics from three-dimensional reconstructions of MRI data. , 1996, Journal of the American Podiatric Medical Association.

[22]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[23]  Malcolm C. Pike.  Algorithm 267: random normal deviate [G5] , 1965, CACM.

[24]  Jayaram K. Udupa,et al.  An ultra-fast user-steered image segmentation paradigm: live wire on the fly , 2000, IEEE Transactions on Medical Imaging.

[25]  Ramesh C. Jain,et al.  Using Dynamic Programming for Solving Variational Problems in Vision , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Alexandre X. Falcão,et al.  User-Steered Image Segmentation Using Live Markers , 2011, CAIP.

[27]  Rachid Deriche,et al.  A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape , 2007, International Journal of Computer Vision.

[28]  Alexandre X. Falcão,et al.  Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking , 2012, IEEE Transactions on Image Processing.

[29]  Alexandre X. Falcão,et al.  Intelligent Understanding of User Input Applied to Arc-Weight Estimation for Graph-Based Foreground Segmentation , 2010, 2010 23rd SIBGRAPI Conference on Graphics, Patterns and Images.

[30]  Alexandre Xavier Falcao,et al.  Hybrid Approaches for Interactive Image Segmentation Using the Live Markers Paradigm , 2014, IEEE Transactions on Image Processing.

[31]  Filip Malmberg,et al.  A 3D Live-Wire Segmentation Method for Volume Images Using Haptic Interaction , 2006, DGCI.

[32]  Xin-She Yang,et al.  Introduction to Algorithms , 2021, Nature-Inspired Optimization Algorithms.

[33]  J. Alison Noble,et al.  Ultrasound image segmentation: a survey , 2006, IEEE Transactions on Medical Imaging.

[34]  E Stindel,et al.  3D MR image analysis of the morphology of the rear foot: application to classification of bones. , 1999, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[35]  Marie-Pierre Jolly,et al.  Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[36]  Oliver Wirjadi,et al.  Survey of 3d image segmentation methods , 2007 .

[37]  Jorge Stolfi,et al.  The image foresting transform: theory, algorithms, and applications , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[38]  Martin Urschler,et al.  The Live Wire Approach for the Segmentation of Left Ventricle Electron-Beam CT Images , 2002 .

[39]  Jayaram K. Udupa,et al.  User-Steered Image Segmentation Paradigms: Live Wire and Live Lane , 1998, Graph. Model. Image Process..

[40]  Gareth Funka-Lea,et al.  Graph Cuts and Efficient N-D Image Segmentation , 2006, International Journal of Computer Vision.

[41]  Xiaodong Wu,et al.  Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[42]  William A. Barrett,et al.  Intelligent scissors for image composition , 1995, SIGGRAPH.

[43]  I. D. Hill,et al.  Algorithm 266: pseudo-random numbers [G5] , 1965, CACM.

[44]  Alok Gupta,et al.  Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours , 1995, IEEE Trans. Pattern Anal. Mach. Intell..