Survey of 3d image segmentation methods

This report reviews selected image binarization and segmentation methods that have been proposed and which are suitable for the processing of volume images. The focus is on thresholding, region growing, and shape–based methods. Rather than trying to give a complete overview of the field, we review the original ideas and concepts of selected methods, because we believe this information to be important for judging when and under what circumstances a segmentation algorithm can be expected to work properly.

[1]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[2]  Françoise Peyrin,et al.  Automated 3D region growing algorithm based on an assessment function , 2002, Pattern Recognit. Lett..

[3]  Th. Hanne,et al.  Applying multiobjective evolutionary algorithms in industrial projects , 2006 .

[4]  Frank-Thomas Lentes,et al.  Three-dimensional radiative heat transfer in glass cooling processes , 1998 .

[5]  Konrad Steiner,et al.  Simulation Of The Fiber Spinning Process , 2001 .

[6]  B. Kapralos,et al.  I An Introduction to Digital Image Processing , 2022 .

[7]  M. Junk,et al.  The Finite-Volume-Particle Method for Conservation Laws , 2001 .

[8]  Horst W. Hamacher,et al.  Inverse Radiation Therapy Planning: A Multiple Objective Optimisation Approach , 1999 .

[9]  M. Schröder,et al.  Optimization of Transfer Quality in Regional Public Transit , 2006 .

[10]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

[11]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  T. W. Ridler,et al.  Picture thresholding using an iterative selection method. , 1978 .

[13]  K. Maravilla,et al.  Visualization-Based Mapping of Language Function in the Brain , 1997, NeuroImage.

[14]  Andreas Wiegmann,et al.  Explicit jump immersed interface method for virtual material design of the effective elastic moduli of composite materials , 2007, Numerical Algorithms.

[15]  Supun Samarasekera,et al.  Fuzzy Connectedness and Object Definition: Theory, Algorithms, and Applications in Image Segmentation , 1996, CVGIP Graph. Model. Image Process..

[16]  Axel Klar,et al.  A Stochastic Model for the Fiber Lay-down Process in the Nonwoven , 2006 .

[17]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[18]  Anil K. Jain,et al.  Goal-Directed Evaluation of Binarization Methods , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  S. Feth,et al.  Resampling-Methoden zur mse-Korrektur und Anwendungen in der Betriebsfestigkeit , 2007 .

[20]  James A. Sethian,et al.  Level Set Methods and Fast Marching Methods , 1999 .

[21]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[23]  J. Orlik Homogenization for viscoelasticity of the integral type with aging and shrinkage , 1998 .

[24]  Matti Pietikäinen,et al.  Adaptive document image binarization , 2000, Pattern Recognit..

[25]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[26]  Jayaram K. Udupa,et al.  Fuzzy-connected 3D image segmentation at interactive speeds , 2000, Graph. Model..

[27]  Axel Klar,et al.  A Hierarchy of Models for Multilane Vehicular Traffic I: Modeling , 1998, SIAM J. Appl. Math..

[28]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  H. W. Hamacher,et al.  Mathematical Modelling of Evacuation Problems: A State of Art , 2001 .

[30]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[31]  O. Iliev,et al.  ON THE PERFORMANCE OF CERTAIN ITERATIVE SOLVERS FOR COUPLED SYSTEMS ARISING IN DISCRETIZATION OF NON-NEWTONIAN FLOW EQUATIONS , 2004 .

[32]  A. Sarishvili,et al.  Blocked neural networks for knowledge extraction in the software development process , 2003 .

[33]  K. Steiner,et al.  A FINITE-VOLUME PARTICLE METHOD FOR COMPRESSIBLE FLOWS , 2000 .

[34]  Michel Jourlin,et al.  A new minimum variance region growing algorithm for image segmentation , 1997, Pattern Recognit. Lett..

[35]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[36]  Bernd Steinbach,et al.  Efficient texture analysis of binary images , 1998 .

[37]  Thomas S. Huang,et al.  Image processing , 1971 .

[38]  H. Knaf,et al.  Diagnosis aiding in Regulation Thermography using Fuzzy Logic , 2003 .

[39]  Luc Vincent,et al.  Morphological grayscale reconstruction in image analysis: applications and efficient algorithms , 1993, IEEE Trans. Image Process..

[40]  Kristel Michielsen,et al.  Morphological image analysis , 2000 .

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

[42]  A. Chambolle,et al.  Inverse problems in image processing and image segmentation : some mathematical and numerical aspects , 2000 .

[43]  A. Klar,et al.  A hierarchy of models for multilane vehicular traffic PART II: Numerical and stochastic investigations , 1998 .

[44]  Rheinland Pfalz,et al.  A HIERARCHY OF MODELS FOR MULTILANE VEHICULAR , 1999 .

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

[46]  Guillermo Sapiro,et al.  Minimal Surfaces Based Object Segmentation , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[47]  V.,et al.  A Spatial Thresholding Method for Image Segmentation , 2022 .

[48]  Zheng Lin,et al.  Unseeded Region Growing for 3D Image Segmentation , 2000, VIP.

[49]  W. Brent Lindquist,et al.  Image Thresholding by Indicator Kriging , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

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

[51]  Ron Kikinis,et al.  Markov random field segmentation of brain MR images , 1997, IEEE Transactions on Medical Imaging.