Data structures and network algorithms
Data structures and network algorithms
Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
Introduction to algorithms
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Graphical Models and Image Processing
Scale-based fuzzy connected image segmentation: theory, algorithms, and validation
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Algorithm 360: shortest-path forest with topological ordering [H]
Communications of the ACM
Composition of Image Analysis Processes Through Object-Centered Hierarchical Planning
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Image Foresting Transform: Theory, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous fuzzy segmentation of multiple objects
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
Vectorial scale-based fuzzy-connected image segmentation
Computer Vision and Image Understanding
Iterative relative fuzzy connectedness for multiple objects with multiple seeds
Computer Vision and Image Understanding
Automatic Image Segmentation by Tree Pruning
Journal of Mathematical Imaging and Vision
Three-dimensional segmentation of tumors from CT image data using an adaptive fuzzy system
Computers in Biology and Medicine
Vectorial scale-based fuzzy-connected image segmentation
Computer Vision and Image Understanding
Simultaneous fuzzy segmentation of multiple objects
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
A three-level graph based interactive volume segmentation system
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Fuzzy segmentation of color video shots
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
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Image segmentation techniques using fuzzy connectedness principles have shown their effectiveness in segmenting a variety of objects in several large applications in recent years. However, one problem with these algorithms has been their excessive computational requirements. In an attempt to substantially speed them up, in the present paper, we study systematically a host of 18 'optimal' graph search algorithms. Extensive testing of these algorithms on a variety of 3D medical images taken from large ongoing applications demonstrates that a 20-1000-fold improvement over current speeds is achievable with a combination of algorithms and fast modern PCs. Utilizing efficient algorithms and careful selection of implementations can speed up the computation of fuzzy connectedness values by a factor of 16-29 (on the same hard-ware), as compared to the implementation previously used in our applications utilizing fuzzy object segmentation. The optimality of an algorithm depends on the input data as well as on the choice of the fuzzy affinity relation. The running time is reduced considerably (by a factor up to 34 for brain MR and even more for bone CT), when the algorithms make use of pre-determined thresholds for the fuzzy objects. The reliable recognition (assisted by human operators) and the accurate, efficient, and sophisticated delineation (automatically performed by the computer) can be effectively incorporated into a single interactive process. If images having intensities with tissue-specific meaning (such as CT or standardized MR images) are utilized, most of the parameters for the segmentation method can be fixed once for all, all intermediate data (feature and fuzzy affinity values for the whole scene) can be computed before the user interaction is needed and the user can be provided with more information at the time of interaction.