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Optimal Simultaneous Multisurface and Multiobject Image Segmentation
Book chapter

Optimal Simultaneous Multisurface and Multiobject Image Segmentation

Xiaodong Wu, Mona K Garvin and Milan Sonka
Image Processing and Analysis with Graphs, pp.265-303
CRC Press, 1
2012
DOI: 10.1201/b12281-10

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Abstract

This chapter exploits the intralayer self-closure structure of the optimal single surface detection problem, and formulates it as a minimum-cost closed set problem based on a nontrivial graph transformation scheme. It explores the interlayer self-closure structure of the pairwise interacting surfaces, which again enables us to model the optimal multiple surface detection (OMSD) problem as a minimum-cost closed set problem. The chapter utilizes the weight of both graph nodes and arcs to represent the desired segmentation properties for optimal single- and multiple-surface segmentation, which can incorporate a wide spectrum of constraints into the problem formulation. It focuses on convex smoothness penalty functions that are widely used in medical image processing and in Markov Random Fields. The chapter introduces the LOGISMOS method for multiobject, multisurface segmentation. It demonstrates its functionality on a knee bone/cartilage segmentation example.
MRF Translation Operation Column Col Triangulated Mesh MR Image Femoral Cartilage Adjacent Columns Graph Construction Separation Constraints Knee Joint OCT Volume Soft Smoothness Simultaneous Segmentation Smoothness Constraints Surface Smoothness Image Segmentation Smoothness Parameters Interacting Objects Interaction Constraints Base Graph Feasible Surface Lowest Neighbor Cartilage Surfaces Surface Detection Closed Set

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