Image Segmentation using Deformable Modelsedited by: JM Fitzpatrick, M SonkaVol. 2 (May 2000), pp. 129-174.
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AbstractImage segmentation plays a crucial role in many medical imaging applications by automating or facilitating the delineation of anatomical structures and other regions of interest. We present herein a critical appraisal of the current status of semi-automated and automated methods for the segmentation of anatomical medical images. Current segmentation approaches are reviewed with an emphasis placed on revealing the advantages and disadvantages of these methods for medical imaging applications. The use of image segmentation in different imaging modalities is also described along with the difficulties encountered in each modality. We conclude with a discussion on the future of image segmentation methods in biomedical research. Contents 3.1 Introduction 131 3.2 Parametric deformable models 133 3.2.1 Energy minimizing formulation 134 3.2.2 Dynamic force formulation 136 3.2.3 External forces 138 3.2.4 Numerical implementation 144 3.3 Geometric deformable models 146 3.3.1 Curve evolution theory 146 3.3.2 Level set method 147 3.3.3 Speed functions 150 3.3.4 Relationship to parametric deformable models 152 3.3.5 Numerical implementation 153 3.4 Extensions of deformable models 154 3.4.1 Deformable Fourier...
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