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A Framework for Level Set Segmentation of Volume Datasets

A Framework for Level Set Segmentation of Volume Datasets,Ross T. Whitaker,David E. Breen,Ken Museth,Neha Soni

A Framework for Level Set Segmentation of Volume Datasets   (Citations: 12)
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This paper presents a framework for extracting surface models from a broad variety of volumetric datasets. These datasets are produced from standard D imaging devices, and are all noisy samplings of complex biological structures with boundaries that have low and often varying contrasts. The level set segmentation method, which is well documented in the literature, creates a new volume from the input data by solving an initial-value partial differential equa- tion (PDE) with user-defined feature-extracting terms. Given the local/global nature of these terms, proper initialization of the level set algorithm is extremely important. Thus, level set deforma- tions alone are not sufficient, they must be combined with powerful initialization techniques in order to produce successful segmenta- tions. Our level set segmentation approach consists of defining a set of suitable pre-processing techniques for initialization and se- lecting/tuning different feature-extracting terms in the level set al- gorithm. This collection of techniques forms a toolkit that can be applied, under the guidance of a user, to segment a variety of vol- umetric data. Users can combine these methods in different ways and thereby access a wide range of functionalities, several of which are described in this paper and demonstrated on noisy volume data.
Conference: Volume Graphics - VG , 2001
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    • ...The majority of these methods focus on delineating the boundary curve (2D) or surface (3D) of the structure, such as using region-growing with interactive initialization [26, 30], interactive graph-cut [3, 5], interactive boundary drawing [11, 19, 21], to name a few...

    Sasakthi S. Abeysingheet al. Interactive skeletonization of intensity volumes

    • ...Many segmentation and classification algorithms are capable of producing sub-pixel accurate results, for instance level-set and random walker methods [4, 28]...
    • ...Level-set segmentations can easily be transformed into signed distance functions with respect to the segmentation boundary [28]...

    Joe Knisset al. IStar: A Raster Representation for Scalable Image and Volume Data

    • ...Given the local/global nature of these terms, level set deformations alone are not sufficient; they must be combined with powerful initialization techniques in order to produce successful segmentations [7]...

    Yongqiang Zhaoet al. Vascular Segmentation Using Level Set Method

    • ...These methods have applications in a wide range of flelds such as visualization, scientiflc computing, computer graphics, and computer vision [2, 3]. Applications in visualization include volume segmentation [4, 5, 6], surface processing [7, 8], and surface reconstruction [9, 10]...
    • ...In general we are concerned with problems that require a curvature term and simultaneously require the model to expand and contract, such as those discussed in [8, 6, 10]...

    Aaron E. Lefohnet al. Interactive Deformation and Visualization of Level Set Surfaces Using ...

    • ...In the context of volume graphics, LSM has recently been used for segmentation problems [32], and the metamorphosis of volumetric solids [4]...

    J. Andreas Bærentzenet al. Volume Sculpting Using the Level-Set Method

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