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Deformable Models and Level Sets in Image Segmentation

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Medical Image Processing

Part of the book series: Biological and Medical Physics, Biomedical Engineering ((BIOMEDICAL))

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Abstract

Segmentation is a partitioning process of an image domain into non-overlapping connected regions that correspond to significant anatomical structures. Automated segmentation of medical images is a difficult task. Images are often noisy and usually contain more than a single anatomical structure with narrow distances between organ boundaries. In addition, the organ boundaries may be diffuse. Although medical image segmentation has been an active field of research for several decades, there is no automatic process that can be applied to all imaging modalities and anatomical structures [1].

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Authors and Affiliations

  1. Surya Research and Education Center Tangerang, Tangerang, Indonesia

    Agung Alfiansyah

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  1. Agung Alfiansyah
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Correspondence to Agung Alfiansyah .

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Editors and Affiliations

  1. , Applied Physics and Medical Imaging, California State University Channel Isla, One University Drive, Camarillo, 93012, USA

    Geoff Dougherty

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Alfiansyah, A. (2011). Deformable Models and Level Sets in Image Segmentation. In: Dougherty, G. (eds) Medical Image Processing. Biological and Medical Physics, Biomedical Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9779-1_4

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