Encyclopedia of Multimedia

2008 Edition
| Editors: Borko Furht

Medical Image Segmentation

Reference work entry
DOI: https://doi.org/10.1007/978-0-387-78414-4_108


Medical image segmentation refers to the segmentation of known anatomic structures from medical images.

Structures of interest include organs or parts thereof, such as cardiac ventricles or kidneys, abnormalities such as tumors and cysts, as well as other structures such as bones, vessels, brain structures etc. The overall objective of such methods is referred to as computer-aided diagnosis; in other words, they are used for assisting doctors in evaluating medical imagery or in recognizing abnormal findings in a medical image.

In contrast to generic segmentation methods, methods used for medical image segmentation are often application-specific; as such, they can make use of prior knowledge for the particular objects of interest and other expected or possible structures in the image. This has led to the development of a wide range of segmentation methods addressing specific problems in medical applications.

Some methods proposed in the literature are extensions of methods...

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  1. 1.
    V. Grau, A.U.J. Mewes, M. Alcaniz, R. Kikinis, and S.K. Warfield, “Improved Watershed Transform for Medical Image Segmentation Using Prior Information,” IEEE Transactions on Medical Imaging, Vol. 23, No. 4, April 2004, pp. 447–458.Google Scholar
  2. 2.
    M.W. Woolrich, T.E.J. Behrens, C.F. Beckmann, and S.M. Smith, “Mixture Models with Adaptive Spatial Regularization for Segmentation with an Application to FMRI Data,” IEEE Transactions on Medical Imaging, Vol. 24, No. 1, January 2005, pp. 1–11.Google Scholar
  3. 3.
    M. Mischi, A.A.C.M. Kalker, and H.H.M. Korsten, “Cardiac Image Segmentation for Contrast Agent Video Densitometry,” IEEE Transactions on Biomedical Engineering, Vol. 52, No. 2, February 2005, pp. 277–286.Google Scholar

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