A review of atlas-based segmentation for magnetic resonance brain images

  • Authors:

  • Mariano Cabezas;Arnau Oliver;Xavier Lladó;Jordi Freixenet;Meritxell Bach Cuadra

  • Affiliations:

  • Institute of Informatics and Applications, Ed. P-IV, Campus Montilivi, University of Girona, 17071 Girona, Spain and Signal Processing Laboratory (LTS5), ícole Polytechnique Fédéral ...;Institute of Informatics and Applications, Ed. P-IV, Campus Montilivi, University of Girona, 17071 Girona, Spain;Institute of Informatics and Applications, Ed. P-IV, Campus Montilivi, University of Girona, 17071 Girona, Spain;Institute of Informatics and Applications, Ed. P-IV, Campus Montilivi, University of Girona, 17071 Girona, Spain;Department of Radiology, University Hospital Center and University of Lausanne, Switzerland and Signal Processing Laboratory (LTS5), ícole Polytechnique Fédérale de Lausanne, Switze ...

  • Venue:
  • Computer Methods and Programs in Biomedicine
  • Year:
  • 2011

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Abstract

Abstract: Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.