Automated Methods for Hippocampus Segmentation: the Evolution and a Review of the State of the Art
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REVIEW
Automated Methods for Hippocampus Segmentation: the Evolution and a Review of the State of the Art Vanderson Dill & Alexandre Rosa Franco & Márcio Sarroglia Pinho
# Springer Science+Business Media New York 2014
Abstract The segmentation of the hippocampus in Magnetic Resonance Imaging (MRI) has been an important procedure to diagnose and monitor several clinical situations. The precise delineation of the borders of this brain structure makes it possible to obtain a measure of the volume and estimate its shape, which can be used to diagnose some diseases, such as Alzheimer’s disease, schizophrenia and epilepsy. As the manual segmentation procedure in three-dimensional images is highly time consuming and the reproducibility is low, automated methods introduce substantial gains. On the other hand, the implementation of those methods is a challenge because of the low contrast of this structure in relation to the neighboring areas of the brain. Within this context, this research presents a review of the evolution of automatized methods for the segmentation of the hippocampus in MRI. Many proposed methods for segmentation of the hippocampus have been published in leading journals in the medical image processing area. This paper describes these methods presenting the techniques used and quantitatively comparing the methods based V. Dill (*) : M. S. Pinho (*) School of Computer Science, PUCRS - Pontifícia Universidade Católica do Rio Grande do Sul, Building 32, Office 607, Av. Ipiranga 6681, 90619-000 Porto Alegre, RS, Brazil e-mail: [email protected] e-mail: [email protected] A. R. Franco Department of Electrical Engineering of School of Engineering; Division of Neuroscience of School of Medicine and Brain Institute of Rio Grande do Sul, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil A. R. Franco Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
on Dice Similarity Coefficient. Finally, we present an evaluation of those methods considering the degree of user intervention, computational cost, segmentation accuracy and feasibility of application in a clinical routine. Keywords Hippocampus segmentation . Magnetic resonance imaging . Neuroimaging . Segmentation methods . Medical images . Evaluation of segmentation . Alzheimer’s disease
Introduction The morphological analysis of the hippocampus is important to diagnose and monitor various clinical conditions. The shape of the hippocampus is altered in cases of Alzheimer’s disease, schizophrenia, epilepsy, and among other conditions (Van Leemput et al. 2009). The atrophy of the hippocampus has been shown to be one of the first observable characteristics for the detection of Alzheimer’s disease or Mild Cognitive Impairment (MCI), even in the early stages (Bobinski 1996). In cases of schizophrenia, the symmetry between the left and the right hippocampus is used as one of the indicators (Csernansky et al. 1998). Through the use of Magnetic Resonance Imaging (MRI), it is possible to quanti
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