Fast and robust extraction of hippocampus from MR images for diagnostics of Alzheimer's disease

Jyrki Lötjönen (Corresponding Author), Robin Wolz, Juha Koikkalainen, Valtteri Julkunen, Lennart Thurfjell, Roger Lundqvist, Gunhild Waldemar, Hilkka Soininen, Daniel Rueckert, The Alzheimer’s Disease Neuroimaging Initiative

Research output: Contribution to journalArticleScientificpeer-review

107 Citations (Scopus)


Assessment of temporal lobe atrophy from magnetic resonance images is a part of clinical guidelines for the diagnosis of prodromal Alzheimer's disease. As hippocampus is known to be among the first areas affected by the disease, fast and robust definition of hippocampus volume would be of great importance in the clinical decision making. We propose a method for computing automatically the volume of hippocampus using a modified multi-atlas segmentation framework, including an improved initialization of the framework and the correction of partial volume effect. The method produced a high similarity index, 0.87, and correlation coefficient, 0.94, with semi-automatically generated segmentations. When comparing hippocampus volumes extracted from 1.5 T and 3 T images, the absolute value of the difference was low: 3.2% of the volume. The correct classification rate for Alzheimer's disease and cognitively normal cases was about 80% while the accuracy 65% was obtained for classifying stable and progressive mild cognitive impairment cases. The method was evaluated in three cohorts consisting altogether about 1000 cases, the main emphasis being in the analysis of the ADNI cohort. The computation time of the method is about 2 minutes on a standard laptop computer. The results show a clear potential for applying the method in clinical practice.

Original languageEnglish
Pages (from-to)185-196
Number of pages12
Issue number1
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed


  • Alzheimer's disease
  • Hippocampus
  • Segmentation
  • Atlases


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