Fast and robust extraction of hippocampus from MR images for diagnostics of Alzheimer's disease
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Fast and robust extraction of hippocampus from MR images for diagnostics of Alzheimer's disease. / Lötjönen, Jyrki; Wolz, Robin; Koikkalainen, Juha; Julkunen, Valtteri; Thurfjell, Lennart; Lundqvist, Roger; Waldemar, Gunhild; Soininen, Hilkka; Rueckert, Daniel; Alzheimer's Disease Neuroimaging Initiative.
I: NeuroImage, Bind 56, Nr. 1, 2011, s. 185-96.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Fast and robust extraction of hippocampus from MR images for diagnostics of Alzheimer's disease
AU - Lötjönen, Jyrki
AU - Wolz, Robin
AU - Koikkalainen, Juha
AU - Julkunen, Valtteri
AU - Thurfjell, Lennart
AU - Lundqvist, Roger
AU - Waldemar, Gunhild
AU - Soininen, Hilkka
AU - Rueckert, Daniel
AU - Alzheimer's Disease Neuroimaging Initiative
N1 - Copyright © 2011 Elsevier Inc. All rights reserved.
PY - 2011
Y1 - 2011
N2 - 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 1.5T and 3T 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.
AB - 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 1.5T and 3T 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.
U2 - 10.1016/j.neuroimage.2011.01.062
DO - 10.1016/j.neuroimage.2011.01.062
M3 - Journal article
C2 - 21281717
VL - 56
SP - 185
EP - 196
JO - NeuroImage
JF - NeuroImage
SN - 1053-8119
IS - 1
ER -
ID: 34042712