Prediction of dementia by hippocampal shape analysis

Hakim C. Achterberg, Fedde van der Lijn, Tom den Heijer, Aad van der Lugt, Monique M. B. Breteler, Wiro J. Niessen, Marleen de Bruijne

7 Citations (Scopus)

Abstract

This work investigates the possibility of predicting future onset of dementia in subjects who are cognitively normal, using hippocampal shape and volume information extracted from MRI scans. A group of 47 subjects who were non-demented normal at the time of the MRI acquisition, but were diagnosed with dementia during a 9 year follow-up period, was selected from a large population based cohort study. 47 Age and gender matched subjects who stayed cognitively intact were selected from the same cohort study as a control group. The hippocampi were automatically segmented and all segmentations were inspected and, if necessary, manually corrected by a trained observer. From this data a statistical model of hippocampal shape was constructed, using an entropy-based particle system. This shape model provided the input for a Support Vector Machine classifier to predict dementia. Cross validation experiments showed that shape information can predict future onset of dementia in this dataset with an accuracy of 70%. By incorporating both shape and volume information into the classifier, the accuracy increased to 74%.
Original languageEnglish
Title of host publicationMachine Learning in Medical Imaging : First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010. Proceedings
EditorsFei Wang, Pingkun Yan, Kenji Suzuki, Dinggang Shen
Number of pages8
PublisherSpringer
Publication date2010
Pages42-49
ISBN (Print)978-3-642-15947-3
ISBN (Electronic)978-3-642-15948-0
DOIs
Publication statusPublished - 2010
Event1st International Workshop on Machine Learning in Medical Imaging - Beijing, China
Duration: 20 Sept 201020 Sept 2010
Conference number: 1

Conference

Conference1st International Workshop on Machine Learning in Medical Imaging
Number1
Country/TerritoryChina
CityBeijing
Period20/09/201020/09/2010
SeriesLecture notes in computer science
Volume6357
ISSN0302-9743

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