- Title
- Rapid and automatic atlas-based approach of alzheimer's disease assessment by positron emission tomography neuroimages
- Creator
- Qian, Guoyu; Shen, Xuezhen; Luo, Suhuai; Jin, Jesse S.; Nowinski, Wieslaw L.
- Relation
- 9th IEEE International Conference on Cognitive Informatives (ICCI 2010). Proceedings of the 9th IEEE International Conference on Cognitive Informatives (ICCI 2010) (Beijing, China 7-9 July, 2010) p. 375-382
- Publisher Link
- http://dx.doi.org/10.1109/COGINF.2010.5599709
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2010
- Description
- Current Alzheimer’s disease diagnosis and cognitive assessment are based on medical history assessment and evaluation of cognitive score systems. They are time-consuming and subjective. A rapid and automated method is developed by processing positron emission tomography neuroimages and performing statistical analysis. The brain areas are firstly extracted from the neuroimages by an atlas-assisted approach, and then transformed piecewise into a common atlas space by dividing the brain into 18 cubic regions based on the landmarks identified automatically. The statistical models of stepwise regressions and discriminant classification are applied to predict the cognitive scores and make a diagnosis on Alzheimer’s disease or mild cognitive impairment. The proposed method is fully automatic and has been tested on 400 cases. The preliminary testing results are promising. For a group of 250 cases which are the samples of the regressions and discriminant classification, the success rates of disease diagnosis are 73.7%, 54.9%, and 79.7% for the patients with Alzheimer’s disease, mild cognitive impairment, and normal subjects, respectively. The average success rate for another group of 150 cases is 61.3%.
- Subject
- image processing; brain atlas; biostatistics
- Identifier
- http://hdl.handle.net/1959.13/927137
- Identifier
- uon:10055
- Identifier
- ISBN:9781424480401
- Rights
- Copyright © 2010 IEEE. Reprinted from the Proceedings of the 9th IEEE International Conference on Cognitive Informatives. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Language
- eng
- Full Text
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