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PET image analysis using parametric response map for mild cognitive impairment
- Issue Date
- 2013
- Publisher
- CSREA Press
- Keywords
- Alzheimer’s disease; Image analysis; Mild cognitive impairment; Parametric response map
- Citation
- Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, v.2, pp.825 - 826
- Journal Title
- Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013
- Volume
- 2
- Start Page
- 825
- End Page
- 826
- ISSN
- 0000-0000
- Abstract
- Longitudinal neuroimaging provides important information to find changes related to advance of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). Finding changes from normal/MCI state to AD state is crucial to apply optimal treatment options depending on the progression of AD. Using PET has been widely accepted to track such changes. A novel image analysis method called parametric response map (PRM) was proposed. Here, we applied PRM to longitudinal PET images to distinguish between healthy control (HC) and converting mild cognitive impairment (cMCI) patients. cMCI patients refers to patients who converted from HC to MCI. We considered five HC and five cMCI. Our approach of using PRM yielded promising performance of distinguishing between HC and cMCI patients. © 2013 CSREA Press. All rights reserved.
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Related Researcher
- PARK, HYUN JIN
- Information and Communication Engineering (Electronic and Electrical Engineering)