Dolph et al.
Classification of Alzheimer's disease using structural MRI
C.V. Dolph, M.D.Samad, K.M. Iftekharuddin (Vision Lab, Old Dominion University, VA, USA)
Alzheimer's disease (AD) typically progresses with the atrophy of white matter along with expansion of cerebrospinal fluid. Our algorithm classifies AD using ratios of WM to CSF in horizontal slices of structural MRI.
There are 5 major steps to our algorithm: skull stripping, registration, segmentation, feature selection, and classification.
1. Skull stripping
Brainsuite  was used to extract the brain. Normally, the default diffusion parameters are used. Each extracted brain is inspected for excessive or inadequate stripping. The diffusion parameters are adjusted if necessary.
Brainsuite is used again for the segmentation into WM, GM, and CSF
4. Feature Extraction
Using an in iterative process, the best features were found to be the WM to CSF ratios from horizontal slices 25 to 70.
A SVM-RBF classifier is used to determine the class of each subject MRI.
- Shattuck DW and Leahy RM (2002) BrainSuite: An Automated Cortical Surface Identification Tool Medical Image Analysis 8(2):129-142.
- DRAMMS: Deformable registration via attribute matching and mutual-saliency weighting. Yangming Ou, Aristeidis Sotiras, Nikos Paragios, Christos Davatzikos. Medical Image Analysis, 15(4): 622-639, 2011.
- Shattuck DW, Sandor-Leahy SR, Schaper KA, Rottenberg DA, and Leahy RM (2001) Magnetic Resonance Image Tissue Classification Using a Partial Volume Model NeuroImage 13(5):856-876.
If you use this methodology, please cite:
CV Dolph, MD Samad, KM Iftekharuddin (Vision Lab, Old Dominion University, VA, USA) Classication of Alzheimer's disease using structural MRI
For questions on the method, please contact Chester Dolph: firstname.lastname@example.org