Machine learning-based Alzheimer’s disease Designation (MAD)
This SPM extension evaluates whether the given brain FDG PET images “look like” an Alzheimer’s disease (AD) patient’s or not (non-AD).
The brain FDG PET images must be already pre-processed (normalized and smoothed with [8 8 8]mm Gaussian filter) using SPM12 (with “old normalize” routine on to a PET template). Please note that the original study was conducted without structural MRI co-registration.
The program computes subject scores and labels (AD vs. non-AD) estimated by 5 different algorithms described in [1].
1. General Linear Model
2. Scaled Subprofile Modeling - single principal component
3. Scaled Subprofile Modeling - linearly regressed principal components
4. Support Vector Machine – Iterative Single Data Algorithm
5. Support Vector Machine – Sequential Minimal Optimization
The package contains MAT file (~1GB). Please contact us for further instructions on how to download the software package.
Requirement: SPM12 must be installed running on MATLAB (with statistics toolbox).
Disclaimer:
The Software and code samples available on this website are provided "as is" without warranty of any kind, either express or implied. Use at your own risk.
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