Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease

@inproceedings{Schouten2016CombiningAD,
  title={Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease},
  author={Tijn M. Schouten and Marisa Koini and Frank de Vos and Stephan Seiler and J van der Grond and Anita Lechner and Anne Hafkemeijer and Christiane M{\"o}ller and Reinhold Schmidt and Mark de Rooij and Serge A. R. B. Rombouts},
  booktitle={NeuroImage: Clinical},
  year={2016}
}
Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N… CONTINUE READING
BETA

Citations

Publications citing this paper.
SHOWING 1-10 OF 21 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-10 OF 40 REFERENCES

Automated detection of functional and structural disconnection in AD using multiple kernels SVM

  • M. Dyrba, M. Grothe, T. Kirste, S. J. Teipel
  • Hum. Brain Mapp
  • 2015
Highly Influential
8 Excerpts

Similar Papers

Loading similar papers…