Dr. Norman Scheel

Photo of Dr. Norman  Scheel


Research Associate
Michigan State University
Radiology Human Medicine Faculty
Lansing, MI
USA

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Research

 

Classification of neurodegenerative brain states based on multivariate fMRI data

 

In medicine, biomarkers associated with a specific disease are often used as diagnostic tools. In particular, the intrinsic functional organization of the human brain, assessed by resting-state fMRI, has gained increasing attention. Given the myriad of parameters of spatio-temporal fMRI-data, one major challenge in this research is to find those features that are most predictive for a given disease.

 

We use machine learning approaches on resting-state fMRI data to unravel differences in brain connectivity in different subject groups. Especiallly comparing the predictive value of fine-scale and global connectomes leads the way to standardized methods for the identification of resting-state biomarkers.

 

Publikationen

2015

  • Scheel, N., Esswanger, A., Münte, T. F., Heldmann, M., Krämer, U. M., and Mamlouk, A. M.: Selection of Seeds for Resting-State fMRI-Based Prediction of Individual Brain Maturity: Bildverarbeitung für die Medizin, Informatik aktuell, pp. 371-376, 2015
    BibTeX

2014

  • Scheel, N., Chang, C., and Mamlouk, A. M.: The importance of physiological noise regression in high temporal resolution fMRI: Artificial Neural Networks - ICANN 2014, Springer, pp. 540-547, 2014
    BibTeX