Abstract #4715
Fast and fully automatic differentiation of patients with idiopathic Parkinsonian syndrome and progressive supranuclear palsy using T1-weighted MRI datasets
Nils Daniel Forkert 1 , Jan Sedlacik 2 , and Kai Boelmans 3
1
Department of Radiology, Stanford
University, Stanford, CA, United States,
2
Department
of Diagnostic and Interventional Neuroradiology,
University Medical Center Hamburg-Eppendorf, Germany,
3
Department
of Psychiatry and Psychotherapy, University Medical
Center Hamburg-Eppendorf, Germany
The differentiation of the progressive nuclear palsy (PSP)
from the idiopathic Parkinsonian syndrome (IPS) based on
clinical criteria is often difficult and high failure
rates have been reported. This work presents a fully
automatic method for the automatic differentiation of
these two neurological diseases using an atlas-based
analysis of high-resolution T1-weighted datasets for
regional brain volume determination and subsequent
classification using a support vector machine. A first
evaluation based on 78 datasets revealed that the
proposed method is capable of differentiating IPS (n=57)
and PSP patients (n=21) fully automatically in less than
10 minutes and an accuracy of 87.2%.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Click here for more information on becoming a member.
