Abstract #0273
3D Weighted Least Squares algorithm for Partial Volume Effect correction in ASL images
Pablo Garca-Polo 1,2 , Adrian Martn 3,4 , Virginia Mato 5 , Alicia Quirs 6 , Fernando Zelaya 7 , and Juan Antonio Hernandez-Tamames 5
1
A. A. Martinos Center for Biomedical
Imaging, Mass. General Hospital, M+Visin Advanced
Fellowship, Charlestown, Massachusetts, United States,
2
Centre
for Biomedical Technology - Universidad Politcnica de
Madrid, Pozuelo de Alarcn, Madrid, Spain,
3
Department
of Electrical Engineering and Computer Science,
Massachusetts Institute of Technology, Cambridge,
Massachusetts, United States,
4
3Applied
Mathematics, Universidad Rey Juan Carlos, Mstoles,
Madrid, Spain,
5
Department
of Electrical Technology, Universidad Rey Juan Carlos,
Mstoles, Madrid, Spain,
6
Cardiology,
Hospital Clnico San Carlos, Madrid, Spain,
7
Department
of Neuroimaging, King's College London, London, United
Kingdom
Arterial Spin Labeling (ASL) is increasingly used in
clinical studies of cerebral perfusion and has shown its
validity in measuring perfusion changes in several
neurodegenerative diseases. The main disadvantage of
this technique is the limited spatial resolution needed
to have a good SNR and the Partial volume effect (PVE)
consequence of the large voxels employed. To correct
this PVE effect and extract clean perfusion maps of only
one single tissue (GM, WM or CSF), we propose an
improvement of Asllanis 2D linear regression method,
with a 3D weighted least squares algorithm, including
weighting matrices for distance and CBF measurement
reliability.
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