Abstract #1672
A Min-Max CRLB Optimization Approach to Scan Selection for Relaxometry
Gopal Nataraj 1 , Jon-Fredrik Nielsen 2,3 , and Jeffrey A. Fessler 1,2
1
Electrical Engineering and Computer Science,
University of Michigan, Ann Arbor, MI, United States,
2
Biomedical
Engineering, University of Michigan, Ann Arbor, MI,
United States,
3
Functional MRI Laboratory,
University of Michigan, Ann Arbor, MI, United States
We describe a CRLB-inspired min-max optimization problem
to guide scan design for relaxometry. In essence, our
method minimizes the theoretical worst-case (i.e.,
maximum) standard deviations of
T
1
and
T
2
estimates.
As an example, we first optimize two DESS acquisitions
for
T
2
relaxometry
in the brain. Our results show that predicted and
empirical
T
2
standard
deviations over WM/GM ROIs recommend similar scan
parameter combinations for precise
T
2
estimation.
We then compare a regularized
T
2
estimate
from our suggested scan protocol against one from many
acquisitions and find that much
T
2
content
in DESS is well captured with only two scans.
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