nibabel.nicom.dwiparams¶
Process diffusion imaging parameters
q
is a vector in Q spaceb
is a b valueg
is the unit vector along the direction of q (the gradient direction)
Thus:
b = norm(q)
g = q / norm(q)
(norm(q)
is the Euclidean norm of q
)
The B matrix B
is a symmetric positive semi-definite matrix. If
q_est
is the closest q vector equivalent to the B matrix, then:
B ~ (q_est . q_est.T) / norm(q_est)
Functions
|
Estimate q vector from input B matrix B |
|
Least squares positive semi-definite tensor estimation |
|
Return b value and q unit vector from q vector q_vector |