Process diffusion imaging parameters
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
B2q(B[, tol]) | Estimate q vector from input B matrix B |
nearest_pos_semi_def(B) | Least squares positive semi-definite tensor estimation |