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Access a cacophony of neuro-imaging file formats

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nibabel.nicom.dwiparams.B2q

Reggie -- the one

nibabel.nicom.dwiparamsΒΆ

Process diffusion imaging parameters

  • q is a vector in Q space
  • b is a b value
  • g 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

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