# Quaternion representation

## quatern_*, qoffset_*

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### nifti1.h header documentation

QUATERNION REPRESENTATION OF ROTATION MATRIX (METHOD 2) ------------------------------------------------------- The orientation of the (x,y,z) axes relative to the (i,j,k) axes in 3D space is specified using a unit quaternion [a,b,c,d], where a*a+b*b+c*c+d*d=1. The (b,c,d) values are all that is needed, since we require that a = sqrt(1.0-(b*b+c*c+d*d)) be nonnegative. The (b,c,d) values are stored in the (quatern_b,quatern_c,quatern_d) fields. The quaternion representation is chosen for its compactness in representing rotations. The (proper) 3x3 rotation matrix that corresponds to [a,b,c,d] is [ a*a+b*b-c*c-d*d 2*b*c-2*a*d 2*b*d+2*a*c ] R = [ 2*b*c+2*a*d a*a+c*c-b*b-d*d 2*c*d-2*a*b ] [ 2*b*d-2*a*c 2*c*d+2*a*b a*a+d*d-c*c-b*b ] [ R11 R12 R13 ] = [ R21 R22 R23 ] [ R31 R32 R33 ] If (p,q,r) is a unit 3-vector, then rotation of angle h about that direction is represented by the quaternion [a,b,c,d] = [cos(h/2), p*sin(h/2), q*sin(h/2), r*sin(h/2)]. Requiring a >= 0 is equivalent to requiring -Pi <= h <= Pi. (Note that [-a,-b,-c,-d] represents the same rotation as [a,b,c,d]; there are 2 quaternions that can be used to represent a given rotation matrix R.) To rotate a 3-vector (x,y,z) using quaternions, we compute the quaternion product [0,x',y',z'] = [a,b,c,d] * [0,x,y,z] * [a,-b,-c,-d] which is equivalent to the matrix-vector multiply [ x' ] [ x ] [ y' ] = R [ y ] (equivalence depends on a*a+b*b+c*c+d*d=1) [ z' ] [ z ] Multiplication of 2 quaternions is defined by the following: [a,b,c,d] = a*1 + b*I + c*J + d*K where I*I = J*J = K*K = -1 (I,J,K are square roots of -1) I*J = K J*K = I K*I = J J*I = -K K*J = -I I*K = -J (not commutative!) For example [a,b,0,0] * [0,0,0,1] = [0,0,-b,a] since this expands to (a+b*I)*(K) = (a*K+b*I*K) = (a*K-b*J). The above formula shows how to go from quaternion (b,c,d) to rotation matrix and direction cosines. Conversely, given R, we can compute the fields for the NIFTI-1 header by a = 0.5 * sqrt(1+R11+R22+R33) (not stored) b = 0.25 * (R32-R23) / a => quatern_b c = 0.25 * (R13-R31) / a => quatern_c d = 0.25 * (R21-R12) / a => quatern_d If a=0 (a 180 degree rotation), alternative formulas are needed. See the nifti1_io.c function mat44_to_quatern() for an implementation of the various cases in converting R to [a,b,c,d]. Note that R-transpose (= R-inverse) would lead to the quaternion [a,-b,-c,-d]. The choice to specify the qoffset_x (etc.) values in the final coordinate system is partly to make it easy to convert DICOM images to this format. The DICOM attribute "Image Position (Patient)" (0020,0032) stores the (Xd,Yd,Zd) coordinates of the center of the first voxel. Here, (Xd,Yd,Zd) refer to DICOM coordinates, and Xd=-x, Yd=-y, Zd=z, where (x,y,z) refers to the NIFTI coordinate system discussed above. (i.e., DICOM +Xd is Left, +Yd is Posterior, +Zd is Superior, whereas +x is Right, +y is Anterior , +z is Superior. ) Thus, if the (0020,0032) DICOM attribute is extracted into (px,py,pz), then qoffset_x = -px qoffset_y = -py qoffset_z = pz is a reasonable setting when qform_code=NIFTI_XFORM_SCANNER_ANAT. That is, DICOM's coordinate system is 180 degrees rotated about the z-axis from the neuroscience/NIFTI coordinate system. To transform between DICOM and NIFTI, you just have to negate the x- and y-coordinates. The DICOM attribute (0020,0037) "Image Orientation (Patient)" gives the orientation of the x- and y-axes of the image data in terms of 2 3-vectors. The first vector is a unit vector along the x-axis, and the second is along the y-axis. If the (0020,0037) attribute is extracted into the value (xa,xb,xc,ya,yb,yc), then the first two columns of the R matrix would be [ -xa -ya ] [ -xb -yb ] [ xc yc ] The negations are because DICOM's x- and y-axes are reversed relative to NIFTI's. The third column of the R matrix gives the direction of displacement (relative to the subject) along the slice-wise direction. This orientation is not encoded in the DICOM standard in a simple way; DICOM is mostly concerned with 2D images. The third column of R will be either the cross-product of the first 2 columns or its negative. It is possible to infer the sign of the 3rd column by examining the coordinates in DICOM attribute (0020,0032) "Image Position (Patient)" for successive slices. However, this method occasionally fails for reasons that I (RW Cox) do not understand.