#!/usr/bin/python # Script for getting a 6 DOF approx to a 12 DOF standard transformation # # Mark Jenkinson # FMRIB Image Analysis Group # # Copyright (C) 2012 University of Oxford # # Part of FSL - FMRIB's Software Library # http://www.fmrib.ox.ac.uk/fsl # fsl@fmrib.ox.ac.uk # # Developed at FMRIB (Oxford Centre for Functional Magnetic Resonance # Imaging of the Brain), Department of Clinical Neurology, Oxford # University, Oxford, UK # # # LICENCE # # FMRIB Software Library, Release 5.0 (c) 2012, The University of # Oxford (the "Software") # # The Software remains the property of the University of Oxford ("the # University"). # # The Software is distributed "AS IS" under this Licence solely for # non-commercial use in the hope that it will be useful, but in order # that the University as a charitable foundation protects its assets for # the benefit of its educational and research purposes, the University # makes clear that no condition is made or to be implied, nor is any # warranty given or to be implied, as to the accuracy of the Software, # or that it will be suitable for any particular purpose or for use # under any specific conditions. Furthermore, the University disclaims # all responsibility for the use which is made of the Software. It # further disclaims any liability for the outcomes arising from using # the Software. # # The Licensee agrees to indemnify the University and hold the # University harmless from and against any and all claims, damages and # liabilities asserted by third parties (including claims for # negligence) which arise directly or indirectly from the use of the # Software or the sale of any products based on the Software. # # No part of the Software may be reproduced, modified, transmitted or # transferred in any form or by any means, electronic or mechanical, # without the express permission of the University. The permission of # the University is not required if the said reproduction, modification, # transmission or transference is done without financial return, the # conditions of this Licence are imposed upon the receiver of the # product, and all original and amended source code is included in any # transmitted product. You may be held legally responsible for any # copyright infringement that is caused or encouraged by your failure to # abide by these terms and conditions. # # You are not permitted under this Licence to use this Software # commercially. Use for which any financial return is received shall be # defined as commercial use, and includes (1) integration of all or part # of the source code or the Software into a product for sale or license # by or on behalf of Licensee to third parties or (2) use of the # Software or any derivative of it for research with the final aim of # developing software products for sale or license to a third party or # (3) use of the Software or any derivative of it for research with the # final aim of developing non-software products for sale or license to a # third party, or (4) use of the Software to provide any service to an # external organisation for which payment is received. If you are # interested in using the Software commercially, please contact Isis # Innovation Limited ("Isis"), the technology transfer company of the # University, to negotiate a licence. Contact details are: # innovation@isis.ox.ac.uk quoting reference DE/9564. import sys from sys import argv from commands import getoutput from numpy import * def usage(): print "Usage: " + argv[0] + " " print " " print " First argument is the FLIRT transform (12 DOF) from the input image to standard" print " Second argument is the output matrix which will go from the input image to standard space (6 DOF)" print " aligning the AC, the AC-PC line and the mid-sagittal plane (in order of decreasing accuracy)" sys.exit(1) if len(argv) < 2: usage() # Load in the necessary info a=loadtxt(argv[1]) # set specific AC and PC coordinates in FLIRT convention (x1=AC, x2=PC, x3=point above x1 in the mid-sag plane) x1=matrix([[91],[129],[67],[1]]) x2=matrix([[91],[100],[70],[1]]) x3=matrix([[91],[129],[117],[1]]) ainv=linalg.inv(a) # vectors v are in MNI space, vectors w are in native space v21=(x2-x1) v31=(x3-x1) # normalise and force orthogonality v21=v21/linalg.norm(v21) v31=v31-multiply(v31.T * v21,v21) v31=v31/linalg.norm(v31) tmp=cross(v21[0:3,0].T,v31[0:3,0].T).T v41=mat(zeros((4,1))) v41[0:3,0]=tmp # Map vectors to native space w21=ainv*(v21) w31=ainv*(v31) # normalise and force orthogonality w21=w21/linalg.norm(w21) w31=w31-multiply(w31.T * w21,w21) w31=w31/linalg.norm(w31) tmp=cross(w21[0:3,0].T,w31[0:3,0].T).T w41=mat(zeros((4,1))) w41[0:3,0]=tmp # setup matrix: native to MNI space r1=matrix(eye(4)) r1[0:4,0]=w21 r1[0:4,1]=w31 r1[0:4,2]=w41 r2=matrix(eye(4)) r2[0,0:4]=v21.T r2[1,0:4]=v31.T r2[2,0:4]=v41.T r=r2.T*r1.T # Fix the translation (keep AC=x1 in the same place) ACmni=x1 ACnat=ainv*x1 trans=ACmni-r*ACnat r[0:3,3]=trans[0:3] # Save out the result savetxt(argv[2],r,fmt='%14.10f')