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4_reconstruction_and_quickbundle_for_all.py
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4_reconstruction_and_quickbundle_for_all.py
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# -*- coding: utf-8 -*-
"""
Created on Wed Oct 17 16:34:20 2012
@author: bao
"""
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 1 18:58:05 2012
@author: bao
"""
import os
import numpy as np
import nibabel as nib
from dipy.reconst.dti import Tensor
#from dipy.reconst.gqi import GeneralizedQSampling
from dipy.tracking.eudx import EuDX
from dipy.io.dpy import Dpy
from dipy.external.fsl import flirt2aff,create_displacements, warp_displacements, warp_displacements_tracks
from dipy.viz import fvtk
from dipy.tracking.metrics import downsample
#==============quick bundles ===================================================
from dipy.segment.quickbundles import QuickBundles
from dipy.io.pickles import save_pickle
from dipy.data import get_sphere
tracks_filename_arr=['tracks_dti_10K_linear.dpy','tracks_dti_1M_linear.dpy','tracks_dti_3M_linear.dpy']
#,
# 'tracks_gqi_10K_linear.dpy','tracks_gqi_1M_linear.dpy','tracks_gqi_3M_linear.dpy']
qb_filename_15=['qb_dti_10K_linear_15.pkl','qb_dti_1M_linear_15.pkl','qb_dti_3M_linear_15.pkl']
#,
# 'qb_gqi_10K_linear_15.pkl','qb_gqi_1M_linear_15.pkl','qb_gqi_3M_linear_15.pkl']
qb_filename_20=['qb_dti_10K_linear_20.pkl','qb_dti_1M_linear_20.pkl','qb_dti_3M_linear_20.pkl']
#,
# 'qb_gqi_10K_linear_20.pkl','qb_gqi_1M_linear_20.pkl','qb_gqi_3M_linear_20.pkl']
qb_filename_30=['qb_dti_10K_linear_30.pkl','qb_dti_1M_linear_30.pkl','qb_dti_3M_linear_30.pkl']
#,
# 'qb_gqi_10K_linear_30.pkl','qb_gqi_1M_linear_30.pkl','qb_gqi_3M_linear_30.pkl']
def load_tracks(filename):
dpr = Dpy(filename, 'r')
tracks=dpr.read_tracks()
dpr.close()
return tracks
#=====================quick bundles ============================================
def transform_tracks(tracks,affine):
return [(np.dot(affine[:3,:3],t.T).T + affine[:3,3]) for t in tracks]
def create_save_tracks(anisotropy,indices, seeds, low_thresh,filename):
euler = EuDX(anisotropy,
ind=indices,
odf_vertices=get_sphere('symmetric362').vertices,
seeds=seeds, a_low=low_thresh)
tensor_tracks_old = [track for track in euler]
tracks = [track for track in tensor_tracks_old if track.shape[0]>1]
dpw = Dpy(filename, 'w')
dpw.write_tracks(tracks)
dpw.close()
def warp_tracks_linearly(flirt_filename,fa_filename, tracks_filename,linear_filename):
fsl_ref = '/usr/share/fsl/data/standard/FMRIB58_FA_1mm.nii.gz'
img_fa = nib.load(fa_filename)
flirt_affine= np.loadtxt(flirt_filename)
img_ref =nib.load(fsl_ref)
#create affine matrix from flirt
mat=flirt2aff(flirt_affine,img_fa,img_ref)
#read tracks
dpr = Dpy(tracks_filename, 'r')
tensor_tracks = dpr.read_tracks()
dpr.close()
#linear tranform for tractography
tracks_warped_linear = transform_tracks(tensor_tracks,mat)
#save tracks_warped_linear
dpr_linear = Dpy(linear_filename, 'w')
dpr_linear.write_tracks(tracks_warped_linear)
dpr_linear.close()
#dirname = "data_temp"
#dirname = "data/1891215/"
dirname = "ADHD"
for root, dirs, files in os.walk(dirname):
if root.endswith('DTI64_1'):
base_dir = root+'/'
filename = 'DTI64'
base_filename = base_dir + filename
nii_filename = base_dir + 'DTI/data_resample.nii.gz'
bvec_filename = base_filename + '.bvec'
bval_filename = base_filename + '.bval'
img = nib.load(nii_filename)
data = img.get_data()
affine = img.get_affine()
bvals = np.loadtxt(bval_filename)
gradients = np.loadtxt(bvec_filename).T # this is the unitary direction of the gradient
base_dir2 = base_dir+ 'DTI/'
tensors = Tensor(data, bvals, gradients, thresh=50)
create_save_tracks(tensors.fa(), tensors.ind(), 10**4, .2, base_dir2+'tracks_dti_10K.dpy')
create_save_tracks(tensors.fa(), tensors.ind(), 10**6, .2, base_dir2+'tracks_dti_1M.dpy')
create_save_tracks(tensors.fa(), tensors.ind(), 3*10**6, .2, base_dir2+'tracks_dti_3M.dpy')
#===================== gqi ========================================
# gqs=GeneralizedQSampling(data,bvals,gradients)
# create_save_tracks(gqs.qa(), gqs.ind(), 10**4, .0239, base_dir2+'tracks_gqi_10K.dpy')
# create_save_tracks(gqs.qa(), gqs.ind(), 10**6, .0239, base_dir2+'tracks_gqi_1M.dpy')
# create_save_tracks(gqs.qa(), gqs.ind(), 3*10**6, .0239, base_dir2+'tracks_gqi_3M.dpy')
#===================== gqi ========================================
print 'Done warped'
flirt_filename =base_dir2+'flirt.mat'
fa_filename= base_dir2 + 'fa_resample.nii.gz'
tracks_filename = base_dir2+'tracks_dti_10K.dpy'
linear_filename = base_dir2+'tracks_dti_10K_linear.dpy'
warp_tracks_linearly(flirt_filename,fa_filename, tracks_filename,linear_filename)
tracks_filename = base_dir2+'tracks_dti_1M.dpy'
linear_filename = base_dir2+'tracks_dti_1M_linear.dpy'
warp_tracks_linearly(flirt_filename,fa_filename, tracks_filename,linear_filename)
tracks_filename = base_dir2+'tracks_dti_3M.dpy'
linear_filename = base_dir2+'tracks_dti_3M_linear.dpy'
warp_tracks_linearly(flirt_filename,fa_filename, tracks_filename,linear_filename)
##===================== gqi ========================================
# tracks_filename = base_dir2+'tracks_gqi_10K.dpy'
# linear_filename = base_dir2+'tracks_gqi_10K_linear.dpy'
# warp_tracks_linearly(flirt_filename,fa_filename, tracks_filename,linear_filename)
#
# tracks_filename = base_dir2+'tracks_gqi_1M.dpy'
# linear_filename = base_dir2+'tracks_gqi_1M_linear.dpy'
# warp_tracks_linearly(flirt_filename,fa_filename, tracks_filename,linear_filename)
#
# tracks_filename = base_dir2+'tracks_gqi_3M.dpy'
# linear_filename = base_dir2+'tracks_gqi_3M_linear.dpy'
# warp_tracks_linearly(flirt_filename,fa_filename, tracks_filename,linear_filename)
##===================== gqi ========================================
#==============quick bundles ==================================
#dirname = "data_temp"
#dirname = "data_qb"
#for root, dirs, files in os.walk(dirname):
# if root.endswith('DIFF2DEPI_EKJ_64dirs_14'):
# base_dir = root+'/'
# filename = 'raw'
# base_dir2 = base_dir+ 'DTI/'
print base_dir+'../MPRAGE_1/T1_flirt_out.nii.gz'
img = nib.load(base_dir+'../MPRAGE_1/T1_flirt_out.nii.gz')
data = img.get_data()
for i in range(len(tracks_filename_arr)):
print '>>>>'
print base_dir2+tracks_filename_arr[i]
tracks=load_tracks(base_dir2+tracks_filename_arr[i])
print len(tracks)
#tracks = [downsample(t, 12) - np.array(data.shape[:3])/2. for t in tracks]
tracks = [downsample(t, 12) - np.array(data.shape)/2. for t in tracks]
#shift in the center of the volume
#tracks=[t-np.array(data.shape)/2. for t in tracks]
#1/0
print base_dir2+qb_filename_15[i]
qb=QuickBundles(tracks,15.,12)
save_pickle(base_dir2+qb_filename_15[i],qb)
print base_dir2+qb_filename_20[i]
qb=QuickBundles(tracks,20.,12)
save_pickle(base_dir2+qb_filename_20[i],qb)
print base_dir2+qb_filename_30[i]
qb=QuickBundles(tracks,30.,12)
save_pickle(base_dir2+qb_filename_30[i],qb)
#================ quick bundles ==============================================
print('Done')
print(linear_filename)
#stop