def dicom_convert(population, data_dir, workspace_dir):
count = 0
for subject in population:
count += 1
print '====================================================================='
print '%s- DICOM CONVERSION for for %s' % (count, subject)
# define dicom directory for each subject
dicom_dir = os.path.join(data_dir, subject, 'DICOM')
# define desitation directory for nifti outputs
try:
os.makedirs(
os.path.join(workspace_dir, subject, 'anatomical_original'))
except OSError:
out_nifti_dir = str(
os.path.join(workspace_dir, subject, 'anatomical_original'))
out_nifti_dir = str(
os.path.join(workspace_dir, subject, 'anatomical_original'))
if not os.path.isfile(os.path.join(out_nifti_dir, 'ANATOMICAL.nii')):
# create a list of all dicoms with absolute paths for each file
dicom_list = []
for dicom in os.listdir(dicom_dir):
dicomstr = os.path.join(dicom_dir, dicom)
dicom_list.append(dicomstr)
# grab SeriesDescription and append T1 files to list
T1_list = []
print 'Reading dicom series descriptions'
for dicom in dicom_list:
try:
dcm_read = pydicom.read_file(dicom, force=True)
sequence = dcm_read.SeriesDescription
except AttributeError:
continue
if 'mp2rage_p3_602B_UNI_Images' in sequence:
T1_list.append(dicom)
# convert T1 anatomical to NIFTI with SPM
print 'Converting Dicom to Nifti for %s' % subject
spm_dicom_convert = spmu.DicomImport()
spm_dicom_convert.inputs.format = 'nii'
spm_dicom_convert.inputs.in_files = T1_list
spm_dicom_convert.inputs.output_dir = out_nifti_dir
spm_dicom_convert.run()
#rename file
for file in os.listdir(out_nifti_dir):
if file.endswith('nii'):
os.rename(
str(os.path.join(out_nifti_dir, file)),
str(os.path.join(out_nifti_dir, 'ANATOMICAL.nii')))
else:
print 'subject already processed.......moving on'
print '====================================================================='
print ''
def dicom_convert(population, data_dir, workspace_dir):
for subject in population:
print '##############################################'
print ' SPM DICOM CONVERSION for for %s' % subject
# define dicom directory for each subject
dicom_dir = os.path.join(data_dir, subject[0:4], 'RawData', subject)
# define desitation directory for nifti outputs
try:
os.makedirs(
os.path.join(workspace_dir, subject[0:4],
'anatomical_original'))
except OSError:
continue
out_nifti_dir = str(
os.path.join(workspace_dir, subject[0:4], 'anatomical_original'))
# create a list of all dicoms with absolute paths for each file
dicom_list = []
for dicom in os.listdir(dicom_dir):
dicom = os.path.join(dicom_dir, dicom)
dicom_list.append(dicom)
# grab SeriesDescription and append T1 files to list
T1_list = []
print 'reading dicom series descriptions'
for dicom in dicom_list:
try:
dcm_read = pydicom.read_file(dicom)
sequence = dcm_read.SeriesDescription
except AttributeError:
continue
if 't1_mpr_sag_short' in sequence:
T1_list.append(dicom)
else:
continue
# convert T1 anatomical to NIFTI with SPM
print 'Converting Dicom to Nifti for %s' % subject
spm_dicom_convert = spmu.DicomImport()
spm_dicom_convert.inputs.format = 'nii'
spm_dicom_convert.inputs.in_files = T1_list
spm_dicom_convert.inputs.output_dir = out_nifti_dir
spm_dicom_convert.run()
print '..................................'
#rename file
for file in os.listdir(out_nifti_dir):
if file.endswith('nii'):
os.rename(str(os.path.join(out_nifti_dir, file)),
str(os.path.join(out_nifti_dir, 'ANATOMICAL.nii')))
print ' DONE %s' % subject
print '##############################################'
print ''
def test_dicom_import():
dicom = example_data(infile='dicomdir/123456-1-1.dcm')
di = spmu.DicomImport(matlab_cmd='mymatlab')
assert_equal(di.inputs.matlab_cmd, 'mymatlab')
assert_equal(di.inputs.output_dir_struct, 'flat')
assert_equal(di.inputs.output_dir, './converted_dicom')
assert_equal(di.inputs.format, 'nii')
assert_equal(di.inputs.icedims, False)
assert_raises(TraitError, di.inputs.trait_set, output_dir_struct='wrong')
assert_raises(TraitError, di.inputs.trait_set, format='FAT')
assert_raises(TraitError, di.inputs.trait_set, in_files=['does_sfd_not_32fn_exist.dcm'])
di.inputs.in_files = [dicom]
assert_equal(di.inputs.in_files, [dicom])
def test_dicom_import():
dicom = example_data(infile='dicomdir/123456-1-1.dcm')
di = spmu.DicomImport(matlab_cmd='mymatlab')
assert di.inputs.matlab_cmd == 'mymatlab'
assert di.inputs.output_dir_struct == 'flat'
assert di.inputs.output_dir == './converted_dicom'
assert di.inputs.format == 'nii'
assert not di.inputs.icedims
with pytest.raises(TraitError):
di.inputs.trait_set(output_dir_struct='wrong')
with pytest.raises(TraitError):
di.inputs.trait_set(format='FAT')
with pytest.raises(TraitError):
di.inputs.trait_set(in_files=['does_sfd_not_32fn_exist.dcm'])
di.inputs.in_files = [dicom]
assert di.inputs.in_files == [dicom]
def test_dicom_import():
dicom = example_data(infile="dicomdir/123456-1-1.dcm")
di = spmu.DicomImport(matlab_cmd="mymatlab")
assert di.inputs.matlab_cmd == "mymatlab"
assert di.inputs.output_dir_struct == "flat"
assert di.inputs.output_dir == "./converted_dicom"
assert di.inputs.format == "nii"
assert not di.inputs.icedims
with pytest.raises(TraitError):
di.inputs.trait_set(output_dir_struct="wrong")
with pytest.raises(TraitError):
di.inputs.trait_set(format="FAT")
with pytest.raises(TraitError):
di.inputs.trait_set(in_files=["does_sfd_not_32fn_exist.dcm"])
di.inputs.in_files = [dicom]
assert di.inputs.in_files == [dicom]
def make_svs_anatomical(population, workspace, voxel_name):
for subject in population:
subject_dir = os.path.join(workspace, subject)
dicom_dir = os.path.join(subject_dir, 'DICOM')
svs_dir = os.path.join(subject_dir, 'SVS')
nifti_dir = mkdir_path(os.path.join(subject_dir, 'NIFTI'))
########## Get MP2RAGE UNI
if not os.path.isfile( os.path.join(nifti_dir, 'ANATOMICAL.nii')):
print 'Converting MP2RAGE '
dicoms = [os.path.join(dicom_dir, dicom) for dicom in os.listdir(dicom_dir)]
T1_list = []
for dicom in dicoms:
try:
dcm_read = pydicom.read_file(dicom, force=True)
sequence = dcm_read.SeriesDescription
except AttributeError:
continue
if 'mp2rage_p3_602B_UNI_Images' in sequence:
T1_list.append(dicom)
# convert T1 anatomical to NIFTI with SPM
print 'Converting Dicom to Nifti for %s' % subject
spm_dicom_convert = spmu.DicomImport()
spm_dicom_convert.inputs.format = 'nii'
spm_dicom_convert.inputs.in_files = T1_list
spm_dicom_convert.inputs.output_dir = nifti_dir
spm_dicom_convert.run()
# rename output file
os.system('mv %s/*nii %s/ANATOMICAL.nii' %(nifti_dir, nifti_dir))
# make svs mask
rda =[]
if not os.path.isfile(os.path.join(svs_dir, voxel_name, 'RDA', '.nii')):
for root, dirs, files, in os.walk(os.path.join(svs_dir, voxel_name, 'RDA'), topdown=False):
for name in files:
if 'supp' in name and 'edit1' in name:
rda.append(os.path.join(name))
if rda is []:
print 'RDA metabolite data does not exist for subject %s' % subject
T1Path = os.path.join(subject_dir, 'NIFTI' + '/')
T1Image = 'ANATOMICAL.nii'
svs_path = os.path.join(svs_dir, voxel_name, 'RDA' + '/')
svs_file = rda[0]
matlab_command = ['matlab', '--version', '8.2', '-nodesktop', '-nosplash', '-nojvm',
'-r "RDA_TO_NIFTI(\'%s\', \'%s\', \'%s\', \'%s\') ; quit;"'
% (T1Path, T1Image, svs_path, svs_file)]
subprocess.call(matlab_command)
os.system('mv %s/*Mask.nii %s' % (nifti_dir, os.path.join(svs_dir, voxel_name, 'RDA')))
os.system('mv %s/*coord.txt %s' % (nifti_dir, os.path.join(svs_dir, voxel_name, 'RDA')))