def rename_reshape_pdt2_scans(quar_dir, is_whicap_V1=False, is_whicap_V2=False , is_whicap_V3=False):
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if is_whicap_V2:
for path in nifti_paths:
if os.path.basename(path).startswith('x'):
os.unlink(path)
continue
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if len(nifti_paths) == 1:
shape = getshape(nifti_paths[0])
if shape[3] != 2:
raise Bad_Nifti_Error(path, "DWI Nifti has {} timepoints but should have 2".format(shape[3]))
split = fslsplit()
split.split(nifti_paths[0], os.path.join(quar_dir, 'pdt2sp_'))
splits1 = [os.path.join(quar_dir, "pdt2sp_{0:04d}.nii.gz".format(x)) for x in range(0, 30)]
os.unlink(nifti_paths[0])
return
elif len(nifti_paths) == 3:
sizes = [(x, os.stat(x).st_size) for x in nifti_paths]
sizes.sort(key=lambda x :x[1])
os.unlink(sizes[2][0])
elif len(nifti_paths) == 2:
return
else:
raise Wrong_Number_Of_Files_Error(quar_dir, "Wrong number of DWI files left after pruning stage, expected 1, got {}".format(len(nifti_paths)))
def rename_reshape_dwi_scans(quar_dir, is_whicap_V1=False, is_whicap_V2=False , is_whicap_V3=False):
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if is_whicap_V1:
for path in nifti_paths:
if os.path.basename(path).startswith('x'):
os.unlink(path)
continue
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if len(nifti_paths) == 1:
shape = getshape(nifti_paths[0])
if shape[3] != 5 and shape[3] != 2:
raise Bad_Nifti_Error(path, "DWI Nifti has {} timepoints but should have 2 or 5".format(shape[3]))
return
else:
raise Wrong_Number_Of_Files_Error(quar_dir, "Wrong number of DWI files left after pruning stage, expected 1, got {}".format(len(nifti_paths)))
if is_whicap_V2:
for path in nifti_paths:
if os.path.basename(path).startswith('x'):
os.unlink(path)
continue
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if len(nifti_paths) == 1:
shape = getshape(nifti_paths[0])
if shape[3] != 5 and shape[3] != 2:
raise Bad_Nifti_Error(path, "DWI Nifti has {} timepoints but should have 2 or 5".format(shape[3]))
return
else:
raise Wrong_Number_Of_Files_Error(quar_dir, "Wrong number of DWI files left after pruning stage, expected 1, got {}".format(len(nifti_paths)))
if is_whicap_V3:
if len(nifti_paths) == 1:
shape = getshape(nifti_paths[0])
if shape[3] != 2:
raise Bad_Nifti_Error(path, "DWI Nifti has {} timepoints but should have 2".format(shape[3]))
return
elif len(nifti_paths) == 2:
for path in nifti_paths:
if os.path.basename(path).startswith('x'):
os.unlink(path)
continue
shape = getshape(path)
if len(shape) < 4 or shape[3] != 2: #delete files that only have 1 image, should have two
os.unlink(path)
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if len(nifti_paths) == 0:
raise Wrong_Number_Of_Files_Error(quar_dir, "Wrong number of DWI files left after pruning stage, expected 1, got {}".format(len(nifti_paths)))
def rename_reshape_pdt2_scans(quar_dir,
is_whicap_V1=False,
is_whicap_V2=False,
is_whicap_V3=False):
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if is_whicap_V2:
for path in nifti_paths:
if os.path.basename(path).startswith('x'):
os.unlink(path)
continue
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if len(nifti_paths) == 1:
shape = getshape(nifti_paths[0])
if shape[3] != 2:
raise Bad_Nifti_Error(
path,
"DWI Nifti has {} timepoints but should have 2".format(
shape[3]))
split = fslsplit()
split.split(nifti_paths[0], os.path.join(quar_dir, 'pdt2sp_'))
splits1 = [
os.path.join(quar_dir, "pdt2sp_{0:04d}.nii.gz".format(x))
for x in range(0, 30)
]
os.unlink(nifti_paths[0])
return
elif len(nifti_paths) == 3:
sizes = [(x, os.stat(x).st_size) for x in nifti_paths]
sizes.sort(key=lambda x: x[1])
os.unlink(sizes[2][0])
elif len(nifti_paths) == 2:
return
else:
raise Wrong_Number_Of_Files_Error(
quar_dir,
"Wrong number of DWI files left after pruning stage, expected 1, got {}"
.format(len(nifti_paths)))
def rename_reshape_dti_scans(quar_dir, is_whicap_V3=False):
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if is_whicap_V3:
if len(nifti_paths) == 1:
shape = getshape(nifti_paths[0])
if shape[3] != 17:
raise Bad_Nifti_Error(path, "DTI Nifti has {} timepoints but should have 17".format(shape[3]))
return
elif len(nifti_paths) == 2:
for path in nifti_paths:
if os.path.basename(path).startswith('x'):
os.unlink(path)
continue
shape = getshape(path)
if len(shape) < 4 or shape[3] != 17: #delete files that only have 1 image, should have two
os.unlink(path)
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if len(nifti_paths) == 0:
raise Wrong_Number_Of_Files_Error(quar_dir, "Wrong number of DWI files left after pruning stage, expected 1, got {}".format(len(nifti_paths)))
def rename_reshape_asl_scans(quar_dir, is_whicap_V2=False):
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if len(nifti_paths) == 2:
if is_whicap_V2:
return
else:
raise Wrong_Number_Of_Files_Error(
series_folder.path,
"Wrong number of ASL files to reshape and not whicap, expected 1, got {}"
.format(len(nifti_paths)))
elif len(nifti_paths) == 1:
if is_whicap_V2:
shape = getshape(nifti_paths[0])
if shape[3] > 60:
raise Bad_Nifti_Error(
quar_dir,
"nifti has {} timepoints, expected 60".format(shape[3]))
if shape[2] == 15:
reshapeASL(nifti_paths[0], z_voxel_size_multiplier=0.5)
os.unlink(nifti_paths[0])
else:
split = fslsplit()
merge = fslmerge()
split.split(nifti_paths[0], os.path.join(quar_dir, 'aslsp_'))
splits1 = [
os.path.join(quar_dir, "aslsp_{0:04d}.nii.gz".format(x))
for x in range(0, 30)
]
splits2 = [
os.path.join(quar_dir, "aslsp_{0:04d}.nii.gz".format(x))
for x in range(30, 60)
]
merge.merge(os.path.join(quar_dir, 'ASLOne.nii.gz'), splits1)
merge.merge(os.path.join(quar_dir, 'ASLTwo.nii.gz'), splits2)
[os.unlink(file) for file in splits1]
[os.unlink(file) for file in splits2]
os.unlink(nifti_paths[0])
else:
reshapeASL(nifti_paths[0], z_voxel_size_multiplier=1)
os.unlink(nifti_paths[0])
else:
raise Wrong_Number_Of_Files_Error(
quar_dir,
"dcm2nii produced {} nifti paths, expected 1 or 2".format(
len(nifti_paths)))
def move_non_niftis(series_folder, folder_name):
'bvecs and bvals'
visit = series_folder.image.visit
quar_dir = os.path.join(visit.path, 'Quarantine')
target_folder = os.path.join(visit.path, folder_name)
reconed_files = os.listdir(quar_dir)
if not os.path.exists(target_folder):
os.mkdir(target_folder)
my_non_niftis = [x for x in reconed_files if not is_nifti(x)]
for i in range(0, len(my_non_niftis)):
old_name_fullpath = os.path.join(quar_dir, my_non_niftis[i])
extension = os.path.splitext(old_name_fullpath)[1]
new_name_fullpath = os.path.join(target_folder, visit.image_basename(series_folder.image.series) + extension)
if os.path.exists(new_name_fullpath):
os.unlink(new_name_fullpath)
shutil.move(old_name_fullpath, new_name_fullpath)
def check_recon_dicom_folder(series_folder, dcm2nii_object, folder_name,
expected_image_quantity):
reconstructed_image_quantity = -1
number_paths_to_generate = expected_image_quantity
if expected_image_quantity < 0:
reconstructed_image_quantity = recon_into_quarantine(
series_folder, dcm2nii_object)
number_paths_to_generate = reconstructed_image_quantity
generated_nifti_paths = gen_nifti_basename_fullpaths(
series_folder, folder_name, number_paths_to_generate)
#if all niftis exist, delete all files in quarantine and exit
niftis_exist = [nifti_exists(x) for x in generated_nifti_paths]
if all(niftis_exist):
visit = series_folder.image.visit
quar_dir = os.path.join(visit.path, 'Quarantine')
if os.path.exists(quar_dir):
shutil.rmtree(quar_dir)
os.mkdir(quar_dir)
return
#reconstruct into nifti if we havn't already
elif reconstructed_image_quantity < 0: #not reconstructed into quarantine before
reconstructed_image_quantity = recon_into_quarantine(
series_folder, dcm2nii_object)
#check that number of reconstructed images matches number expected
if expected_image_quantity > 0 and expected_image_quantity != reconstructed_image_quantity:
visit = series_folder.image.visit
quar_dir = os.path.join(visit.path, 'Quarantine')
reconed_files = os.listdir(quar_dir)
reconstructed_niftis = [x for x in reconed_files if is_nifti(x)]
quar_dir = os.path.join(visit.path, 'Quarantine')
raise Wrong_Number_Of_Files_Error(
quar_dir,
"Unexpected number niftis produced by reconstruction. Expected:{0} Reconstructed:{1}\nReconstructedPaths\n{2}\nExpectedBasenames\n{3}"
.format(expected_image_quantity, reconstructed_image_quantity,
'\n'.join(reconstructed_niftis),
'\n'.join(generated_nifti_paths)))
move_niftis(series_folder, folder_name, generated_nifti_paths)
move_non_niftis(series_folder, folder_name)
def move_niftis(series_folder, folder_name, expected_nifti_paths):
visit = series_folder.image.visit
quar_dir = os.path.join(visit.path, 'Quarantine')
target_folder = os.path.join(visit.path, folder_name)
reconed_files = os.listdir(quar_dir)
if not os.path.exists(target_folder):
os.mkdir(target_folder)
myniftis = [x for x in reconed_files if is_nifti(x)]
myniftis.sort()
for i in range(0, len(expected_nifti_paths)):
old_name_fullpath = os.path.join(quar_dir, reconed_files[i])
extension = get_nifti_extension(old_name_fullpath)
new_name_fullpath = os.path.join(quar_dir, expected_nifti_paths[i] + extension)
if os.path.exists(new_name_fullpath):
os.unlink(new_name_fullpath)
shutil.move(old_name_fullpath, new_name_fullpath)
visit.check_add_nifti(folder_name, expected_nifti_paths[i])
def move_non_niftis(series_folder, folder_name):
'bvecs and bvals'
visit = series_folder.image.visit
quar_dir = os.path.join(visit.path, 'Quarantine')
target_folder = os.path.join(visit.path, folder_name)
reconed_files = os.listdir(quar_dir)
if not os.path.exists(target_folder):
os.mkdir(target_folder)
my_non_niftis = [x for x in reconed_files if not is_nifti(x)]
for i in range(0, len(my_non_niftis)):
old_name_fullpath = os.path.join(quar_dir, my_non_niftis[i])
extension = os.path.splitext(old_name_fullpath)[1]
new_name_fullpath = os.path.join(
target_folder,
visit.image_basename(series_folder.image.series) + extension)
if os.path.exists(new_name_fullpath):
os.unlink(new_name_fullpath)
shutil.move(old_name_fullpath, new_name_fullpath)
def move_niftis(series_folder, folder_name, expected_nifti_paths):
visit = series_folder.image.visit
quar_dir = os.path.join(visit.path, 'Quarantine')
target_folder = os.path.join(visit.path, folder_name)
reconed_files = os.listdir(quar_dir)
if not os.path.exists(target_folder):
os.mkdir(target_folder)
myniftis = [x for x in reconed_files if is_nifti(x)]
myniftis.sort()
for i in range(0, len(expected_nifti_paths)):
old_name_fullpath = os.path.join(quar_dir, reconed_files[i])
extension = get_nifti_extension(old_name_fullpath)
new_name_fullpath = os.path.join(quar_dir,
expected_nifti_paths[i] + extension)
if os.path.exists(new_name_fullpath):
os.unlink(new_name_fullpath)
shutil.move(old_name_fullpath, new_name_fullpath)
visit.check_add_nifti(folder_name, expected_nifti_paths[i])
def check_recon_dicom_folder(series_folder, dcm2nii_object, folder_name, expected_image_quantity):
reconstructed_image_quantity = -1
number_paths_to_generate = expected_image_quantity
if expected_image_quantity < 0:
reconstructed_image_quantity = recon_into_quarantine(series_folder, dcm2nii_object)
number_paths_to_generate = reconstructed_image_quantity
generated_nifti_paths = gen_nifti_basename_fullpaths(series_folder, folder_name, number_paths_to_generate)
#if all niftis exist, delete all files in quarantine and exit
niftis_exist = [nifti_exists(x) for x in generated_nifti_paths]
if all(niftis_exist):
visit = series_folder.image.visit
quar_dir = os.path.join(visit.path, 'Quarantine')
if os.path.exists(quar_dir):
shutil.rmtree(quar_dir)
os.mkdir(quar_dir)
return
#reconstruct into nifti if we havn't already
elif reconstructed_image_quantity < 0: #not reconstructed into quarantine before
reconstructed_image_quantity = recon_into_quarantine(series_folder, dcm2nii_object)
#check that number of reconstructed images matches number expected
if expected_image_quantity > 0 and expected_image_quantity != reconstructed_image_quantity:
visit = series_folder.image.visit
quar_dir = os.path.join(visit.path, 'Quarantine')
reconed_files = os.listdir(quar_dir)
reconstructed_niftis = [x for x in reconed_files if is_nifti(x)]
quar_dir = os.path.join(visit.path, 'Quarantine')
raise Wrong_Number_Of_Files_Error(quar_dir, "Unexpected number niftis produced by reconstruction. Expected:{0} Reconstructed:{1}\nReconstructedPaths\n{2}\nExpectedBasenames\n{3}".format(
expected_image_quantity,
reconstructed_image_quantity,
'\n'.join(reconstructed_niftis),
'\n'.join(generated_nifti_paths)
))
move_niftis(series_folder, folder_name, generated_nifti_paths)
move_non_niftis(series_folder, folder_name)
def recon_into_quarantine(series_folder, dcm2nii_object):
print "Recon {0.path}".format(series_folder)
visit = series_folder.image.visit
studyname = visit.subject.index.project.name
#wipe contents of quarantine dir
quar_dir = os.path.join(visit.path, 'Quarantine')
if os.path.exists(quar_dir):
shutil.rmtree(quar_dir)
os.makedirs(quar_dir)
#reconstruct
dcm2nii_object.recon(input_path=series_folder.path, output_path=quar_dir)
#treat ASL scans specially
if studyname == 'WHICAP':
if visit.visid == 'V1':
if series_folder.image.series == 'DWI':
rename_reshape_dwi_scans(quar_dir, is_whicap_V1=True)
elif visit.visid == 'V2':
if series_folder.image.series == 'ASL':
rename_reshape_asl_scans(quar_dir, is_whicap_V2=True)
elif series_folder.image.series == 'DWI':
rename_reshape_dwi_scans(quar_dir, is_whicap_V2=True)
elif series_folder.image.series == 'PDT2':
rename_reshape_pdt2_scans(quar_dir, is_whicap_V2=True)
elif visit.visid == 'V3':
if series_folder.image.series == 'DWI':
rename_reshape_dwi_scans(quar_dir, is_whicap_V3=True)
elif series_folder.image.series == 'DTI_1':
rename_reshape_dti_scans(quar_dir, is_whicap_V3=True)
if series_folder.image.series == 'ASL':
rename_reshape_asl_scans(quar_dir, is_whicap_V2=False)
elif series_folder.image.series in ['pASL', 'ASL']:
rename_reshape_asl_scans(quar_dir, is_whicap_V2=False)
reconed_files = os.listdir(quar_dir)
myniftis = [x for x in reconed_files if is_nifti(x)]
return len(myniftis)
def recon_into_quarantine(series_folder, dcm2nii_object):
print "Recon {0.path}".format(series_folder)
visit = series_folder.image.visit
studyname = visit.subject.index.project.name
#wipe contents of quarantine dir
quar_dir = os.path.join(visit.path, 'Quarantine')
if os.path.exists(quar_dir):
shutil.rmtree(quar_dir)
os.makedirs(quar_dir)
#reconstruct
dcm2nii_object.recon(input_path=series_folder.path, output_path=quar_dir)
#treat ASL scans specially
if studyname == 'WHICAP':
if visit.visid == 'V1':
if series_folder.image.series == 'DWI':
rename_reshape_dwi_scans(quar_dir, is_whicap_V1=True)
elif visit.visid == 'V2':
if series_folder.image.series == 'ASL':
rename_reshape_asl_scans(quar_dir, is_whicap_V2=True)
elif series_folder.image.series == 'DWI':
rename_reshape_dwi_scans(quar_dir, is_whicap_V2=True)
elif series_folder.image.series == 'PDT2':
rename_reshape_pdt2_scans(quar_dir, is_whicap_V2=True)
elif visit.visid == 'V3':
if series_folder.image.series == 'DWI':
rename_reshape_dwi_scans(quar_dir, is_whicap_V3=True)
elif series_folder.image.series == 'DTI_1':
rename_reshape_dti_scans(quar_dir, is_whicap_V3=True)
if series_folder.image.series == 'ASL':
rename_reshape_asl_scans(quar_dir, is_whicap_V2=False)
elif series_folder.image.series in ['pASL', 'ASL']:
rename_reshape_asl_scans(quar_dir, is_whicap_V2=False)
reconed_files = os.listdir(quar_dir)
myniftis = [x for x in reconed_files if is_nifti(x)]
return len(myniftis)
def rename_reshape_asl_scans(quar_dir, is_whicap_V2=False):
files = os.listdir(quar_dir)
nifti_paths = [os.path.join(quar_dir, x) for x in files if is_nifti(x)]
if len(nifti_paths) == 2:
if is_whicap_V2:
return
else:
raise Wrong_Number_Of_Files_Error(
series_folder.path,
"Wrong number of ASL files to reshape and not whicap, expected 1, got {}".format(len(nifti_paths)),
)
elif len(nifti_paths) == 1:
if is_whicap_V2:
shape = getshape(nifti_paths[0])
if shape[3] > 60:
raise Bad_Nifti_Error(quar_dir, "nifti has {} timepoints, expected 60".format(shape[3]))
if shape[2] == 15:
reshapeASL(nifti_paths[0], z_voxel_size_multiplier=0.5)
os.unlink(nifti_paths[0])
else:
split = fslsplit()
merge = fslmerge()
split.split(nifti_paths[0], os.path.join(quar_dir, "aslsp_"))
splits1 = [os.path.join(quar_dir, "aslsp_{0:04d}.nii.gz".format(x)) for x in range(0, 30)]
splits2 = [os.path.join(quar_dir, "aslsp_{0:04d}.nii.gz".format(x)) for x in range(30, 60)]
merge.merge(os.path.join(quar_dir, "ASLOne.nii.gz"), splits1)
merge.merge(os.path.join(quar_dir, "ASLTwo.nii.gz"), splits2)
[os.unlink(file) for file in splits1]
[os.unlink(file) for file in splits2]
os.unlink(nifti_paths[0])
else:
reshapeASL(nifti_paths[0], z_voxel_size_multiplier=1)
os.unlink(nifti_paths[0])
else:
raise Wrong_Number_Of_Files_Error(
quar_dir, "dcm2nii produced {} nifti paths, expected 1 or 2".format(len(nifti_paths))
)
