def start_process(self):
"""starts the process linked to the module selected; that is in case of dcm2nii it runs the extraction of nifti-
files from the DICOM folder or in case of displayN4corr it displays all nifti files available in the folder"""
input2process = []
[
input2process.append(self.mOutput.item(x).text())
for x in range(self.mOutput.count())
]
if not input2process:
Output.msg_box(
text="At least one folder with data must be selected!",
title='No directory selected')
elif len(input2process) != 0 and self.option_gui == 'dcm2niix':
print('in total, {} folders were selected'.format(
len(input2process)))
preprocDCM2NII.PreprocessDCM(input2process)
elif len(
input2process) != 0 and self.option_gui == 'displayNiftiFiles':
input_with_path = []
[
input_with_path.extend(
glob.glob(self.working_dir + '/**/' + x, recursive=True))
for x in input2process
]
Imaging.load_imageviewer(
'itk-snap', input_with_path
) # to-date, only itk-snap available. could be changed
def save_cfg_dicomdir(self):
"""Function intended to save the DICOM directory once button is pressed"""
self.cfg['folders']['dicom'] = self.working_dir
Configuration.save_config(self.cfg['folders']["rootdir"], self.cfg)
Output.msg_box(
text="Folder changed in the configuration file to {}".format(
self.working_dir),
title='Changed folder')
def start_converting(self):
folderlist = []
[folderlist.append(self.mOutput.item(x).text()) for x in range(self.mOutput.count())]
print('in total, {} folders were selected'.format(len(folderlist)))
if not folderlist:
Output.msg_box(text="At least one folder with DICOM data needed!", title="No directory selected")
else:
preprocDCM2NII.PreprocessDCM(folderlist)
def view_template(self):
"""this function opens a list dialog and enables selecting NIFTI files for e.g. check the content (identical
function as in GUITabPreprocessANTs.py."""
if not self.selected_subj_Gen:
Output.msg_box(text="No image selected. Please indicate image(s) to load.", title="No templates selected")
return
else:
template_list = [FileOperations.return_full_filename(self.wdirTemplate, x) for x in self.selected_subj_Gen]
Imaging.load_imageviewer('itk-snap', template_list) # to-date, only itk-snap available. could be changed
def wrapper_multiprocessing(self, fileIDs, subjects, modality):
"""To avoid redundancy between CT and MR registration to common space, this part is wrapped up here """
working_dir = self.cfg['folders']['nifti']
prefix = '{}2template'.format(modality)
# Start multiprocessing framework
start_multi = time.time()
status = mp.Queue()
processes = [
mp.Process(target=self.ANTsCoregisterMultiprocessing,
args=(filename_fixed, filename_moving, no_subj,
os.path.join(working_dir, no_subj),
'registration', prefix, status))
for filename_fixed, filename_moving, no_subj in fileIDs
]
for p in processes:
p.start()
while any([p.is_alive() for p in processes]):
while not status.empty():
filename_fixed, filename_moving, no_subj = status.get()
print("\tRegistering {} (f) to {} (m), in ANTsPy\n".format(
filename_fixed,
os.path.split(filename_moving)[1], no_subj))
time.sleep(0.1)
for p in processes:
p.join()
# Functions creating/updating pipeline log, which documents all steps along with settings
for subjID in subjects:
files_processed = [(os.path.split(file_moving)[1],
os.path.split(file_fixed)[1])
for file_fixed, file_moving, subj_no in fileIDs
if subj_no == subjID]
log_text = "{} successfully registered (@{}) to \n{}, \n\n Mean Duration per subject: {:.2f} " \
"secs".format(files_processed[0][0], time.strftime("%Y%m%d-%H%M%S"), files_processed[0][1],
(time.time() - start_multi) / len(subjects))
Output.logging_routine(text=Output.split_lines(log_text),
cfg=self.cfg,
subject=str(subjID),
module='{}-Registration'.format(modality),
opt=self.cfg['preprocess']['registration'],
project="")
print(
'\nIn total, a list of {} subject(s) was processed; {} registration took {:.2f}secs. '
'overall'.format(len(subjects), modality,
time.time() - start_multi))
def run_n4Bias_corr(self):
"""wrapper to start the preprocessing, that is the GUI in which the different options for ANTs routines
are displayed"""
if not self.selected_subj_ANT:
Output.msg_box(text="No folder selected. To proceed, please indicate what folder to process. "
"(For this option, numerous folders are possible for batch processing)",
title="No subject selected")
else:
msg = "Are you sure you want to de-bias all NIFTI-files in the following folder(s):\n\n" \
"{}".format(''.join('--> {}\n'.format(c) for c in self.selected_subj_ANT))
ret = QMessageBox.question(self, "Start Debiasing", msg, QMessageBox.Yes | QMessageBox.No, QMessageBox.Yes)
if ret == QMessageBox.Yes:
N4BiasCorr.BiasCorrection().N4BiasCorrection(subjects=self.selected_subj_ANT)
def save_leadModel(lead_models,
intensityProfiles,
skelSkalms,
filename=''):
if not filename:
Output.msg_box(text='No filename for saving lead model provided',
title='No filename provided')
return
with open(filename, "wb") as f:
pickle.dump(lead_models, f)
pickle.dump(intensityProfiles, f)
pickle.dump(skelSkalms, f)
def redefineDefault(self):
"""redefines which template is set as default on the right list and in the cfg-file"""
if not self.selected_subj_Gen:
Output.msg_box(text="No template selected. Please indicate new default one.", title="No data selected")
return
elif len(self.selected_subj_Gen) > 1:
Output.msg_box(text="Please select only one image as default.", title="Too many templates selected")
return
else:
default_template = [FileOperations.return_full_filename(self.wdirTemplate, x) for x in self.selected_subj_Gen]
self.cfg['folders']['default_template'] = default_template[0]
Configuration.save_config(ROOTDIR, self.cfg)
self.run_reload_files()
def run_RegisterMRI2template(self):
"""Wrapper to run the coregistration routines for the MRI (moving image) to MRI templates (fixed image)
specified in the config file using ANTs routines"""
if not self.selected_subj_ANT:
Output.msg_box(text="No folder selected. To proceed, please indicate what folder to process. "
"(For this option, numerous folders are possible for batch processing)",
title="No subject selected")
else:
msg = "Are you sure you want to coregister the preoperative imaging in the following folders:\n\n" \
"{}".format(''.join(' -> {}\n'.format(c) for c in self.selected_subj_ANT))
ret = QMessageBox.question(self, 'MessageBox', msg,
QMessageBox.Yes | QMessageBox.No, QMessageBox.Yes)
if ret == QMessageBox.Yes:
ANTspyRoutines.RegistrationANTs().CoregisterMRI2template(subjects=self.selected_subj_ANT)
def display_nifti_files(self):
"""this function enables to select NIFTI files and e.g. compare the results obtained at this step."""
if not self.selected_subj_ANT:
Output.msg_box(text="No folder selected. Please select subject.", title="No subject selected")
return
elif len(self.selected_subj_ANT) > 1:
Output.msg_box(text="Please select only one subject to avoid loading too many images",
title="Too many subjects selected")
return
else:
image_folder = os.path.join(self.cfg['folders']['nifti'], self.selected_subj_ANT[0])
self.SelectFiles = TwoListGUI(working_directory=image_folder, option_gui="displayNiftiFiles")
self.SelectFiles.show()
def CoregisterMRI2template(self, subjects):
"""Co-Registration of preoperative MRI to specific template"""
print('\nStarting Co-Registration for {} subject(s)'.format(
len(subjects)))
all_files = FileOperations.get_filelist_as_tuple(
inputdir=self.cfg['folders']['nifti'], subjects=subjects)
sequences = self.cfg['preprocess']['normalisation']['sequences'].split(
sep=',') # sequences of interest
template = glob.glob(
os.path.join(
ROOTDIR, 'ext', 'templates',
self.cfg['preprocess']['normalisation']['template_image'] +
'/*'))
fileIDs = []
for idx, seqs in enumerate(sequences):
file_template = [
x for x in template
if re.search(r'\w+.({}).'.format(seqs), x, re.IGNORECASE)
] # corresponding template
if not file_template:
Output.msg_box(
text=
"No template found. Please ensure templates are installed at './ext/templates'",
title="Template missing!"
) # TODO install templates by default!
return
regex_complete = '{}{}'.format(
self.cfg['preprocess']['ANTsN4']['prefix'], seqs)
files_subj = [
x for x in all_files
if x[0].endswith('.nii') and 'run' not in x[0]
and re.search(r'\w+(?!_).({}).'.format(regex_complete), x[0],
re.IGNORECASE)
]
fileIDs.extend(
tuple([(file_template[0], file_id, subj)
for file_id, subj in files_subj]))
if not fileIDs:
Output.msg_box(
text="No bias-corrected MRI found. Please double-check",
title="Preprocessed MRI missing")
return
self.wrapper_multiprocessing(fileIDs, subjects, 'MRI')
def check_for_complete_input(self, item_list, modalities = ['CT', 'MRI']):
"""this function ensures, that only those subjects are displayed where MRI and CT data is available in the
correct folders (surname_nameMRI or surname_nameCT)"""
available_subjects = set([re.split(r'CT|MRI', x)[0] for x in list(item_list)])
item_list_complete = []
[item_list_complete.append(subj) for subj in list(available_subjects) if
all([os.path.isdir(os.path.join(self.dicomdir, subj + y)) for y in modalities])]
if len(available_subjects) != len(item_list_complete):
incomplete = list(set(available_subjects) - set(item_list_complete))
Output.msg_box(text="There is incomplete data or directories have unknown names. Please ensure the presence"
" of two folders (surname_nameCT) and (surname_nameMRI) for:"
"\n{}".format(''.join(' -> {}\n'.format(c) for c in incomplete)),
title="Incomplete data")
return set(item_list_complete)
def run_RegisterCT2MRI(self):
"""Wrapper to run the coregistration routines for the CT (moving image) to the T1-sequence of the MRI
(fixed image) using ANTs routines"""
if not self.selected_subj_ANT:
Output.msg_box(text="No folder selected. To proceed, please indicate what folder to process. "
"(For this option, numerous folders are possible for batch processing)",
title="No subject selected")
else:
msg = "Are you sure you want to coregister the postoperative CT imaging in the following folders:\n\n" \
"{}".format(''.join(' -> {}\n'.format(c) for c in self.selected_subj_ANT))
ret = QMessageBox.question(self, 'MessageBox', msg,
QMessageBox.Yes | QMessageBox.No, QMessageBox.Yes)
if ret == QMessageBox.Yes:
ANTspyRoutines.RegistrationANTs().CoregisterCT2MRI(subjects=self.selected_subj_ANT,
input_folder=self.cfg['folders']['nifti'])
def RegisterCT2MRI():
text = "Runs registration of CT imaging (moving) and T1-sequence (fixed) in order to get them into same space. " \
"The default option (see cfg-file) constitutes three steps: a) Rigid, b) Affine registration and c) " \
"Symmetric image Normalisation (SyN). For details see 'SyNRA'-option at " \
"https://github.com/ANTsX/ANTsPy/blob/master/ants/registration/interface.py. Non-default means, that the " \
"command-line for running ANTsRegistration can be modified according to the file: " \
"cmdline_ANTsRegistration.txt in the .utils directory. Please make sure to include all terms within *...* " \
"into the text-file as they will be replaced."
return Output.split_lines(text)
def run_ManualCorrection(self):
"""wrapper which starts the plotting routine for the detected lead which enables manual corrections"""
if len(self.selected_subj_ANT) != 1:
Output.msg_box(text="Please select one and only one subject",
title="Subjects selected")
return
else:
msg = "Are you sure you want to process the following subject:\n\n" \
"{}".format(''.join(' -> {}\n'.format(c) for c in self.selected_subj_ANT))
ret = QMessageBox.question(self, 'MessageBox', msg,
QMessageBox.Yes | QMessageBox.No,
QMessageBox.Yes)
if ret == QMessageBox.Yes:
plotElecModel.PlotRoutines(subject=self.selected_subj_ANT[0],
inputfolder=os.path.join(
self.niftidir,
self.selected_subj_ANT[0]))
def RegisterMRI2template():
text = "Runs registration of MR-imaging (moving) to template sequences (fixed) as defined in the config file in " \
"order to get them into same space. The default option constitutes three steps: a) Rigid, " \
"b) Affine registration and c) Symmetric image Normalisation (SyN), although all options available in ANTsPy" \
"are possible (for details see https://github.com/ANTsX/ANTsPy/blob/master/ants/registration/interface.py. " \
"Non-default means, that the command-line for running ANTsRegistration can be modified according to " \
"the file: cmdline_ANTsRegistration.txt in the .utils directory. Please make sure to include all terms " \
"within *...* into the text-file as they will be replaced."
return Output.split_lines(text)
def run_LeadDetectionPaCER(self):
"""wrapper to start lead detection with PaCER routines translated to python; original data can be found at:
https://github.com/adhusch/PaCER/"""
if len(self.selected_subj_ANT) > 1:
Output.msg_box(
text=
"Please select only one subject, as multiprocessing for lead detection is not intended",
title="Too many subjects selected")
return
else:
msg = "Are you sure you want to process the following subject:\n\n" \
"{}".format(''.join(' -> {}\n'.format(c) for c in self.selected_subj_ANT))
ret = QMessageBox.question(self, 'MessageBox', msg,
QMessageBox.Yes | QMessageBox.No,
QMessageBox.Yes)
if ret == QMessageBox.Yes:
LeadDetectionRoutines.PaCER_script(
subjects=self.selected_subj_ANT)
def VisualiseLeadDetection(self):
"""wrapper to start comparisons between pre- and post-processed images after N4BiasCorrection"""
if not self.selected_subj_ANT:
Output.msg_box(
text=
"No folder selected. To proceed, please select at least one.",
title="No subject selected")
return
elif len(self.selected_subj_ANT) > 1:
Output.msg_box(text="Please select only one subj.",
title="Too many subjects selected")
return
else:
image_folder = os.path.join(self.cfg['folders']['nifti'],
self.selected_subj_ANT[0])
self.SelectFiles = TwoListGUI(working_directory=image_folder,
option_gui='displayNiftiFiles')
self.SelectFiles.show()
def get_default_lead(lead_data):
"""obtains default lead properties according to the model proposed in the PaCER algorithm @ ./template"""
if lead_data[
'model'] == 'Boston Vercise Directional': # load mat-file to proceed
mat_filename = 'boston_vercise_directed.mat'
lead_model = loadmat(
os.path.join(ROOTDIR, 'ext', 'LeadDBS', mat_filename),
'r')['electrode']
default_positions = {
x: np.hstack(vals)
for x, vals in lead_model.items() if x.endswith('position')
}
default_coordinates = np.array(lead_model['coords_mm']) # in [mm]
else:
Output.msg_box(text="Lead type not yet implemented.",
title="Lead type not implemented")
return
return lead_model, default_positions, default_coordinates
def openDetails(self):
"""opens details file which has additional information on subjects """
import subprocess
fileName = os.path.join(self.cfg['folders']['nifti'],
'subjdetails.csv')
if os.path.isfile(fileName):
if sys.platform == 'linux':
subprocess.Popen(['xdg-open', ''.join(fileName)])
else:
os.system('open"%s"' % fileName)
subprocess.run(['open', fileName], check=True)
else:
Output.msg_box(
text="Subject details unavailable, creating empty csv-file!",
title="Detail file not found")
subprocess.call([
'touch',
'{}subjdetails.csv'.format(self.cfg['folders']['nifti'])
])
def CoregisterCT2MRI(self,
subjects,
input_folder,
fixed_image='reg_run[0-9]_bc_t1'):
"""Co-registration of postoperative CT to preoperative MRI for further analyses in same space; before registration
presence of registered MRI data is ensured to avoid redundancy"""
print('\nStarting co-registration for {} subject(s)'.format(
len(subjects)))
allfiles = FileOperations.get_filelist_as_tuple(inputdir=input_folder,
subjects=subjects)
self.check_for_normalisation(subjects)
regex_complete = ['CT_', '{}_'.format(fixed_image.upper())]
included_sequences = [
x for x in list(
filter(re.compile(r"^(?!~).*").match, regex_complete))
]
file_ID_CT, file_ID_MRI = ([] for _ in range(2))
[
file_ID_CT.append(x) for x in allfiles
if 'run' not in x[0] and re.search(
r'\w+{}.'.format(included_sequences[0]), x[0], re.IGNORECASE)
and x[0].endswith('.nii')
]
[
file_ID_MRI.append(x) for x in
allfiles # for simplicity written in a second line as regexp is slightly different
if re.search(r'\w+(?!_).({}).'.format(included_sequences[1]), x[0],
re.IGNORECASE) and x[0].endswith('.nii')
]
if not file_ID_MRI:
Output.msg_box(text="Bias-corrected MRI not found!",
title="Preprocessed MRI unavailable")
return
fileIDs = list(FileOperations.inner_join(file_ID_CT, file_ID_MRI))
self.wrapper_multiprocessing(fileIDs, subjects, 'CT')
def __init__(self, _folderlist):
self.logfile = True
self.cfg = Configuration.load_config(ROOTDIR)
self.DCM2NIIX_ROOT = os.path.join(ROOTDIR, 'ext', 'dcm2niix')
if not os.path.isdir(self.cfg['folders']['dicom']):
Output.msg_box(
text="Please indicate a correct folder in the main GUI",
title="Wrong folder")
else:
self.inputdir = self.cfg['folders']['dicom']
subjlist = self.create_subjlist(_folderlist)
if not os.path.isdir(self.DCM2NIIX_ROOT):
Output.msg_box(
text=
"Extracting imaging data from DICOM-files not successful because of wrong "
"folder for 'dcm2niix'.",
title="Wrong folder!")
return
if not os.path.isdir(self.cfg['folders']['nifti']):
print(
"\nDirectory for output is invalid; assuming same base and creating folder named 'nifti' therein!"
)
self.outdir = os.path.join(
os.path.split(self.inputdir)[0], 'nifti')
if not os.path.isdir(self.outdir):
os.mkdir(self.outdir)
else:
self.outdir = self.cfg['folders']['nifti']
lastsubj = self.get_index_nifti_folders(
self.outdir, prefix=self.cfg['folders']['prefix'])
self.create_csv_subjlist(subjlist, int(lastsubj))
self.convert_dcm2nii(subjlist, last_idx=int(lastsubj))
def load_leadModel(inputdir, filename):
"""Function loading results from [preprocLeadCT.py] which emulates the PaCER toolbox"""
if not inputdir:
Output.msg_box(
text="No input folder provided, please double-check!",
title="Missing input folder")
return
elif not os.path.isfile(filename):
Output.msg_box(
text=
"Models for electrode unavailable, please run detection first!",
title="Models not available")
return
else:
with open(
filename, "rb"
) as model: # roughly ea_loadreconstruction in the LeadDBS script
lead_models = pickle.load(model)
intensityProfiles = pickle.load(model)
skelSkalms = pickle.load(model)
return lead_models, intensityProfiles, skelSkalms
def show_nifti_files(self):
"""this function opens a list dialog and enables selecting NIFTI files for e.g. check the content (identical
function as in GUITabPreprocessANTs.py."""
if not self.selected_subj_Gen:
Output.msg_box(
text=
"No folder selected. To proceed, please indicate what folder to process.",
title="No subject selected")
return
elif len(self.selected_subj_Gen) > 1:
Output.msg_box(
text=
"Please select only one folder to avoid excessive image load",
title="Number of selected files")
return
else:
image_folder = os.path.join(self.cfg['folders']['nifti'],
self.selected_subj_Gen[0])
self.SelectFiles = TwoListGUI(working_directory=image_folder,
option_gui='displayNiftiFiles')
self.SelectFiles.show()
def get_settings_from_config(self):
"""function which enters the settings according to cfg variable which is loaded"""
if self.cfg == "":
print()
Output.msg_box(
title="Warning",
text=
"No default settings found, please double check the folder content. "
"Continuing with same settings.")
else:
if self.cfg["preprocess"]["dcm2nii"]["BIDSsidecar"] == 'yes':
self.rbtnBIDSy.setChecked(True)
else:
self.rbtnBIDSn.setChecked(True)
if self.cfg["preprocess"]["dcm2nii"]["OutputCompression"] == 'yes':
self.rbtnCompressiony.setChecked(True)
else:
self.rbtnCompressionn.setChecked(True)
if self.cfg["preprocess"]["dcm2nii"]["Verbosity"] == 0:
self.rbtnVerbosity0.setChecked(True)
elif self.cfg["preprocess"]["dcm2nii"]["Verbosity"] == 1:
self.rbtnVerbosity1.setChecked(True)
else:
self.rbtnVerbosity2.setChecked(True)
self.lineEditFilename.setText(
self.cfg["preprocess"]["dcm2nii"]["OutputFileStruct"])
self.lineEditIncludeFiles.setText(
self.cfg["preprocess"]["dcm2nii"]["IncludeFiles"])
if self.cfg["preprocess"]["dcm2nii"]["ReorientCrop"] == 'yes':
self.rbtnReorientCropy.setChecked(True)
else:
self.rbtnReorientCropn.setChecked(True)
def LabelFilenameDCM2NII():
text = "Please enter here the prefix/file information that should be included when saving NIFTI files. " \
"Characters such as '<', '>', ':', '/' ... MUST be avoided (default is %p_%s). " \
"From documentation:\n\t %a : antenna (coil) number inserted. For example, the output filename" \
" 'myName%a' would generate 'myName1', 'myName2', each for each coil. Note that most scans combine data " \
"from all coils and in these cases this option is ignored. For example, most scans which combine " \
"data from all coils would simply be called 'myName'\n\t%d :" \
"series description (0008,103E) inserted. For example, an echo-planar image " \
"converted with 'myName%d' would yield 'myNameEPI' \n\t%e : echo number " \
"inserted. For example, a sequence with two echo times converted with the output" \
"filename 'myName%e' will yield 'myName1' and 'myName2'. Note that most MRI" \
" sequences only use a single echo time, and in these cases you would only get " \
"'myName1'.\n\t%f : input folder name inserted. For example, the output " \
"filename'myName%f' combined with an input folder '/usr/Subj22' will result in " \
"the output file named'myNameSubj22.nii' \n\t%i : patient ID " \
"(DICOM tag 0010,0020) inserted. For example, the output filename 'myName%i' " \
" would convert an image where the patient ID is named 'ID123' to be " \
" 'myNameID123.nii' \n\t%m : manufacturer name For example, the output filename" \
" 'myName%m' would convert an image from a GE scanner to 'myNameGE.nii', while " \
" an image from Philips would be 'myNamePh.nii', whereas Siemens would be " \
" 'myNameSi.nii', otherwise the manufacturer is not available ('myNameNA.nii')." \
" (requires dcm2nii versions from 2015 or later). \n\t%n : subject name (DICOM" \
" tag 0010,0010) inserted. For example, the output filename 'myName%n' would " \
" convert an image from John Doe to 'myNameJohnDoe.nii'. This option works best" \
" if your participant names use only English letters, for other European " \
" languages you may find it makes some basic conversions ('Müller' will become " \
" 'Muller'). For non-European languages you will find this option unsatisfactory" \
". Perhaps future versions can support DICOM tag 0008,0005. \n\t %p: protocol" \
" name (DICOM tag 0018,1030) inserted. For example, the output filename" \
" 'myName%p' would convert image where protocol is named T1 to be 'myNameT1.nii'" \
" \n\t%q: sequence name (DICOM tag 0018,1020) inserted.For example," \
" the output filename 'myName%q' would convert a Spin Echo sequence to be " \
"'myNameSE.nii' (new feature, in versions from 30Aug2015).\n\t%s : series (DICOM " \
"tag 0020,0011) inserted. For example, the output filename 'myName%s' would " \
"convert the second series to be 'myName2.nii'. If you want to zero-pad the " \
"series number, insert the number of digits desired (0..9). For example applying " \
"the filter 'm%s' when converting 11 series will create files that will cause" \
" problems for a simple alphabetical sort, e.g. 'm1.nii,m11.nii,m2.nii...m9.nii'." \
" In contrast specifying 'm%3s' will help sorting (e.g. 'm001.nii,m002.nii" \
"...m011.nii').\n\t%t : session date and time inserted (DICOM tags 0008,0021 and " \
"0008,0030). For example, the output filename 'myName%t' would convert an image " \
"where the session began at 1:23pm on 13 Jan 2014 as 'myName20140113132322.nii' " \
"\n\t%z : Sequence Name (0018,0024) inserted, so a T1 scan converted with " \
"'myName%z' might yield 'myNameT1'."
return Output.split_lines(text)
def __init__(self, parent=None):
super(QWidget, self).__init__(parent)
# Load configuration files and general settings
self.cfg = Configuration.load_config(ROOTDIR)
if os.path.isdir(self.cfg['folders']['dicom']):
self.dicomdir = self.cfg['folders']['dicom']
else:
self.dicomdir = FileOperations.set_wdir_in_config(self.cfg, foldername='dicom', init=True)
self.cfg['folders']['dicom'] = self.dicomdir
self.cfg['folders']['rootdir'] = ROOTDIR
Configuration.save_config(ROOTDIR, self.cfg)
# Create general layout
self.tot_layout = QVBoxLayout(self)
self.mid_layout = QHBoxLayout(self)
# ============================ Create upper of GUI, i.e. working directory ============================
self.folderboxDcm2nii = QGroupBox("Directory (DICOM-files)")
self.HBoxUpperDcm2nii = QVBoxLayout(self.folderboxDcm2nii)
self.label_dicomdir = QLabel('dicom DIR: {}'.format(self.dicomdir))
self.HBoxUpperDcm2nii.addWidget(self.label_dicomdir)
self.btn_dicomdir = QPushButton('Change working \ndirectory')
self.btn_dicomdir.setFixedSize(150, 40)
self.btn_dicomdir.clicked.connect(self.change_dicomdir)
self.btn_savedir = QPushButton('Save directory \nto config file')
self.btn_savedir.setFixedSize(150, 40)
self.btn_savedir.setToolTip(Output.split_lines(setToolTips.saveDirButton()))
self.btn_savedir.clicked.connect(self.save_cfg)
hlay_upper = QHBoxLayout()
hlay_upper.addWidget(self.btn_dicomdir)
hlay_upper.addWidget(self.btn_savedir)
hlay_upper.addStretch(1)
self.HBoxUpperDcm2nii.addLayout(hlay_upper)
# ==================== Create Content for Lists, i.e. input/output ====================
self.listboxInputDcm2nii = QGroupBox('Available subjects in working directory')
self.listboxInput = QVBoxLayout(self.listboxInputDcm2nii)
self.mInput = QListWidget()
self.listboxInput.addWidget(self.mInput)
self.mButtonToAvailable = QPushButton("<<")
self.mBtnMoveToAvailable = QPushButton(">")
self.mBtnMoveToSelected = QPushButton("<")
self.mButtonToSelected = QPushButton(">>")
self.mBtnUp = QPushButton("Up")
self.mBtnDown = QPushButton("Down")
self.listboxOutputDcm2nii = QGroupBox('Subjects to process')
self.listboxOutput = QVBoxLayout(self.listboxOutputDcm2nii)
self.mOutput = QListWidget()
self.listboxOutput.addWidget(self.mOutput)
# First column on the left side
vlay = QVBoxLayout()
vlay.addStretch()
vlay.addWidget(self.mBtnMoveToAvailable)
vlay.addWidget(self.mBtnMoveToSelected)
vlay.addStretch()
vlay.addWidget(self.mButtonToAvailable)
vlay.addWidget(self.mButtonToSelected)
vlay.addStretch()
# Second column on the right side
vlay2 = QVBoxLayout()
vlay2.addStretch()
vlay2.addWidget(self.mBtnUp)
vlay2.addWidget(self.mBtnDown)
vlay2.addStretch()
# ==================== Lower part of GUI, i.e. Preferences/Start estimation ====================
self.btn_preferences = QPushButton("Preferences")
self.btn_preferences.clicked.connect(self.settings_show)
self.btn_run_dcm2niix = QPushButton("Run dcm2niix")
self.btn_run_dcm2niix.setToolTip(setToolTips.run_dcm2niix())
self.btn_run_dcm2niix.clicked.connect(self.start_converting)
hlay_bottom = QHBoxLayout()
hlay_bottom.addStretch(1)
hlay_bottom.addWidget(self.btn_preferences)
hlay_bottom.addWidget(self.btn_run_dcm2niix)
hlay_bottom.addStretch()
# ==================== Set all contents to general Layout =======================
self.mid_layout.addWidget(self.listboxInputDcm2nii)
self.mid_layout.addLayout(vlay)
self.mid_layout.addWidget(self.listboxOutputDcm2nii)
self.mid_layout.addLayout(vlay2)
self.tot_layout.addWidget(self.folderboxDcm2nii)
self.tot_layout.addLayout(self.mid_layout)
self.tot_layout.addLayout(hlay_bottom)
try:
self.mInput.clear()
items = FileOperations.list_folders(inputdir=self.cfg['folders']['dicom'], prefix='', files2lookfor='')
items = self.check_for_complete_input(list(items))
self.add_available_subj(items)
except FileExistsError:
print('{} without any valid files/folders, continuing ...'.format(self.dicomdir))
self.update_buttons_status()
self.connections()
def save_cfg(self):
"""Function intended to save the DICOM directory once button is pressed"""
self.cfg['folders']['dicom'] = self.dicomdir
Configuration.save_config(self.cfg['folders']['rootdir'], self.cfg)
Output.msg_box(text="Folder changed in configuration to {}".format(self.dicomdir), title="Changed folder")
def dcm2niix_multiprocessing(self, name_subj, no_subj, dcm2niix_bin,
last_idx, total_subj, status):
"""function intended to provide multiprocessing approach to speed up extraction of DICOM data to nifti files"""
modalities = ['CT', 'MRI']
if self.logfile:
log_filename = os.path.join(
ROOTDIR, 'logs', 'log_DCM2NII_' + str(no_subj + last_idx) +
time.strftime("%Y%m%d-%H%M%S"))
else:
log_filename = os.devnull
subj_outdir = os.path.join(
self.outdir,
self.cfg['folders']['prefix'] + str(no_subj + last_idx))
FileOperations.create_folder(subj_outdir)
start_time_subject = time.time()
keptfiles, deletedfiles = ([] for _ in range(2))
for mod in modalities:
status.put((name_subj, mod, no_subj, total_subj))
input_folder_name = os.path.join(self.inputdir, name_subj + mod)
# input_folder_files = [f.path for f in os.scandir(input_folder_name)
# if (f.is_dir() and ('100' in f.path or 'DICOM' in f.path or '001' in f.path))]
input_folder_files = []
[
input_folder_files.append(item)
for item in os.listdir(input_folder_name)
if (os.path.isdir(os.path.join(input_folder_name, item)) and (
'100' in item or 'DICOM' in item or '001' in item))
]
orig_stdout = sys.stdout
sys.stdout = open(log_filename, 'w')
for folder in input_folder_files:
subprocess.call(
[
dcm2niix_bin,
'-a',
'y', # anonimisation of DICOM data
'-b',
self.cfg['preprocess']['dcm2nii']['BIDSsidecar'][0],
'-z',
self.cfg['preprocess']['dcm2nii']['OutputCompression']
[0],
'-f',
self.cfg['preprocess']['dcm2nii']['OutputFileStruct'],
'-o',
subj_outdir,
'-w',
str(self.cfg['preprocess']['dcm2nii']
['NameConflicts']),
'-v',
str(self.cfg['preprocess']['dcm2nii']['Verbosity']),
'-x',
str(self.cfg['preprocess']['dcm2nii']['ReorientCrop']),
folder
],
stdout=sys.stdout,
stderr=subprocess.STDOUT)
sys.stdout.close()
sys.stdout = orig_stdout
files_kept, files_deleted = self.select_sequences(subj_outdir)
keptfiles.extend(files_kept)
deletedfiles.extend(files_deleted)
# Functions creating/updating pipeline log, which document individually all steps along with settings
log_text = "{} files successfully converted: {}, \n\nand {} deleted: {}.\nDuration: {:.2f} secs" \
.format(len(set(keptfiles)),
'\n\t{}'.format('\n\t'.join(os.path.split(x)[1] for x in sorted(set(keptfiles)))),
len(set(deletedfiles)),
'\n\t{}'.format('\n\t'.join(os.path.split(x)[1] for x in sorted(set(deletedfiles)))),
time.time() - start_time_subject)
Output.logging_routine(text=Output.split_lines(log_text),
cfg=self.cfg,
subject=self.cfg['folders']['prefix'] +
str(no_subj),
module='dcm2nii',
opt=self.cfg['preprocess']['dcm2nii'],
project="")
def run_dcm2niix():
text = "Before running this script, please make sure that the prefrences are set properly. moreover it is " \
"recommended to name DICOM folders xxxCT and xxxMRI or one of both. cDBS will specifically look for these " \
"folders to convert DICOM data from."
return Output.split_lines(text)