def MergeSeriesCopy(objWeasel):
ui = UserInterfaceTools(objWeasel)
imageList = ui.getCheckedImages()
if imageList is None: return # Exit function if no images are checked
mergedSeries = Image.merge(imageList, series_name='Overwritten_Series', overwrite=True)
ui.refreshWeasel()
mergedSeries.DisplaySeries()
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# Get all series in the Checkboxes
studiesList = ui.getCheckedStudies()
if studiesList is None: return # Exit function if no study are checked
for study in studiesList:
seriesList = study.children
# List of series that will be used for T1 Map calculation
seriesListTI = []
for series in seriesList:
# First, collect all series that belong to T1 calculation. This is because 1 series <=> 1 image/TI
if checkT1(series):
seriesListTI.append(series)
if seriesListTI:
mergedSeries = Series.merge(seriesListTI, series_name='All_TIs', overwrite=False)
mergedSeries.sort("SliceLocation", "InversionTime")
magnitudeSeries = mergedSeries.Magnitude
# CONSIDER REFORMAT_SHAPE - 4D such as (256, 256, 5, 10) for eg.
ti = magnitudeSeries.InversionTimes
magnitude = magnitudeSeries.PixelArray
phaseSeries = mergedSeries.Phase
if phaseSeries.images:
phase = convert_to_pi_range(phaseSeries.PixelArray)
complex_data = magnitude * (np.cos(phase) + 1j * np.sin(phase)) # convert magnitude and phase into complex data
magnitude_corrected = magnitude_correct(complex_data)
inputArray = magnitude_corrected
else:
inputArray = magnitude
mapper = T1(np.transpose(inputArray), ti, multithread=True, parameters=2)
pixelArray = mapper.t1_map
outputSeries = mergedSeries.new(series_name="T1Map_UKRIN", suffix=FILE_SUFFIX)
outputSeries.write(np.transpose(pixelArray))
ui.refreshWeasel()
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
seriesList = ui.getCheckedSeries()
if seriesList is None: return # Exit function if no series are checked
mergedSeries = Series.merge(seriesList, series_name='NewSeries', overwrite=False)
ui.refreshWeasel()
mergedSeries.DisplaySeries()
def selectXNATPathDownload(self, tree_view_dir=False):
if tree_view_dir == False:
ui = UserInterfaceTools(self)
directory = ui.selectFolder(
title="Select the directory where you wish to download")
else:
directory = self.DICOMfolderPath
return directory
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
seriesList = ui.getCheckedSeries()
if seriesList is None: return # Exit function if no series are checked
# Lower and upper threshold from the input window
inputDict = {"Lower Threshold": "integer", "Upper Threshold": "integer"}
info = "Insert a value between 0 and 100. Upper threshold must be greater than lower threshold"
paramList = ui.inputWindow(inputDict,
title="Input Parameters",
helpText=info)
if paramList is None:
return # Exit function if the user hits the "Cancel" button
low_thresh = paramList[0]
high_thresh = paramList[1]
index_series = 1
for series in seriesList:
newSeries = series.new(suffix=FILE_SUFFIX)
index_bar = 0
for image in series.children:
newImage = image.new(series=newSeries)
index_bar = ui.progressBar(maxNumber=series.numberChildren,
index=index_bar,
msg="Thresholding and saving image {}",
title="Threshold of series " +
str(index_series))
pixelArray = image.PixelArray
pixelArray = thresholdPixelArray(
pixelArray, low_thresh,
high_thresh) # NOT WORKING WELL ON NEGATIVE IMAGES
newImage.write(pixelArray, series=newSeries)
index_series += 1
ui.closeMessageWindow()
# Refresh the UI screen
ui.refreshWeasel(new_series_name=newSeries.seriesID)
newSeries.DisplaySeries()
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
seriesList = ui.getCheckedSeries()
if seriesList is None: return # Exit function if no series are checked
for series in seriesList:
newSeries = series.new(suffix=FILE_SUFFIX)
pixelArray = series.PixelArray
pixelArray = np.square(pixelArray)
newSeries.write(pixelArray)
ui.refreshWeasel(new_series_name=newSeries.seriesID)
newSeries.DisplaySeries()
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# Get all images in the Checkboxes
imageList = ui.getCheckedImages()
if imageList is None: return # Exit function if no images are checked
index_bar = 0
for image in imageList:
# Get PixelArray from the corresponding slice
pixelArray = image.PixelArray
dataset = image.PydicomObject
# Apply Invert
pixelArray = invertAlgorithm(pixelArray, dataset)
# Progress Bar
index_bar = ui.progressBar(maxNumber=len(imageList),
index=index_bar,
msg="Inverting and overwriting image {}",
title="Invert checked series ")
# Overwrite - write() checks if file already exists so it writes new or overwrite
image.write(pixelArray)
# Close the progress bar
ui.closeMessageWindow()
# Refresh the UI screen
ui.refreshWeasel(new_series_name=imageList[-1].seriesID)
# Display all checked images
Image.DisplayImages(imageList)
def selectXNATPathUpload(self, tree_view=False):
listPaths = []
ui = UserInterfaceTools(self)
if tree_view == True:
images = ui.getCheckedImages()
for image in images:
listPaths.append(image.path)
else:
directory = ui.selectFolder(
title="Select the directory with the files you wish to upload")
for root, _, files in os.walk(directory):
for filename in files:
filepath = os.path.join(root, filename)
listPaths.append(filepath)
return listPaths
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# Get all series in the Checkboxes
seriesList = ui.getCheckedSeries()
if seriesList is None: return # Exit function if no series are checked
for series in seriesList:
seriesPhase = series.Phase
seriesReal = series.Real
seriesImaginary = series.Imaginary
if checkB0(seriesPhase):
seriesPhase.sort("SliceLocation", "EchoTime")
te = np.unique(seriesPhase.EchoTimes)
pixelArray = seriesPhase.PixelArray # (32, 256, 256)
reformatShape = (len(te), int(np.shape(pixelArray)[0] / len(te)),
np.shape(pixelArray)[1], np.shape(pixelArray)[2])
phase = np.transpose(
pixelArray.reshape(reformatShape)
) # (2, 16, 256, 256) => (256, 256, 16, 2) after the np.transpose
# Initialise B0 mapping object
mapper_B0 = B0(phase, te, unwrap=True)
b0map = mapper_B0.b0_map # (256, 256, 16)
newSeries = seriesPhase.new(suffix=FILE_SUFFIX)
newSeries.write(np.transpose(b0map)) # (16, 256, 256)
# Refresh the UI screen
ui.refreshWeasel(new_series_name=newSeries.seriesID)
# Display series
newSeries.DisplaySeries()
elif checkB0(seriesReal) and checkB0(seriesImaginary):
seriesReal.sort("SliceLocation", "EchoTime")
seriesImaginary.sort("SliceLocation", "EchoTime")
te = np.unique(seriesReal.EchoTimes)
pixelArray = np.arctan2(seriesImaginary.PixelArray,
seriesReal.PixelArray) # (32, 256, 256)
reformatShape = (len(te), int(np.shape(pixelArray)[0] / len(te)),
np.shape(pixelArray)[1], np.shape(pixelArray)[2])
phase = np.transpose(
pixelArray.reshape(reformatShape)
) # (2, 16, 256, 256) => (256, 256, 16, 2) after the np.transpose
# Initialise B0 mapping object
mapper_B0 = B0(phase, te, unwrap=True)
b0map = mapper_B0.b0_map # (256, 256, 16)
newSeries = seriesReal.new(suffix=FILE_SUFFIX)
newSeries.write(np.transpose(b0map)) # (16, 256, 256)
# Refresh the UI screen
ui.refreshWeasel(new_series_name=newSeries.seriesID)
# Display series
newSeries.DisplaySeries()
else:
ui.showMessageWindow(
msg=
'The checked series doesn\'t meet the criteria to calculate the B0 Map',
title='NOT POSSIBLE TO CALCULATE B0 MAP')
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# Get all series in the Checkboxes
seriesList = ui.getCheckedSeries()
if seriesList is None: return # Exit function if no series are checked
for series in seriesList:
seriesMagnitude = series.Magnitude
if checkT2Star(seriesMagnitude):
if seriesMagnitude.Multiframe:
seriesMagnitude.sort("PerFrameFunctionalGroupsSequence.MREchoSequence.EffectiveEchoTime", "PerFrameFunctionalGroupsSequence.FrameContentSequence.InStackPositionNumber")
else:
seriesMagnitude.sort("EchoTime", "SliceLocation")
te = np.unique(seriesMagnitude.EchoTimes)
pixelArray = np.transpose(seriesMagnitude.PixelArray) # (256, 256, 60)
reformatShape = (np.shape(pixelArray)[0], np.shape(pixelArray)[1], int(np.shape(pixelArray)[2]/len(te)), len(te))
pixelArray = pixelArray.reshape(reformatShape) # (256, 256, 5, 12)
# Initialise the loglin mapping object
mapper_loglin = T2Star(pixelArray, te, method='loglin')
# mapper_2p_exp = T2Star(pixelArray, te, method='2p_exp')
# Extract the T2* map from the object
t2star_loglin = mapper_loglin.t2star_map # (256, 256, 5)
newSeries = seriesMagnitude.new(suffix=FILE_SUFFIX)
newSeries.write(np.transpose(t2star_loglin)) # (5, 256, 256)
# Refresh the UI screen
ui.refreshWeasel(new_series_name=newSeries.seriesID)
# Display series
newSeries.DisplaySeries()
else:
ui.showMessageWindow(msg='The checked series doesn\'t meet the criteria to calculate the T2* Map', title='NOT POSSIBLE TO CALCULATE T2* MAP')
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# Get all series in the Checkboxes
seriesList = ui.getCheckedSeries()
if seriesList is None: return # Exit function if no series are checked
for series in seriesList:
seriesMagnitude = series.Magnitude
if checkT2(seriesMagnitude):
seriesMagnitude.sort("EchoTime")
seriesMagnitude.sort("SliceLocation")
te = np.unique(seriesMagnitude.EchoTimes)
pixelArray = np.transpose(seriesMagnitude.PixelArray)
reformatShape = (np.shape(pixelArray)[0], np.shape(pixelArray)[1],
int(np.shape(pixelArray)[2] / len(te)), len(te))
pixelArray = pixelArray.reshape(reformatShape)
mapper = T2(pixelArray, te)
t2Map = mapper.t2_map
newSeries = seriesMagnitude.new(suffix=FILE_SUFFIX)
newSeries.write(np.transpose(t2Map))
# Refresh the UI screen
ui.refreshWeasel(new_series_name=newSeries.seriesID)
# Display series
newSeries.DisplaySeries()
else:
ui.showMessageWindow(
msg=
'The checked series doesn\'t meet the criteria to calculate the T2 Map',
title='NOT POSSIBLE TO CALCULATE T2 MAP')
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# Get all series in the Checkboxes
seriesList = ui.getCheckedSeries()
# If all dimensions are not the same then return error
if checkDimensionsMatch(seriesList) is None: return
newSeries = seriesList[0].new(suffix=FILE_SUFFIX)
nrOfImages = seriesList[0].numberChildren
for i in range(nrOfImages):
outputArray = seriesList[0].children[i].PixelArray
for series in seriesList[1:]:
outputArray *= series.children[i].PixelArray
newImage = seriesList[0].children[i].new(series=newSeries)
newImage.write(outputArray, series=newSeries)
# Refresh the UI screen
ui.refreshWeasel(new_series_name=newSeries.seriesID)
# Display series
newSeries.DisplaySeries()
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# In this case, the user introduces the sigma value intended for the gaussian filter
inputDict = {"Standard Deviation": "float"}
paramList = ui.inputWindow(
inputDict, title="Input Parameters for the Gaussian Filter")
if paramList is None:
return # Exit function if the user hits the "Cancel" button
standard_deviation_filter = paramList[0]
# Get checked images
imageList = ui.getCheckedImages()
if imageList is None: return # Exit function if no images are checked
# Create new Series where the resulting images will be saved
newSeries = Image.newSeriesFrom(imageList, suffix=FILE_SUFFIX)
for image in imageList:
# Create new image based on the current image
newImage = image.new(series=newSeries)
# Get PixelArray from the selected images
pixelArray = image.PixelArray
# Apply Gaussian Filter
pixelArray = gaussianFilter(pixelArray, standard_deviation_filter)
# Save as individual image into new Series
newImage.write(pixelArray, series=newSeries)
# Refresh the UI screen
ui.refreshWeasel(new_series_name=newSeries.seriesID)
# Display resulting image
newSeries.DisplaySeries()
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# In this case, the user introduces the sigma value intended for the gaussian filter
inputDict = {"Standard Deviation": "float"}
paramList = ui.inputWindow(
inputDict, title="Input Parameters for the Gaussian Filter")
if paramList is None:
return # Exit function if the user hits the "Cancel" button
standard_deviation_filter = paramList[0]
# Get checked series
seriesList = ui.getCheckedSeries()
if seriesList is None: return # Exit function if no series are checked
for series in seriesList:
# Create a new Series for each Series checked
newSeries = series.new(series_name="GaussianFiltered_" +
str(series.seriesID))
# Get series' PixelArray
pixelArray = series.PixelArray
# Apply Gaussian filter
pixelArray = gaussianFilter(pixelArray, standard_deviation_filter)
# Save resulting PixelArray into the new Series
newSeries.write(pixelArray)
# Refresh the UI screen
ui.refreshWeasel(new_series_name=newSeries.seriesID)
# Display resulting image
newSeries.DisplaySeries()
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
inputDict = {"DICOM Tag":"string", "Value":"string"}
helpMsg = 'The DICOM Tag can be inserted in string or hexadecimal format.\nExample:\n'\
'(0010,0010) => type PatientName or 0x00100010'
paramList = ui.inputWindow(inputDict, title="Insert DICOM Tag element to change and its new value", helpText=helpMsg)
if paramList is None: return # Exit function if the user hits the "Cancel" button
tag = paramList[0]
value = paramList[1]
imageList = ui.getCheckedImages()
if imageList is None: return # Exit function if no images are checked
ui.showMessageWindow(msg="Overwriting the checked DICOM files with the typed values", title="Edit DICOM")
for image in imageList:
image.Item(tag, value)
ui.closeMessageWindow()
imageList[0].DisplayMetadata()
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# Get all series in the Checkboxes
seriesList = ui.getCheckedSeries() # getSelectedStudy()
if seriesList is None: return # Exit function if no series are checked
# List of series that will be used for T1 Map calculation
seriesListTI = []
for series in seriesList:
# First, collect all series that belong to T1 calculation. This is because 1 series <=> 1 image/TI
if checkT1(series):
seriesListTI.append(series)
if seriesListTI:
mergedSeries = Series.merge(seriesListTI,
series_name='All_TIs',
overwrite=False)
mergedSeries.sort("SliceLocation", "InversionTime")
magnitudeSeries = mergedSeries.Magnitude
# CONSIDER REFORMAT_SHAPE - 4D such as (256, 256, 5, 10) for eg.
ti = magnitudeSeries.InversionTimes
magnitude = magnitudeSeries.PixelArray
phaseSeries = mergedSeries.Phase
if phaseSeries.images:
phase = convert_to_pi_range(phaseSeries.PixelArray)
complex_data = magnitude * (
np.cos(phase) + 1j * np.sin(phase)
) # convert magnitude and phase into complex data
magnitude_corrected = magnitude_correct(complex_data)
inputArray = magnitude_corrected
else:
inputArray = magnitude
mapper = T1(np.transpose(inputArray),
ti,
multithread=True,
parameters=2)
pixelArray = mapper.t1_map
#outputSeries = mergedSeries.new(series_name="T1Map_UKRIN", suffix=FILE_SUFFIX)
outputSeries = seriesListTI[0].new(series_name="T1Map_UKRIN",
suffix=FILE_SUFFIX)
outputSeries.write(np.transpose(pixelArray))
# Refresh Weasel
ui.refreshWeasel(new_series_name=outputSeries.seriesID)
# Display series
outputSeries.DisplaySeries()
else:
ui.showMessageWindow(
msg=
'The checked series doesn\'t meet the criteria to calculate the T1 Map',
title='NOT POSSIBLE TO CALCULATE T1 MAP')
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
if tools.treeView.isASeriesSelected(objWeasel):
seriesList = ui.getSelectedSeries()
if seriesList is None: return # Exit function if no series are checked
series = seriesList[
0] # Because the if conditional only gets the last series selected
inputDict = {"New Series Name": "string"}
paramList = ui.inputWindow(inputDict,
title="Please type in the new series name")
if paramList is None:
return # Exit function if the user hits the "Cancel" button
name = str(paramList[0])
# Perform the change
series.Item("SeriesDescription", name)
# Change it in the TreeView
ui.refreshWeasel()
else:
ui.showMessageWindow(msg="Please select a series to run this script",
title="ERROR: Can't rename series")
def main(objWeasel):
ui = UserInterfaceTools(objWeasel)
# Get the series in the Checkboxes
seriesList = ui.getCheckedSeries()
if seriesList is None: return # Exit function if no series are checked
series = seriesList[0]
if checkT1(series):
seriesMagnitude = series.Magnitude
try:
seriesMagnitude.sort("InversionTime")
except:
seriesMagnitude.sort(0x20051572)
seriesMagnitude.sort("SliceLocation")
numSlices = seriesMagnitude.NumberOfSlices
ti = np.array(
seriesMagnitude.InversionTimes) # array of length = 50 or 10
ti = ti.reshape((int(len(ti) / numSlices),
numSlices)) # array of size (10, 5) or (10, 1)
pixelArray = np.transpose(
seriesMagnitude.PixelArray) # (256, 256, 50) or (256, 256, 10)
reformatShape = (np.shape(pixelArray)[0], np.shape(pixelArray)[1],
numSlices, int(np.shape(pixelArray)[2] / numSlices))
pixelArray = pixelArray.reshape(
reformatShape) # (256, 256, 5, 10) or (256, 256, 1, 10)
#######################################################
outputArray = []
for zSlice in range(np.shape(pixelArray)[2]):
tempImage = ukrinMaps(np.squeeze(
pixelArray[:, :, zSlice, :])).T1Map(
ti[:, zSlice]) # There's MATLAB version T1MapMolli
outputArray.append(np.transpose(tempImage))
outputArray = np.squeeze(np.array(outputArray))
del tempImage
########################################################
outputSeries = series.new(series_name="T1Map_iBEAT",
suffix=FILE_SUFFIX)
outputSeries.write(outputArray)
# Refresh Weasel
ui.refreshWeasel(new_series_name=outputSeries.seriesID)
# Display series
outputSeries.DisplaySeries()
else:
ui.showMessageWindow(
msg=
'The checked series doesn\'t meet the criteria to calculate the T1 Map',
title='NOT POSSIBLE TO CALCULATE T1 MAP')
def upload(objWeasel):
# Insert Try/Except
ui = UserInterfaceTools(objWeasel)
credentialsWindow = {
"URL": "string,https://test-ukrin.dpuk.org",
"Username": "******",
"Password": "******"
}
info = "Please insert the XNAT URL and your XNAT credentials"
loginDetails = ui.inputWindow(credentialsWindow,
title="XNAT Login",
helpText=info)
url = loginDetails[0] # https://test-ukrin.dpuk.org
username = loginDetails[1]
password = loginDetails[2]
with xnat.connect(url, user=username, password=password) as session:
xnatProjects = [
project.secondary_id for project in session.projects.values()
]
projectWindow = {"Project": "dropdownlist"}
projectInfo = "URL: " + url + "<p>Select the Project to upload the images from</p>"
projectName = ui.inputWindow(projectWindow,
title="XNAT Upload",
helpText=projectInfo,
lists=[xnatProjects])
if projectName:
xnatSubjects = [
subject.label for subject in session.projects[
projectName[0]].subjects.values()
]
xnatSubjects.insert(0, "Upload at Project Level")
subjectWindow = {"Subject": "dropdownlist"}
subjectInfo = "URL: " + url + "<p>Project: " + projectName[
0] + "</p><p>Select the Subject to upload the images from</p>"
subjectName = ui.inputWindow(subjectWindow,
title="XNAT Upload",
helpText=subjectInfo,
lists=[xnatSubjects])
if subjectName:
if subjectName[0] == "Upload at Project Level":
uploadPaths = selectXNATPathUpload(objWeasel)
uploadZipFile = zipFiles(uploadPaths)
ui.showInformationWindow(
"XNAT Upload",
"The selected images will be uploaded to the selected project. The upload progress can be checked in the terminal and you may continue using Weasel."
)
try:
session.services.import_(
uploadZipFile,
overwrite='none',
project=session.projects[projectName[0]].id,
content_type='application/zip')
except:
warnings.warn(
'The zip file being uploaded contains files already present in the selected image session and the upload assistant cannot overwrite or give the option to not overwrite. \n The selected file or folder was pre-archived in the selected XNAT project. \n Please login to the portal and review and/or archive the images.'
)
ui.showInformationWindow("XNAT Upload",
"Upload completed!")
else:
xnatExperiments = [
experiment.label
for experiment in session.projects[projectName[0]].
subjects[subjectName[0]].experiments.values()
]
xnatExperiments.insert(0, "Upload at Subject Level")
experimentWindow = {"Experiment": "dropdownlist"}
experimentInfo = "URL: " + url + "<p>Project: " + projectName[
0] + "</p><p>Subject: " + subjectName[
0] + "</p><p>Select the Experiment to upload the images from</p>"
experimentName = ui.inputWindow(experimentWindow,
title="XNAT Upload",
helpText=experimentInfo,
lists=[xnatExperiments])
if experimentName:
if experimentName[0] == "Upload at Subject Level":
uploadPaths = selectXNATPathUpload(objWeasel)
uploadZipFile = zipFiles(uploadPaths)
ui.showInformationWindow(
"XNAT Upload",
"The selected images will be uploaded to the selected subject. The upload progress can be checked in the terminal and you may continue using Weasel."
)
try:
session.services.import_(
uploadZipFile,
overwrite='none',
project=session.projects[
projectName[0]].id,
subject=session.projects[projectName[0]].
subjects[subjectName[0]].id,
content_type='application/zip')
except:
warnings.warn(
'The zip file being uploaded contains files already present in the selected image session and the upload assistant cannot overwrite or give the option to not overwrite. \n The selected file or folder was pre-archived in the selected XNAT project. \n Please login to the portal and review and/or archive the images.'
)
ui.showInformationWindow("XNAT Upload",
"Upload completed!")
else:
uploadPaths = selectXNATPathUpload(objWeasel)
uploadZipFile = zipFiles(uploadPaths)
ui.showInformationWindow(
"XNAT Upload",
"The selected images will be uploaded to the selected experiment. The upload progress can be checked in the terminal and you may continue using Weasel."
)
try:
session.services.import_(
uploadZipFile,
overwrite='none',
project=session.projects[
projectName[0]].id,
subject=session.projects[projectName[0]].
subjects[subjectName[0]].id,
experiment=session.projects[projectName[0]]
.subjects[subjectName[0]].experiments[
experimentName[0]].id,
content_type='application/zip')
except:
warnings.warn(
'The zip file being uploaded contains files already present in the selected image session and the upload assistant cannot overwrite or give the option to not overwrite. \n The selected file or folder was pre-archived in the selected XNAT project. \n Please login to the portal and review and/or archive the images.'
)
ui.showInformationWindow("XNAT Upload",
"Upload completed!")
# Curl Command
headers = {"Content-Type": "application/json", "Accept": "*/*"}
# Update the project's indices
for individual_experiment in session.projects[projectName[0]].experiments:
curl_url = url + "/xapi/viewer/projects/" + session.projects[
projectName[0]].id + "/experiments/" + individual_experiment
response = requests.post(curl_url,
headers=headers,
auth=(username, password))
# Delete Login Details
del loginDetails, url, username, password
# Delete ZIP File
os.remove(uploadZipFile)
session.disconnect()
def download(objWeasel):
# Insert Try/Except
ui = UserInterfaceTools(objWeasel)
credentialsWindow = {
"URL": "string,https://test-ukrin.dpuk.org",
"Username": "******",
"Password": "******"
}
info = "Please insert the XNAT URL and your XNAT credentials"
loginDetails = ui.inputWindow(credentialsWindow,
title="XNAT Login",
helpText=info)
url = loginDetails[0] # https://test-ukrin.dpuk.org
username = loginDetails[1]
password = loginDetails[2]
with xnat.connect(url, user=username, password=password) as session:
xnatProjects = [
project.secondary_id for project in session.projects.values()
]
projectWindow = {"Project": "dropdownlist"}
projectInfo = "URL: " + url + "<p>Select the Project to download the images from</p>"
projectName = ui.inputWindow(projectWindow,
title="XNAT Download",
helpText=projectInfo,
lists=[xnatProjects])
if projectName is None: return
if projectName:
xnatSubjects = [
subject.label for subject in session.projects[
projectName[0]].subjects.values()
]
xnatSubjects.insert(0, "All")
subjectWindow = {"Subject": "dropdownlist"}
subjectInfo = "URL: " + url + "<p>Project: " + projectName[
0] + "</p><p>Select the Subject to download the images from</p>"
subjectName = ui.inputWindow(subjectWindow,
title="XNAT Download",
helpText=subjectInfo,
lists=[xnatSubjects])
if subjectName is None: return
if subjectName:
if subjectName[0] == "All":
dataset = session.projects[projectName[0]]
downloadFolder = selectXNATPathDownload(objWeasel)
ui.showInformationWindow(
"XNAT Download",
"The selected images will be downloaded to the root folder of the TreeView. The download progress can be checked in the terminal and you may continue using Weasel."
)
dataset.download_dir(downloadFolder)
ui.showInformationWindow("XNAT Download",
"Download completed!")
else:
xnatExperiments = [
experiment.label
for experiment in session.projects[projectName[0]].
subjects[subjectName[0]].experiments.values()
]
xnatExperiments.insert(0, "All")
experimentWindow = {"Experiment": "dropdownlist"}
experimentInfo = "URL: " + url + "<p>Project: " + projectName[
0] + "</p><p>Subject: " + subjectName[
0] + "</p><p>Select the Experiment to download the images from</p>"
experimentName = ui.inputWindow(experimentWindow,
title="XNAT Download",
helpText=experimentInfo,
lists=[xnatExperiments])
if experimentName is None: return
if experimentName:
if experimentName[0] == "All":
dataset = session.projects[
projectName[0]].subjects[subjectName[0]]
downloadFolder = selectXNATPathDownload(objWeasel)
ui.showInformationWindow(
"XNAT Download",
"The selected images will be downloaded to the root folder of the TreeView. The download progress can be checked in the terminal and you may continue using Weasel."
)
dataset.download_dir(downloadFolder)
ui.showInformationWindow("XNAT Download",
"Download completed!")
else:
xnatScans = [
scan.series_description
for scan in session.projects[projectName[0]].
subjects[subjectName[0]].experiments[
experimentName[0]].scans.values()
]
xnatScans.insert(0, "All")
scanWindow = {"Scan": "dropdownlist"}
scanInfo = "URL: " + url + "<p>Project: " + projectName[
0] + "</p><p>Subject: " + subjectName[
0] + "</p><p>Experiment: " + experimentName[
0] + "</p><p>Select the Scan to download the images from</p>"
scanName = ui.inputWindow(scanWindow,
title="XNAT Download",
helpText=scanInfo,
lists=[xnatScans])
if scanName:
if scanName[0] == "All":
dataset = session.projects[
projectName[0]].subjects[subjectName[
0]].experiments[experimentName[0]]
downloadFolder = selectXNATPathDownload(
objWeasel)
ui.showInformationWindow(
"XNAT Download",
"The selected images will be downloaded to the root folder of the TreeView. The download progress can be checked in the terminal and you may continue using Weasel."
)
dataset.download_dir(downloadFolder)
ui.showInformationWindow(
"XNAT Download", "Download completed!")
else:
dataset = session.projects[
projectName[0]].subjects[
subjectName[0]].experiments[
experimentName[0]].scans[
scanName[0]]
downloadFolder = selectXNATPathDownload(
objWeasel)
ui.showInformationWindow(
"XNAT Download",
"The selected images will be downloaded to the root folder of the TreeView. The download progress can be checked in the terminal and you may continue using Weasel."
)
dataset.download_dir(downloadFolder)
ui.showInformationWindow(
"XNAT Download", "Download completed!")
# Delete Login Details
del loginDetails, url, username, password
session.disconnect()
return