def test_simple_dictionary(self):
expected = 'title:' + os.linesep + ' a 1' + os.linesep
self.assertEqual(echo_arguments('title', {'a':1}), expected)
def test_empty_dictionary(self):
expected = 'title:'+os.linesep
self.assertEqual(echo_arguments('title', {}), expected)
def standard(ct_file_name, rods_file_name, density_file_name, densities,
csv_file_name):
'''Determine the calibration equation for a standard phantom.'''
click.echo(echo_arguments('Standard Calibration', locals()))
# Read
click.echo('Reading input {}'.format(ct_file_name))
ct = sitk.ReadImage(ct_file_name)
click.echo('Reading input {}'.format(rods_file_name))
rods = sitk.ReadImage(rods_file_name)
# Determine number of components
click.echo('Determining mean intensities')
filt = sitk.LabelStatisticsImageFilter()
filt.Execute(ct, rods)
n_labels = len(filt.GetLabels())
click.echo('Found {} labels'.format(n_labels))
if len(densities) < 2:
click.fail('Need at least 2 samples to fit a function.'
' Only found {}'.format(len(densities)))
# Get the HU samples
HU = []
for label in filt.GetLabels():
# Skip background label
if label == 0:
continue
HU.append(filt.GetMean(label))
click.echo('Fitting parameters:')
click.echo(' Densities: {}'.format(densities))
click.echo(' HU: {}'.format(HU))
# Perform calibration
calibrator = StandardCalibration()
calibrator.fit(HU, densities)
click.echo('Found fit:')
click.echo(' Slope: {}'.format(calibrator.slope))
click.echo(' Intercept: {}'.format(calibrator.intercept))
click.echo(' R^2: {}'.format(calibrator.r_value**2))
header = [
'CT File Name', 'Rods File Name', 'Density File Name', 'slope',
'intercept', 'r_value', 'p_value', 'std_err'
]
data = {
'CT File Name': ct_file_name,
'Rods File Name': rods_file_name,
'Density File Name': density_file_name,
'slope': round(calibrator.slope, 16),
'intercept': round(calibrator.intercept, 16),
'r_value': round(calibrator.r_value, 16),
'p_value': round(calibrator.p_value, 16),
'std_err': round(calibrator.std_err, 16)
}
click.echo('Writing complete results to {}'.format(csv_file_name))
write_csv(data, csv_file_name, header)
click.echo('Calibrating density file')
density = calibrator.slope * sitk.Cast(ct, sitk.sitkFloat32) + \
calibrator.intercept
click.echo('Writing density file to {}'.format(density_file_name))
sitk.ReadImage(density, density_file_name)
def resample(input_file_name, output_file_name,
isotropic_resolution):
'''Resample a CT image to an isotropic resolution'''
click.echo(echo_arguments('Isotropic Resampling', locals()))
# Read
click.echo('Reading input {}'.format(input_file_name))
image = sitk.ReadImage(input_file_name)
# Determine sigma
click.echo('Resampling to a resolution of {}'.format(isotropic_resolution))
sigma = isotropic_resolution * np.sqrt(2 * np.log(2)) / np.pi
click.echo(' For a half-power cut-off frequency of {:0.3f}, '
'a standard deviation of {} is being used.'.format(
1/(2.0*isotropic_resolution), sigma))
# Filter each sampling directions as needed
for i, spacing in enumerate(image.GetSpacing()):
if spacing > isotropic_resolution:
click.echo(' No antialiasing in direction {}'.format(i))
continue
click.echo(' Antialiasing in direction {}'.format(i))
image = sitk.RecursiveGaussian(
image,
sigma, False,
sitk.RecursiveGaussianImageFilter.ZeroOrder,
i
)
# Determine the output size
resolution = [isotropic_resolution for i in range(image.GetDimension())]
size = [int(np.ceil(s * i / o)) for o, i, s in
zip(resolution, image.GetSpacing(), image.GetSize())]
click.echo(' Input Size: {}'.format(image.GetSize()))
click.echo(' Output Size: {}'.format(size))
click.echo('Finding minimum in image')
stats = sitk.StatisticsImageFilter()
stats.Execute(image)
vox_min = stats.GetMinimum()
click.echo(' Minimum intensity: {}'.format(vox_min))
click.echo('Resampling...')
transform = sitk.Euler3DTransform()
transform.SetIdentity()
click.echo(' Using BSpline interpolation')
output = sitk.Resample(
image,
size,
transform,
sitk.sitkBSpline,
image.GetOrigin(),
resolution,
image.GetDirection(),
vox_min,
image.GetPixelID()
)
click.echo('Writing output to file {}'.format(output_file_name))
sitk.WriteImage(output, output_file_name)
def mindways(ct_file_name, rods_file_name, density_file_name, csv_file_name,
water, densities):
'''Determine the calibration equation for a Mindways phantom.
Water and K2HPO4 densities are taken from the QC documentation
accompanying your specific phantom.'''
click.echo(echo_arguments('Mindways Calibration', locals()))
# Read
click.echo('Reading input {}'.format(ct_file_name))
ct = sitk.ReadImage(ct_file_name)
click.echo('Reading input {}'.format(rods_file_name))
rods = sitk.ReadImage(rods_file_name)
# Determine number of components
click.echo('Determining mean intensities')
filt = sitk.LabelStatisticsImageFilter()
filt.Execute(ct, rods)
n_labels = len(filt.GetLabels())
click.echo('Found {} labels'.format(n_labels))
if len(water) != len(densities) or len(water) != n_labels - 1:
click.fail(
'Number of water, K2HPO4, and segmented labels are not the same '
'({}, {}, and {})'.format(len(water), len(densities),
n_labels - 1))
if len(water) < 2:
click.fail('Need at least 2 samples to fit a function.'
' Only found {}'.format(len(water)))
# Get the HU samples
HU = []
for label in filt.GetLabels():
# Skip background label
if label == 0:
continue
HU.append(filt.GetMean(label))
click.echo('Fitting parameters:')
click.echo(' Water: {}'.format(water))
click.echo(' K2HPO4: {}'.format(densities))
click.echo(' HU: {}'.format(HU))
# Perform calibration
calibrator = MindwaysCalibration()
calibrator.fit(HU, densities, water)
click.echo('Found fit:')
click.echo(' Slope: {}'.format(calibrator.slope))
click.echo(' Intercept: {}'.format(calibrator.intercept))
click.echo(' R^2: {}'.format(calibrator.r_value**2))
header = [
'CT File Name', 'Rods File Name', 'Density File Name', 'sigma_ref',
'beta_ref', 'sigma_ct', 'beta_ct', 'slope', 'intercept', 'r_value',
'p_value', 'std_err'
]
data = {
'CT File Name': ct_file_name,
'Rods File Name': rods_file_name,
'Density File Name': density_file_name,
'sigma_ref': round(calibrator.sigma_ref, 16),
'beta_ref': round(calibrator.beta_ref, 16),
'sigma_ct': round(calibrator.sigma_ct, 16),
'beta_ct': round(calibrator.beta_ct, 16),
'slope': round(calibrator.slope, 16),
'intercept': round(calibrator.intercept, 16),
'r_value': round(calibrator.r_value, 16),
'p_value': round(calibrator.p_value, 16),
'std_err': round(calibrator.std_err, 16)
}
click.echo('Writing complete results to {}'.format(csv_file_name))
write_csv(data, csv_file_name, header)
click.echo('Calibrating density file')
density = calibrator.slope * sitk.Cast(ct, sitk.sitkFloat32) + \
calibrator.intercept
click.echo('Writing density file to {}'.format(density_file_name))
sitk.ReadImage(density, density_file_name)