N4BiasFieldCorrection/N4BiasFieldCorrection.py

#!/usr/bin/env python
# =========================================================================
#
#  Copyright NumFOCUS
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#         http://www.apache.org/licenses/LICENSE-2.0.txt
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
#  limitations under the License.
#
# =========================================================================
 
 
import SimpleITK as sitk
import sys
import os
 
if len(sys.argv) < 2:
    print(
        "Usage: N4BiasFieldCorrection inputImage "
        + "outputImage [shrinkFactor] [maskImage] [numberOfIterations] "
        + "[numberOfFittingLevels]"
    )
    sys.exit(1)
 
inputImage = sitk.ReadImage(sys.argv[1], sitk.sitkFloat32)
image = inputImage
 
if len(sys.argv) > 4:
    maskImage = sitk.ReadImage(sys.argv[4], sitk.sitkUInt8)
else:
    maskImage = sitk.OtsuThreshold(inputImage, 0, 1, 200)
 
shrinkFactor = 1
if len(sys.argv) > 3:
    shrinkFactor = int(sys.argv[3])
    if shrinkFactor > 1:
        image = sitk.Shrink(
            inputImage, [shrinkFactor] * inputImage.GetDimension()
        )
        maskImage = sitk.Shrink(
            maskImage, [shrinkFactor] * inputImage.GetDimension()
        )
 
corrector = sitk.N4BiasFieldCorrectionImageFilter()
 
numberFittingLevels = 4
 
if len(sys.argv) > 6:
    numberFittingLevels = int(sys.argv[6])
 
if len(sys.argv) > 5:
    corrector.SetMaximumNumberOfIterations(
        [int(sys.argv[5])] * numberFittingLevels
    )
 
corrected_image = corrector.Execute(image, maskImage)
 
 
log_bias_field = corrector.GetLogBiasFieldAsImage(inputImage)
 
corrected_image_full_resolution = inputImage / sitk.Exp(log_bias_field)
 
sitk.WriteImage(corrected_image_full_resolution, sys.argv[2])
 
if shrinkFactor > 1:
    sitk.WriteImage(
        corrected_image, "Python-Example-N4BiasFieldCorrection-shrunk.nrrd"
    )
 
if "SITK_NOSHOW" not in os.environ:
    sitk.Show(corrected_image, "N4 Corrected")