Python/BoarderSegmentation.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.
#
# =========================================================================
 
""" An example script demonstrating boarder segmentation in SimpleITK. """
 
import sys
import os
import SimpleITK as sitk
 
# verify that we have the correct number of arguments
if len(sys.argv) != 5:
    sys.stderr.write("Usage: {sys.argv[0]} inputFile outputFile replaceValue upperThreshold\n")
    sys.exit(1)
 
# copy the arguments in to variables
inputFileName = sys.argv[1]
outputFileName = sys.argv[2]
replaceValue = int(sys.argv[3])
upperThreshold = float(sys.argv[4])
 
# Read the file into an sitkImage
image = sitk.ReadImage(inputFileName)
 
# Threshold the value [0,2), results in values inside the range 1, 0 otherwise
boundary = sitk.BinaryThreshold(image, 0, upperThreshold, 1, 0)
 
boundary = sitk.BinaryMorphologicalClosing(boundary, [1] * image.GetDimension())
 
# Remove any label pixel not connected to the boarder
boundary = sitk.BinaryGrindPeak(boundary)
 
boundary = sitk.Cast(boundary, image.GetPixelID())
 
# Multiply, the input image by not the boarder.
# This will multiply the image by 0 or 1, where 0 is the
# boarder. Making the board 0
image = image * ~boundary
 
# add the replace value to the pixel on the board
image = image + (boundary * replaceValue)
 
if "SITK_NOSHOW" not in os.environ:
    sitk.Show(image, "Boarder Segmentation")