MedProIO package

A package to perform specific Medical Image processing operations based on SimpleITK such as alignment, resapling, and volume cropping\padding

Installation

Install MedProIO via pip

pip install MedProIO

Usage/Examples

Sequences Alignment

from MedProIO import Alignment
res = Alignment.AlignmentRegistration()

# set the reference Sitk object 
res.set_reference_image(T2)

# set the moving Sitk object 
res.set_moving_image(ADC)

# execute
res.execute_processing()

# get the transformed moving object
tr = res.get_transformed_image()

# Get a list with potential issues arose
issues = res.get_issues()

Resampling to Spacing

from MedProIO import Resampler
res = Resampler.ResamplerToSpacing()

# set the reference Sitk object 
res.set_reference_image(T2)

# set the spacing 
res.set_spacing(spacing=(0.5, 0.5, 3.0))

# execute
res.execute_processing()

# get the transformed moving object
tr = res.get_transformed_image()

# Get a list with potential issues arose
issues = res.get_issues()

Resampling between Sequences

from MedProIO import Coregistrator
res = Coregistrator.SequenceResampler()

# set the reference Sitk object 
res.set_reference_image(T2)

# set the moving Sitk object 
res.set_moving_image(ADC)

# execute
res.execute_processing()

# get the transformed moving object
tr = res.get_transformed_image()

# Get a list with potential issues arose
issues = res.get_issues()

Volume Crop or Padding to dimensions

from MedProIO import CropAndPad
res = CropAndPad.VolumeCropperAndPadder()

# set the reference Sitk object 
res.set_reference_image(T2)

# set the target size
res.set_target_size(target_size=(256,256,24))

# execute
res.execute_processing()

# get the transformed moving object
tr = res.get_transformed_image()

# Get a list with potential issues arose
issues = res.get_issues()

Authors

• Dimitrios Zaridis

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