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############################################################################
#
# Program: GDCM (Grassroots DICOM). A DICOM library
#
# Copyright (c) 2006-2011 Mathieu Malaterre
# All rights reserved.
# See Copyright.txt or http://gdcm.sourceforge.net/Copyright.html for details.
#
# This software is distributed WITHOUT ANY WARRANTY; without even
# the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
# PURPOSE. See the above copyright notice for more information.
#
############################################################################
"""
save a DICOM image with PIL via numpy
Caveats:
- Does not support UINT12/INT12
Usage:
python ConvertNumpy.py "IM000000"
Thanks:
plotting example - Ray Schumacher 2009
"""
import gdcm
import numpy
from PIL import Image, ImageOps
def get_gdcm_to_numpy_typemap():
"""Returns the GDCM Pixel Format to numpy array type mapping."""
_gdcm_np = {gdcm.PixelFormat.UINT8 :numpy.int8,
gdcm.PixelFormat.INT8 :numpy.uint8,
gdcm.PixelFormat.UINT16 :numpy.uint16,
gdcm.PixelFormat.INT16 :numpy.int16,
gdcm.PixelFormat.UINT32 :numpy.uint32,
gdcm.PixelFormat.INT32 :numpy.int32,
gdcm.PixelFormat.FLOAT32:numpy.float32,
gdcm.PixelFormat.FLOAT64:numpy.float64 }
return _gdcm_np
def get_numpy_array_type(gdcm_pixel_format):
"""Returns a numpy array typecode given a GDCM Pixel Format."""
return get_gdcm_to_numpy_typemap()[gdcm_pixel_format]
def gdcm_to_numpy(image):
"""Converts a GDCM image to a numpy array.
"""
pf = image.GetPixelFormat().GetScalarType()
print 'pf', pf
print image.GetPixelFormat().GetScalarTypeAsString()
assert pf in get_gdcm_to_numpy_typemap().keys(), \
"Unsupported array type %s"%pf
d = image.GetDimension(0), image.GetDimension(1)
print 'Image Size: %d x %d' % (d[0], d[1])
dtype = get_numpy_array_type(pf)
gdcm_array = image.GetBuffer()
result = numpy.frombuffer(gdcm_array, dtype=dtype)
maxV = float(result[result.argmax()])
## linear gamma adjust
#result = result + .5*(maxV-result)
## log gamma
result = numpy.log(result+50) ## 50 is apprx background level
maxV = float(result[result.argmax()])
result = result*(2.**8/maxV) ## histogram stretch
result.shape = d
return result
if __name__ == "__main__":
import sys
r = gdcm.ImageReader()
filename = sys.argv[1]
r.SetFileName( filename )
if not r.Read(): sys.exit(1)
numpy_array = gdcm_to_numpy( r.GetImage() )
## L is 8 bit grey
## http://www.pythonware.com/library/pil/handbook/concepts.htm
pilImage = Image.frombuffer('L',
numpy_array.shape,
numpy_array.astype(numpy.uint8),
'raw','L',0,1)
## cutoff removes background noise and spikes
pilImage = ImageOps.autocontrast(pilImage, cutoff=.1)
pilImage.save(sys.argv[1]+'.jpg')
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