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refactor: handle multi-frame DICOM files by extracting the middle frame in get_PIL_image functions

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Ross
2026-07-13 11:23:04 +01:00
parent d322806b80
commit 8ae33e32ee
1 changed files with 14 additions and 16 deletions
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helpers/pydicom_PIL.py
+14 -16
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@@ -89,9 +89,13 @@ def get_PIL_image(dataset):
raise TypeError("Cannot show image -- DICOM dataset does not have "
"pixel data")
# Handle multi-frame DICOM files by extracting the middle frame
pixel_array = dataset.pixel_array
if len(pixel_array.shape) == 3:
pixel_array = pixel_array[pixel_array.shape[0] // 2]
# Apply modality lut
array = apply_modality_lut(dataset.pixel_array, dataset)
array = apply_modality_lut(pixel_array, dataset)
# voi lut doesn't seem to help
#array = apply_voi_lut(array, dataset)
@@ -115,7 +119,8 @@ def get_PIL_image(dataset):
# PIL size = (width, height)
size = (dataset.Columns, dataset.Rows)
array = dataset.pixel_array
# For multi-frame we already have the middle frame sliced as 2D in pixel_array
array = pixel_array
#array = apply_modality_lut(array, dataset)
@@ -124,17 +129,11 @@ def get_PIL_image(dataset):
#array = apply_windowing(array, dataset)
array = lin_stretch_img(array, 0.1, 99.9) # Apply "linear stretching" (lower percentile 0.1 goes to 0, and percentile 99.9 to 255).
if dataset["PhotometricInterpretation"].value == "MONOCHROME1":
# We need to invert
array = np.invert(array)
return PIL.Image.fromarray(array).convert('L')
pixel_data = array.tostring()
# Recommended to specify all details
# by http://www.pythonware.com/library/pil/handbook/image.htm
im = PIL.Image.frombuffer(mode, size, pixel_data,
"raw", mode, 0, 1)
else:
ew = dataset['WindowWidth']
ec = dataset['WindowCenter']
@@ -159,6 +158,11 @@ def get_PIL_image2(dataset):
if ('PixelData' not in dataset):
raise TypeError("Cannot show image -- DICOM dataset does not have "
"pixel data")
pixel_array = dataset.pixel_array
if len(pixel_array.shape) == 3:
pixel_array = pixel_array[pixel_array.shape[0] // 2]
# can only apply LUT if these window info exists
if ('WindowWidth' not in dataset) or ('WindowCenter' not in dataset):
bits = dataset.BitsAllocated
@@ -176,20 +180,14 @@ def get_PIL_image2(dataset):
raise TypeError("Don't know PIL mode for %d BitsAllocated "
"and %d SamplesPerPixel" % (bits, samples))
# PIL size = (width, height)
size = (dataset.Columns, dataset.Rows)
# Recommended to specify all details
# by http://www.pythonware.com/library/pil/handbook/image.htm
im = PIL.Image.frombuffer(mode, size, dataset.PixelData,
"raw", mode, 0, 1)
im = PIL.Image.fromarray(pixel_array).convert('L')
else:
ew = dataset['WindowWidth']
ec = dataset['WindowCenter']
ww = int(ew.value[0] if ew.VM > 1 else ew.value)
wc = int(ec.value[0] if ec.VM > 1 else ec.value)
image = get_LUT_value(dataset.pixel_array, ww, wc)
image = get_LUT_value(pixel_array, ww, wc)
# Convert mode to L since LUT has only 256 values:
# http://www.pythonware.com/library/pil/handbook/image.htm
im = PIL.Image.fromarray(image).convert('L')