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Simplify alpha_blend/alpha_blend_masked and overlay_segmentations in 05_Results_Visualization #512

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Merged
blowekamp merged 2 commits into from
Sep 24, 2026
+72 −50
Merged

Simplify alpha_blend/alpha_blend_masked and overlay_segmentations in 05_Results_Visualization #512

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714e76c
Simplify alpha_blend/alpha_blend_masked and overlay_segmentations
blowekamp Sep 21, 2026
874d27b
Adding missing words to additional_dictionary
blowekamp Sep 23, 2026
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121 changes: 71 additions & 50 deletions Python/05_Results_Visualization.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -292,59 +292,80 @@
"metadata": {},
"outputs": [],
"source": [
"def mask_image_multiply(mask, image):\n",
" components_per_pixel = image.GetNumberOfComponentsPerPixel()\n",
" if components_per_pixel == 1:\n",
" return mask * image\n",
"def alpha_blend(image1, image2, alpha=0.5):\n",
" \"\"\"\n",
" Alpha blend two images, pixels can be scalars or vectors.\n",
" The alpha blending factor can be either a scalar or an image whose\n",
" pixel type is sitkFloat32 and values are in [0,1].\n",
" \"\"\"\n",
" components_per_pixel = image1.GetNumberOfComponentsPerPixel()\n",
" if components_per_pixel > 1:\n",
" # MultiplyImageFilter doesn't support a vector image times a scalar\n",
" # (per-pixel) image, so blend one channel at a time. The 1-alpha\n",
" # factor doesn't depend on the channel, so it's only computed once.\n",
" one_minus_alpha = 1 - alpha\n",
" channels = []\n",
" for channel in range(components_per_pixel):\n",
" scaled1 = sitk.VectorIndexSelectionCast(image1, channel, sitk.sitkFloat32)\n",
" scaled1 *= alpha\n",
" blended_channel = sitk.VectorIndexSelectionCast(\n",
" image2, channel, sitk.sitkFloat32\n",
" )\n",
" blended_channel *= one_minus_alpha\n",
" blended_channel += scaled1\n",
" channels.append(blended_channel)\n",
" return sitk.Compose(channels)\n",
" else:\n",
" return sitk.Compose(\n",
" [\n",
" mask * sitk.VectorIndexSelectionCast(image, channel)\n",
" for channel in range(components_per_pixel)\n",
" ]\n",
" )\n",
" scaled1 = sitk.Cast(image1, sitk.sitkFloat32)\n",
" scaled1 *= alpha\n",
" blended = sitk.Cast(image2, sitk.sitkFloat32)\n",
" blended *= 1 - alpha\n",
" blended += scaled1\n",
" return blended\n",
"\n",
"\n",
"def alpha_blend(image1, image2, alpha=0.5, mask1=None, mask2=None):\n",
"def alpha_blend_masked(image1, image2, alpha=0.5, mask1=None, mask2=None):\n",
" \"\"\"\n",
" Alaph blend two images, pixels can be scalars or vectors.\n",
" The alpha blending factor can be either a scalar or an image whose\n",
" pixel type is sitkFloat32 and values are in [0,1].\n",
" The region that is alpha blended is controled by the given masks.\n",
" Alpha blend two images as done by alpha_blend, restricted to the region(s)\n",
" indicated by the given masks. Masks are treated as binary indicators\n",
" (non-zero selects the region), as returned by, e.g., OtsuThreshold.\n",
" \"\"\"\n",
" if mask1 is None and mask2 is None:\n",
" return alpha_blend(image1, image2, alpha)\n",
"\n",
" if not mask1:\n",
" mask1 = sitk.Image(image1.GetSize(), sitk.sitkFloat32) + 1.0\n",
" mask1.CopyInformation(image1)\n",
" else:\n",
" mask1 = sitk.Cast(mask1, sitk.sitkFloat32)\n",
" if not mask2:\n",
" mask2 = sitk.Image(image2.GetSize(), sitk.sitkFloat32) + 1\n",
" mask2.CopyInformation(image2)\n",
" else:\n",
" mask2 = sitk.Cast(mask2, sitk.sitkFloat32)\n",
" # if we received a scalar, convert it to an image\n",
" # Build a per-pixel alpha image so the mask1/mask2-only regions can be\n",
" # expressed as alpha=1/alpha=0 and blended by reusing alpha_blend. The\n",
" # neither-mask region can't be expressed this way (it's 0, not image1\n",
" # or image2), so it's overwritten separately below.\n",
" if type(alpha) != sitk.SimpleITK.Image:\n",
" alpha = sitk.Image(image1.GetSize(), sitk.sitkFloat32) + alpha\n",
" alpha.CopyInformation(image1)\n",
" components_per_pixel = image1.GetNumberOfComponentsPerPixel()\n",
" if components_per_pixel > 1:\n",
" img1 = sitk.Cast(image1, sitk.sitkVectorFloat32)\n",
" img2 = sitk.Cast(image2, sitk.sitkVectorFloat32)\n",
" alpha_image = sitk.Image(image1.GetSize(), sitk.sitkFloat32) + alpha\n",
" alpha_image.CopyInformation(image1)\n",
" else:\n",
" img1 = sitk.Cast(image1, sitk.sitkFloat32)\n",
" img2 = sitk.Cast(image2, sitk.sitkFloat32)\n",
"\n",
" intersection_mask = mask1 * mask2\n",
"\n",
" intersection_image = mask_image_multiply(\n",
" alpha * intersection_mask, img1\n",
" ) + mask_image_multiply((1 - alpha) * intersection_mask, img2)\n",
" return (\n",
" intersection_image\n",
" + mask_image_multiply(mask2 - intersection_mask, img2)\n",
" + mask_image_multiply(mask1 - intersection_mask, img1)\n",
" )"
" # Copy so the caller's alpha image isn't mutated by the in-place\n",
" # mask edits below.\n",
" alpha_image = sitk.Image(alpha)\n",
"\n",
" # Comparison operators always return a sitkUInt8 image, regardless of the\n",
" # input pixel type, so there's no need to cast beforehand.\n",
" if mask1 is not None:\n",
" mask1 = mask1 != 0\n",
" if mask2 is not None:\n",
" mask2 = mask2 != 0\n",
"\n",
" if mask2 is None: # only mask1 given, outside it show image2 as is\n",
" alpha_image[mask1 == 0] = 0.0\n",
" elif mask1 is None: # only mask2 given, outside it show image1 as is\n",
" alpha_image[mask2 == 0] = 1.0\n",
" else: # both given, only the intersection is blended\n",
" alpha_image[mask1 * (mask2 == 0)] = 1.0\n",
" alpha_image[mask2 * (mask1 == 0)] = 0.0\n",
"\n",
" blended = alpha_blend(image1, image2, alpha_image)\n",
"\n",
" if mask1 is not None and mask2 is not None:\n",
" neither = (mask1 == 0) * (mask2 == 0)\n",
" blended[neither] = 0\n",
" return blended"
]
},
{
Expand All @@ -363,10 +384,10 @@
"# Combine the two volumes\n",
"images_list = [\n",
" (alpha_blend(img1_255, img2_255), \"alpha_blend_standard\"),\n",
" (alpha_blend(img1_255, img2_255, mask1=msk1), \"alpha_blend_mask1\"),\n",
" (alpha_blend(img1_255, img2_255, mask2=msk2), \"alpha_blend_mask2\"),\n",
" (alpha_blend_masked(img1_255, img2_255, mask1=msk1), \"alpha_blend_mask1\"),\n",
" (alpha_blend_masked(img1_255, img2_255, mask2=msk2), \"alpha_blend_mask2\"),\n",
" (\n",
" alpha_blend(img1_255, img2_255, mask1=msk1, mask2=msk2),\n",
" alpha_blend_masked(img1_255, img2_255, mask1=msk1, mask2=msk2),\n",
" \"alpha_blend_mask1_mask2\",\n",
" ),\n",
"]\n",
Expand Down Expand Up @@ -557,7 +578,7 @@
"source": [
"gui.MultiImageDisplay(\n",
" image_list=[\n",
" alpha_blend(img1_255, img2_255, mask2=msk2),\n",
" alpha_blend_masked(img1_255, img2_255, mask2=msk2),\n",
" multiresolution_blend(img1_255, img2_255, msk2),\n",
" ],\n",
" title_list=[\"alpha_blend_mask2\", \"multiresolution_blend_mask2\"],\n",
Expand Down Expand Up @@ -718,7 +739,7 @@
" )\n",
"elif blending_approach == \"mask\":\n",
" combined_volume = sitk.Cast(\n",
" alpha_blend(\n",
" alpha_blend_masked(\n",
" sitk.Compose(img1_255, img1_255, img1_255), overlay_color_img, mask2=roi\n",
" ),\n",
" sitk.sitkVectorUInt8,\n",
Expand Down
1 change: 1 addition & 0 deletions tests/additional_dictionary.txt
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -200,6 +200,7 @@ MeanSquares
MetaDataDictionaryArrayUpdateOn
MetaImageIO
MetricEvaluate
MultiplyImageFilter
Multiresolution
NamedTemporaryFile
Nanometers
Expand Down
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