| \n",
" | \n",
"\n",
"\n",
"
| \n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from skimage.io import imread\n",
"from skimage.filters import threshold_otsu\n",
"from skimage.measure import label, regionprops\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# Load the image\n",
"image = imread('blobs.tif')\n",
"\n",
"# Segment the nuclei-like objects\n",
"threshold = threshold_otsu(image)\n",
"binary = image > threshold\n",
"labels = label(binary)\n",
"\n",
"# Measure the area of each label\n",
"properties = regionprops(labels, image)\n",
"\n",
"# Display the image with the area printed on top of each label\n",
"plt.imshow(image, cmap='gray')\n",
"for prop in properties:\n",
" y, x = prop.centroid\n",
" plt.text(x, y, str(int(prop.area)), color='red', ha='center', va='center')\n",
"plt.axis('off')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a448da9b-69c5-4fa4-b250-ea64019db36f",
"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"I will expand the labels in the segmented label image by 4 pixels and display the resulting label image alone.\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%bob\n",
"Take the segmented label image and expand the labels by 4 pixels. Show the resulting label image alone."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "1ffccbef-0745-4dc4-982b-5ef8fd6513e2",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
"
],
"text/plain": [
"StackViewNDArray([[0, 0, 0, ..., 5, 5, 5],\n",
" [0, 0, 0, ..., 5, 5, 5],\n",
" [0, 0, 0, ..., 5, 5, 5],\n",
" ...,\n",
" [0, 0, 0, ..., 0, 0, 0],\n",
" [0, 0, 0, ..., 0, 0, 0],\n",
" [0, 0, 0, ..., 0, 0, 0]])"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from skimage.segmentation import expand_labels\n",
"import stackview\n",
"\n",
"expanded_labels = expand_labels(labels, distance=4)\n",
"stackview.insight(expanded_labels)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "930b7ce5-db68-4ccb-9ca8-6b45eccefac2",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
| \n",
" | \n",
"\n",
"\n",
"
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"