diff --git a/Python/01_Image_Basics.ipynb b/Python/01_Image_Basics.ipynb
index 712ea9c4..b9b789f9 100644
--- a/Python/01_Image_Basics.ipynb
+++ b/Python/01_Image_Basics.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# SimpleITK Image Basics ![](\"https://mybinder.org/badge_logo.svg\")
\n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " ![\"Colab\"/](\"https://colab.research.google.com/assets/colab-badge.svg\") \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# SimpleITK Image Basics \n",
"\n",
"This document will give a brief orientation to the SimpleITK Image class.\n",
"\n",
@@ -427,7 +458,7 @@
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -441,9 +472,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.5"
+ "version": "3.12.11"
}
},
"nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
}
diff --git a/Python/02_Pythonic_Image.ipynb b/Python/02_Pythonic_Image.ipynb
index a6bc81e8..9f0dfd17 100644
--- a/Python/02_Pythonic_Image.ipynb
+++ b/Python/02_Pythonic_Image.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Pythonic Syntactic Sugar \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Pythonic Syntactic Sugar\n",
"\n",
"The Image Basics Notebook was straight forward and closely follows ITK's C++ interface.\n",
"\n",
@@ -423,7 +454,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.11"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/03_Image_Details.ipynb b/Python/03_Image_Details.ipynb
index 271d44ea..483260d0 100644
--- a/Python/03_Image_Details.ipynb
+++ b/Python/03_Image_Details.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# SimpleITK Images, They're Physical Objects \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# SimpleITK Images, They're Physical Objects\n",
"\n",
"**SimpleITK conventions**:\n",
"* Image access is in x,y,z order, image.GetPixel(x,y,z) or image[x,y,z], with zero based indexing.\n",
@@ -1429,7 +1460,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.10"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/04_Image_Display.ipynb b/Python/04_Image_Display.ipynb
index 2f925c36..91cb5e03 100644
--- a/Python/04_Image_Display.ipynb
+++ b/Python/04_Image_Display.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Image Display \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Image Display\n",
"\n",
"The native SimpleITK approach to displaying images is to use an external viewing program. In the notebook environment it is convenient to use matplotlib to display inline images and if the need arises we can implement some reasonably rich inline graphical user interfaces, combining control components from the ipywidgets package and matplotlib based display.\n",
"\n",
@@ -338,7 +369,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/05_Results_Visualization.ipynb b/Python/05_Results_Visualization.ipynb
index abe06a6c..4969dc0d 100644
--- a/Python/05_Results_Visualization.ipynb
+++ b/Python/05_Results_Visualization.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Visualization of Segmentation and Registration Results \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Visualization of Segmentation and Registration Results\n",
"\n",
"In this notebook we illustrate various ways one can display the results of segmentation and registration algorithms so that they can be easily incorporated into a manuscript or presentation. For interactive data exploration we recommend using dedicated programs (e.g. 3D slicer). \n",
"\n",
@@ -1430,7 +1461,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/10_matplotlibs_imshow.ipynb b/Python/10_matplotlibs_imshow.ipynb
index 9f425d1a..17dfe13b 100644
--- a/Python/10_matplotlibs_imshow.ipynb
+++ b/Python/10_matplotlibs_imshow.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Using `matplotlib` to display inline images \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Using `matplotlib` to display inline images\n",
"\n",
"In this notebook we will explore using `matplotlib` to display images in our notebooks, and work towards developing a reusable function to display 2D,3D, color, and label overlays for SimpleITK images.\n",
"\n",
@@ -15,6 +46,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
+ "collapsed": true,
"jupyter": {
"outputs_hidden": true
}
@@ -85,6 +117,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
+ "collapsed": true,
"jupyter": {
"outputs_hidden": true
}
@@ -132,6 +165,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
+ "collapsed": true,
"jupyter": {
"outputs_hidden": true
}
@@ -338,6 +372,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
+ "collapsed": true,
"jupyter": {
"outputs_hidden": true
}
@@ -540,7 +575,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/11_Progress.ipynb b/Python/11_Progress.ipynb
index 33431b11..c059a61b 100644
--- a/Python/11_Progress.ipynb
+++ b/Python/11_Progress.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Progress Reporting and Command Observers \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Progress Reporting and Command Observers\n",
"\n",
"SimpleITK `Filter`s and other classes derived from `ProcessObject`s have the ability for user code to be executed when certain events occur. This is known as the Command and Observer design patters to implement user callbacks. This allows for the monitoring and abortion of processes as they are being executed.\n",
"\n",
@@ -571,7 +602,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/20_Expand_With_Interpolators.ipynb b/Python/20_Expand_With_Interpolators.ipynb
index 4f39a154..14bfee3c 100644
--- a/Python/20_Expand_With_Interpolators.ipynb
+++ b/Python/20_Expand_With_Interpolators.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Expand With Interpolators \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Expand With Interpolators\n",
"\n",
"This notebook demonstrates the different interpolators available in SimpleITK available for image resampling. Their effect is demonstrated on the Marschner-Lobb image."
]
@@ -142,7 +173,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/21_Transforms_and_Resampling.ipynb b/Python/21_Transforms_and_Resampling.ipynb
index ac7e2edc..18f56bd6 100644
--- a/Python/21_Transforms_and_Resampling.ipynb
+++ b/Python/21_Transforms_and_Resampling.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Transforms and Resampling "
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Transforms and Resampling"
]
},
{
@@ -258,9 +289,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [],
"source": [
"def affine_translate(transform, x_translation=3.1, y_translation=4.6):\n",
@@ -355,9 +384,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [],
"source": [
"def affine_shear(transform, x_shear=0.3, y_shear=0.1):\n",
@@ -670,9 +697,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [],
"source": [
"# Create an image of size [num_samples,1...1], actual size is dependent on the image dimensionality. The pixel\n",
@@ -1221,7 +1246,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/22_Transforms.ipynb b/Python/22_Transforms.ipynb
index e6343e54..c459f803 100644
--- a/Python/22_Transforms.ipynb
+++ b/Python/22_Transforms.ipynb
@@ -4,8 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# SimpleITK Spatial Transformations \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
"\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# SimpleITK Spatial Transformations\n",
"\n",
"**Summary:**\n",
"\n",
@@ -1200,9 +1230,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [],
"source": [
"def composite2affine(composite_transform, result_center=None):\n",
@@ -1492,9 +1520,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [],
"source": [
"# Create a 2D rigid transformation, write it to disk and read it back.\n",
@@ -1622,7 +1648,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/300_Segmentation_Overview.ipynb b/Python/300_Segmentation_Overview.ipynb
index 5ba1b1fe..87283135 100644
--- a/Python/300_Segmentation_Overview.ipynb
+++ b/Python/300_Segmentation_Overview.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Introduction to ITK Segmentation in SimpleITK Notebooks \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Introduction to ITK Segmentation in SimpleITK Notebooks\n",
"\n",
"Goal: To become familiar with basic segmentation algorithms available in ITK, and interactively explore their parameter space.\n",
"\n",
@@ -366,7 +397,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/30_Segmentation_Region_Growing.ipynb b/Python/30_Segmentation_Region_Growing.ipynb
index 373665b8..9bcc791c 100644
--- a/Python/30_Segmentation_Region_Growing.ipynb
+++ b/Python/30_Segmentation_Region_Growing.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Segmentation: Region Growing \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Segmentation: Region Growing\n",
"\n",
"In this notebook we use one of the simplest segmentation approaches, region growing. We illustrate \n",
"the use of three variants of this family of algorithms. The common theme for all algorithms is that a voxel's neighbor is considered to be in the same class if its intensities are similar to the current voxel. The definition of similar is what varies:\n",
@@ -80,6 +111,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
+ "collapsed": true,
"jupyter": {
"outputs_hidden": true
}
@@ -256,7 +288,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/31_Levelset_Segmentation.ipynb b/Python/31_Levelset_Segmentation.ipynb
index 34210aaf..e9469b4f 100644
--- a/Python/31_Levelset_Segmentation.ipynb
+++ b/Python/31_Levelset_Segmentation.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Levelset Segmentation \n"
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Levelset Segmentation"
]
},
{
@@ -185,7 +216,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/32_Watersheds_Segmentation.ipynb b/Python/32_Watersheds_Segmentation.ipynb
index 4405b7fc..3928821f 100644
--- a/Python/32_Watersheds_Segmentation.ipynb
+++ b/Python/32_Watersheds_Segmentation.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Watersheds Segmentation "
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Watersheds Segmentation"
]
},
{
@@ -306,7 +337,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/33_Segmentation_Thresholding_Edge_Detection.ipynb b/Python/33_Segmentation_Thresholding_Edge_Detection.ipynb
index bf9da513..a533524e 100644
--- a/Python/33_Segmentation_Thresholding_Edge_Detection.ipynb
+++ b/Python/33_Segmentation_Thresholding_Edge_Detection.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Segmentation: Thresholding and Edge Detection \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Segmentation: Thresholding and Edge Detection\n",
"\n",
"In this notebook our goal is to estimate the location and radius of spherical markers visible in a Cone-Beam CT volume.\n",
"\n",
@@ -393,7 +424,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/34_Segmentation_Evaluation.ipynb b/Python/34_Segmentation_Evaluation.ipynb
index d410dfb2..ada74379 100644
--- a/Python/34_Segmentation_Evaluation.ipynb
+++ b/Python/34_Segmentation_Evaluation.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Segmentation Evaluation \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Segmentation Evaluation\n",
"\n",
"Evaluating segmentation algorithms is most often done using reference data to which you compare your results. \n",
"\n",
@@ -597,7 +628,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/60_Registration_Introduction.ipynb b/Python/60_Registration_Introduction.ipynb
index 056191e4..3099e42f 100644
--- a/Python/60_Registration_Introduction.ipynb
+++ b/Python/60_Registration_Introduction.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Introduction to SimpleITKv4 Registration \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Introduction to SimpleITKv4 Registration\n",
"\n",
"First, a reminder of some SimpleITK conventions:\n",
"* The dimensionality of images being registered is required to be the same (i.e. 2D/2D or 3D/3D).\n",
@@ -446,7 +477,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.5"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/62_Registration_Tuning.ipynb b/Python/62_Registration_Tuning.ipynb
index 35690413..3381013e 100644
--- a/Python/62_Registration_Tuning.ipynb
+++ b/Python/62_Registration_Tuning.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Registration Settings: Choices, Choices, Choices \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Registration Settings: Choices, Choices, Choices\n",
"\n",
"The performance of most registration algorithms is dependent on a large number of parameter settings. For optimal performance you will need to customize your settings, turning all the knobs to their \"optimal\" position:
\n",
"![](\"knobs.jpg\")
\n",
@@ -389,7 +420,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/64_Registration_Memory_Time_Tradeoff.ipynb b/Python/64_Registration_Memory_Time_Tradeoff.ipynb
index fc18f20a..1a77fd83 100644
--- a/Python/64_Registration_Memory_Time_Tradeoff.ipynb
+++ b/Python/64_Registration_Memory_Time_Tradeoff.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Registration: Memory-Time Trade-off \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Registration: Memory-Time Trade-off\n",
"\n",
"When developing a registration algorithm or when selecting parameter value settings for an existing algorithm our choices are dictated by two, often opposing, constraints:\n",
"\n",
@@ -341,7 +372,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/67_Registration_Semiautomatic_Homework.ipynb b/Python/67_Registration_Semiautomatic_Homework.ipynb
index 3df23df3..d15e5f5a 100644
--- a/Python/67_Registration_Semiautomatic_Homework.ipynb
+++ b/Python/67_Registration_Semiautomatic_Homework.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Improving Registration via Registration:
Semiautomatic Landmark Localization \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Improving Registration via Registration:
Semiautomatic Landmark Localization \n",
"\n",
"This notebook is intentionally missing code, an example of a homework assignment using SimpleITK.\n",
"\n",
@@ -325,7 +356,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/68_Registration_Errors.ipynb b/Python/68_Registration_Errors.ipynb
index d6222922..971173b8 100644
--- a/Python/68_Registration_Errors.ipynb
+++ b/Python/68_Registration_Errors.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Registration Errors, Terminology and Interpretation \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Registration Errors, Terminology and Interpretation\n",
"\n",
"Registration is defined as the estimation of a geometric transformation aligning objects such that the distance between corresponding points on these objects is minimized, bringing the objects into alignment.\n",
"\n",
@@ -391,7 +422,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/69_x-ray-panorama.ipynb b/Python/69_x-ray-panorama.ipynb
index 98584793..25b01e26 100755
--- a/Python/69_x-ray-panorama.ipynb
+++ b/Python/69_x-ray-panorama.ipynb
@@ -4,8 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Creating a Lower Limb Panoramic X-ray \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
"\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Creating a Lower Limb Panoramic X-ray\n",
"\n",
"Measurement of knee alignment is useful for diagnosis of arthritic conditions and for planning and evaluation of surgical interventions. Alignment is measured by the hip-knee-ankle ($HKA$) angle in standing, load bearing, x-ray images. The angle is defined by the femoral and tibial mechanical axes. The femoral axis is defined by the center of the femur head and the mid condylar point. The tibial axis is defined by the center of the tibial plateau to the center of the tibial plafond. \n",
"\n",
@@ -712,7 +742,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/Python/70_Data_Augmentation.ipynb b/Python/70_Data_Augmentation.ipynb
index 032bbfa5..43e982d2 100755
--- a/Python/70_Data_Augmentation.ipynb
+++ b/Python/70_Data_Augmentation.ipynb
@@ -4,7 +4,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Data Augmentation for Deep Learning \n",
+ "\n",
+ " \n",
+ " | \n",
+ " \n",
+ " | \n",
+ " \n",
+ " \n",
+ " | \n",
+ "
\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Setup to enable running the notebook in the Google Colab environment\n",
+ "import os\n",
+ "\n",
+ "if \"COLAB_NOTEBOOK_ID\" in os.environ:\n",
+ " !git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks\n",
+ " %cd SimpleITK-Notebooks/Python\n",
+ " !pip install -q -r requirements.txt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Data Augmentation for Deep Learning\n",
"\n",
"This notebook illustrates the use of SimpleITK to perform data augmentation for deep learning. Note that the code is written so that the relevant functions work for both 2D and 3D images without modification.\n",
"\n",
@@ -1187,7 +1218,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.12"
+ "version": "3.12.11"
}
},
"nbformat": 4,
diff --git a/README.md b/README.md
index f271cba6..a161d8f3 100644
--- a/README.md
+++ b/README.md
@@ -1,82 +1,79 @@
-# SimpleITK Notebooks
-
- [](https://dl.circleci.com/status-badge/redirect/gh/InsightSoftwareConsortium/SimpleITK-Notebooks/tree/main)
- [](http://insightsoftwareconsortium.github.io/SimpleITK-Notebooks/)
- [](https://github.com/psf/black)
-
-
-[SimpleITK](https://simpleitk.org) is an abstraction layer and wrapper around the Insight Segmentation and Registration Toolkit [(ITK)](http://www.itk.org). It is available in the following programming languages: C++, Python, R, Java, C#, Lua, Tcl and Ruby.
-
-This repository contains a collection of Jupyter Notebooks illustrating the use of SimpleITK for educational and research activities. The notebooks demonstrate the use of SimpleITK for interactive image analysis using the Python and R programming languages.
-
-The repository and its contents can be used for:
-1. Learning SimpleITK.
-2. As a basis for your teaching activities.
-3. As a basis for your research activities.
-
-For the latter two use cases you can take advantage of the the repository's infrastructure which supports remote data downloads and notebook testing. These readily facilitate collaborative research.
-
-The animation below is a visualization of a rigid CT/MR registration process
-created with SimpleITK and Python (the [script](Utilities/intro_animation.py) used to generate the frames for the animated gif is found in the repository's Utilities directory).
-
-
-
-# Getting Started
-
-Note that currently SimpleITK with R is only available on Linux and Mac (see the [remotes based installer](https://github.com/SimpleITK/SimpleITKRInstaller)).
-
-1. Language specific details for installing the notebooks is given in the README files in the respective directories ([Python](Python/README.md), [R](R/README.md)). For general information about installing SimpleITK please see the [SimpleITK read-the-docs](https://simpleitk.readthedocs.io/en/latest/) pages.
-
-2. The [SimpleITK API documentation](https://simpleitk.org/doxygen/latest/html/index.html) is based on the C++ implementation which is readily mapped to your language of choice.
-
-3. Learn the general concepts underlying the implementations of segmentation and registration by reading the ([ITK book](https://itk.org/ITKSoftwareGuide/html/)). The relevant portion is "Book 2: Design and Functionality". The ITK API is significantly different from the SimpleITK one, but the general concepts are the same (e.g. combination of optimizer and similarity metric for registration).
-
-4. General notebook setup. By default the contents of the Jupyter notebooks do not occupy the full browser window width. To take advantage of the full window width you can either configure each notebook independently by adding the following into a code cell:
-```
-from IPython.core.display import display, HTML
-display(HTML(""))
-```
-Or apply this configuration to all notebooks by adding the following to
-the custom.css jupyter configuration file:
-```
-.container { width:100% !important; }
-```
-On OSX/Linux this file is found in `~/.jupyter/custom/custom.css` on windows it is
-found in `C:\Users\[your_user_name]\.jupyter\custom\custom.css`.
-
-# Kicking the Tires
-
-Before you clone the repository to your computer you may want to try it out, kick the tires so to speak.
-
-Thanks to the awesome people from the [BinderHub Project](https://github.com/jupyterhub/binderhub)
-you can try out the Python notebooks without installing a thing.
-
-Some caveats:
-
-1. This is a free public service with limited resources, so may not always be available.
-2. Some of our notebooks require significant computational
- resources which may not be available.
-3. All cells that use the sitk.Show() command will generate an exception because they require a Fiji installation. Either ignore this or modify the code for the session.
-
-After you launch binder, go to the Python directory and select the notebook of interest:
-
-[](https://mybinder.org/v2/gh/InsightSoftwareConsortium/SimpleITK-Notebooks/main)
-
-# Contributions from the Community
-
-We encourage contributions from the community!!!
-
-1. Ask questions on the [ITK discourse](https://discourse.itk.org/).
-2. Report issues you encounter (compatibility/bugs) using the
- [GitHub issue reporting system](https://guides.github.com/features/issues/).
-2. Contribute code ([instructions](CONTRIBUTING.md)):
- 1. bug fixes.
- 2. improved versions of existing notebooks, both text and code.
- 3. new notebooks.
-
-# How to Cite
-
-If you find these notebooks or the notebook testing infrastructure useful in your research, support our efforts by citing it as:
-
-Z. Yaniv, B. C. Lowekamp, H. J. Johnson, R. Beare, "SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research", J Digit Imaging., https://doi.org/10.1007/s10278-017-0037-8, 31(3): 290-303, 2018.
+# SimpleITK Notebooks
+
+ [](https://dl.circleci.com/status-badge/redirect/gh/InsightSoftwareConsortium/SimpleITK-Notebooks/tree/main)
+ [](http://insightsoftwareconsortium.github.io/SimpleITK-Notebooks/)
+ [](https://github.com/psf/black)
+
+
+[SimpleITK](https://simpleitk.org) is an abstraction layer and wrapper around the Insight Segmentation and Registration Toolkit [(ITK)](http://www.itk.org). It is available in the following programming languages: C++, Python, R, Java, C#, Lua, Tcl and Ruby.
+
+This repository contains a collection of Jupyter Notebooks illustrating the use of SimpleITK for educational and research activities. The notebooks demonstrate the use of SimpleITK for interactive image analysis using the Python and R programming languages.
+
+The repository and its contents can be used for:
+1. Learning SimpleITK.
+2. As a basis for your teaching activities.
+3. As a basis for your research activities.
+
+For the latter two use cases you can take advantage of the the repository's infrastructure which supports remote data downloads and notebook testing. These readily facilitate collaborative research.
+
+The animation below is a visualization of a rigid CT/MR registration process
+created with SimpleITK and Python (the [script](Utilities/intro_animation.py) used to generate the frames for the animated gif is found in the repository's Utilities directory).
+
+
+
+# Getting Started
+
+Note that currently SimpleITK with R is only available on Linux and Mac (see the [remotes based installer](https://github.com/SimpleITK/SimpleITKRInstaller)).
+
+1. Language specific details for installing the notebooks is given in the README files in the respective directories ([Python](Python/README.md), [R](R/README.md)). For general information about installing SimpleITK please see the [SimpleITK read-the-docs](https://simpleitk.readthedocs.io/en/latest/) pages.
+
+2. The [SimpleITK API documentation](https://simpleitk.org/doxygen/latest/html/index.html) is based on the C++ implementation which is readily mapped to your language of choice.
+
+3. Learn the general concepts underlying the implementations of segmentation and registration by reading the ([ITK book](https://itk.org/ITKSoftwareGuide/html/)). The relevant portion is "Book 2: Design and Functionality". The ITK API is significantly different from the SimpleITK one, but the general concepts are the same (e.g. combination of optimizer and similarity metric for registration).
+
+4. General notebook setup. By default the contents of the Jupyter notebooks do not occupy the full browser window width. To take advantage of the full window width you can either configure each notebook independently by adding the following into a code cell:
+```
+from IPython.core.display import display, HTML
+display(HTML(""))
+```
+Or apply this configuration to all notebooks by adding the following to
+the custom.css jupyter configuration file:
+```
+.container { width:100% !important; }
+```
+On OSX/Linux this file is found in `~/.jupyter/custom/custom.css` on windows it is
+found in `C:\Users\[your_user_name]\.jupyter\custom\custom.css`.
+
+# Kicking the Tires
+
+Before you clone the repository to your computer you may want to try it out, kick the tires so to speak. You can try out the Python notebooks without installing anything. We support two paths that enable this. The first uses [BinderHub](https://github.com/jupyterhub/binderhub) (binder). The second uses [Google Colaboratory](https://colab.google/) (colab). To launch a notebook using one of these services, go to the notebook and click on the shield icon first notebook cell, if it exists.
+
+You can run all of the notebooks in a single Binder environment, just [](https://mybinder.org/v2/gh/InsightSoftwareConsortium/SimpleITK-Notebooks/main) navigate to the Python directory and open a notebook.
+
+Some caveats:
+
+1. Some of the notebooks require significant computational resources which may not be available from these services.
+2. All cells that use the sitk.Show() command will generate an exception because they require a [Fiji](https://imagej.net/software/fiji/) installation. Either ignore this or modify the code for the session.
+3. Binder is a free public service, no login required, with limited resources. As a result it may not always be available or launch quickly.
+4. Colab is a free Google service that requires login.
+5. Colab launches each notebook in an independent environment.
+
+
+# Contributions from the Community
+
+We encourage contributions from the community!!!
+
+1. Ask questions on the [ITK discourse](https://discourse.itk.org/).
+2. Report issues you encounter (compatibility/bugs) using the
+ [GitHub issue reporting system](https://guides.github.com/features/issues/).
+2. Contribute code ([instructions](CONTRIBUTING.md)):
+ 1. bug fixes.
+ 2. improved versions of existing notebooks, both text and code.
+ 3. new notebooks.
+
+# How to Cite
+
+If you find these notebooks or the notebook testing infrastructure useful in your research, support our efforts by citing it as:
+
+Z. Yaniv, B. C. Lowekamp, H. J. Johnson, R. Beare, "SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research", J Digit Imaging., https://doi.org/10.1007/s10278-017-0037-8, 31(3): 290-303, 2018.
diff --git a/tests/additional_dictionary.txt b/tests/additional_dictionary.txt
index cac924f5..7dd32576 100644
--- a/tests/additional_dictionary.txt
+++ b/tests/additional_dictionary.txt
@@ -45,6 +45,7 @@ Clarysse
Clin
Clunie's
CoRR
+Colab
Colocalization
ComposeImageFilter
ComposeScaleSkewVersor