### Install Dependencies

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Installs the necessary itk-minimalpathextraction library for the example. Ensure itkwidgets is installed separately if needed.

```python
# Install dependencies for this example
# Note: This does not include itkwidgets, itself
import sys
!{sys.executable} -m pip install --upgrade itk-minimalpathextraction
```

--------------------------------

### Setup Image Interpolator

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Initializes a linear interpolator for the DSA speed image, which will be used by the cost function.

```python
interpolator = itk.LinearInterpolateImageFunction.New(dsa_speed)
interpolator.SetInputImage(dsa_speed)
```

--------------------------------

### Visualize Path with Waypoints

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Visualizes the DSA speed image and overlays the extracted start, way, and end points with specified colors.

```python
view(dsa_speed,
     point_sets=[start_point, way_points, end_point],
     point_set_colors=[(1.0,0.0,0.0), (1.0,0.0,0.5), (1.0,0.0,0.8)],
     ui_collapsed=True)
```

--------------------------------

### Parse Path Information from File

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Parses a path file to extract start, end, and waypoints, storing them in a PathInformationType object.

```python
path_information = PathInformationType.New()
with open(path_file, 'r') as fp:
    for line in fp:
        line = line.replace("Path: ", "")
        line = line.replace("[", "").strip()
        points = line.split(']')[:-1]
        way_points = np.empty((0, 2))
        for index, point in enumerate(points):
            point_float = PointType()
            point_float[0] = float(point.split(',')[0])
            point_float[1] = float(point.split(',')[1])
            if index == 0:
                start_point = np.array(point_float).reshape(1,2)
                path_information.SetStartPoint(point_float)
            elif index == len(points)-1:
                end_point = np.array(point_float).reshape(1,2)
                path_information.SetEndPoint(point_float)
            else:
                way_points = np.vstack((way_points, np.array(point_float).reshape(1,2)))
                path_information.AddWayPoint(point_float)
```

--------------------------------

### Add Path Information to Filter

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Adds the parsed path information (start, end, and waypoints) to the path filter.

```python
path_filter.AddPathInformation(path_information)
```

--------------------------------

### Configure Optimizer

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Sets up the RegularStepGradientDescentOptimizer with parameters for maximum and minimum step lengths, relaxation factor, and number of iterations.

```python
spacing = list(dsa_speed.GetSpacing())
min_spacing = min(spacing)
step_length_factor = 0.25
step_length_relax = 0.5
number_of_iterations = 4000

optimizer = itk.RegularStepGradientDescentOptimizer.New(
    number_of_iterations=number_of_iterations,
    maximum_step_length=1.0*step_length_factor*min_spacing,
    minimum_step_length=0.5*step_length_factor*min_spacing,
    relaxation_factor=step_length_relax)
```

--------------------------------

### Initialize Path Extraction Filter

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Creates a SpeedFunctionToPathFilter, setting the cost function, optimizer, and termination value. The input image is also set.

```python
termination_value = 3.0
path_filter = itk.SpeedFunctionToPathFilter.New(dsa_speed,
                                               cost_function=cost_function,
                                               optimizer=optimizer,
                                               termination_value=termination_value)
path_filter.SetInput(dsa_speed)
```

--------------------------------

### CMakeLists.txt Configuration for ITK MinimalPathExtraction

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/CMakeLists.txt

This snippet shows the basic CMake configuration to build an executable that uses the ITK MinimalPathExtraction module. It ensures the necessary ITK components are found and linked.

```cmake
cmake_minimum_required(VERSION 3.10.2)
project(MinimalPathExtractionExamples)

find_package(ITK REQUIRED
  COMPONENTS MinimalPathExtraction
    ITKIOImageBase
    ITKImageFunction
    ITKOptimizers
    ITKPath
    ITKIOMeta
    ITKIOPNG
    ITKIOJPEG
    )

include(${ITK_USE_FILE})

add_executable(MinimalPathExamples example.cxx)
target_link_libraries(MinimalPathExamples ${ITK_LIBRARIES})
```

--------------------------------

### Execute Path Extraction

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Runs the path extraction process using the configured filter and measures the execution time.

```python
%time path_filter.Update()
```

--------------------------------

### Import Libraries

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Imports essential libraries including ITK for image processing, NumPy for numerical operations, and itkwidgets for visualization.

```python
from pathlib import Path

import itk
import numpy as np

from itkwidgets import view
```

--------------------------------

### Visualize Minimal Path on DSA Image

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Displays the original DSA image and overlays the extracted minimal path as a geometry.

```python
view(dsa, geometries=path, ui_collapsed=True)
```

--------------------------------

### Define Data Directory

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Sets the directory path where input test data is located.

```python
DATA_DIR = Path('../test/Input')
```

--------------------------------

### Display Path File Content

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Reads and displays the content of a path file, which defines waypoints for path extraction.

```python
path_file = str(DATA_DIR / 'Real-DSA-01.path')
!cat {path_file}
```

--------------------------------

### Load and View DSA Speed Image

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Loads the corresponding speed image for the DSA data and visualizes it.

```python
dsa_speed = itk.imread(str(DATA_DIR / 'Real-DSA-01-Speed-02.mhd'))
view(dsa_speed, ui_collapsed=True)
```

--------------------------------

### Configure Cost Function

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Creates a SingleImageCostFunction using the previously set up interpolator. This function evaluates the cost of traversing the image.

```python
cost_function = itk.SingleImageCostFunction[type(dsa_speed)].New(interpolator=interpolator)
cost_function.SetInterpolator(interpolator)
```

--------------------------------

### Load and View DSA Image

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Loads a Digital Subtraction Angiography (DSA) image using ITK and displays it using itkwidgets.

```python
dsa = itk.imread(str(DATA_DIR / 'Real-DSA-01.jpg'))
view(dsa, ui_collapsed=True)
```

--------------------------------

### Retrieve and Count Path Vertices

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Retrieves the extracted minimal path from the filter and counts the number of vertices it contains.

```python
path = path_filter.GetOutput(0)
path.GetVertexList().Size()
```

--------------------------------

### Define Path Types

Source: https://github.com/insightsoftwareconsortium/itkminimalpathextraction/blob/main/examples/DigitalSubtractionAngiographyVesselPath.ipynb

Defines the necessary ITK types for points and path information, specifying a 2D double-precision point type.

```python
PointType = itk.Point[itk.D,2]
PathInformationType = itk.SpeedFunctionPathInformation[PointType]
```

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