medialaxis3d 1.0.3
Module to perform 3D skeletonization using Medial Axis Transform
Requires Python: >=3.8
Keywords: MAT, skeletonization, 3D

# medialaxis3d

This package extends the [scikit-image](https://scikit-image.org/) function [medial_axis](https://scikit-image.org/docs/stable/api/skimage.morphology.html#skimage.morphology.medial_axis)
to the 3D case.

## Install

```bash
pip install medialaxis3d
```

### Dependencies
Automatically installed with `pip`:

- `numpy`
- `scipy`
- `cython`

Optional only for visualization

- `napari`

## Documentation 

WIP

## Quickstart

Use it without returning the medial distance.

```Python
>>> import numpy as np
>>> import skimage as ski
>>> import medialaxis3d
>>> import napari

>>> rng = np.random.default_rng(1278)

>>> image = ski.data.binary_blobs(length = 128,
>>>                           blob_size_fraction = 0.2,
>>>                           n_dim = 3,
>>>                           volume_fraction = 0.6,
>>>                           rng = rng)

>>> skeleton = medialaxis3d.medial_axis_3d(image, 
>>>                                        return_distance = False, 
>>>                                        size = 8, 
>>>                                        rng = rng)

>>> viewer = napari.Viewer()
>>> viewer.add_image(image, 
>>>                  rendering = "attenuated_mip", 
>>>                  attenuation = 0.5, 
>>>                  scale = [1, 1, 1])
>>> viewer.add_image(skeleton, 
>>>                  interpolation3d = "nearest", 
>>>                  colormap = "magenta", 
>>>                  scale = [1, 1, 1])
>>> napari.run()
```

<img src="https://raw.githubusercontent.com/jb-sharp/medialaxis3d/main/screenshots/example_nodist1.png" width="32%"/> <img src="https://raw.githubusercontent.com/jb-sharp/medialaxis3d/main/screenshots/example_nodist2.png" width="32%"/> <img src="https://raw.githubusercontent.com/jb-sharp/medialaxis3d/main/screenshots/example_nodist3.png" width="32%"/>

or use it to return the distance as well.

```Python
>>> import numpy as np
>>> import skimage as ski
>>> import medialaxis3d
>>> import napari

>>> rng = np.random.default_rng(1278)
>>> image = ski.data.binary_blobs(length = 128,
                              blob_size_fraction = 0.2,
                              n_dim = 3,
                              volume_fraction = 0.6,
                              rng = rng)

>>> skeleton, distance = medialaxis3d.medial_axis_3d(image, 
>>>                                                  return_distance = True, 
>>>                                                  size = 8, 
>>>                                                  rng = rng)

>>> viewer = napari.Viewer()
>>> viewer.add_image(image, 
>>>                  rendering = "attenuated_mip", 
>>>                  attenuation = 0.5, 
>>>                  scale = [1, 1, 1])
>>> viewer.add_image(skeleton*distance, 
>>>                  interpolation3d = "nearest", 
>>>                  colormap = "turbo", 
>>>                  scale = [1, 1, 1])
>>> napari.run()
```

<img src="https://raw.githubusercontent.com/jb-sharp/medialaxis3d/main/screenshots/example_nodist1.png" width="32%"/> <img src="https://raw.githubusercontent.com/jb-sharp/medialaxis3d/main/screenshots/example_dist2.png" width="32%"/> <img src="https://raw.githubusercontent.com/jb-sharp/medialaxis3d/main/screenshots/example_dist3.png" width="32%"/>