Image data 

astype(dtype: str | np.dtype) → np.ndarray: Shortcut for np.ndarray.astype().

binary_digitize(threshold: Optional[Union[float, str]] = None)

Convert into a binary image.

Parameters: threshold (float, optional) – Threshold used for segmentation. If given as a string, apply corresponding theshold via Plane.threshold(). Defaults to median.
Returns: New instance of Plane.
Return type: Plane

clear_border(*, object_label: int, fill_val: int, **kwargs) → Plane[source]

Remove objects at the border of the image.

Parameters

object_label (int) – Label of the objects to remove.
fill_val (int) – Cleared objects are set to this value.
**kwargs – These parameters are passed to skimage.segmentation.clear_border().

Returns

New instance of Plane.

Return type

compare_with_digitized(digitized: Union[ndarray, Plane], cmap: Optional[str] = None, **kwargs) → plt.Axes[source]

Compare image with digitized (segmented) image. Returns a plot with the overlay of the digitized image.

Parameters

digitized (numpy.ndarray, Plane) – Digitized image of the same dimensions to overlay
cmap (str) – Matplotlib color map for matplotlib.pyplot.imshow()
**kwargs – These parameters are passed to skimage.color.label2rgb().

Returns

ax

Return type

compare_with_mesh(mesh: TriangleMesh) → plt.Axes[source]

Make a plot comparing the image with the given mesh.

Parameters: mesh (TriangleMesh) – Mesh to compare the image with.
Return type: plt.Axes

compare_with_other(other: Union[ndarray, Plane], cmap: Optional[str] = None, **kwargs) → plt.Axes[source]

Compare image with other image.

Parameters

other (numpy.ndarray, Plane) – Other image of the same dimensions to overlay
cmap (str) – Matplotlib color map for matplotlib.pyplot.imshow()
**kwargs – These parameters are passed to skimage.util.compare_images().

Returns

ax

Return type

crop(left: int, top: int, right: int, bottom: int) → Plane[source]

Crop image to pixel indices.

Parameters

left (int) – Index of pixel delimiting cropping box.
top (int) – Index of pixel delimiting cropping box.
right (int) – Index of pixel delimiting cropping box.
bottom (int) – Index of pixel delimiting cropping box.

Returns

New instance of Plane.

Return type

crop_to_roi(bbox: ndarray) → Plane[source]

Crop plane to rectangle defined by bounding box.

Parameters: bbox ((4,2) numpy.ndarray) – List of points describing region of interest. The bounding box may be rotated.
Returns: Cropped region as Plane object.
Return type: Plane

digitize(bins: Union[list, tuple], **kwargs)

Digitize image.

For more info see numpy.digitize().

Parameters

bins (list, tuple) – List of bin values. Must be monotonic and one-dimensional.
**kwargs – These parameters are passed to numpy.digitize().

Returns

New instance of Plane.

Return type

fft() → Image

Apply fourier transform to image.

Returns: Real component of fourier transform with the zero-frequency component shifted to the center of the spectrum.
Return type: Plane

classmethod from_sitk_image(sitk_image) → Image: Return instance from SimpleITK.Image.

gaussian(sigma: int = 1, **kwargs)

Apply Gaussian blur to image.

Parameters

sigma (int) – Standard deviation for Gaussian kernel.
**kwargs – These parameters are passed to skimage.filters.gaussian().

Returns

New instance of Plane.

Return type

generate_mesh(**kwargs) → TriangleMesh[source]

Generate mesh from binary (segmented) image.

Parameters: **kwargs – Keyword arguments are passed to nanomesh.plane2mesh()
Returns: mesh – Description of the mesh.
Return type: TriangleMesh

invert_contrast()

Invert the contrast of the image.

Returns: out – Inverted image
Return type: Plane

classmethod load(**kwargs) → Image

Load the data. Supported filetypes: .npy, .vol.

For memory mapping, use mmap_mode=’r’. Memory-mapped

files are used for accessing small segments of large files on disk, without reading the entire file into memory. Note that this can still result in some slow / unexpected behaviour with some operations.

More info: numpy.memmap()

Parameters

filename (PathLike) – Name of the file to load.
**kwargs – These parameters are passed on to data readers.

Returns

Instance of Plane.

Return type

Raises

IOError – Raised if the file extension is unknown.

normalize_values()

Rescale values to 0.0 to 1.0.

Returns: out – Normalized image
Return type: Plane

plot(*args, **kwargs)[source]

Plot the image using matplotlib.

Parameters

ax (matplotlib.axes.Axes, optional) – Axes to use for plotting.
title (str, optional) – Title for the plot.
**kwargs – These parameters are passed to matplotlib.pyplot.imshow().

Returns

ax – Instance of matplotlib.axes.Axes

Return type

save(filename: PathLike)

Save the data. Supported filetypes: .npy.

Parameters: filename (Pathlike) – Name of the file to save to.

select_roi(from_points: Optional[ndarray] = None)[source]

Select region of interest in interactive matplotlib figure.

Parameters: from_points ((n, 2) numpy.ndarray, optional) – List of points that are used as anchors for the roi selection.
Returns: roi – Region of interest object. Bounding box is stored in roi.bbox.
Return type: nanomesh.image._roi2d.ROISelector

show(*, ax: Optional[Axes] = None, title: Optional[str] = None, **kwargs) → plt.Axes[source]

Plot the image using matplotlib.

Parameters

ax (matplotlib.axes.Axes, optional) – Axes to use for plotting.
title (str, optional) – Title for the plot.
**kwargs – These parameters are passed to matplotlib.pyplot.imshow().

Returns

ax – Instance of matplotlib.axes.Axes

Return type

threshold(method: str = 'otsu', **kwargs) → float

Compute threshold value using given method.

For more info, see skimage.filters

Parameters

method (str) – Thresholding method to use. Defaults to otsu.
**kwargs – These parameters are passed to threshold method.

Returns

threshold – Threshold value.

Return type

float

to_sitk_image(): Return instance of SimpleITK.Image from Plane.image().

try_all_threshold(**kwargs)[source]

Produce a plot trying all available thresholds using skimage.filters.try_all_threshold().

Parameters: **kwargs – These parameters are passed to skimage.filters.try_all_threshold().

class nanomesh.Volume(image: ndarray)[source]

Bases: Image

Data class for working with 3D (volumetric) image data..

Depending on the dimensions of the image data, the appropriate subclass will be chosen if possible.

Parameters: image ((i,j,k) numpy.array) – N-dimensional numpy array containing image data.

image

The raw image data

Type: (i,j,k) numpy.ndarray

Methods:

`apply`(function, **kwargs)	Apply function to `Volume.image` array.
`astype`(dtype)	Shortcut for `np.ndarray.astype()`.
`binary_digitize`([threshold])	Convert into a binary image.
`digitize`(bins, **kwargs)	Digitize image.
`fft`()	Apply fourier transform to image.
`from_sitk_image`(sitk_image)	Return instance from `SimpleITK.Image`.
`gaussian`([sigma])	Apply Gaussian blur to image.
`generate_mesh`(**kwargs)	Generate mesh from binary (segmented) image.
`invert_contrast`()	Invert the contrast of the image.
`load`(**kwargs)	Load the data.
`normalize_values`()	Rescale values to 0.0 to 1.0.
`plot`(args, *kwargs)	Shortcut for `Volume.show()`.
`save`(filename)	Save the data.
`select_plane`([x, y, z])	Select a slice in the volume.
`select_subvolume`(*[, xs, ys, zs])	Select a subvolume from the current volume.
`show`([renderer])	Show volume using itkwidgets or ipyvolume.
`show_slice`(**kwargs)	Show slice using `nanomesh.image.SliceViewer`.
`threshold`([method])	Compute threshold value using given method.
`to_sitk_image`()	Return instance of `SimpleITK.Image` from `Volume.image()`.

apply(function: Callable, **kwargs)

Apply function to Volume.image array. Return an instance of Volume if the result is of the same dimensions, otherwise return the result of the operation.

Parameters

function (callable) – Function to apply to Volume.image.
**kwargs – Keyword arguments to pass to function.

Returns

New instance of Volume.

Return type

astype(dtype: str | np.dtype) → np.ndarray: Shortcut for np.ndarray.astype().

binary_digitize(threshold: Optional[Union[float, str]] = None)

Convert into a binary image.

Parameters: threshold (float, optional) – Threshold used for segmentation. If given as a string, apply corresponding theshold via Volume.threshold(). Defaults to median.
Returns: New instance of Volume.
Return type: Volume

digitize(bins: Union[list, tuple], **kwargs)

Digitize image.

For more info see numpy.digitize().

Parameters

bins (list, tuple) – List of bin values. Must be monotonic and one-dimensional.
**kwargs – These parameters are passed to numpy.digitize().

Returns

New instance of Volume.

Return type

fft() → Image

Apply fourier transform to image.

Returns: Real component of fourier transform with the zero-frequency component shifted to the center of the spectrum.
Return type: Volume

classmethod from_sitk_image(sitk_image) → Image: Return instance from SimpleITK.Image.

gaussian(sigma: int = 1, **kwargs)

Apply Gaussian blur to image.

Parameters

sigma (int) – Standard deviation for Gaussian kernel.
**kwargs – These parameters are passed to skimage.filters.gaussian().

Returns

New instance of Volume.

Return type

generate_mesh(**kwargs) → MeshContainer[source]

Generate mesh from binary (segmented) image.

Parameters: **kwargs – These parameters are passed to mesh3d.volume2mesh
Returns: Instance of MeshContainer
Return type: MeshContainer

invert_contrast()

Invert the contrast of the image.

Returns: out – Inverted image
Return type: Volume

classmethod load(**kwargs) → Image

Load the data. Supported filetypes: .npy, .vol.

For memory mapping, use mmap_mode=’r’. Memory-mapped

files are used for accessing small segments of large files on disk, without reading the entire file into memory. Note that this can still result in some slow / unexpected behaviour with some operations.

More info: numpy.memmap()

Parameters

filename (PathLike) – Name of the file to load.
**kwargs – These parameters are passed on to data readers.

Returns

Instance of Volume.

Return type

Raises

IOError – Raised if the file extension is unknown.

normalize_values()

Rescale values to 0.0 to 1.0.

Returns: out – Normalized image
Return type: Volume

plot(*args, **kwargs)[source]: Shortcut for Volume.show().

save(filename: PathLike)

Save the data. Supported filetypes: .npy.

Parameters: filename (Pathlike) – Name of the file to save to.

select_plane(x: Optional[int] = None, y: Optional[int] = None, z: Optional[int] = None) → Plane[source]

Select a slice in the volume. Either x, y or z must be specified.

Parameters

x (int, optional) – Index along the x-axis
y (int, optional) – Index along the y-axis
z (int, optional) – Index along the z-axis

Returns

Return plane as Plane.

Return type

Raises

ValueError – If none of the x, y, or z arguments have been specified

select_subvolume(*, xs: Optional[tuple] = None, ys: Optional[tuple] = None, zs: Optional[tuple] = None) → Volume[source]

Select a subvolume from the current volume.

Each range must include a start and stop value, for example:

vol.select_subvolume(xs=(10, 20)) is equivalent to: vol.image[[:,:,10:20]

or

vol.select_subvolume(ys=(20, 25), zs=(40, 50)) is equivalent to: vol.image[[40:50,20:25,:]

Parameters

xs (tuple, optional) – Range to select along y-axis
ys (tuple, optional) – Range to select along y-axis
zs (tuple, optional) – Range to select along z-axis

Returns

Subvolume as Volume

Return type