pyvista.examples.downloads.download_whole_body_ct_female#
- download_whole_body_ct_female(load=True, *, high_resolution=False)[source]#
Download a CT image of a female subject with 117 segmented anatomic structures.
This dataset is subject
's1380'
from the TotalSegmentator dataset, version 2.0.1, available from zenodo. See the original paper for details:Jakob Wasserthal et al., “TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images,” Radiology, Jul. 2023, doi: https://doi.org/10.1148/ryai.230024.
The dataset is loaded as a
MultiBlock
with three blocks:'ct'
:ImageData
with CT data.'segmentations'
:MultiBlock
with 117ImageData
blocks, each containing a binary segmentation label. The blocks are named by their anatomic structure (e.g.'heart'
) and are sorted alphabetically. See the examples below for a complete list label names.'label_map'
:ImageData
with a label map array. The label map is an alternative representation of the segmentation where the masks are combined into a single scalar array.Note
The label map is not part of the original data source.
Licensed under Creative Commons Attribution 4.0 International.
Added in version 0.45: Three dictionaries are now included with the dataset’s
user_dict
to map label names to ids and colors:'names_to_colors'
: maps segment names to 8-bit RGB colors.'names_to_ids'
: maps segment names to integer ids used by the label map.'ids_to_colors'
: maps label ids to colors.
The label ids are the ids used by the included label map.
Changed in version 0.45: A downsampled version of this dataset with dimensions
(160, 160, 273)
is now returned. Previously, a high-resolution version with dimensions(320, 320, 547)
was returned. Usehigh_resolution=True
for the high-resolution version.- Parameters:
- loadbool, default:
True
Load the dataset after downloading it when
True
. Set this toFalse
and only the filename will be returned.- high_resolutionbool, default:
False
Set this to
True
to return a high-resolution version of this dataset. By default, aresampled
version with a0.5
sampling rate is returned.Added in version 0.45.
- loadbool, default:
- Returns:
pyvista.MultiBlock
orstr
DataSet or filename depending on
load
.
Examples
Load the dataset.
>>> from pyvista import examples >>> import pyvista as pv >>> dataset = examples.download_whole_body_ct_female()
Get the names of the dataset’s blocks.
>>> dataset.keys() ['ct', 'segmentations', 'label_map']
Get the CT image.
>>> ct_image = dataset['ct'] >>> ct_image ImageData (...) N Cells: 6825870 N Points: 6937600 X Bounds: 7.500e-01, 4.778e+02 Y Bounds: 7.500e-01, 4.778e+02 Z Bounds: 7.528e-01, 8.122e+02 Dimensions: 160, 160, 271 Spacing: 3.000e+00, 3.000e+00, 3.006e+00 N Arrays: 1
Get the segmentation label names and show the first three.
>>> segmentations = dataset['segmentations'] >>> label_names = segmentations.keys() >>> label_names[:3] ['adrenal_gland_left', 'adrenal_gland_right', 'aorta']
Get the label map and show its data range.
>>> label_map = dataset['label_map'] >>> label_map.get_data_range() (np.uint8(0), np.uint8(117))
Show the
'names_to_colors'
dictionary with RGB colors for each segment.>>> dataset.user_dict['names_to_colors']
Show the
'names_to_ids'
dictionary with a mapping from segment names to segment ids.>>> dataset.user_dict['names_to_ids']
Create a surface mesh of the segmentation labels.
>>> labels_mesh = label_map.contour_labels()
Color the surface using
color_labels()
. Use the'ids_to_colors'
dictionary included with the dataset to map the colors.>>> colored_mesh = labels_mesh.color_labels( ... colors=dataset.user_dict['ids_to_colors'] ... )
Plot the CT image and segmentation labels together.
>>> pl = pv.Plotter() >>> _ = pl.add_volume( ... ct_image, ... cmap='bone', ... opacity='sigmoid_7', ... show_scalar_bar=False, ... ) >>> _ = pl.add_mesh(colored_mesh) >>> pl.view_zx() >>> pl.camera.up = (0, 0, 1) >>> pl.camera.zoom(1.3) >>> pl.show()
See also
- Visualize Anatomical Groups
Additional examples using this dataset.
- Whole Body Ct Female Dataset
See this dataset in the Dataset Gallery for more info.
- Whole Body Ct Male Dataset
Similar dataset of a male subject.
- Medical Datasets
Browse other medical datasets.
- Volume With Segmentation Mask
See additional examples using this dataset.