Skip to main content

An open-source toolkit, led by Kitware, Inc., for the segmentation, registration, and analysis of tubes and surfaces in images.

Project description

ITKTubeTK: Tubular Object Extraction, Registration, and Analysis

License

Build, test, package

Documentation Status

Available in C++ and Python for Linux, Windows, and MacOS.

Overview

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images, developed by Kitware, Inc.

Tubes and surfaces, as generalized 1D and 2D manifolds in N-dimensional images, are essential components in a variety of image analysis tasks. Instances of tubular structures in images include blood vessels in magnetic resonance angiograms and b-mode ultrasound images, wires in microscopy images of integrated circuits, roads in aerial photographs, and nerves in confocal microscopy.

A guiding premise of TubeTK is that by focusing on 1D and 2D manifolds we can devise methods that are insensitive to the modality, noise, contrast, and scale of the images being analyzed and to the arrangement and deformations of the objects in them. In particular, we propose that TubeTK's manifold methods offer improved performance for many applications, compared to methods involving the analysis of independent geometric measures (e.g., edges and corners) or requiring complete shape models.

TubeTK offers various interface layers:

  • TubeTK/src: This is the algorithms library. It is the lowest level of access to the methods of TubeTK. It is only available via C++, and it requires considerable expertise to effectively combine and call its methods to do anything useful. Interfacing directly with these algorithms is not recommended and is not well supported. Unit-level testing is performed continuously on these methods.

  • TubeTK/include: This is the ITK interface to select methods in TubeTK/src. This level of interface is intended for ITK users and Python scripts writers. The methods exposed represent a level of modularization that invites experimentation, integration with other toolkits (e.g., Scikit-Learn), and development of processing pipelines that accomplish significant image analysis goals. The interface is available as an ITK Extension and thereby available via Python using Wrapped ITK.

  • TubeTK/examples/Applications: These are optional command-line interface applications. These applications are mostly also available via the TubeTK/include interface, and thereby are available via python. Expansion of ITK will focus on the TubeTK/include directory, and new applications will only rarely be added. These applications are built when the cmake options BUILD_EXAMPLES is enabled. These applications also require SlicerExecutionModel, see https://github.com/Slicer/SlicerExecutionModel.

Using TubeTK

Minimal $ python -c "from itk import TubeTK"

Recommended $ python -c "from itk import TubeTK as ttk"

Acknowledgements

If you find TubeTK to be useful for your work, please cite the following publication when publishing your work:

  • S. R. Aylward and E. Bullitt, "Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction," Medical Imaging, IEEE Transactions on, vol. 21, no. 2, pp. 61-75, 2002.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

itk_tubetk-1.2.1-cp310-cp310-macosx_10_9_x86_64.whl (22.6 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

itk_tubetk-1.2.1-cp39-cp39-win_amd64.whl (8.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

itk_tubetk-1.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (22.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

itk_tubetk-1.2.1-cp39-cp39-macosx_10_9_x86_64.whl (22.6 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

itk_tubetk-1.2.1-cp38-cp38-win_amd64.whl (8.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

itk_tubetk-1.2.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (22.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

itk_tubetk-1.2.1-cp38-cp38-macosx_10_9_x86_64.whl (22.6 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

itk_tubetk-1.2.1-cp37-cp37m-win_amd64.whl (8.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

itk_tubetk-1.2.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (22.2 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

itk_tubetk-1.2.1-cp37-cp37m-macosx_10_9_x86_64.whl (22.6 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file itk_tubetk-1.2.1-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2a691580f8bf3cc1c1d9ce9f6ba7018ad90b088d8bf077b8dfc89a4f09a8760f
MD5 939119c1e16a596754c722e214500861
BLAKE2b-256 88b9eb724b1d62e49980ad4268ce397ae2cdc4898a50146313e2181e6c8af996

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 9a22e8c7f8ee7a329a221a766d55d7d3f24c8d66004a89bc1cd2ff433d4e8364
MD5 f3bc1e90c4caf45fa57b987ae8a2c941
BLAKE2b-256 2f740b04da9964767e74535ad0d90b92bd7c2632c8b940e770166dda0b646132

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2496e78d09de8b3df4263a337a3fd9a605ede94e3ac809e75ac27e7b23e6ac97
MD5 275497906a7687d768f01ece65c4b9fd
BLAKE2b-256 71623e69b859bf2f9fe364238047751f0e4f6b2df3b0b3619e925a862094a1c2

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cdb4b264279e277134d63d7632aea8565a3b027393acc781d40bdba422810d9d
MD5 bdd05b9bcc345c5be6e8df0edd9fdfe4
BLAKE2b-256 2cb1a8202300e35e23fe9c3e12412205b566b88373f7cf59177b18048b0f286d

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 9989621d0cf395273f55c3ea653ab50c20e69fad816890e887d96f4d66ecdf2b
MD5 37b7dd2beb0e77f9bdf6448f5d1746db
BLAKE2b-256 10199b35d7a2b8d8cc9fcbe6a4597a8ef0afee96f6c50778f371f95f2414ba89

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6a80cfce3353d9c331f1796ed8cf5988d762ee4cf470a6734c2096005cddbbb9
MD5 1da6e133c137dc030f7b0803447b92e1
BLAKE2b-256 63ea8ad8e3a6c7979dcaef8e0dc9552df228b24efd4d17869d103f842a30a21f

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 bcaaab96b497ae0506be227b31d7d1d23716f1f6bea100633a40265a73e7087e
MD5 522522d40c64127b0ef05b437d4ecefe
BLAKE2b-256 03b2d65850ed4d123de0aba7b810c51c26df2efd386b044af1105d8df7df06e7

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 6a5c43ca7a9ce9851a5d1c8c30b38d145d65d997b5eae4c13816c472534ae37e
MD5 96eca3054be7da440481a8f6f20c24f4
BLAKE2b-256 f066cca6f0d69dcc3a9af3307acb949fbb81fa05db0610eb8211d3bcc83c1a7b

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b6a34f6abf8abc8a373bd605ecaef84b962b745bdcc0b028cb3907aa531e3142
MD5 86c461879d8ad7cbc47f74dbc69f984e
BLAKE2b-256 bbc6b40baafb14677a4850558aaa826c59b8c7cb807e051557dfe75c53004f12

See more details on using hashes here.

File details

Details for the file itk_tubetk-1.2.1-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_tubetk-1.2.1-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ba407be392b3417da6ccafdc5311f11eb16d5fe3b023a52d6918b3aad9130682
MD5 d18e437b02a5f59534b437f250922a92
BLAKE2b-256 40081f78215e47241ed01243a9ba3904dedac3f186689ecf728a0a8a86787320

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page