https://github.com/insightsoftwareconsortium/lesionsizingtoolkit
A module for the Insight Toolkit (ITK) that provides a generic, modular, and extensible architecture for lesion sizing algorithms in medical images as well as a reference algorithm for lung solid lesion segmentation in CT images.
https://github.com/insightsoftwareconsortium/lesionsizingtoolkit
computed-tomography insight-toolkit itk itk-module lung-cancer segmentation
Last synced: 4 months ago
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A module for the Insight Toolkit (ITK) that provides a generic, modular, and extensible architecture for lesion sizing algorithms in medical images as well as a reference algorithm for lung solid lesion segmentation in CT images.
- Host: GitHub
- URL: https://github.com/insightsoftwareconsortium/lesionsizingtoolkit
- Owner: InsightSoftwareConsortium
- License: other
- Created: 2013-09-20T15:38:28.000Z (over 12 years ago)
- Default Branch: main
- Last Pushed: 2025-05-28T16:30:09.000Z (8 months ago)
- Last Synced: 2025-09-24T06:32:47.809Z (4 months ago)
- Topics: computed-tomography, insight-toolkit, itk, itk-module, lung-cancer, segmentation
- Language: C++
- Homepage:
- Size: 3.97 MB
- Stars: 10
- Watchers: 9
- Forks: 13
- Open Issues: 4
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
Awesome Lists containing this project
README
The Lesion Sizing Toolkit (LSTK)
================================
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:target: https://github.com/InsightSoftwareConsortium/LesionSizingToolkit/actions/workflows/build-test-package.yml
:alt: Build Status
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:target: https://github.com/InsightSoftwareConsortium/LesionSizingToolkit/blob/master/LICENSE
:alt: License
Overview
--------
This is a module for the `Insight Toolkit (ITK) `_ that
provides a generic, modular, and extensible architecture for lesion sizing
algorithms in medical images as well as a reference algorithm for lung
solid lesion segmentation in CT images.
For more information, see the `Insight Journal article `_::
Liu X., Helba B., Krishnan K., Reynolds P., McCormick M., Turner W., Ibáñez L., Yankelevitz D., Avila R.
Fostering Open Science in Lung Cancer Lesion Sizing with ITK module LSTK
The Insight Journal. January-December. 2012.
https://hdl.handle.net/10380/3369
https://www.insight-journal.org/browse/publication/869
Installation
------------
Python
^^^^^^
Binary `Python packages `_
are available for Linux, macOS, and Windows. They can be installed with::
python -m pip install --upgrade pip
python -m pip install itk-lesionsizingtoolkit
Data
----
The project has extensively used the CT lesion data assembled by NIST for the
`Biochange 2008 Pilot Study `_.
The data collection can be obtained via ftp from
`here `_.
The team participated in the
`Volcano'09 Challenge benchmark `_.
The project has also been used on the
`BioChange 2011 `_
study. The clinical data used here was chosen from the publicly available
Reference Image Database to Evaluate Therapy Response
(`RIDER `_) database and from the
NIST-generated CT phantom series. 96 pairs of clinical
`datasets `_ are
present. Datasets have slice thickness varying from 0.63 to 2.5 mm. Kitware's
results on the Biochange2011 challenge may be found
`here `_.
License
-------
This software is distributed under the Apache 2.0 license. Please see
the *LICENSE* file for details.
Acknowledgements
----------------
This work was supported by the Optical Society of America (OSA), the Air Force
Research Laboratory (AFRL), and the National Library of Medicine (NLM).