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Lesion Sizing Toolkit (LSTK)\n================================\n\n.. image:: https://github.com/InsightSoftwareConsortium/LesionSizingToolkit/actions/workflows/build-test-package.yml/badge.svg\n    :target: https://github.com/InsightSoftwareConsortium/LesionSizingToolkit/actions/workflows/build-test-package.yml\n    :alt: Build Status\n\n.. image:: https://img.shields.io/badge/License-Apache%202.0-blue.svg\n    :target: https://github.com/InsightSoftwareConsortium/LesionSizingToolkit/blob/master/LICENSE\n    :alt: License\n\n\nOverview\n--------\n\nThis is a module for the `Insight Toolkit (ITK) \u003chttps://itk.org\u003e`_ that\nprovides a generic, modular, and extensible architecture for lesion sizing\nalgorithms in medical images as well as a reference algorithm for lung\nsolid lesion segmentation in CT images.\n\nFor more information, see the `Insight Journal article \u003chttps://hdl.handle.net/10380/3369\u003e`_::\n\n  Liu X., Helba B., Krishnan K., Reynolds P., McCormick M., Turner W., Ibáñez L., Yankelevitz D., Avila R.\n  Fostering Open Science in Lung Cancer Lesion Sizing with ITK module LSTK\n  The Insight Journal. January-December. 2012.\n  https://hdl.handle.net/10380/3369\n  https://www.insight-journal.org/browse/publication/869\n\nInstallation\n------------\n\nPython\n^^^^^^\n\nBinary `Python packages \u003chttps://pypi.python.org/pypi/itk-lesionsizingtoolkit\u003e`_\nare available for Linux, macOS, and Windows. They can be installed with::\n\n  python -m pip install --upgrade pip\n  python -m pip install itk-lesionsizingtoolkit\n\nData\n----\nThe project has extensively used the CT lesion data assembled by NIST for the\n`Biochange 2008 Pilot Study \u003chttps://www.itl.nist.gov/iad/894.05/biochange2008/Biochange2008-webpage.htm\u003e`_.\nThe data collection can be obtained via ftp from\n`here \u003cftp://ftp.nist.gov/pub/itl/biochange/Biochange2008/FindingCT_ScansForBiochange2008.htm\u003e`_.\n\nThe team participated in the\n`Volcano'09 Challenge benchmark \u003chttps://www.via.cornell.edu/challenge/\u003e`_.\n\nThe project has also been used on the\n`BioChange 2011 \u003cftp://ftp.nist.gov/pub/itl/biochange/BiochangeChallenge/BiochangeChallengeProtocol.pdf\u003e`_\nstudy. The clinical data used here was chosen from the publicly available\nReference Image Database to Evaluate Therapy Response\n(`RIDER \u003chttps://wiki.nci.nih.gov/display/CIP/RIDER\u003e`_) database and from the\nNIST-generated CT phantom series. 96 pairs of clinical\n`datasets \u003chttps://www.nist.gov/itl/iad/dmg/biochangechallenge.cfm\u003e`_ are\npresent. Datasets have slice thickness varying from 0.63 to 2.5 mm. Kitware's\nresults on the Biochange2011 challenge may be found\n`here \u003chttps://public.kitware.com/LesionSizingKit/index.php/Users/BioChange2011Results\u003e`_.\n\nLicense\n-------\n\nThis software is distributed under the Apache 2.0 license. Please see\nthe *LICENSE* file for details.\n\nAcknowledgements\n----------------\n\nThis work was supported by the Optical Society of America (OSA), the Air Force\nResearch Laboratory (AFRL), and the National Library of Medicine (NLM).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finsightsoftwareconsortium%2Flesionsizingtoolkit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finsightsoftwareconsortium%2Flesionsizingtoolkit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finsightsoftwareconsortium%2Flesionsizingtoolkit/lists"}