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docs/itcr_connectivity.md

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This section includes a reference of all ongoing and existing connections between FeTS and other projects funded under the [Informatics Technology for Cancer Research (ITCR)](https://itcr.cancer.gov/) program.
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A connectivity map featuring all ITCR projects can be found [here](https://www.ndexbio.org/#/network/04c0a7e8-af92-11e7-94d3-0ac135e8bacf).
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<!-- vscode-markdown-toc -->
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* [Existing Connections](#ExistingConnections)
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* [DCMTK](#DCMTK)
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* [DCMQI](#DCMQI)
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* [CaPTk](#CaPTk)
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* [Synapse PACS](#SynapsePACS)
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* [TCIA and IDC](#TCIAandIDC)
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* [Ongoing Development](#OngoingDevelopment)
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* [XNAT](#XNAT)
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* [FLAIM](#FLAIM)
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* [PRISM](#PRISM)
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- [<a name='ExistingConnections'></a>Existing Connections](#existing-connections)
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- [<a name='DCMTK'></a>DCMTK](#dcmtk)
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- [<a name='DCMQI'></a>DCMQI](#dcmqi)
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- [<a name='CaPTk'></a>CaPTk](#captk)
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- [<a name='SynapsePACS'></a>Synapse PACS](#synapse-pacs)
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- [<a name='TCIAandIDC'></a>TCIA and IDC](#tcia-and-idc)
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- [<a name='OngoingDevelopment'></a>Ongoing Development](#ongoing-development)
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- [<a name='XNAT'></a>XNAT](#xnat)
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- [<a name='FLAIM'></a>FLAIM](#flaim)
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- [<a name='PRISM'></a>PRISM](#prism)
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## 1. <a name='ExistingConnections'></a>Existing Connections
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## <a name='ExistingConnections'></a>Existing Connections
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### 1.1. <a name='DCMTK'></a>DCMTK
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### <a name='DCMTK'></a>DCMTK
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FeTS uses [DCMTK - DICOM ToolKit (DCMTK)](https://dicom.offis.de/dcmtk.php.en) for DICOM file handling.
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### 1.2. <a name='DCMQI'></a>DCMQI
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### <a name='DCMQI'></a>DCMQI
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FeTS leverages [DICOM for Quantitative Imaging (DCMQI)](http://qiicr.org/dcmqi-guide/tutorials/intro.html) for generating DICOM-Seg files from NIfTI files.
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### 1.3. <a name='CaPTk'></a>CaPTk
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### <a name='CaPTk'></a>CaPTk
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FeTS leverages the [Cancer Imaging Phenomics Toolkit (CaPTk)](https://www.med.upenn.edu/cbica/captk) for integrating CaPTk's current functionality into FeTS.
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### 1.4. <a name='SynapsePACS'></a>Synapse PACS
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### <a name='SynapsePACS'></a>Synapse PACS
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FeTS' performance evaluation metrics are used by [Synapse PACS](https://www.synapse.org/).
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### 1.5. <a name='TCIAandIDC'></a>TCIA and IDC
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### <a name='TCIAandIDC'></a>TCIA and IDC
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Enriching [The Cancer Imaging Archive (TCIA)](https://www.cancerimagingarchive.net/) and [Imaging Data Commons (IDC)](https://datacommons.cancer.gov/repository/imaging-data-commons) data collections with segmentations and radiomic features. Robustness analysis on radiomic features on TCIA data has also been posted back to TCIA.
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## 2. <a name='OngoingDevelopment'></a>Ongoing Development
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## <a name='OngoingDevelopment'></a>Ongoing Development
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### 2.1. <a name='XNAT'></a>XNAT
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### <a name='XNAT'></a>XNAT
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Use FeTS' federated learning functionality for data discovery through [XNAT](https://xnat.org) features through its feature extraction functionality.
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### 2.2. <a name='FLAIM'></a>FLAIM
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### <a name='FLAIM'></a>FLAIM
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Interoperability and privacy preservation algorithmic comparison.
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### 2.3. <a name='PRISM'></a>PRISM
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### <a name='PRISM'></a>PRISM
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Federated learning for segmentation of PRISM data.
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Contact [contact [at] fets.ai](mailto:contact@fets.ai) with any questions.

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