# Introduction

![](/files/-L-1m0u9OKQxEXZrRi53)

## Overview

`QuantitativeReporting` is an [3D Slicer](http://slicer.org) extension to support segmentation-based measurements with DICOM-based import and export of the results. The extension comes with a variety of plugins for loading DICOM Segmentations, Parametric Maps and Structured reports into Slicer.

### Capabilities of `QuantitativeReporting` Include:

* Loading of DICOM image series (CT, MRI)
* Interactive image annotation using automated segmentation tools of 3D Slicer
* Automatic calculation of segmentation-based measurements statistics
* Saving of the segmentation-based measurements as a linked collection of DICOM objects: 
  * DICOM Structured Report [TID 1500](http://dicom.nema.org/medical/dicom/current/output/chtml/part16/chapter_A.html#sect_TID_1500) 
  * DICOM Segmentation 
* Loading and display of the volumetric measurements from SR+SEG

![](/files/-L-1m0uAj-XP8HrNBfTY)

#### Support

Please feel free to contact us for questions, feedback, suggestions, bugs, or you can create issues in the issue tracker: <https://github.com/QIICR/QuantitativeReporting/issues>

* [Andrey Fedorov](https://github.com/fedorov) <fedorov@bwh.harvard.edu>
* [Christian Herz](https://github.com/che85) <cherz@bwh.harvard.edu>

#### Acknowledgments

This work is supported in part the National Institutes of Health, National Cancer Institute, Informatics Technology for Cancer Research (ITCR) program, grant Quantitative Image Informatics for Cancer Research (QIICR) (U24 CA180918, PIs Kikinis and Fedorov).

#### References

1. [Informatics Technology for Cancer Research (ITCR)](http://itcr.nci.nih.gov/)
2. [Quantitative Imaging Network (QIN)](http://imaging.cancer.gov/programsandresources/specializedinitiatives/qin)
3. Fedorov A, Clunie D, Ulrich E, Bauer C, Wahle A, Brown B, et al. DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ \[Internet]. 2016;4:e2057. Available from: <http://dx.doi.org/10.7717/peerj.2057>
4. Sample data: [TCIA QIN-HEADNECK](https://wiki.cancerimagingarchive.net/display/Public/QIN-HEADNECK) collection


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://qiicr.gitbook.io/quantitativereporting-guide/master.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.