dcmqi : A hands-on
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Andrey Fedorov, Brigham and Women's Hospital
Motivation
DICOM is the format of images that we get from clinical equipmentQuantitative imaging is the extraction of quantifiable features from medical imagesImages are pixels + metadata in the DICOM-defined format
Metadata is typically lost while converting from DICOM into research formats
Metadata is most often missing in the results produced by the image analysis tools
dcmqi = DICOM for Quantitative Imaging
conversion of common derived image data types produced by quantitative image analysis
segmentations, parametric maps, scalar measurements over segmented regions of interest
command line converters
C++ Application Programming Interface
schemas for metadata
This tutorial will teach you how to ...
set up your computer to use dcmqi
convert basic segmentation into DICOM
visualize DICOM images and segmentations
What you will need to repeat the steps in the video
Docker 3D Slicer Atom If you are using Windows, we recommend PowerShell for running
Docker commands
What we tested
Tutorial was recorded on a Mac OS X 10.10.5 Yosemite
We also tested Docker and 3D Slicer operation on Windows 10 Pro and
Ubuntu 14.04
Docker requires Windows 10 Pro 64-bit or above!
Configuration of the Atom editor to enable dicom-dump on Linux and
Windows is a bit different - please see these instructions
Video 2: First conversion task
VIDEO
Note: the tutorial was recorded in a Mac environment! If you are
using Windows, your command line format will have to be different! See our documentation for
details!
What you will need to repeat the steps in the video
Video 3: Visualizing the result
VIDEO
What you will need to repeat the steps in the video
TCIA collection TCIA-HEADNECK subject 139 (don't forget to unzip the top-level package and all the compressed files underneath!)You can also download this dataset using TCIA Browser module of 3D Slicer that we installed in the Part 1 of the tutorial
Want to know more?
Check out user guide for detailed documentation of all of the dcmqi converters!
Give us your feedback, share your experience, get help:
Let us know what we can do to improve dcmqi!