This package provides a point-and-click interface for exploring the content of DICOM files. At the moment, the functionality provided is allowing to run DCMTK command-line tools dcmdump and dsrdump, and GDCM gdcmdump tool (gdcmdump provides functionality not available in dcmdump, such as view of the Siemens CSA header).

By using this Atom package instead of running the DCMTK tools in the command line, you can:

• conveniently copy content to the clipboard
• do folding of the indented sections of the dump
• search for content of interest
• add a lot more features using powerful Atom engine ;)

Install the package from Atom > Settings > Install

You can download precompiled DCMTK packages from the official DCMTK page here:

http://dcmtk.org/dcmtk.php.en (look for the "DCMTK 3.6.2 - executable binaries" section)

If you cannot find the binary for your platform, you can use the following links for downloading unofficial DCMTK binaries we prepared. All of them are for 64-bit platforms.

• DCMTK binaries for Windows
• DCMTK binaries for Linux
• DCMTK binaries for macOS

We do not provide the binaries to download packages of GDCM for individual platforms, you can check SourceForge for binaries here: https://sourceforge.net/projects/gdcm/.

After opening a DICOM file in Atom, use context menu to invoke dcmdump, dsrdump or gdcmdump tools.

This package is work in progress. Contributions from the community in the form of encouragements, comments, feature requests, bug repots and pull requests are very welcome!

This package is being developed by Andrey Fedorov as part of the QIICR project activities. QIICR was supported by NIH National Cancer Institute in 2013-2018 by the award U24 CA180918. Please contact Andrey, join QIICR community on Google+, or submit an issue on the issue tracker!

If you found this package useful in preparing an academic publication, we would appreciate if you cite this article:

Fedorov, A., Beichel, R., Kalpathy-Cramer, J., Clunie, D., Onken, M., Riesmeier, J., Herz, C., Bauer, C., Beers, A., Fillion-Robin, J.-C., Lasso, A., Pinter, C., Pieper, S., Nolden, M., Maier-Hein, K., Herrmann, M. D., Saltz, J., Prior, F., Fennessy, F., Buatti, J. & Kikinis, R. Quantitative Imaging Informatics for Cancer Research. JCO Clin Cancer Inform 4, 444–453 (2020). https://ascopubs.org/doi/full/10.1200/CCI.19.00165