# Writing DICOM Files

How to write DICOM files using pydicom.

## Introduction

Probably the most common use of pydicom is to read an existing DICOM file, alter some items, and write it back out again. The first example in Introduction to pydicom shows how to do this.

If you need to create a DICOM file from scratch, there are a couple of ways of going about this: using the “codify” script, or creating a Dataset directly and populating it.

Warning

To be truly DICOM compliant, certain data elements will be required in the file meta information, and in the main dataset. Also, you should create your own UIDs, implementation name, and so on.

## Using the Codify Script

In the pydicom ‘util’ folder, there is a script called codify.py. It takes an existing DICOM file, and produces python code. The python code uses pydicom to produce a copy of the original file again, when the code is run.

In other words: pydicom has a tool that can automatically generate well-designed python code for you - code that creates DICOM files. The only requirement is that you have an existing DICOM file that looks approximately like the one you need. You can then use the code as a model to work from. The tool is especially useful with Sequences, which can be tricky to code correctly.

Warning

The code produced by codify will contain all the information in the original file, which may include private health information or other sensitive information. If the code is run, the resulting dicom file will also contain that information. You may want to consider using de-identified dicom files with codify, or handling the output files according to your requirements for sensitive information.

One issue to be aware of is that codify will not create code for large items like pixel data. Instead it creates a line like:

    ds.PixelData = # XXX Array of 524288 bytes excluded

In that case, the code will produce a syntax error when run, and you will have to edit the code to supply a valid value.

Note

The –exclude-size parameter can set the maximum size of the data element value that is coded. Data elements bigger than that will have the syntax error line as shown above.

One potential disadvantage of codify, depending on your use case, is that it does not create loops. If you have, say, 30 items in a Sequence, codify will produce code that makes them one at a time. Code you wrote by hand would likely create them in a loop, because most of the code needed is quite repetitive. If you want to switch to a loop, you could use the first item’s code as a starting point, and modify as needed, deleting the code for the other individual items.

Codify could also be called from code, rather than as a script; you can look at the codify.py source and the `code_file` function for a starting point for that.

To call codify as a script, use:

    python <path-to-pydicom-util folder>/codify.py -s savename dicom-file createdicomfile.py

The -s parameter is optional, but if present, is followed by a save filename (the DICOM filename that would be created when the code is run). If not specified, then a modified version of the input dicom filename is used. The output file (createdicomfile.py in the example above) is optional. If nothing is specified, the code is written to standard output.

There is also a parameter `--exclude-private` if you don’t want private data elements to be included in the generated code.

You can also call codify with `--help` to see details of all the parameters.

## Writing a file from Scratch

The codify tool, described in the previous section, is a good starting point for pydicom code, but if you can’t (or don’t want to) use that tool, then you can certainly write code from scratch to make a complete DICOM file using pydicom.

It’s not particularly difficult, but to produce a valid DICOM file requires specific items to be created. A basic example of that is available in the example file Write DICOM data.

Just don’t forget the warnings in the Introduction section above, and be sure to create all the required DICOM data elements.