# Handling of compressed image data

How to get image data from compressed DICOM images

## Preconditions

To be able to decompress compressed DICOM image data, you need to have one or more packages installed that are able to handle this kind of data. `pydicom` detects the installed packages and provides image data handlers that use the available packages.

The following packages can be used with `pydicom`:

- GDCM - this is the package that supports most compressed formats
- Pillow, ideally with `jpeg` and `jpeg2000` plugins
- jpeg_ls

Note that you always need the NumPy package to be able to handle image data.

Caution

We rely on the image handling capacity of the mentioned packages and cannot guarantee the correctness of the generated uncompressed images. Be sure to verify the correctness of generated images using other means before you use them for medical purposes.

## Supported Transfer Syntaxes

To get the transfer syntax of a dataset you can do:

    >>> from pydicom import dcmread
    >>> ds = dcmread('path/to/dicom/file')
    >>> ds.file_meta.TransferSyntaxUID
    '1.2.840.10008.1.2.1'

As far as we have been able to verify, the following transfer syntaxes are handled by the given packages:

Transfer Syntax | NumPy | NumPy + JPEG-LS | NumPy + GDCM | NumPy + Pillow
--- | --- | --- | --- | ---
Name | UID
Explicit VR Little Endian | 1.2.840.10008.1.2.1 | ✓ | ✓ | ✓ | ✓
Implicit VR Little Endian | 1.2.840.10008.1.2 | ✓ | ✓ | ✓ | ✓
Explicit VR Big Endian | 1.2.840.10008.1.2.2 | ✓ | ✓ | ✓ | ✓
Deflated Explicit VR Little Endian | 1.2.840.10008.1.2.1.99 | ✓ | ✓ | ✓ | ✓
RLE Lossless | 1.2.840.10008.1.2.5 | ✓ | ✓ | ✓ | ✓
JPEG Baseline (Process 1) | 1.2.840.10008.1.2.4.50 |  |  | ✓ | ✓1
JPEG Extended (Process 2 and 4) | 1.2.840.10008.1.2.4.51 |  |  | ✓ | ✓1
JPEG Lossless (Process 14) | 1.2.840.10008.1.2.4.57 |  |  | ✓ |
JPEG Lossless (Process 14, SV1) | 1.2.840.10008.1.2.4.70 |  |  | ✓ | ✓3
JPEG LS Lossless | 1.2.840.10008.1.2.4.80 |  | ✓ | ✓ |
JPEG LS Lossy | 1.2.840.10008.1.2.4.81 |  | ✓ | ✓ |
JPEG2000 Lossless | 1.2.840.10008.1.2.4.90 |  |  | ✓ | ✓2
JPEG2000 | 1.2.840.10008.1.2.4.91 |  |  | ✓ | ✓2
JPEG2000 Multi-component Lossless | 1.2.840.10008.1.2.4.92 |  |  |  |
JPEG2000 Multi-component | 1.2.840.10008.1.2.4.93 |  |  |  |

1 only with JpegImagePlugin
2 only with Jpeg2KImagePlugin
3 not supported for > 8 bit

## Usage

To use decompressed image data from compressed DICOM images, you have two options:

- use `decompress()` on the dataset to convert it in-place and work with the pixel data as described before
- get an uncompressed copy of the pixel data as a NumPy array using `Dataset.pixel_array` without touching the original dataset

Note

Using `decompress()` adapts the transfer syntax of the data set, but not the Photometric Interpretation. The Photometric Interpretation may not match the pixel data, depending on the used decompression handler.