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https://github.com/marcodebe/dicom-ecg-plot
Dicom ECG Viewer and Converter. Convert to PDF, PNG, JPG, SVG, ...
https://github.com/marcodebe/dicom-ecg-plot
dicom ecg ecg-signal ecg-signal-python pdf python svg viewer wado waveform-visualizer
Last synced: 9 days ago
JSON representation
Dicom ECG Viewer and Converter. Convert to PDF, PNG, JPG, SVG, ...
- Host: GitHub
- URL: https://github.com/marcodebe/dicom-ecg-plot
- Owner: marcodebe
- License: mit
- Created: 2013-08-21T13:17:43.000Z (almost 11 years ago)
- Default Branch: master
- Last Pushed: 2022-10-17T08:42:09.000Z (over 1 year ago)
- Last Synced: 2024-06-04T01:31:31.446Z (28 days ago)
- Topics: dicom, ecg, ecg-signal, ecg-signal-python, pdf, python, svg, viewer, wado, waveform-visualizer
- Language: Python
- Homepage: https://ecg.galliera.it
- Size: 4.12 MB
- Stars: 133
- Watchers: 14
- Forks: 70
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome-dicom - dicom-ecg-plot - Plot ECG data from DICOM ([demo](https://ecg.galliera.it/)). (Libraries / Python)
README
[logo]: https://raw.github.com/marcodebe/dicomecg_convert/master/images/logo.png
![ECG Dicom Convert][logo]
# Dicom ECG plot
A python tool to plot Dicom ECG.
The DICOM file can also be specified as `studyUID seriesUID objectUID` and
retrieved from your WADO server.
Github repository: [here](https://github.com/marcodebe/dicomecg_convert)
**THE PROGRAM IS DISTRIBUTED IN THE HOPE THAT IT WILL BE USEFUL, BUT WITHOUT ANY WARRANTY OF ANY KIND.**
## Online demo
**[demo site](https://ecg.galliera.it)**
You can convert your own DICOM files or use preloaded sample files from different modality models.
## Install
```bash
python3 -m venv ecg
. ecg/bin/activate
pip install dicom-ecg-plot
```
## Usage of `dicom-ecg-plot` tool
```bash
dicom-ecg-plot [--layout=LAYOUT] [--output=FILE|--format=FMT] --minor-grid
dicom-ecg-plot [--layout=LAYOUT] [--output=FILE|--format=FMT] --minor-grid
dicom-ecg-plot --help
```
Examples:
```bash
dicom-ecg-plot anonymous_ecg.dcm -o anonymous_ecg.pdf
dicom-ecg-plot anonymous_ecg.dcm --layout 6x2 --output anonymous_ecg.png
dicom-ecg-plot anonymous_ecg.dcm --format svg > anonymous_ecg.svg
```
The input can be a (dicom ecg) file or the triplet `studyUID, seriesUID,
objectUID`. In the latter case dicom file is downloaded via
[WADO](http://medical.nema.org/Dicom/2011/11_18pu.pdf).
If `--output` is given the ouput format is deduced from the extension of the `FILE`.
If the output file is not given `--format` must be defined.
Supported output formats are: eps, jpeg, jpg, pdf, pgf, png, ps, raw, rgba, svg, svgz, tif, tiff.
By default the 5mm grid is drawn, `--minor-grid` add the minor grid (1mm).
The signals are filtered using a lowpass (40 Hz)
[butterworth filter](http://en.wikipedia.org/wiki/Butterworth_filter)
of order 2.
`LAYOUT` can be one of: 3x4\_1 (that is 3 rows for 4 columns plus 1 row), 3x4, 6x2, 12x1 (default: 3x4_1).
New layouts can be defined adding the corresponding matrix in LAYOUT dictionary in `config.py`.
## References
* http://medical.nema.org/Dicom/supps/sup30_lb.pdf
* http://dicomlookup.com/html/03_03PU.html#LinkTarget_229354
* http://libir.tmu.edu.tw/bitstream/987654321/21661/1/B09.pdf
* [Mortara ECG Conformance Statement](http://www.mortara.com/fileadmin/user_upload/global/Products/Healthcare/DICOM/ELI%20Electrocardiographs%20DICOM%20Conformance%20Statement.pdf)