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
THE PROGRAM IS DISTRIBUTED IN THE HOPE THAT IT WILL BE USEFUL, BUT WITHOUT ANY WARRANTY OF ANY KIND.
demo site You can convert your own DICOM files or use preloaded sample files from different modality models.
python3 -m venv ecg
. ecg/bin/activate
pip install dicom-ecg-plot
dicom-ecg-plot <inputfile> [--layout=LAYOUT] [--output=FILE|--format=FMT] --minor-grid
dicom-ecg-plot <stu> <ser> <obj> [--layout=LAYOUT] [--output=FILE|--format=FMT] --minor-grid
dicom-ecg-plot --help
Examples:
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.
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 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
.