Conversion of medical images to MHA and TIFF.
Project description
panimg
NOT FOR CLINICAL USE
Conversion of medical images to MHA and TIFF.
Requires Python 3.7, 3.8 or 3.9.
libvips-dev
and libopenslide-dev
must be installed on your system.
Under the hood we use:
SimpleITK
pydicom
pylibjpeg
Pillow
openslide-python
pyvips
oct-converter
Usage
panimg
takes a folder and tries to convert the containing files to MHA or TIFF.
By default, it will try to convert files from subdirectories as well.
To only convert files in the top level directory, set recurse_subdirectories
to False
.
It will try several strategies for loading the contained files, and if an image is found it will output it to the output folder.
It will return a structure containing information about what images were produced, what images were used to form the new images, image metadata, and any errors from any of the strategies.
NOTE: Alpha software, do not run this on folders you do not have a backup of.
from pathlib import Path
from panimg import convert
result = convert(
input_directory=Path("/path/to/files/"),
output_directory=Path("/where/files/will/go/"),
)
Command Line Interface
panimg
is also accessible from the command line.
Install the package from pip as before, then you can use:
NOTE: Alpha software, do not run this on folders you do not have a backup of.
panimg convert /path/to/files/ /where/files/will/go/
To access the help test you can use panimg -h
.
Supported Formats
Input | Output | Strategy | Notes |
---|---|---|---|
.mha |
.mha |
metaio |
|
.mhd with .raw or .zraw |
.mha |
metaio |
|
.dcm |
.mha |
dicom |
|
.nii |
.mha |
nifti |
|
.nii.gz |
.mha |
nifti |
|
.nrrd |
.mha |
nrrd |
1 |
.e2e |
.mha |
oct |
2 |
.fds |
.mha |
oct |
2 |
.fda |
.mha |
oct |
2 |
.png |
.mha |
fallback |
3 |
.jpeg |
.mha |
fallback |
3 |
.tiff |
.tiff |
tiff |
|
.svs (Aperio) |
.tiff |
tiff |
|
.vms , .vmu , .ndpi (Hamamatsu) |
.tiff |
tiff |
|
.scn (Leica) |
.tiff |
tiff |
|
.mrxs (MIRAX) |
.tiff |
tiff |
|
.biff (Ventana) |
.tiff |
tiff |
1: Detached headers are not supported.
2: Only OCT volume(s), no fundus image(s) will be extracted.
3: 2D only, unitary dimensions
Post Processors
You can also define a set of post processors that will operate on each output file.
We provide a dzi_to_tiff
post processor that is enabled by default, which will produce a DZI file if it is able to.
To customise the post processors that run you can do this with
result = convert(..., post_processors=[...])
Using Strategies Directly
If you want to run a particular strategy directly which returns a generator of images for a set of files you can do this with
files = {f for f in Path("/foo/").glob("*.dcm") if f.is_file()}
try:
for result in image_builder_dicom(files=files):
sitk_image = result.image
process(sitk_image) # etc. you can also look at result.name for the name of the file,
# and result.consumed_files to see what files were used for this image
except UnconsumedFilesException as e:
# e.errors is keyed with a Path to a file that could not be consumed,
# with a list of all the errors found with loading it,
# the user can then choose what to do with that information
...
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