- also return statistics from python api
- add
totalseg_get_phase
- major bugfix: rib labels were in wrong order
- hide nnunetv2 2.3.1 warning:
Detected old nnU-Net plans format. Attempting to reconstruct network architecture...
- Bugfix: add flush to DummyFile
- Require python >= 3.9 in setup.py
- properly add
vertebrae_body
model - add
--roi_subset_robust
argument - add
--fastest
argument - allow
mps
as device (but not supported by pytorch yet) - add inline python version requirement for
requests
package - if input spacing same as resampling spacing then skip resampling
- from python api also return nifti with label map in header
- input to python api can be a Nifti1Image object or a file path
- upgrade to
nnunetv2>=2.2.1
- for
total
task use nnU-Netstep_size=0.8
instead of0.5
for faster runtime while only decreasing dice by 0.001 - minor edits and bugfixes
- downgrade nnunet to 2.1 to fix bug in
fast
model
- temporary fix of critical bug in
fast
model. Proper fix in next release.
- download all weights from github releases instead of zenodo
- fix critical bug in
body
task postprocessing: sometimes all foreground removed
- allow more than 10 classes in
--roi_subset
- bugfix in
appendicular_bones
auxiliary mapping - in multilable output only show classes selected in
--roi_subset
if selected - make statistics work with dicom input
- add option
--v1_order
to use the old class order from v1
- train models with nnU-Net v2 (nnunet_cust dependency no longer needed)
- roi_subset a lot faster, because cropping with 6mm low res model to roi first
- more classes and improved training dataset (for details see
resources/improvements_in_v2.md
) - bugfix to make cli available on windows
- bugfixes in dicom io
- add
--skip_saving
argument - automatic tests on windows, linux and mac
- statistics are not calculated anymore for ROIs which are cut off by the top or bottom of the image (use
stats_include_incomplete
to change this behaviour) - add postprocessing for body segmentation: remove small blobs
- use dicom2nifti for dicom conversion instead of dcm2niix because easier to use across platforms
- remove verbose print outs not needed
- add helper script for manual setup
- add fast statistics
- download weights from different server for faster and more stable download
- fix
requests
version to avoidurllib3
openssl error - minor bugfixes
- add independent script to download weights
- bugfixes
- support dicom input
- support dicom rt struct output
- add usage stats
- Correct wording in error messages
- add
--roi_subset
argument - Use newer nnunet-customized version to avoid sklearn import error
- add
totalseg_import_weights
function - add python api
- bugfix in cucim resampling
- add 6mm body model
- multilabel files contain label names in extended header
- add body model
- add pleural effusion model
- remove SimpleITK version requirement
- bugfixes
- add lung_vessels model
- add intracerebral hemorrhage model
- add coronary artery model
- preview file was renamed from
preview.png
topreview_total.png
- Split very big images into 3 parts and process one by one to avoid memory problems
- fix: check if input is 4d and then truncate to 3d
- make it work with windows
- make it work with cpu
- make output spacing exactly match input spacing
- improve weights download
- fix SimpleITK version to 2.0.2 to avoid nifti loading error
- Optimise statistics runtime
- fix server bugs
- add radiomics feature calculation
- Initial release