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Master

Release 2.10.0

  • add abdominal_muscles task

Release 2.9.0

  • use --higher_order_resampling argument
  • add --save_probabilities argument: save softmax probabilities. Very experimental. Requires python skills.
  • bugfix in task brain_structures: resampling was in different order than model. resulted in slower runtime and higher RAM usage and slightly reduced accuracy.
  • add craniofacial_structures task: add skull, mandible, teeth, sinus, etc.

Release 2.8.0

  • make totalseg_get_modality work with normalized intensities (images which do not have original HU values anymore)
  • replace pkg_resources for python 3.12 compatibility
  • remove torch < 2.6.0 requirement (fixed in nnU-Net)
  • add --robust_crop
  • improved tissue_types_mr model
  • add mode nearest to ndimage.zoom to fix resampling bug (thanks to @baderstine for spotting this bug)

Release 2.7.0

  • add liver_segments and liver_segments_mr tasks

Release 2.6.0

  • add evans index calculation
  • require torch < 2.6.0 to avoid weight loading error (waiting for nnU-Net to fix this issue)

Release 2.5.0

  • major update to all MR models: double the number of training subjects (this includes a retraining of these models. Therefore results can be different from previous versions.)
  • breaking change: the total_mr task now contains 50 main classes instead of 56. Some classes moved to some other tasks and total_mr now contains also some classes which were not part of it previously. Please see the new total_mr class map in the readme or in totalsegmentator/map_to_binary.py.
  • add tissue_4_types task: add intermuscular fat class
  • add vertebrae_mr task: numbered single vertebrae segmentation in MR images (for CT this is already part of the total task)
  • add appendicular_bones_mr task: add appendicular bones segmentation for MR images
  • add thigh_shoulder_muscles_mr task: add thigh and shoulder muscles segmentation for CT and MR images
  • add vertebrae_body with new class intervertebral_discs
  • add body_mr task: add body segmentation for MR images
  • add kidney_cysts task: greatly improved kidney cyst segmentation compared to the kidney_cyst class which is part of total task
  • add breasts task: add breast segmentation
  • add oculomotor_muscles task: add oculomotor muscles model (thanks to Philippe)
  • add lung_nodules task (thanks to BLUEMIND AI)
  • update coronary_arteries task: increased number of training subjects, including non-contrast images
  • add option to remove small connected components in postprocessing
  • add totalseg_get_modality: estimate modality (CT or MR) from input image
  • removed rt_utils and p_tqdm dependency
  • change pi_time threshold for arterial late phase from 50s to 60s

Release 2.4.0

  • add brain structures
  • add liver vessels
  • greatly improved phase classification model

Release 2.3.0

  • Bugfixes
  • add headneck structures

Release 2.2.1

  • 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...
  • add mr models

Release 2.1.0

  • 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-Net step_size=0.8 instead of 0.5 for faster runtime while only decreasing dice by 0.001
  • minor edits and bugfixes

Release 2.0.5

  • downgrade nnunet to 2.1 to fix bug in fast model

Release 2.0.4

  • temporary fix of critical bug in fast model. Proper fix in next release.

LEGACY BUGFIX Release 1.5.7

  • download all weights from github releases instead of zenodo

Release 2.0.3

  • fix critical bug in body task postprocessing: sometimes all foreground removed

Release 2.0.2

  • 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

Release 2.0.1

  • add option --v1_order to use the old class order from v1

Release 2.0.0

  • 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

Release 1.5.6

  • 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 avoid urllib3 openssl error
  • minor bugfixes

Release 1.5.5

  • add independent script to download weights
  • bugfixes

Release 1.5.4

  • support dicom input
  • support dicom rt struct output
  • add usage stats

Release 1.5.3

  • 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

Release 1.5.2

  • 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

Release 1.4.0

  • bugfixes
  • add lung_vessels model
  • add intracerebral hemorrhage model
  • add coronary artery model
  • preview file was renamed from preview.png to preview_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

Release 1.3

  • make output spacing exactly match input spacing
  • improve weights download

Release 1.2

  • fix SimpleITK version to 2.0.2 to avoid nifti loading error

Release 1.1

  • Optimise statistics runtime
  • fix server bugs
  • add radiomics feature calculation

Release 1.0

  • Initial release