Changelog

All notable changes to MONAI are documented in this file.

The format is based on Keep a Changelog.

Unreleased

1.4.0 - 2024-10-17

What's Changed

Added

Implemented Conjugate Gradient Solver to generate confidence maps. (#7876)
Added norm parameter to ResNet (#7752, #7805)
Introduced alpha parameter to DiceFocalLoss for improved flexibility (#7841)
Integrated Tailored ControlNet Implementations (#7875)
Integrated Tailored Auto-Encoder Model (#7861)
Integrated Tailored Diffusion U-Net Model (7867)
Added Maisi morphological functions (#7893)
Added support for downloading bundles from NGC private registry (#7907, #7929, #8076)
Integrated generative refactor into the core (#7886, #7962)
Made ViT and UNETR models compatible with TorchScript (#7937)
Implemented post-download checks for MONAI bundles and compatibility warnings (#7938)
Added NGC prefix argument when downloading bundles (#7974)
Added flash attention support in the attention block for improved performance (#7977)
Enhanced MLPBlock for compatibility with VISTA-3D (#7995)
Added support for Neighbor-Aware Calibration Loss (NACL) for calibrated models in segmentation tasks (#7819)
Added label_smoothing parameter to DiceCELoss for enhanced model calibration (#8000)
Add include_fc and use_combined_linear argument in the SABlock (#7996)
Added utilities, networks, and an inferer specific to VISTA-3D (#7999, #7987, #8047, #8059, #8021)
Integrated a new network, CellSamWrapper, for cell-based applications (#7981)
Introduced WriteFileMapping transform to map between input image paths and their corresponding output paths (#7769)
Added TrtHandler to accelerate models using TensorRT (#7990, #8064)
Added box and points conversion transforms for more flexible spatial manipulation (#8053)
Enhanced RandSimulateLowResolutiond transform with deterministic support (#8057)
Added a contiguous argument to the Fourier class to facilitate contiguous tensor outputs (#7969)
Allowed ApplyTransformToPointsd to receive a sequence of reference keys for more versatile point manipulation (#8063)
Made MetaTensor an optional print in DataStats and DataStatsd for more concise logging (#7814)

misc.

Refactored Dataset to utilize Compose for handling transforms. (#7784)
Combined map_classes_to_indices and generate_label_classes_crop_centers into a unified function (#7712)
Introduced metadata schema directly into the codebase for improved structure and validation (#7409)
Renamed optional_packages_version to required_packages_version for clearer package dependency management. (#7253)
Replaced pkg_resources with the more modern packaging module for package handling (#7953)
Refactored MAISI-related networks to align with the new generative components (#7989, #7993, #8005)
Added a badge displaying monthly download statistics to enhance project visibility (#7891)

Fixed

transforms

Ensured deterministic behavior in MixUp, CutMix, and CutOut transforms (#7813)
Applied a minor correction to AsDiscrete transform (#7984)
Fixed handling of integer weightmaps in RandomWeightedCrop (#8097)
Resolved data type bug in ScaleIntensityRangePercentile (#8109)

data

Fixed negative strides issue in the NrrdReader (#7809)
Addressed wsireader issue with retrieving MPP (7921)
Ensured location is returned as a tuple in wsireader (#8007)
Corrected interpretation of space directions in nrrd reader (#8091)

metrics and losses

Improved memory management for NACLLoss (#8020)
Fixed reduction logic in GeneralizedDiceScore (#7970)

networks

Resolved issue with loading pre-trained weights in ResNet (#7924)
Fixed error where torch.device object had no attribute gpu_id during TensorRT export (#8019)
Corrected function for loading older weights in DiffusionModelUNet (#8031)
Switched to torch_tensorrt.Device instead of torch.device during TensorRT compilation (#8051)

engines and handlers

Attempted to resolve the "experiment already exists" issue in MLFlowHandler (#7916)
Refactored the model export process for conversion and saving (#7934)

misc.

Adjusted requirements to exclude Numpy version 2.0 (#7859)
Updated deprecated scipy.ndimage namespaces in optional imports (#7847, #7897)
Resolved load_module() deprecation in Python 3.12 (#7881)
Fixed Ruff type check issues (#7885)
Cleaned disk space in the conda test pipeline (#7902)
Replaced deprecated pkgutil.find_loader usage (#7906)
Enhanced docstrings in various modules (#7913, #8055)
Test cases fixing (#7905, #7794, #7808)
Fix mypy issue introduced in 1.11.0 (#7941)
Cleaned up warnings during test collection (#7914)
Fix incompatible types in assignment issue (#7950)
Fix outdated link in the docs (#7971)
Addressed CI issues (#7983, #8013)
Fix module can not import correctly issue (#8015)
Fix AttributeError when using torch.min and max (#8041)
Ensure synchronization by adding cuda.synchronize (#8058)
Ignore warning from nptyping as workaround (#8062)
Suppress deprecated warning when importing monai (#8067)
Fix link in test bundle under MONAI-extra-test-data (#8092)

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:24.08-py3 from nvcr.io/nvidia/pytorch:23.08-py3
Change blossom-ci to ACL security format (#7843)
Move PyType test to weekly test (#8025)
Adjusted to meet Numpy 2.0 requirements (#7857)

Deprecated

Dropped support for Python 3.8 (#7909)
Remove deprecated arguments and class for v1.4 (#8079)

Removed

Remove use of deprecated python 3.12 strtobool (#7900)
Removed the pipeline for publishing to testpypi (#8086)
Cleaning up some very old and now obsolete infrastructure (#8113, #8118, #8121)

1.3.2 - 2024-06-25

Fixed

misc.

Updated Numpy version constraint to < 2.0 (#7859)

1.3.1 - 2024-05-17

Added

Support for by_measure argument in RemoveSmallObjects (#7137)
Support for pretrained flag in ResNet (#7095)
Support for uploading and downloading bundles to and from the Hugging Face Hub (#6454)
Added weight parameter in DiceLoss to apply weight to voxels of each class (#7158)
Support for returning dice for each class in DiceMetric (#7163)
Introduced ComponentStore for storage purposes (#7159)
Added utilities used in MONAI Generative (#7134)
Enabled Python 3.11 support for convert_to_torchscript and convert_to_onnx (#7182)
Support for MLflow in AutoRunner (#7176)
fname_regex option in PydicomReader (#7181)
Allowed setting AutoRunner parameters from config (#7175)
VoxelMorphUNet and VoxelMorph (#7178)
Enabled cache option in GridPatchDataset (#7180)
Introduced class_labels option in write_metrics_reports for improved readability (#7249)
DiffusionLoss for image registration task (#7272)
Supported specifying filename in Saveimage (#7318)
Compile support in SupervisedTrainer and SupervisedEvaluator (#7375)
mlflow_experiment_name support in Auto3DSeg (#7442)
Arm support (#7500)
BarlowTwinsLoss for representation learning (#7530)
SURELoss and ConjugateGradient for diffusion models (#7308)
Support for CutMix, CutOut, and MixUp augmentation techniques (#7198)
meta_file and logging_file options to BundleWorkflow (#7549)
properties_path option to BundleWorkflow for customized properties (#7542)
Support for both soft and hard clipping in ClipIntensityPercentiles (#7535)
Support for not saving artifacts in MLFlowHandler (#7604)
Support for multi-channel images in PerceptualLoss (#7568)
Added ResNet backbone for FlexibleUNet (#7571)
Introduced dim_head option in SABlock to set dimensions for each head (#7664)
Direct links to github source code to docs (#7738, #7779)

misc.

Refactored list_data_collate and collate_meta_tensor to utilize the latest PyTorch API (#7165)
Added str method in Metric base class (#7487)
Made enhancements for testing files (#7662, #7670, #7663, #7671, #7672)
Improved documentation for bundles (#7116)

Fixed

transforms

Addressed issue where lazy mode was ignored in SpatialPadd (#7316)
Tracked applied operations in ImageFilter (#7395)
Warnings are now given only if missing class is not set to 0 in generate_label_classes_crop_centers (#7602)
Input is now always converted to C-order in distance_transform_edt to ensure consistent behavior (#7675)

data

Modified .npz file behavior to use keys in NumpyReader (#7148)
Handled corrupted cached files in PersistentDataset (#7244)
Corrected affine update in NrrdReader (#7415)

metrics and losses

Addressed precision issue in get_confusion_matrix (#7187)
Harmonized and clarified documentation and tests for dice losses variants (#7587)

networks

Removed hard-coded spatial_dims in SwinTransformer (#7302)
Fixed learnable position_embeddings in PatchEmbeddingBlock (#7564, #7605)
Removed memory_pool_limit in TRT config (#7647)
Propagated kernel_size to ConvBlocks within AttentionUnet (#7734)
Addressed hard-coded activation layer in ResNet (#7749)

bundle

Resolved bundle download issue (#7280)
Updated bundle_root directory for NNIGen (#7586)
Checked for num_fold and failed early if incorrect (#7634)
Enhanced logging logic in ConfigWorkflow (#7745)

misc.

Enabled chaining in Auto3DSeg CLI (#7168)
Addressed useless error message in nnUNetV2Runner (#7217)
Resolved typing and deprecation issues in Mypy (#7231)
Quoted $PY_EXE variable to handle Python path that contains spaces in Bash (#7268)
Improved documentation, code examples, and warning messages in various modules (#7234, #7213, #7271, #7326, #7569, #7584)
Fixed typos in various modules (#7321, #7322, #7458, #7595, #7612)
Enhanced docstrings in various modules (#7245, #7381, #7746)
Handled error when data is on CPU in DataAnalyzer (#7310)
Updated version requirements for third-party packages (#7343, #7344, #7384, #7448, #7659, #7704, #7744, #7742, #7780)
Addressed incorrect slice compute in ImageStats (#7374)
Avoided editing a loop's mutable iterable to address B308 (#7397)
Fixed issue with CUDA_VISIBLE_DEVICES setting being ignored (#7408, #7581)
Avoided changing Python version in CICD (#7424)
Renamed partial to callable in instantiate mode (#7413)
Imported AttributeError for Python 3.12 compatibility (#7482)
Updated nnUNetV2Runner to support nnunetv2 2.2 (#7483)
Used uint8 instead of int8 in LabelStats (#7489)
Utilized subprocess for nnUNet training (#7576)
Addressed deprecated warning in ruff (#7625)
Fixed downloading failure on FIPS machine (#7698)
Updated torch_tensorrt compile parameters to avoid warning (#7714)
Restrict Auto3DSeg fold input based on datalist (#7778)

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:24.03-py3 from nvcr.io/nvidia/pytorch:23.08-py3

Removed

Removed unrecommended star-arg unpacking after a keyword argument, addressed B026 (#7262)
Skipped old PyTorch version test for SwinUNETR (#7266)
Dropped docker build workflow and migrated to Nvidia Blossom system (#7450)
Dropped Python 3.8 test on quick-py3 workflow (#7719)

1.3.0 - 2023-10-12

Added

Intensity transforms ScaleIntensityFixedMean and RandScaleIntensityFixedMean (#6542)
UltrasoundConfidenceMapTransform used for computing confidence map from an ultrasound image (#6709)
channel_wise support in RandScaleIntensity and RandShiftIntensity (#6793, #7025)
RandSimulateLowResolution and RandSimulateLowResolutiond (#6806)
SignalFillEmptyd (#7011)
Euclidean distance transform DistanceTransformEDT with GPU support (#6981)
Port loss and metrics from monai-generative (#6729, #6836)
Support invert_image and retain_stats in AdjustContrast and RandAdjustContrast (#6542)
New network DAF3D and Quicknat (#6306)
Support sincos position embedding (#6986)
ZarrAvgMerger used for patch inference (#6633)
Dataset tracking support to MLFlowHandler (#6616)
Considering spacing and subvoxel borders in SurfaceDiceMetric (#6681)
CUCIM support for surface-related metrics (#7008)
loss_fn support in IgniteMetric and renamed it to IgniteMetricHandler (#6695)
CallableEventWithFilter and Events options for trigger_event in GarbageCollector (#6663)
Support random sorting option to GridPatch, RandGridPatch, GridPatchd and RandGridPatchd (#6701)
Support multi-threaded batch sampling in PatchInferer (#6139)
SoftclDiceLoss and SoftDiceclDiceLoss (#6763)
HausdorffDTLoss and LogHausdorffDTLoss (#6994)
Documentation for TensorFloat-32 (#6770)
Docstring format guide (#6780)
GDSDataset support for GDS (#6778)
PyTorch backend support for MapLabelValue (#6872)
filter_func in copy_model_state to filter the weights to be loaded and filter_swinunetr (#6917)
stats_sender to MonaiAlgo for FL stats (#6984)
freeze_layers to help freeze specific layers (#6970)

misc.

Refactor multi-node running command used in Auto3DSeg into dedicated functions (#6623)
Support str type annotation to device in ToTensorD (#6737)
Improve logging message and file name extenstion in DataAnalyzer for Auto3DSeg (#6758)
Set data_range as a property in SSIMLoss (#6788)
Unify environment variable access (#7084)
end_lr support in WarmupCosineSchedule (#6662)
Add ClearML as optional dependency (#6827)
yandex.disk support in download_url (#6667)
Improve config expression error message (#6977)

Fixed

transforms

Make convert_box_to_mask throw errors when box size larger than the image (#6637)
Fix lazy mode in RandAffine (#6774)
Raise ValueError when map_items is bool in Compose (#6882)
Improve performance for NormalizeIntensity (#6887)
Fix mismatched shape in Spacing (#6912)
Avoid FutureWarning in CropForeground (#6934)
Fix Lazy=True ignored when using Dataset call (#6975)
Shape check for arbitrary types for DataStats (#7082)

data

Fix wrong spacing checking logic in PydicomReader and broken link in ITKReader (#6660)
Fix boolean indexing of batched MetaTensor (#6781)
Raise warning when multiprocessing in DataLoader (#6830)
Remove shuffle in DistributedWeightedRandomSampler (#6886)
Fix missing SegmentDescription in PydicomReader (#6937)
Fix reading dicom series error in ITKReader (#6943)
Fix KeyError in PydicomReader (#6946)
Update metatensor_to_itk_image to accept RAS MetaTensor and update default 'space' in NrrdReader to SpaceKeys.LPS (#7000)
Collate common meta dictionary keys (#7054)

metrics and losses

Fixed bug in GeneralizedDiceLoss when batch=True (#6775)
Support for BCEWithLogitsLoss in DiceCELoss (#6924)
Support for weight in Dice and related losses (#7098)

networks

Use np.prod instead of np.product (#6639)
Fix dimension issue in MBConvBlock (#6672)
Fix hard-coded up_kernel_size in ViTAutoEnc (#6735)
Remove hard-coded bias_downsample in resnet (#6848)
Fix unused kernel_size in ResBlock (#6999)
Allow for defining reference grid on non-integer coordinates (#7032)
Padding option for autoencoder (#7068)
Lower peak memory usage for SegResNetDS (#7066)

bundle

Set train_dataset_data and dataset_data to unrequired in BundleProperty (#6607)
Set None to properties that do not have REF_ID (#6607)
Fix AttributeError for default value in get_parsed_content for ConfigParser (#6756)
Update monai.bundle.scripts to support NGC hosting (#6828, #6997)
Add MetaProperties (#6835)
Add create_workflow and update load function (#6835)
Add bundle root directory to Python search directories automatically (#6910)
Generate properties for bundle docs automatically (#6918)
Move download_large_files from model zoo to core (#6958)
Bundle syntax # as alias of :: (#6955)
Fix bundle download naming issue (#6969, #6963)
Simplify the usage of ckpt_export (#6965)
update_kwargs in monai.bundle.script for merging multiple configs (#7109)

engines and handlers

Added int options for iteration_log and epoch_log in TensorBoardStatsHandler (#7027)
Support to run validator at training start (#7108)

misc.

Fix device fallback error in DataAnalyzer (#6658)
Add int check for current_mode in convert_applied_interp_mode (#6719)
Consistent type in convert_to_contiguous (#6849)
Label argmax in DataAnalyzer when retry on CPU (#6852)
Fix DataAnalyzer with histogram_only=True (#6874)
Fix AttributeError in RankFilter in single GPU environment (#6895)
Remove the default warning on TORCH_ALLOW_TF32_CUBLAS_OVERRIDE and add debug print info (#6909)
Hide user information in print_config (#6913, #6922)
Optionally pass coordinates to predictor during sliding window (#6795)
Proper ensembling when trained with a sigmoid in AutoRunner (#6588)
Fixed test_retinanet by increasing absolute differences (#6615)
Add type check to avoid comparing a np.array with a string in _check_kwargs_are_present (#6624)
Fix md5 hashing with FIPS mode (#6635)
Capture failures from Auto3DSeg related subprocess calls (#6596)
Code formatting tool for user-specified directory (#7106)
Various docstring fixes

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:23.08-py3 from nvcr.io/nvidia/pytorch:23.03-py3

Deprecated

allow_smaller=True; allow_smaller=False will be the new default in CropForeground and generate_spatial_bounding_box (#6736)
dropout_prob in VNet in favor of dropout_prob_down and dropout_prob_up (#6768)
workflow in BundleWorkflow in favor of workflow_type(#6768)
pos_embed in PatchEmbeddingBlock in favor of proj_type(#6986)
net_name and net_kwargs in download in favor of model(#7016)
img_size parameter in SwinUNETR (#7093)

Removed

pad_val, stride, per_channel and upsampler in OcclusionSensitivity (#6642)
compute_meaniou (#7019)
AsChannelFirst, AddChanneland SplitChannel (#7019)
create_multigpu_supervised_trainer and create_multigpu_supervised_evaluator (#7019)
runner_id in run (#7019)
data_src_cfg_filename in AlgoEnsembleBuilder (#7019)
get_validation_stats in Evaluator and get_train_stats in Trainer (#7019)
epoch_interval and iteration_interval in TensorBoardStatsHandler (#7019)
some self-hosted test (#7041)

1.2.0 - 2023-06-08

Added

Various Auto3DSeg enhancements and integration tests including multi-node multi-GPU optimization, major usability improvements
TensorRT and ONNX support for monai.bundle API and the relevant models
nnU-Net V2 integration monai.apps.nnunet
Binary and categorical metrics and event handlers using MetricsReloaded
Python module and CLI entry point for bundle workflows in monai.bundle.workflows and monai.fl.client
Modular patch inference API including PatchInferer, merger, and splitter
Initial release of lazy resampling including transforms and MetaTensor implementations
Bridge for ITK Image object and MetaTensor monai.data.itk_torch_bridge
Sliding window inference memory efficiency optimization including SlidingWindowInfererAdapt
Generic kernel filtering transforms ImageFiltered and RandImageFiltered
Trainable bilateral filters and joint bilateral filters
ClearML stats and image handlers for experiment tracking

misc.

Utility functions to warn API default value changes (#5738)
Support of dot notation to access content of ConfigParser (#5813)
Softmax version to focal loss (#6544)
FROC metric for N-dimensional (#6528)
Extend SurfaceDiceMetric for 3D images (#6549)
A track_meta option for Lambda and derived transforms (#6385)
CLIP pre-trained text-to-vision embedding (#6282)
Optional spacing to surface distances calculations (#6144)
WSIReader read by power and mpp (#6244)
Support GPU tensor for GridPatch and GridPatchDataset (#6246)
SomeOf transform composer (#6143)
GridPatch with both count and threshold filtering (#6055)

Fixed

transforms

map_classes_to_indices efficiency issue (#6468)
Adaptive resampling mode based on backends (#6429)
Improve Compose encapsulation (#6224)
User-provided FolderLayout in SaveImage and SaveImaged transforms (#6213)
SpacingD output shape compute stability (#6126)
No mutate ratio /user inputs croppad (#6127)
A warn flag to RandCropByLabelClasses (#6121)
nan to indicate no_channel, split dim singleton (#6090)
Compatible padding mode (#6076)
Allow for missing filename_or_obj key (#5980)
Spacing pixdim in-place change (#5950)
Add warning in RandHistogramShift (#5877)
Exclude cuCIM wrappers from get_transform_backends (#5838)

data

__format__ implementation of MetaTensor (#6523)
channel_dim in TiffFileWSIReader and CuCIMWSIReader (#6514)
Prepend "meta" to MetaTensor.__repr__ and MetaTensor.__str__ for easier identification (#6214)
MetaTensor slicing issue (#5845)
Default writer flags (#6147)
WSIReader defaults and tensor conversion (#6058)
Remove redundant array copy for WSITiffFileReader (#6089)
Fix unused arg in SlidingPatchWSIDataset (#6047)
reverse_indexing for PILReader (#6008)
Use np.linalg for the small affine inverse (#5967)

metrics and losses

Removing L2-norm in contrastive loss (L2-norm already present in CosSim) (#6550)
Fixes the SSIM metric (#6250)
Efficiency issues of Dice metrics (#6412)
Generalized Dice issue (#5929)
Unify output tensor devices for multiple metrics (#5924)

networks

Make RetinaNet throw errors for NaN only when training (#6479)
Replace deprecated arg in torchvision models (#6401)
Improves NVFuser import check (#6399)
Add device in HoVerNetNuclearTypePostProcessing and HoVerNetInstanceMapPostProcessing (#6333)
Enhance hovernet load pretrained function (#6269)
Access to the att_mat in self-attention modules (#6493)
Optional swinunetr-v2 (#6203)
Add transform to handle empty box as training data for retinanet_detector (#6170)
GPU utilization of DiNTS network (#6050)
A pixelshuffle upsample shape mismatch problem (#5982)
GEGLU activation function for the MLP Block (#5856)
Constructors for DenseNet derived classes (#5846)
Flexible interpolation modes in regunet (#5807)

bundle

Optimized the deepcopy logic in ConfigParser (#6464)
Improve check and error message of bundle run (#6400)
Warn or raise ValueError on duplicated key in json/yaml config (#6252)
Default metadata and logging values for bundle run (#6072)
pprint head and tail in bundle script (#5969)
Config parsing issue for substring reference (#5932)
Fix instantiate for object instantiation with attribute path (#5866)
Fix _get_latest_bundle_version issue on Windows (#5787)

engines and handlers

MLflow handler run bug (#6446)
monai.engine training attribute check (#6132)
Update StatsHandler logging message (#6051)
Added callable options for iteration_log and epoch_log in TensorBoard and MLFlow (#5976)
CheckpointSaver logging error (#6026)
Callable options for iteration_log and epoch_log in StatsHandler (#5965)

misc.

Avoid creating cufile.log when import monai (#6106)
monai._extensions module compatibility with rocm (#6161)
Issue of repeated UserWarning: "TypedStorage is deprecated" (#6105)
Use logging config at module level (#5960)
Add ITK to the list of optional dependencies (#5858)
RankFilter to skip logging when the rank is not meeting criteria (#6243)
Various documentation issues

Changed

Overall more precise and consistent type annotations
Optionally depend on PyTorch-Ignite v0.4.11 instead of v0.4.10
Base Docker image upgraded to nvcr.io/nvidia/pytorch:23.03-py3 from nvcr.io/nvidia/pytorch:22.10-py3

Deprecated

resample=True; resample=False will be the new default in SaveImage
random_size=True; random_size=False will be the new default for the random cropping transforms
image_only=False; image_only=True will be the new default in LoadImage
AddChannel and AsChannelFirst in favor of EnsureChannelFirst

Removed

Deprecated APIs since v0.9, including WSIReader from monai.apps, NiftiSaver and PNGSaver from monai.data
Support for PyTorch 1.8
Support for Python 3.7

1.1.0 - 2022-12-19

Added

Hover-Net based digital pathology workflows including new network, loss, postprocessing, metric, training, and inference modules
Various enhancements for Auto3dSeg AutoRunner including template caching, selection, and a dry-run mode nni_dry_run
Various enhancements for Auto3dSeg algo templates including new state-of-the-art configurations, optimized GPU memory utilization
New bundle API and configurations to support experiment management including MLFlowHandler
New bundle.script API to support model zoo query and download
LossMetric metric to compute loss as cumulative metric measurement
Transforms and base transform APIs including RandomizableTrait and MedianSmooth
runtime_cache option for CacheDataset and the derived classes to allow for shared caching on the fly
Flexible name formatter for SaveImage transform
pending_operations MetaTensor property and basic APIs for lazy image resampling
Contrastive sensitivity for SSIM metric
Extensible backbones for FlexibleUNet
Generalize SobelGradients to 3D and any spatial axes
warmup_multiplier option for WarmupCosineSchedule
F beta score metric based on confusion matrix metric
Support of key overwriting in Lambdad
Basic premerge tests for Python 3.11
Unit and integration tests for CUDA 11.6, 11.7 and A100 GPU
DataAnalyzer handles minor image-label shape inconsistencies

Fixed

Review and enhance previously untyped APIs with additional type annotations and casts
switch_endianness in LoadImage now supports tensor input
Reduced memory footprint for various Auto3dSeg tests
Issue of @ in monai.bundle.ReferenceResolver
Compatibility issue with ITK-Python 5.3 (converting itkMatrixF44 for default collate)
Inconsistent of sform and qform when using different backends for SaveImage
MetaTensor.shape call now returns a torch.Size instead of tuple
Issue of channel reduction in GeneralizedDiceLoss
Issue of background handling before softmax in DiceFocalLoss
Numerical issue of LocalNormalizedCrossCorrelationLoss
Issue of incompatible view size in ConfusionMatrixMetric
NetAdapter compatibility with Torchscript
Issue of extract_levels in RegUNet
Optional bias_downsample in ResNet
dtype overflow for ShiftIntensity transform
Randomized transforms such as RandCuCIM now inherit RandomizableTrait
fg_indices.size compatibility issue in generate_pos_neg_label_crop_centers
Issue when inverting ToTensor
Issue of capital letters in filename suffixes check in LoadImage
Minor tensor compatibility issues in apps.nuclick.transforms
Issue of float16 in verify_net_in_out
std variable type issue for RandRicianNoise
DataAnalyzer accepts None as label key and checks empty labels
iter_patch_position now has a smaller memory footprint
CumulativeAverage has been refactored and enhanced to allow for simple tracking of metric running stats.
Multi-threading issue for MLFlowHandler

Changed

Printing a MetaTensor now generates a less verbose representation
DistributedSampler raises a ValueError if there are too few devices
OpenCV and VideoDataset modules are loaded lazily to avoid dependency issues
device in monai.engines.Workflow supports string values
Activations and AsDiscrete take kwargs as additional arguments
DataAnalyzer is now more efficient and writes summary stats before detailed all case stats
Base Docker image upgraded to nvcr.io/nvidia/pytorch:22.10-py3 from nvcr.io/nvidia/pytorch:22.09-py3
Simplified Conda environment file environment-dev.yml
Versioneer dependency upgraded to 0.23 from 0.19

Deprecated

NibabelReader input argument dtype is deprecated, the reader will use the original dtype of the image

Removed

Support for PyTorch 1.7

1.0.1 - 2022-10-24

Fixes

DiceCELoss for multichannel targets
Auto3DSeg DataAnalyzer out-of-memory error and other minor issues
An optional flag issue in the RetinaNet detector
An issue with output offset for Spacing
A LoadImage issue when track_meta is False
1D data output error in VarAutoEncoder
An issue with resolution computing in ImageStats

Added

Flexible min/max pixdim options for Spacing
Upsample mode deconvgroup and optional kernel sizes
Docstrings for gradient-based saliency maps
Occlusion sensitivity to use sliding window inference
Enhanced Gaussian window and device assignments for sliding window inference
Multi-GPU support for MonaiAlgo
ClientAlgoStats and MonaiAlgoStats for federated summary statistics
MetaTensor support for OneOf
Add a file check for bundle logging config
Additional content and an authentication token option for bundle info API
An anti-aliasing option for Resized
SlidingWindowInferer adaptive device based on cpu_thresh
SegResNetDS with deep supervision and non-isotropic kernel support
Premerge tests for Python 3.10

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:22.09-py3 from nvcr.io/nvidia/pytorch:22.08-py3
Replace None type metadata content with "none" for collate_fn compatibility
HoVerNet Mode and Branch to independent StrEnum
Automatically infer device from the first item in random elastic deformation dict
Add channel dim in ComputeHoVerMaps and ComputeHoVerMapsd
Remove batch dim in SobelGradients and SobelGradientsd

Deprecated

Deprecating compute_meandice, compute_meaniou in monai.metrics, in favor of compute_dice and compute_iou respectively

1.0.0 - 2022-09-16

Added

monai.auto3dseg base APIs and monai.apps.auto3dseg components for automated machine learning (AutoML) workflow
monai.fl module with base APIs and MonaiAlgo for federated learning client workflow
An initial backwards compatibility guide
Initial release of accelerated MRI reconstruction components, including CoilSensitivityModel
Support of MetaTensor and new metadata attributes for various digital pathology components
Various monai.bundle enhancements for MONAI model-zoo usability, including config debug mode and get_all_bundles_list
new monai.transforms components including SignalContinuousWavelet for 1D signal, ComputeHoVerMaps for digital pathology, and SobelGradients for spatial gradients
VarianceMetric and LabelQualityScore metrics for active learning
Dataset API for real-time stream and videos
Several networks and building blocks including FlexibleUNet and HoVerNet
MeanIoUHandler and LogfileHandler workflow event handlers
WSIReader with the TiffFile backend
Multi-threading in WSIReader with cuCIM backend
get_stats API in monai.engines.Workflow
prune_meta_pattern in monai.transforms.LoadImage
max_interactions for deepedit interaction workflow
Various profiling utilities in monai.utils.profiling

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:22.08-py3 from nvcr.io/nvidia/pytorch:22.06-py3
Optionally depend on PyTorch-Ignite v0.4.10 instead of v0.4.9
The cache-based dataset now matches the transform information when read/write the cache
monai.losses.ContrastiveLoss now infers batch_size during forward()
Rearrange the spatial axes in RandSmoothDeform transforms following PyTorch's convention
Unified several environment flags into monai.utils.misc.MONAIEnvVars
Simplified __str__ implementation of MetaTensor instead of relying on the __repr__ implementation

Fixed

Improved error messages when both monai and monai-weekly are pip-installed
Inconsistent pseudo number sequences for different num_workers in DataLoader
Issue of repeated sequences for monai.data.ShuffleBuffer
Issue of not preserving the physical extent in monai.transforms.Spacing
Issue of using inception_v3 as the backbone of monai.networks.nets.TorchVisionFCModel
Index device issue for monai.transforms.Crop
Efficiency issue when converting the array dtype and contiguous memory

Deprecated

Addchannel and AsChannelFirst transforms in favor of EnsureChannelFirst
monai.apps.pathology.data components in favor of the corresponding components from monai.data
monai.apps.pathology.handlers in favor of the corresponding components from monai.handlers

Removed

Status section in the pull request template in favor of the pull request draft mode
monai.engines.BaseWorkflow
ndim and dimensions arguments in favor of spatial_dims
n_classes, num_classes arguments in AsDiscrete in favor of to_onehot
logit_thresh, threshold_values arguments in AsDiscrete in favor of threshold
torch.testing.assert_allclose in favor of tests.utils.assert_allclose

0.9.1 - 2022-07-22

Added

Support of monai.data.MetaTensor as core data structure across the modules
Support of inverse in array-based transforms
monai.apps.TciaDataset APIs for The Cancer Imaging Archive (TCIA) datasets, including a pydicom-backend reader
Initial release of components for MRI reconstruction in monai.apps.reconstruction, including various FFT utilities
New metrics and losses, including mean IoU and structural similarity index
monai.utils.StrEnum class to simplify Enum-based type annotations

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:22.06-py3 from nvcr.io/nvidia/pytorch:22.04-py3
Optionally depend on PyTorch-Ignite v0.4.9 instead of v0.4.8

Fixed

Fixed issue of not skipping post activations in Convolution when input arguments are None
Fixed issue of ignoring dropout arguments in DynUNet
Fixed issue of hard-coded non-linear function in ViT classification head
Fixed issue of in-memory config overriding with monai.bundle.ConfigParser.update
2D SwinUNETR incompatible shapes
Fixed issue with monai.bundle.verify_metadata not raising exceptions
Fixed issue with monai.transforms.GridPatch returns inconsistent type location when padding
Wrong generalized Dice score metric when denominator is 0 but prediction is non-empty
Docker image build error due to NGC CLI upgrade
Optional default value when parsing id unavailable in a ConfigParser instance
Immutable data input for the patch-based WSI datasets

Deprecated

*_transforms and *_meta_dict fields in dictionary-based transforms in favor of MetaTensor
meta_keys, meta_key_postfix, src_affine arguments in various transforms, in favor of MetaTensor
AsChannelFirst and AddChannel, in favor of EnsureChannelFirst transform

0.9.0 - 2022-06-08

Added

monai.bundle primary module with a ConfigParser and command-line interfaces for configuration-based workflows
Initial release of MONAI bundle specification
Initial release of volumetric image detection modules including bounding boxes handling, RetinaNet-based architectures
API preview monai.data.MetaTensor
Unified monai.data.image_writer to support flexible IO backends including an ITK writer
Various new network blocks and architectures including SwinUNETR
DeepEdit interactive training/validation workflow
NuClick interactive segmentation transforms
Patch-based readers and datasets for whole-slide imaging
New losses and metrics including SurfaceDiceMetric, GeneralizedDiceFocalLoss
New pre-processing transforms including RandIntensityRemap, SpatialResample
Multi-output and slice-based inference for SlidingWindowInferer
NrrdReader for NRRD file support
Torchscript utilities to save models with meta information
Gradient-based visualization module SmoothGrad
Automatic regular source code scanning for common vulnerabilities and coding errors

Changed

Simplified TestTimeAugmentation using de-collate and invertible transforms APIs
Refactoring monai.apps.pathology modules into monai.handlers and monai.transforms
Flexible activation and normalization layers for TopologySearch and DiNTS
Anisotropic first layers for 3D resnet
Flexible ordering of activation, normalization in UNet
Enhanced performance of connected-components analysis using Cupy
INSTANCE_NVFUSER for enhanced performance in 3D instance norm
Support of string representation of dtype in convert_data_type
Added new options iteration_log, iteration_log to the logging handlers
Base Docker image upgraded to nvcr.io/nvidia/pytorch:22.04-py3 from nvcr.io/nvidia/pytorch:21.10-py3
collate_fn generates more data-related debugging info with dev_collate

Fixed

Unified the spellings of "meta data", "metadata", "meta-data" to "metadata"
Various inaccurate error messages when input data are in invalid shapes
Issue of computing symmetric distances in compute_average_surface_distance
Unnecessary layer self.conv3 in UnetResBlock
Issue of torchscript compatibility for ViT and self-attention blocks
Issue of hidden layers in UNETR
allow_smaller in spatial cropping transforms
Antialiasing in Resize
Issue of bending energy loss value at different resolutions
kwargs_read_csv in CSVDataset
In-place modification in Metric reduction
wrap_array for ensure_tuple
Contribution guide for introducing new third-party dependencies

Removed

Deprecated nifti_writer, png_writer in favor of monai.data.image_writer
Support for PyTorch 1.6

0.8.1 - 2022-02-16

Added

Support of matshow3d with given channel_dim
Support of spatial 2D for ViTAutoEnc
Support of dataframe object input in CSVDataset
Support of tensor backend for Orientation
Support of configurable delimiter for CSV writers
A base workflow API
DataFunc API for dataset-level preprocessing
write_scalar API for logging with additional engine parameter in TensorBoardHandler
Enhancements for NVTX Range transform logging
Enhancements for set_determinism
Performance enhancements in the cache-based datasets
Configurable metadata keys for monai.data.DatasetSummary
Flexible kwargs for WSIReader
Logging for the learning rate schedule handler
GridPatchDataset as subclass of monai.data.IterableDataset
is_onehot option in KeepLargestConnectedComponent
channel_dim in the image readers and support of stacking images with channels
Skipping workflow run if epoch length is 0
Enhanced CacheDataset to avoid duplicated cache items
save_state utility function

Changed

Optionally depend on PyTorch-Ignite v0.4.8 instead of v0.4.6
monai.apps.mmars.load_from_mmar defaults to the latest version

Fixed

Issue when caching large items with pickle
Issue of hard-coded activation functions in ResBlock
Issue of create_file_name assuming local disk file creation
Issue of WSIReader when the backend is TiffFile
Issue of deprecated_args when the function signature contains kwargs
Issue of channel_wise computations for the intensity-based transforms
Issue of inverting OneOf
Issue of removing temporary caching file for the persistent dataset
Error messages when reader backend is not available
Output type casting issue in ScaleIntensityRangePercentiles
Various docstring typos and broken URLs
mode in the evaluator engine
Ordering of Orientation and Spacing in monai.apps.deepgrow.dataset

Removed

Additional deep supervision modules in DynUnet
Deprecated reduction argument for ContrastiveLoss
Decollate warning in Workflow
Unique label exception in ROCAUCMetric
Logger configuration logic in the event handlers

0.8.0 - 2021-11-25

Added

Overview of new features in v0.8
Network modules for differentiable neural network topology search (DiNTS)
Multiple Instance Learning transforms and models for digital pathology WSI analysis
Vision transformers for self-supervised representation learning
Contrastive loss for self-supervised learning
Finalized major improvements of 200+ components in monai.transforms to support input and backend in PyTorch and NumPy
Initial registration module benchmarking with GlobalMutualInformationLoss as an example
monai.transforms documentation with visual examples and the utility functions
Event handler for MLfLow integration
Enhanced data visualization functions including blend_images and matshow3d
RandGridDistortion and SmoothField in monai.transforms
Support of randomized shuffle buffer in iterable datasets
Performance review and enhancements for data type casting
Cumulative averaging API with distributed environment support
Module utility functions including require_pkg and pytorch_after
Various usability enhancements such as allow_smaller when sampling ROI and wrap_sequence when casting object types
tifffile support in WSIReader
Regression tests for the fast training workflows
Various tutorials and demos including educational contents at MONAI Bootcamp 2021

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:21.10-py3 from nvcr.io/nvidia/pytorch:21.08-py3
Decoupled TraceKeys and TraceableTransform APIs from InvertibleTransform
Skipping affine-based resampling when resample=False in NiftiSaver
Deprecated threshold_values: bool and num_classes: int in AsDiscrete
Enhanced apply_filter for spatially 1D, 2D and 3D inputs with non-separable kernels
Logging with logging in downloading and model archives in monai.apps
API documentation site now defaults to stable instead of latest
skip-magic-trailing-comma in coding style enforcements
Pre-merge CI pipelines now include unit tests with Nvidia Ampere architecture

Removed

Support for PyTorch 1.5
The deprecated DynUnetV1 and the related network blocks
GitHub self-hosted CI/CD pipelines for package releases

Fixed

Support of path-like objects as file path inputs in most modules
Issue of decollate_batch for dictionary of empty lists
Typos in documentation and code examples in various modules
Issue of no available keys when allow_missing_keys=True for the MapTransform
Issue of redundant computation when normalization factors are 0.0 and 1.0 in ScaleIntensity
Incorrect reports of registered readers in ImageReader
Wrong numbering of iterations in StatsHandler
Naming conflicts in network modules and aliases
Incorrect output shape when reduction="none" in FocalLoss
Various usability issues reported by users

0.7.0 - 2021-09-24

Added

Overview of new features in v0.7
Initial phase of major usability improvements in monai.transforms to support input and backend in PyTorch and NumPy
Performance enhancements, with profiling and tuning guides for typical use cases
Reproducing training modules and workflows of state-of-the-art Kaggle competition solutions
24 new transforms, including
- OneOf meta transform
- DeepEdit guidance signal transforms for interactive segmentation
- Transforms for self-supervised pre-training
- Integration of NVIDIA Tools Extension (NVTX)
- Integration of cuCIM
- Stain normalization and contextual grid for digital pathology
Transchex network for vision-language transformers for chest X-ray analysis
DatasetSummary utility in monai.data
WarmupCosineSchedule
Deprecation warnings and documentation support for better backwards compatibility
Padding with additional kwargs and different backend API
Additional options such as dropout and norm in various networks and their submodules

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:21.08-py3 from nvcr.io/nvidia/pytorch:21.06-py3
Deprecated input argument n_classes, in favor of num_classes
Deprecated input argument dimensions and ndims, in favor of spatial_dims
Updated the Sphinx-based documentation theme for better readability
NdarrayTensor type is replaced by NdarrayOrTensor for simpler annotations
Self-attention-based network blocks now support both 2D and 3D inputs

Removed

The deprecated TransformInverter, in favor of monai.transforms.InvertD
GitHub self-hosted CI/CD pipelines for nightly and post-merge tests
monai.handlers.utils.evenly_divisible_all_gather
monai.handlers.utils.string_list_all_gather

Fixed

A Multi-thread cache writing issue in LMDBDataset
Output shape convention inconsistencies of the image readers
Output directory and file name flexibility issue for NiftiSaver, PNGSaver
Requirement of the label field in test-time augmentation
Input argument flexibility issues for ThreadDataLoader
Decoupled Dice and CrossEntropy intermediate results in DiceCELoss
Improved documentation, code examples, and warning messages in various modules
Various usability issues reported by users

0.6.0 - 2021-07-08

Added

10 new transforms, a masked loss wrapper, and a NetAdapter for transfer learning
APIs to load networks and pre-trained weights from Clara Train Medical Model ARchives (MMARs)
Base metric and cumulative metric APIs, 4 new regression metrics
Initial CSV dataset support
Decollating mini-batch as the default first postprocessing step, Migrating your v0.5 code to v0.6 wiki shows how to adapt to the breaking changes
Initial backward compatibility support via monai.utils.deprecated
Attention-based vision modules and UNETR for segmentation
Generic module loaders and Gaussian mixture models using the PyTorch JIT compilation
Inverse of image patch sampling transforms
Network block utilities get_[norm, act, dropout, pool]_layer
unpack_items mode for apply_transform and Compose
New event INNER_ITERATION_STARTED in the deepgrow interactive workflow
set_data API for cache-based datasets to dynamically update the dataset content
Fully compatible with PyTorch 1.9
--disttests and --min options for runtests.sh
Initial support of pre-merge tests with Nvidia Blossom system

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:21.06-py3 from nvcr.io/nvidia/pytorch:21.04-py3
Optionally depend on PyTorch-Ignite v0.4.5 instead of v0.4.4
Unified the demo, tutorial, testing data to the project shared drive, and Project-MONAI/MONAI-extra-test-data
Unified the terms: post_transform is renamed to postprocessing, pre_transform is renamed to preprocessing
Unified the postprocessing transforms and event handlers to accept the "channel-first" data format
evenly_divisible_all_gather and string_list_all_gather moved to monai.utils.dist

Removed

Support of 'batched' input for postprocessing transforms and event handlers
TorchVisionFullyConvModel
set_visible_devices utility function
SegmentationSaver and TransformsInverter handlers

Fixed

Issue of handling big-endian image headers
Multi-thread issue for non-random transforms in the cache-based datasets
Persistent dataset issue when multiple processes sharing a non-exist cache location
Typing issue with Numpy 1.21.0
Loading checkpoint with both model and optmizier using CheckpointLoader when strict_shape=False
SplitChannel has different behaviour depending on numpy/torch inputs
Transform pickling issue caused by the Lambda functions
Issue of filtering by name in generate_param_groups
Inconsistencies in the return value types of class_activation_maps
Various docstring typos
Various usability enhancements in monai.transforms

0.5.3 - 2021-05-28

Changed

Project default branch renamed to dev from master
Base Docker image upgraded to nvcr.io/nvidia/pytorch:21.04-py3 from nvcr.io/nvidia/pytorch:21.02-py3
Enhanced type checks for the iteration_metric handler
Enhanced PersistentDataset to use tempfile during caching computation
Enhanced various info/error messages
Enhanced performance of RandAffine
Enhanced performance of SmartCacheDataset
Optionally requires cucim when the platform is Linux
Default device of TestTimeAugmentation changed to cpu

Fixed

Download utilities now provide better default parameters
Duplicated key_transforms in the patch-based transforms
A multi-GPU issue in ClassificationSaver
A default meta_data issue in SpacingD
Dataset caching issue with the persistent data loader workers
A memory issue in permutohedral_cuda
Dictionary key issue in CopyItemsd
box_start and box_end parameters for deepgrow SpatialCropForegroundd
Tissue mask array transpose issue in MaskedInferenceWSIDataset
Various type hint errors
Various docstring typos

Added

Support of to_tensor and device arguments for TransformInverter
Slicing options with SpatialCrop
Class name alias for the networks for backward compatibility
k_divisible option for CropForeground
map_items option for Compose
Warnings of inf and nan for surface distance computation
A print_log flag to the image savers
Basic testing pipelines for Python 3.9

0.5.0 - 2021-04-09

Added

Overview document for feature highlights in v0.5.0
Invertible spatial transforms
- InvertibleTransform base APIs
- Batch inverse and decollating APIs
- Inverse of Compose
- Batch inverse event handling
- Test-time augmentation as an application
Initial support of learning-based image registration:
- Bending energy, LNCC, and global mutual information loss
- Fully convolutional architectures
- Dense displacement field, dense velocity field computation
- Warping with high-order interpolation with C++/CUDA implementations
Deepgrow modules for interactive segmentation:
- Workflows with simulations of clicks
- Distance-based transforms for guidance signals
Digital pathology support:
- Efficient whole slide imaging IO and sampling with Nvidia cuCIM and SmartCache
- FROC measurements for lesion
- Probabilistic post-processing for lesion detection
- TorchVision classification model adaptor for fully convolutional analysis
12 new transforms, grid patch dataset, ThreadDataLoader, EfficientNets B0-B7
4 iteration events for the engine for finer control of workflows
New C++/CUDA extensions:
- Conditional random field
- Fast bilateral filtering using the permutohedral lattice
Metrics summary reporting and saving APIs
DiceCELoss, DiceFocalLoss, a multi-scale wrapper for segmentation loss computation
Data loading utilities：
- decollate_batch
- PadListDataCollate with inverse support
Support of slicing syntax for Dataset
Initial Torchscript support for the loss modules
Learning rate finder
Allow for missing keys in the dictionary-based transforms
Support of checkpoint loading for transfer learning
Various summary and plotting utilities for Jupyter notebooks
Contributor Covenant Code of Conduct
Major CI/CD enhancements covering the tutorial repository
Fully compatible with PyTorch 1.8
Initial nightly CI/CD pipelines using Nvidia Blossom Infrastructure

Changed

Enhanced list_data_collate error handling
Unified iteration metric APIs
densenet* extensions are renamed to DenseNet*
se_res* network extensions are renamed to SERes*
Transform base APIs are rearranged into compose, inverse, and transform
_do_transform flag for the random augmentations is unified via RandomizableTransform
Decoupled post-processing steps, e.g. softmax, to_onehot_y, from the metrics computations
Moved the distributed samplers to monai.data.samplers from monai.data.utils
Engine's data loaders now accept generic iterables as input
Workflows now accept additional custom events and state properties
Various type hints according to Numpy 1.20
Refactored testing utility runtests.sh to have --unittest and --net (integration tests) options
Base Docker image upgraded to nvcr.io/nvidia/pytorch:21.02-py3 from nvcr.io/nvidia/pytorch:20.10-py3
Docker images are now built with self-hosted environments
Primary contact email updated to monai.contact@gmail.com
Now using GitHub Discussions as the primary communication forum

Removed

Compatibility tests for PyTorch 1.5.x
Format specific loaders, e.g. LoadNifti, NiftiDataset
Assert statements from non-test files
from module import * statements, addressed flake8 F403

Fixed

Uses American English spelling for code, as per PyTorch
Code coverage now takes multiprocessing runs into account
SmartCache with initial shuffling
ConvertToMultiChannelBasedOnBratsClasses now supports channel-first inputs
Checkpoint handler to save with non-root permissions
Fixed an issue for exiting the distributed unit tests
Unified DynUNet to have single tensor output w/o deep supervision
SegmentationSaver now supports user-specified data types and a squeeze_end_dims flag
Fixed *Saver event handlers output filenames with a data_root_dir option
Load image functions now ensure little-endian
Fixed the test runner to support regex-based test case matching
Usability issues in the event handlers

0.4.0 - 2020-12-15

Added

Overview document for feature highlights in v0.4.0
Torchscript support for the net modules
New networks and layers:
- Discrete Gaussian kernels
- Hilbert transform and envelope detection
- Swish and mish activation
- Acti-norm-dropout block
- Upsampling layer
- Autoencoder, Variational autoencoder
- FCNet
Support of initialisation from pretrained weights for densenet, senet, multichannel AHNet
Layer-wise learning rate API
New model metrics and event handlers based on occlusion sensitivity, confusion matrix, surface distance
CAM/GradCAM/GradCAM++
File format-agnostic image loader APIs with Nibabel, ITK readers
Enhancements for dataset partition, cross-validation APIs
New data APIs:
- LMDB-based caching dataset
- Cache-N-transforms dataset
- Iterable dataset
- Patch dataset
Weekly PyPI release
Fully compatible with PyTorch 1.7
CI/CD enhancements:
- Skipping, speed up, fail fast, timed, quick tests
- Distributed training tests
- Performance profiling utilities
New tutorials and demos:
- Autoencoder, VAE tutorial
- Cross-validation demo
- Model interpretability tutorial
- COVID-19 Lung CT segmentation challenge open-source baseline
- Threadbuffer demo
- Dataset partitioning tutorial
- Layer-wise learning rate demo
- MONAI Bootcamp 2020

Changed

Base Docker image upgraded to nvcr.io/nvidia/pytorch:20.10-py3 from nvcr.io/nvidia/pytorch:20.08-py3

Backwards Incompatible Changes

monai.apps.CVDecathlonDataset is extended to a generic monai.apps.CrossValidation with an dataset_cls option
Cache dataset now requires a monai.transforms.Compose instance as the transform argument
Model checkpoint file name extensions changed from .pth to .pt
Readers' get_spatial_shape returns a numpy array instead of list
Decoupled postprocessing steps such as sigmoid, to_onehot_y, mutually_exclusive, logit_thresh from metrics and event handlers, the postprocessing steps should be used before calling the metrics methods
ConfusionMatrixMetric and DiceMetric computation now returns an additional not_nans flag to indicate valid results
UpSample optional mode now supports "deconv", "nontrainable", "pixelshuffle"; interp_mode is only used when mode is "nontrainable"
SegResNet optional upsample_mode now supports "deconv", "nontrainable", "pixelshuffle"
monai.transforms.Compose class inherits monai.transforms.Transform
In Rotate, Rotated, RandRotate, RandRotated transforms, the angle related parameters are interpreted as angles in radians instead of degrees.
SplitChannel and SplitChanneld moved from transforms.post to transforms.utility

Removed

Support of PyTorch 1.4

Fixed

Enhanced loss functions for stability and flexibility
Sliding window inference memory and device issues
Revised transforms:
- Normalize intensity datatype and normalizer types
- Padding modes for zoom
- Crop returns coordinates
- Select items transform
- Weighted patch sampling
- Option to keep aspect ratio for zoom
Various CI/CD issues

0.3.0 - 2020-10-02

Added

Overview document for feature highlights in v0.3.0
Automatic mixed precision support
Multi-node, multi-GPU data parallel model training support
3 new evaluation metric functions
11 new network layers and blocks
6 new network architectures
14 new transforms, including an I/O adaptor
Cross validation module for DecathlonDataset
Smart Cache module in dataset
monai.optimizers module
monai.csrc module
Experimental feature of ImageReader using ITK, Nibabel, Numpy, Pillow (PIL Fork)
Experimental feature of differentiable image resampling in C++/CUDA
Ensemble evaluator module
GAN trainer module
Initial cross-platform CI environment for C++/CUDA code
Code style enforcement now includes isort and clang-format
Progress bar with tqdm

Changed

Now fully compatible with PyTorch 1.6
Base Docker image upgraded to nvcr.io/nvidia/pytorch:20.08-py3 from nvcr.io/nvidia/pytorch:20.03-py3
Code contributions now require signing off on the Developer Certificate of Origin (DCO)
Major work in type hinting finished
Remote datasets migrated to Open Data on AWS
Optionally depend on PyTorch-Ignite v0.4.2 instead of v0.3.0
Optionally depend on torchvision, ITK
Enhanced CI tests with 8 new testing environments

Removed

MONAI/examples folder (relocated into Project-MONAI/tutorials)
MONAI/research folder (relocated to Project-MONAI/research-contributions)

Fixed

dense_patch_slices incorrect indexing
Data type issue in GeneralizedWassersteinDiceLoss
ZipDataset return value inconsistencies
sliding_window_inference indexing and device issues
importing monai modules may cause namespace pollution
Random data splits issue in DecathlonDataset
Issue of randomising a Compose transform
Various issues in function type hints
Typos in docstring and documentation
PersistentDataset issue with existing file folder
Filename issue in the output writers

0.2.0 - 2020-07-02

Added

Overview document for feature highlights in v0.2.0
Type hints and static type analysis support
MONAI/research folder
monai.engine.workflow APIs for supervised training
monai.inferers APIs for validation and inference
7 new tutorials and examples
3 new loss functions
4 new event handlers
8 new layers, blocks, and networks
12 new transforms, including post-processing transforms
monai.apps.datasets APIs, including MedNISTDataset and DecathlonDataset
Persistent caching, ZipDataset, and ArrayDataset in monai.data
Cross-platform CI tests supporting multiple Python versions
Optional import mechanism
Experimental features for third-party transforms integration

Changed

For more details please visit the project wiki

Core modules now require numpy >= 1.17
Categorized monai.transforms modules into crop and pad, intensity, IO, post-processing, spatial, and utility.
Most transforms are now implemented with PyTorch native APIs
Code style enforcement and automated formatting workflows now use autopep8 and black
Base Docker image upgraded to nvcr.io/nvidia/pytorch:20.03-py3 from nvcr.io/nvidia/pytorch:19.10-py3
Enhanced local testing tools
Documentation website domain changed to https://docs.monai.io

Removed

Support of Python < 3.6
Automatic installation of optional dependencies including pytorch-ignite, nibabel, tensorboard, pillow, scipy, scikit-image

Fixed

Various issues in type and argument names consistency
Various issues in docstring and documentation site
Various issues in unit and integration tests
Various issues in examples and notebooks

0.1.0 - 2020-04-17

Added

Public alpha source code release under the Apache 2.0 license (highlights)
Various tutorials and examples
- Medical image classification and segmentation workflows
- Spacing/orientation-aware preprocessing with CPU/GPU and caching
- Flexible workflows with PyTorch Ignite and Lightning
Various GitHub Actions
- CI/CD pipelines via self-hosted runners
- Documentation publishing via readthedocs.org
- PyPI package publishing
Contributing guidelines
A project logo and badges

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CHANGELOG.md

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Changelog

Unreleased

1.4.0 - 2024-10-17

What's Changed

Added

misc.

Fixed

transforms

data

metrics and losses

networks

engines and handlers

misc.

Changed

Deprecated

Removed

1.3.2 - 2024-06-25

Fixed

misc.

1.3.1 - 2024-05-17

Added

misc.

Fixed

transforms

data

metrics and losses

networks

bundle

misc.

Changed

Removed

1.3.0 - 2023-10-12

Added

misc.

Fixed

transforms

data

metrics and losses

networks

bundle

engines and handlers

misc.

Changed

Deprecated

Removed

1.2.0 - 2023-06-08

Added

misc.

Fixed

transforms

data

metrics and losses

networks

bundle

engines and handlers

misc.

Changed

Deprecated

Removed

1.1.0 - 2022-12-19

Added

Fixed

Changed

Deprecated

Removed

1.0.1 - 2022-10-24

Fixes

Added

Changed

Deprecated

1.0.0 - 2022-09-16

Added

Changed

Fixed