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Release 1.6 Doc Updates [skip ci] #8882

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29a5713
Initial 1.6 doc changes
ericspod May 28, 2026
84db9db
Merge branch 'dev' into updates_for_1_6_release
ericspod May 28, 2026
6c95d43
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] May 28, 2026
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2 changes: 1 addition & 1 deletion .github/workflows/weekly-preview.yml
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Expand Up @@ -69,7 +69,7 @@ jobs:
export YEAR_WEEK=$(date +'%y%U')
echo "Year week for tag is ${YEAR_WEEK}"
if ! [[ $YEAR_WEEK =~ ^[0-9]{4}$ ]] ; then echo "Wrong 'year week' format. Should be 4 digits."; exit 1 ; fi
git tag "1.6.dev${YEAR_WEEK}"
git tag "1.7.dev${YEAR_WEEK}"
git log -1
git tag --list
python setup.py sdist bdist_wheel
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7 changes: 6 additions & 1 deletion CHANGELOG.md
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Expand Up @@ -5,6 +5,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).

## [Unreleased]

## [1.6.0] - 2026-05-??



## [1.5.2] - 2026-01-28

## What's Changed
Expand Down Expand Up @@ -1267,7 +1271,8 @@ the postprocessing steps should be used before calling the metrics methods

[highlights]: https://github.com/Project-MONAI/MONAI/blob/master/docs/source/highlights.md

[Unreleased]: https://github.com/Project-MONAI/MONAI/compare/1.5.2...HEAD
[Unreleased]: https://github.com/Project-MONAI/MONAI/compare/1.6.0...HEAD
[1.6.0]: https://github.com/Project-MONAI/MONAI/compare/1.5.2...1.6.0
[1.5.2]: https://github.com/Project-MONAI/MONAI/compare/1.5.1...1.5.2
[1.5.1]: https://github.com/Project-MONAI/MONAI/compare/1.5.0...1.5.1
[1.5.0]: https://github.com/Project-MONAI/MONAI/compare/1.4.0...1.5.0
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2 changes: 1 addition & 1 deletion CITATION.cff
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Expand Up @@ -7,7 +7,7 @@ abstract: "AI Toolkit for Healthcare Imaging"
authors:
- name: "MONAI Consortium"
date-released: 2026-01-29
version: "1.5.2"
version: "1.6.0"
identifiers:
- description: "This DOI represents all versions of MONAI, and will always resolve to the latest one."
type: doi
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1 change: 1 addition & 0 deletions docs/source/whatsnew.rst
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Expand Up @@ -6,6 +6,7 @@ What's New
.. toctree::
:maxdepth: 1

whatsnew_1_6.md
whatsnew_1_5_2.md
whatsnew_1_5_1.md
whatsnew_1_5.md
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2 changes: 1 addition & 1 deletion docs/source/whatsnew_1_5_2.md
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@@ -1,5 +1,5 @@

# What's new in 1.5.2 🎉🎉
# What's new in 1.5.2

This is a minor update for MONAI to address a security concern.

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2 changes: 2 additions & 0 deletions docs/source/whatsnew_1_6.md
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@@ -0,0 +1,2 @@

# What's new in 1.6.0 🎉🎉
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@ericspod ericspod May 28, 2026

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@coderabbitai propose highlight content to put here in the same style as that in docs/source/whatsnew_1_5_0.md. This should highlight major new features and additions, with a very brief summary of the minor changes done in a bullet-point list.

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@coderabbitai coderabbitai Bot May 28, 2026

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🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
# Get style reference
cat docs/source/whatsnew_1_5_0.md

echo "=== CHANGELOG ==="
cat CHANGELOG.md 2>/dev/null | head -200 || echo "No CHANGELOG.md"

echo "=== Current PR description ==="
gh pr view 8882 --json title,body | jq -r '.title, .body'

echo "=== Recent merged PRs into main targeting 1.6 ==="
gh pr list --state merged --limit 80 --json number,title,labels,mergedAt | jq -r '.[] | "#\(.number) \(.title)"'

Length of output: 16950

🏁 Script executed:

#!/bin/bash
fd -e md whatsnew docs/
echo "---"
# Try to find any whatsnew file
fd whatsnew . --type f

Length of output: 997

🏁 Script executed:

#!/bin/bash
cat docs/source/whatsnew_1_5.md
echo "=== 1.5.2 ==="
cat docs/source/whatsnew_1_5_2.md

Length of output: 5323

@ericspod, here's proposed content matching the whatsnew_1_5.md style:

# What's new in 1.6.0 🎉🎉

- New metrics: `EmbeddingCollapseMetric` and `CalibrationErrorMetric`
- New losses: `MCCLoss` (Matthews Correlation Coefficient) and `AUCMarginLoss`
- `GradientAccumulation` utility for `SupervisedTrainer`
- Nested dot-notation access in `ConfigParser`
- Global coordinates support in spatial crop transforms
- `TestTimeAugmentation` generalized to non-spatial predictions
- MIG UUID and `CUDA_VISIBLE_DEVICES` support in `nnUNetV2Runner`
- Auto3DSeg: replaced `pickle` with JSON for improved security in algo serialization

## New Metrics

### EmbeddingCollapseMetric
A new metric [`EmbeddingCollapseMetric`](https://github.com/Project-MONAI/MONAI/pull/8815) detects representational collapse in medical imaging model embeddings, useful for self-supervised and contrastive learning workflows.

### CalibrationErrorMetric
[`CalibrationErrorMetric`](https://github.com/Project-MONAI/MONAI/pull/8707) and a corresponding `CalibrationError` handler measure how well predicted probabilities align with observed outcomes — important for clinical deployment of models.

## New Losses

### MCCLoss
[`MCCLoss`](https://github.com/Project-MONAI/MONAI/pull/8785) implements the Matthews Correlation Coefficient as a differentiable loss function, providing a balanced measure even under class imbalance.

### AUCMarginLoss
[`AUCMarginLoss`](https://github.com/Project-MONAI/MONAI/pull/8719) enables direct optimization of the AUROC metric via a margin-based surrogate loss.

## GradientAccumulation for SupervisedTrainer
A new [`GradientAccumulation`](https://github.com/Project-MONAI/MONAI/pull/8763) utility for `SupervisedTrainer` enables effective larger batch sizes on memory-constrained hardware by accumulating gradients over multiple steps.

## Nested Dot-Notation Access in ConfigParser
[`ConfigParser`](https://github.com/Project-MONAI/MONAI/pull/8858) now supports nested dot-notation access, making it easier to address deeply nested configuration keys in bundle configs (e.g., `network_def.layers.0.out_channels`).

## Global Coordinates in Spatial Crop Transforms
Spatial crop transforms [now support global coordinates](https://github.com/Project-MONAI/MONAI/pull/8794), allowing crops to be specified in world space rather than voxel indices.

## Minor Changes
- Generalized `TestTimeAugmentation` to support non-spatial predictions (`#8715`)
- Added MIG UUID and `CUDA_VISIBLE_DEVICES` support to `nnUNetV2Runner` (`#8716`)
- Replaced `pickle` with JSON in Auto3DSeg algo serialization (`#8695`)
- Fixed align_corners mismatch in `AffineTransform` (`#8690`)
- Fixed batch size broadcasting bug in `GeneralizedWassersteinDiceLoss` (`#8744`)
- Fixed swapped `input_amplitude`/`target_amplitude` in `JukeboxLoss` (`#8821`)
- Fixed `register_buffer` usage for kernel in `LocalNormalizedCrossCorrelationLoss` (`#8818`)
- Fixed `load_old_state_dict` key mapping in `AutoencoderKL` (`#8786`)
- Fixed nested `Compose` `map_items` in forward and inverse paths (`#8787`)
- Fixed multi-axis shear transform matrix composition (`#8778`)
- Fixed `AutoencoderKlMaisi` forcing CUDA transfer on CPU inputs (`#8736`)
- Fixed `TrainableBilateralFilter` 3D input validation (`#8729`)
- Fixed memory leak in `optional_import` traceback handling (`#8782`)
- Fixed `make_gaussian_kernel` truncated parameter unit mismatch (`#8781`, `#8783`)
- Fixed `SoftclDiceLoss` API compatibility with `DiceLoss` (`#8703`)
- Fixed `EnsureChannelFirst` `meta_data` handling when `track_meta=False` (`#8835`)
- Replaced `BaseException` with `Exception` across codebase (`#8859`)
- Avoided eager C-order copy in `NibabelReader` (`#8825`)
- Replaced direct `np.random.*` calls with `np.random.RandomState` instances (`#8798`)
- FFT module cleanup and updates (`#8762`, `#8766`)
- Various documentation and docstring improvements (`#8730`, `#8797`, `#8817`, `#8849`, `#8850`)
- Performance micro-optimizations in core utilities (`#8748`, `#8749`, `#8751`)
- Updated base Docker image to 25.12 (`#8738`)

Feel free to adjust the major-feature sections — particularly if any features need images or more detail added later (similar to the MAISI section in 1.5).

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