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Enhance 0.7 README doc (#3017)
* [DLMED] update README Signed-off-by: Nic Ma <[email protected]> * [DLMED] update what's new Signed-off-by: Nic Ma <[email protected]> * [DLMED] use whatsnew link Signed-off-by: Nic Ma <[email protected]>
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README.md

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## Features
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> _The codebase is currently under active development._
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> _Please see [the technical highlights](https://docs.monai.io/en/latest/highlights.html) and [What's New in 0.6](https://docs.monai.io/en/latest/whatsnew_0_6.html) of the current milestone release._
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> _Please see [the technical highlights](https://docs.monai.io/en/latest/highlights.html) and [What's New](https://docs.monai.io/en/latest/whatsnew.html) of the current milestone release._
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- flexible pre-processing for multi-dimensional medical imaging data;
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- compositional & portable APIs for ease of integration in existing workflows;

docs/source/whatsnew_0_7.md

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With the performance profiling and enhancements, several typical use cases were studied to
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improve the training efficiency. The following figure shows that fast
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training using MONAI can be 20 times faster than a regular baseline ([learn
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more](https://github.com/Project-MONAI/tutorials/blob/master/acceleration/fast_training_tutorial.ipynb)).
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training using MONAI can be `200` times faster than a regular baseline ([learn
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more](https://github.com/Project-MONAI/tutorials/blob/master/acceleration/fast_training_tutorial.ipynb)), and it's `20` times faster than the MONAI v0.6 fast training solution.
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![fast_training](../images/fast_training.png)
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## Major usability improvements in `monai.transforms` for NumPy/PyTorch inputs and backends

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