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Update vista3d tutorial readme (#1859)
Fixes #1856. ### Description A few sentences describing the changes proposed in this pull request. ### Checks <!--- Put an `x` in all the boxes that apply, and remove the not applicable items --> - [ ] Avoid including large-size files in the PR. - [ ] Clean up long text outputs from code cells in the notebook. - [ ] For security purposes, please check the contents and remove any sensitive info such as user names and private key. - [ ] Ensure (1) hyperlinks and markdown anchors are working (2) use relative paths for tutorial repo files (3) put figure and graphs in the `./figure` folder - [ ] Notebook runs automatically `./runner.sh -t <path to .ipynb file>` --------- Signed-off-by: heyufan1995 <[email protected]> Signed-off-by: YunLiu <[email protected]> Co-authored-by: YunLiu <[email protected]>
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vista_3d/README.md

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# MONAI **V**ersatile **I**maging **S**egmen**T**ation and **A**nnotation
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[[`Paper`](https://arxiv.org/pdf/2406.05285)] [[`Demo`](https://build.nvidia.com/nvidia/vista-3d)] [[`Checkpoint`](https://developer.download.nvidia.com/assets/Clara/monai/tutorials/model_zoo/model_vista3d.pt)]
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## Overview
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The **VISTA3D** is a foundation model trained systematically on 11,454 volumes encompassing 127 types of human anatomical structures and various lesions. It provides accurate out-of-the-box segmentation that matches state-of-the-art supervised models which are trained on each dataset. The model also achieves state-of-the-art zero-shot interactive segmentation in 3D, representing a promising step toward developing a versatile medical image foundation model.
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The tutorial demonstrates how to finetune the VISTA3D model on user data, where we use the MSD Task09 Spleen as the example.
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In Summary the tutorial covers the following:
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- Creation of datasets and data transforms for training and validation
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- Create and VISTA3D model and load the pretrained checkpoint
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- Implementation of the finetuning loop
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- Mixed precision training with GradScaler
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- Visualization of training loss and validation accuracy
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- Inference on a single validation image
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- Visualization of input image, ground truth, and model prediction
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For more advanced use, please refer to [VISTA3D research codebase](https://github.com/Project-MONAI/VISTA/tree/main/vista3d) and [VISTA3D bundle](https://github.com/Project-MONAI/model-zoo/tree/dev/models/vista3d)
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## License
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The codebase is under Apache 2.0 Licence. The model weight is released under [NVIDIA OneWay Noncommercial License](./NVIDIA%20OneWay%20Noncommercial%20License.txt).

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