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Add more doc in maisi readme (#1890)
Fixes # . ### 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: Can Zhao <[email protected]>
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generation/maisi/README.md

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@@ -49,8 +49,8 @@ We retrained several state-of-the-art diffusion model-based methods using our da
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| | Dedicated VAE | 0.047 | 0.971 | 34.750 | 619h |
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| MSD Task08 | MAIS VAE | 0.046 | 0.970 | 36.559 | **0h** |
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| | Dedicated VAE | **0.041**|**0.973**|**37.110**| 669h |
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| Brats18 | MAIS VAE | **0.026**|**0.0977**| **39.003**| **0h** |
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| | Dedicated VAE | 0.030 | 0.0975 | 38.971 | 672h |
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| Brats18 | MAIS VAE | **0.026**|**0.977**| **39.003**| **0h** |
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| | Dedicated VAE | 0.030 | 0.975 | 38.971 | 672h |
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**Table 2:** Performance comparison of the `MAIS VAE` model on out-of-distribution datasets (i.e., unseen during MAISI VAE training) versus `Dedicated VAE` models (i.e., train from scratch on in-distribution data). The “GPU” column shows additional GPU hours for training with one 32G V100 GPU. MAISI VAE model achieved comparable results without additional GPU resource expenditure on unseen datasets.
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@@ -140,12 +140,28 @@ The information for the inference input, such as the body region and anatomy to
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#### Recommended spacing for different output sizes:
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|`output_size`| Recommended `"spacing"`|
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|:-----:|:-----:|
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[256, 256, 256] | [1.5, 1.5, 1.5] |
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[512, 512, 128] | [0.8, 0.8, 2.5] |
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[512, 512, 512] | [1.0, 1.0, 1.0] |
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According to the statistics of the training data, we have recommended input parameters for the body region that are included in the training data.
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The Recommended `"output_size"` is the median value of the training data, the Recommended `"spacing"` is the median FOV (the product of `"output_size"` and `"spacing"`) divided by the Recommended `"output_size"`.
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|`"body_region"` |percentage of training data |Recommended `"output_size"`| Recommended `"spacing"` [mm]|
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|:--------------------------------------|:--------------------------|:----------------------|---------------------------:|
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| ['chest', 'abdomen'] | 58.55% | [512, 512, 128] | [0.781, 0.781, 2.981] |
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| ['chest'] | 38.35% | [512, 512, 128] | [0.684, 0.684, 2.422] |
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| ['chest', 'abdomen', 'lower'] | 1.42% | [512, 512, 256] | [0.793, 0.793, 1.826] |
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| ['lower'] | 0.61% | [512, 512, 384] | [0.839, 0.839, 0.728] |
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| ['abdomen', 'lower'] | 0.37% | [512, 512, 384] | [0.808, 0.808, 0.729] |
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| ['head', 'chest', 'abdomen'] | 0.33% | [512, 512, 384] | [0.977, 0.977, 2.103] |
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| ['abdomen'] | 0.13% | [512, 512, 128] | [0.723, 0.723, 1.182] |
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| ['head', 'chest', 'abdomen', 'lower'] | 0.13% | [512, 512, 384] | [1.367, 1.367, 4.603] |
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| ['head', 'chest'] | 0.10% | [512, 512, 128] | [0.645, 0.645, 2.219] |
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If users want to try different `"output_size"`, please adjust `"spacing"` to ensure a reasonable FOV, which is the product of `"output_size"` and `"spacing"`.
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For example,
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|`"output_size"`| Recommended `"spacing"`|
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|:--------------------------------------|:--------------------------|
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|[256, 256, 256] | [1.5, 1.5, 1.5] |
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|[512, 512, 128] | [0.8, 0.8, 2.5] |
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|[512, 512, 512] | [1.0, 1.0, 1.0] |
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#### Execute Inference:
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To run the inference script, please run:

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