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Add more doc in maisi readme (Project-MONAI#1890)
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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 <69829124+Can-Zhao@users.noreply.github.com>
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Can-Zhao authored Dec 5, 2024
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Expand Up @@ -49,8 +49,8 @@ We retrained several state-of-the-art diffusion model-based methods using our da
| | Dedicated VAE | 0.047 | 0.971 | 34.750 | 619h |
| MSD Task08 | MAIS VAE | 0.046 | 0.970 | 36.559 | **0h** |
| | Dedicated VAE | **0.041**|**0.973**|**37.110**| 669h |
| Brats18 | MAIS VAE | **0.026**|**0.0977**| **39.003**| **0h** |
| | Dedicated VAE | 0.030 | 0.0975 | 38.971 | 672h |
| Brats18 | MAIS VAE | **0.026**|**0.977**| **39.003**| **0h** |
| | Dedicated VAE | 0.030 | 0.975 | 38.971 | 672h |

**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.

Expand Down Expand Up @@ -140,12 +140,28 @@ The information for the inference input, such as the body region and anatomy to


#### Recommended spacing for different output sizes:

|`output_size`| Recommended `"spacing"`|
|:-----:|:-----:|
[256, 256, 256] | [1.5, 1.5, 1.5] |
[512, 512, 128] | [0.8, 0.8, 2.5] |
[512, 512, 512] | [1.0, 1.0, 1.0] |
According to the statistics of the training data, we have recommended input parameters for the body region that are included in the training data.
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"`.
|`"body_region"` |percentage of training data |Recommended `"output_size"`| Recommended `"spacing"` [mm]|
|:--------------------------------------|:--------------------------|:----------------------|---------------------------:|
| ['chest', 'abdomen'] | 58.55% | [512, 512, 128] | [0.781, 0.781, 2.981] |
| ['chest'] | 38.35% | [512, 512, 128] | [0.684, 0.684, 2.422] |
| ['chest', 'abdomen', 'lower'] | 1.42% | [512, 512, 256] | [0.793, 0.793, 1.826] |
| ['lower'] | 0.61% | [512, 512, 384] | [0.839, 0.839, 0.728] |
| ['abdomen', 'lower'] | 0.37% | [512, 512, 384] | [0.808, 0.808, 0.729] |
| ['head', 'chest', 'abdomen'] | 0.33% | [512, 512, 384] | [0.977, 0.977, 2.103] |
| ['abdomen'] | 0.13% | [512, 512, 128] | [0.723, 0.723, 1.182] |
| ['head', 'chest', 'abdomen', 'lower'] | 0.13% | [512, 512, 384] | [1.367, 1.367, 4.603] |
| ['head', 'chest'] | 0.10% | [512, 512, 128] | [0.645, 0.645, 2.219] |

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"`.
For example,

|`"output_size"`| Recommended `"spacing"`|
|:--------------------------------------|:--------------------------|
|[256, 256, 256] | [1.5, 1.5, 1.5] |
|[512, 512, 128] | [0.8, 0.8, 2.5] |
|[512, 512, 512] | [1.0, 1.0, 1.0] |

#### Execute Inference:
To run the inference script, please run:
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