Unconditional Image Generation
latent_diffusion
medical-imaging
diffusion
Can-Zhao commited on
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Update README.md

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@@ -66,7 +66,7 @@ This model was developed from scratch using MONAI components.
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  **Input Type(s):** Integer, List, Array
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  **Input Format(s):** Integer values, String arrays, Float arrays
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  **Input Parameters:** Number of Samples (1D), Output Size (1D), and Spacing (1D)
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- **Other Properties Related to Input:** Supports controllable synthetic MR generation with whole brain or skull-stripped brain selection, customizable output dimensions, configurable voxel spacing (0.5-5.0mm).
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  ### num_output_samples
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  - **Type:** Integer
@@ -94,7 +94,7 @@ This model was developed from scratch using MONAI components.
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  ### spacing
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  - **Type:** Array of 3 Floats
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  - **Description:** Optional voxel spacing specification
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- - **Range:** 0.5mm to 5.0mm per element
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  ## Output:
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  **Output Type(s):** Image
 
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  **Input Type(s):** Integer, List, Array
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  **Input Format(s):** Integer values, String arrays, Float arrays
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  **Input Parameters:** Number of Samples (1D), Output Size (1D), and Spacing (1D)
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+ **Other Properties Related to Input:** Supports controllable synthetic MR generation with whole brain or skull-stripped brain selection, customizable output dimensions, configurable voxel spacing (0.4-5.0mm).
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  ### num_output_samples
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  - **Type:** Integer
 
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  ### spacing
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  - **Type:** Array of 3 Floats
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  - **Description:** Optional voxel spacing specification
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+ - **Range:** 0.4mm to 5.0mm per element
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  ## Output:
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  **Output Type(s):** Image