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README.md
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# VesselTok Data Release
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This archive contains the preprocessed data used to train the **Stage 1 implicit-function autoencoder** in the [VesselTok](https://arxiv.org/abs/2603.18797) codebase.
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## Contents
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### `all_centerlines/`
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Contains centerline graphs (`.vtp`) for all anatomies used in this work:
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* ATM'22
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* AIIB23
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* AeroPath
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* CoSTA
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* PARSE 2022
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* HiPaS
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* Pulmonary_AV
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* TopCoW
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Set this directory as:
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```yaml
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configs/base_config.yaml
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setup.ALL_CENTERLINES_PATH
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```
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### `sampled_points/`
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Contains precomputed occupancy query points at a grid resolution of **512**.
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There is one `.npz` file per centerline graph, with filenames matching those in `all_centerlines/`, except that the `.vtp` extension is replaced by `.npz`.
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These files constitute the training-time cache used with:
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```yaml
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im_configs.training.use_precomputed_gt_distance: True
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im_configs.training.num_points_per_axis_sampling: 512
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```
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Place this directory at:
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```text
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<MC_MESH_PATH>/occupancy/resolution_512/sampled_points
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```
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where `<MC_MESH_PATH>` corresponds to:
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```yaml
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configs/base_config.yaml
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setup.MC_MESH_PATH
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```
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## Not Included
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The following data are **not** included in this release:
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* **Ablation-specific data**
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Data used for resolution or occupancy-radius sweeps, sub-/supersampled centerlines, OOD kidney chunks, and related ablation experiments are not included.
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* **Other query-point resolutions**
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Precomputed query points at resolutions other than **512** are not included.
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## Setup Instructions
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See the **Data Setup** section of the main repository `README.md` for complete setup instructions.
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VesselTok_Data_Release.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:05eada2567174bc41cd6b1ab84a231ad2ac7e40e2abcb1da5a6138c80586475d
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size 32918607692
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