The PVT1010 dataset includes 1,010 pairs of high resolution inhale/exhale lung vascular trees extracted from 3D computed tomography (CT) images.
Details on how we extracted the lung vascular trees as high-resolution 3D point clouds from the raw CT images can be found at Suppl.A.1.
We use public DirLab-COPD Gene dataset to evaluate our registration results. Please follow the official instruction to download the data.
DirLab-COPD includes 10 pair cases. For each pair, 300 expert annotated landmarks that are in correspondence with each other.
These 10 cases are used as test cases.
The full dataset can be accessed at
https://drive.google.com/drive/folders/1iA6VSAjmMP_iEHp1iae4anu-RELxtgTq?usp=sharing
The vascular tree reconstructions that are used in this study were part of the COPDGene study (NCT00608764). This study has been IRB approved and participants have provided their consent.
cd robot/experiments/datasets/lung
sh prepare_lung_data.sh DIRLAB_DATA_FOLDER PVT1010_DATA_FOLDER DATASPLITS_FOLDER
DIRLAB_DATA_FOLDER
refers to unzipped dirlab data, including 10 data folders: copd1-copd10.PVT1010_DATA_FOLDER
refers to PVT1010 data, including 2020 vtk (1010 pairs) data files.DATASPLITS_FOLDER
(output folder) records the data splits. Four folders will be created inDATASPLITS_FOLDER
, which refers to the "train", "val", "test", "debug"* splits.
*Here the "debug" split refers to a subset of training set, to help diagnose the model behavior on training set.
- lung_local_plot.py visualizes the anistropic kernel on vessels
- lung_data_anlsysis.py computes and matches the lung radius distribution