Datasets:
language:
- en
license: mit
tags:
- biology
- medical
- point cloud
- completion
task_categories:
- GRAPH_MACHINE_LEARNING
MedPointS-CPL
This is the medical point cloud completion dataset from MedPointS, as presented in the paper "Hierarchical Feature Learning for Medical Point Clouds via State Space Model".
- Paper: Hierarchical Feature Learning for Medical Point Clouds via State Space Model
- Code: https://github.com/wlsdzyzl/flemme
- Project page: https://flemme-docs.readthedocs.io/en/latest/medpoints.html
In this dataset, partial is the partial point cloud, 'target' is the target point cloud, and label is the class label.
Each point cloud has been normalized and sub-sampled to 2048 points. The correspondence between class names and labels is listed as follows (the label value plus 1 is the actual key of following map):
coarse_label_to_organ = {1: 'adrenalgland',
2: 'aorta',
3: 'autochthon',
4: 'bladder',
5: 'brain',
6: 'breast',
7: 'bronchie',
8: 'celiactrunk',
9: 'cheek',
10: 'clavicle',
11: 'colon',
12: 'costa',
13: 'duodenum',
14: 'esophagus',
15: 'eyeball',
16: 'femur',
17: 'gallbladder',
18: 'gluteusmaximus',
19: 'heart',
20: 'hip',
21: 'humerus',
22: 'iliacartery',
23: 'iliacvena',
24: 'iliopsoas',
25: 'inferiorvenacava',
26: 'kidney',
27: 'liver',
28: 'lung',
29: 'mediastinaltissue',
30: 'pancreas',
31: 'portalveinandsplenicvein',
32: 'smallbowel',
33: 'spleen',
34: 'stomach',
35: 'thymus',
36: 'thyroid',
37: 'trachea',
38: 'uterocervix',
39: 'uterus',
40: 'vertebrae',
41: 'gonads',
42: 'sacrum',
43: 'clavicula',
# 44: 'prostate',
44: 'pulmonaryartery',
# 45: 'ribcartilage',
45: 'rib',
46: 'scapula',
# 48: 'skull',
# 49: 'spinalcanal',
# 50: 'sternum'
}
Sample Usage
To train and evaluate models for point cloud completion using the Flemme framework, you can use the following commands. Note that you may need to adjust /path/to/project/flemme/ to your local Flemme installation path.
## completion
train_flemme --config /path/to/project/flemme/resources/pcd/medpoints/cpl/train_pointmamba2knn_cpl.yaml
test_flemme --config /path/to/project/flemme/resources/pcd/medpoints/cpl/test_pointmamba2knn_cpl.yaml
Citation
If you find our project helpful, please consider to cite the following work:
@misc{zhang2025hierarchicalfeaturelearningmedical,
title={Hierarchical Feature Learning for Medical Point Clouds via State Space Model},
author={Guoqing Zhang and Jingyun Yang and Yang Li},
year={2025},
eprint={2504.13015},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2504.13015},
}