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Update README.md
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README.md
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| 1 |
---
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| 2 |
dataset_info:
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features:
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@@ -17,4 +101,4 @@ configs:
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data_files:
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- split: train
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path: data/train-*
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-
---
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---
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license: mit
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language:
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- en
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tags:
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- biology
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- point cloud
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- classification
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- medical
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---
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### MedPointS-CLS
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This is the medical point cloud classification dataset from [MedPoints](https://flemme-docs.readthedocs.io/en/latest/medpoints.html), where `data` is input point cloud, and `label` is the class label.
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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):
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```
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coarse_label_to_organ = {1: 'adrenalgland',
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2: 'aorta',
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3: 'autochthon',
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4: 'bladder',
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5: 'brain',
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6: 'breast',
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7: 'bronchie',
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8: 'celiactrunk',
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9: 'cheek',
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10: 'clavicle',
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11: 'colon',
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12: 'costa',
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13: 'duodenum',
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14: 'esophagus',
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15: 'eyeball',
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16: 'femur',
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17: 'gallbladder',
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18: 'gluteusmaximus',
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19: 'heart',
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20: 'hip',
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21: 'humerus',
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22: 'iliacartery',
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23: 'iliacvena',
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24: 'iliopsoas',
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25: 'inferiorvenacava',
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26: 'kidney',
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27: 'liver',
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28: 'lung',
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29: 'mediastinaltissue',
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30: 'pancreas',
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31: 'portalveinandsplenicvein',
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32: 'smallbowel',
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33: 'spleen',
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34: 'stomach',
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35: 'thymus',
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36: 'thyroid',
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37: 'trachea',
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38: 'uterocervix',
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39: 'uterus',
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40: 'vertebrae',
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41: 'gonads',
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42: 'sacrum',
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43: 'clavicula',
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# 44: 'prostate',
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44: 'pulmonaryartery',
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# 45: 'ribcartilage',
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45: 'rib',
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46: 'scapula',
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# 48: 'skull',
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# 49: 'spinalcanal',
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# 50: 'sternum'
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}
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```
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If you find our project helpful, please consider to cite the following works:
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```
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@misc{zhang2025hierarchicalfeaturelearningmedical,
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title={Hierarchical Feature Learning for Medical Point Clouds via State Space Model},
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author={Guoqing Zhang and Jingyun Yang and Yang Li},
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year={2025},
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eprint={2504.13015},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2504.13015},
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}
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```
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---
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dataset_info:
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features:
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data_files:
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- split: train
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path: data/train-*
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---
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