| Name | amid JSON |
| Version |
0.14.0
JSON |
| download |
| home_page | None |
| Summary | A curated list of medical imaging datasets with unified interfaces |
| upload_time | 2024-10-04 16:24:42 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2022-2024 NeuroML Group Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
medical imaging
dataset
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
connectome
numpy
nibabel
more-itertools
dicom-csv
tqdm
pandas
pylidc
joblib
deli
scipy
scikit-image
pydicom
imops
highdicom
SimpleITK
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://neuro-ml.github.io/amid/)
[](https://neuro-ml.github.io/amid/latest/CONTRIBUTING/)
[](https://pypi.org/project/amid/)
Awesome Medical Imaging Datasets (AMID) - a curated list of medical imaging datasets with unified interfaces
# Getting started
Just import a dataset and start using it!
Note that for some datasets you must manually download the raw files first.
```python
from amid.verse import VerSe
ds = VerSe(root='/path/to/raw/data')
# get the available ids
print(len(ds.ids))
i = ds.ids[0]
# use the available methods:
# load the image and vertebrae masks
x, y = ds.image(i), ds.masks(i)
print(ds.split(i), ds.patient(i))
# or get a namedTuple-like object:
entry = ds(i)
x, y = entry.image, entry.masks
print(entry.split, entry.patient)
```
# Available datasets
| Name | Entries | Body region | Modality |
|:-----------------------------------------------------------------------------------------------------------------------------------|----------:|:------------------------------------|:-----------------------------------------------------------------------|
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.amos.dataset.AMOS">AMOS</a> | 2465 | Abdomen | CT, MRI |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.bimcv.BIMCVCovid19">BIMCVCovid19</a> | 16364 | Chest | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.brats2021.BraTS2021">BraTS2021</a> | 5880 | Head | MRI T1, MRI T1Gd, MRI T2, MRI T2-FLAIR |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.cc359.dataset.CC359">CC359</a> | 359 | Head | MRI T1 |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.cl_detection.CLDetection2023">CLDetection2023</a> | 400 | Head | X-ray |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.crlm.CRLM">CRLM</a> | 197 | Abdomen | CT, SEG |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.ct_ich.CT_ICH">CT_ICH</a> | 75 | Head | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.curvas.CURVAS">CURVAS</a> | 90 | Abdomen | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.crossmoda.CrossMoDA">CrossMoDA</a> | 484 | Head | MRI T1c, MRI T2hr |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.deeplesion.DeepLesion">DeepLesion</a> | 20094 | Abdomen, Thorax | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.egd.EGD">EGD</a> | 3096 | Head | FLAIR, MRI T1, MRI T1GD, MRI T2 |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.flare2022.FLARE2022">FLARE2022</a> | 2100 | Abdomen | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.hcp.HCP">HCP</a> | 1113 | Head | MRI |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.kits.KiTS23">KiTS23</a> | 489 | thorax | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.lidc.dataset.LIDC">LIDC</a> | 1018 | Chest | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.lits.dataset.LiTS">LiTS</a> | 201 | Abdominal | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.liver_medseg.LiverMedseg">LiverMedseg</a> | 50 | Chest, Abdomen | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.midrc.MIDRC">MIDRC</a> | 229 | Thorax | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.mood.MOOD">MOOD</a> | 1358 | Head, Abdominal | MRI, CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.msd.MSD">MSD</a> | 2628 | Chest, Abdominal, Head | CT, CE CT, MRI, MRI FLAIR, MRI T1w, MRI t1gd, MRI T2w, MRI T2, MRI ADC |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.mslub.dataset.MSLUB">MSLUB</a> | 70 | Head | MRI |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.medseg9.Medseg9">Medseg9</a> | 9 | Chest | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.cancer_500.dataset.MoscowCancer500">MoscowCancer500</a> | 979 | Thorax | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.covid_1110.MoscowCovid1110">MoscowCovid1110</a> | 1110 | Thorax | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.nlst.NLST">NLST</a> | 26254 | Thorax | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.nsclc.NSCLC">NSCLC</a> | 422 | Thorax | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.rsna_bc.dataset.RSNABreastCancer">RSNABreastCancer</a> | 54710 | Thorax | MG |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.ribfrac.dataset.RibFrac">RibFrac</a> | 660 | Chest | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.stanford_coca.StanfordCoCa">StanfordCoCa</a> | 1000 | Coronary, Chest | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.tbad.TBAD">TBAD</a> | 100 | Chest | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.totalsegmentator.dataset.Totalsegmentator">Totalsegmentator</a> | 1204 | Head, Thorax, Abdomen, Pelvis, Legs | CT |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.upenn_gbm.upenn_gbm.UPENN_GBM">UPENN_GBM</a> | 671 | Head | FLAIR, MRI T1, MRI T1GD, MRI T2, DSC MRI, DTI MRI |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.vs_seg.dataset.VSSEG">VSSEG</a> | 484 | Head | MRI T1c, MRI T2 |
| <a href="https://neuro-ml.github.io/amid/latest/datasets-api/#amid.verse.VerSe">VerSe</a> | 374 | Thorax, Abdomen | CT |
Check out [our docs](https://neuro-ml.github.io/amid/) for a more detailed list of available datasets and their fields.
# Install
Just get it from PyPi:
```shell
pip install amid
```
# Contribute
Check our [contribution guide](https://neuro-ml.github.io/amid/latest/CONTRIBUTING/) if you want to add a new dataset to
AMID.
Raw data
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"description": "[](https://neuro-ml.github.io/amid/)\n[](https://neuro-ml.github.io/amid/latest/CONTRIBUTING/)\n[](https://pypi.org/project/amid/)\n\n\nAwesome Medical Imaging Datasets (AMID) - a curated list of medical imaging datasets with unified interfaces\n\n# Getting started\n\nJust import a dataset and start using it!\n\nNote that for some datasets you must manually download the raw files first.\n\n```python\nfrom amid.verse import VerSe\n\n\nds = VerSe(root='/path/to/raw/data')\n# get the available ids\nprint(len(ds.ids))\ni = ds.ids[0]\n\n# use the available methods:\n# load the image and vertebrae masks\nx, y = ds.image(i), ds.masks(i)\nprint(ds.split(i), ds.patient(i))\n\n# or get a namedTuple-like object:\nentry = ds(i)\nx, y = entry.image, entry.masks\nprint(entry.split, entry.patient)\n```\n\n# Available datasets\n\n| Name | Entries | Body region | Modality |\n|:-----------------------------------------------------------------------------------------------------------------------------------|----------:|:------------------------------------|:-----------------------------------------------------------------------|\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.amos.dataset.AMOS\">AMOS</a> | 2465 | Abdomen | CT, MRI |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.bimcv.BIMCVCovid19\">BIMCVCovid19</a> | 16364 | Chest | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.brats2021.BraTS2021\">BraTS2021</a> | 5880 | Head | MRI T1, MRI T1Gd, MRI T2, MRI T2-FLAIR |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.cc359.dataset.CC359\">CC359</a> | 359 | Head | MRI T1 |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.cl_detection.CLDetection2023\">CLDetection2023</a> | 400 | Head | X-ray |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.crlm.CRLM\">CRLM</a> | 197 | Abdomen | CT, SEG |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.ct_ich.CT_ICH\">CT_ICH</a> | 75 | Head | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.curvas.CURVAS\">CURVAS</a> | 90 | Abdomen | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.crossmoda.CrossMoDA\">CrossMoDA</a> | 484 | Head | MRI T1c, MRI T2hr |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.deeplesion.DeepLesion\">DeepLesion</a> | 20094 | Abdomen, Thorax | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.egd.EGD\">EGD</a> | 3096 | Head | FLAIR, MRI T1, MRI T1GD, MRI T2 |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.flare2022.FLARE2022\">FLARE2022</a> | 2100 | Abdomen | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.hcp.HCP\">HCP</a> | 1113 | Head | MRI |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.kits.KiTS23\">KiTS23</a> | 489 | thorax | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.lidc.dataset.LIDC\">LIDC</a> | 1018 | Chest | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.lits.dataset.LiTS\">LiTS</a> | 201 | Abdominal | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.liver_medseg.LiverMedseg\">LiverMedseg</a> | 50 | Chest, Abdomen | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.midrc.MIDRC\">MIDRC</a> | 229 | Thorax | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.mood.MOOD\">MOOD</a> | 1358 | Head, Abdominal | MRI, CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.msd.MSD\">MSD</a> | 2628 | Chest, Abdominal, Head | CT, CE CT, MRI, MRI FLAIR, MRI T1w, MRI t1gd, MRI T2w, MRI T2, MRI ADC |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.mslub.dataset.MSLUB\">MSLUB</a> | 70 | Head | MRI |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.medseg9.Medseg9\">Medseg9</a> | 9 | Chest | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.cancer_500.dataset.MoscowCancer500\">MoscowCancer500</a> | 979 | Thorax | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.covid_1110.MoscowCovid1110\">MoscowCovid1110</a> | 1110 | Thorax | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.nlst.NLST\">NLST</a> | 26254 | Thorax | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.nsclc.NSCLC\">NSCLC</a> | 422 | Thorax | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.rsna_bc.dataset.RSNABreastCancer\">RSNABreastCancer</a> | 54710 | Thorax | MG |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.ribfrac.dataset.RibFrac\">RibFrac</a> | 660 | Chest | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.stanford_coca.StanfordCoCa\">StanfordCoCa</a> | 1000 | Coronary, Chest | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.tbad.TBAD\">TBAD</a> | 100 | Chest | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.totalsegmentator.dataset.Totalsegmentator\">Totalsegmentator</a> | 1204 | Head, Thorax, Abdomen, Pelvis, Legs | CT |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.upenn_gbm.upenn_gbm.UPENN_GBM\">UPENN_GBM</a> | 671 | Head | FLAIR, MRI T1, MRI T1GD, MRI T2, DSC MRI, DTI MRI |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.vs_seg.dataset.VSSEG\">VSSEG</a> | 484 | Head | MRI T1c, MRI T2 |\n| <a href=\"https://neuro-ml.github.io/amid/latest/datasets-api/#amid.verse.VerSe\">VerSe</a> | 374 | 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