A curated list of medical imaging datasets with unified interfaces
Project description
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.
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 |
---|---|---|---|
AMOS | 2465 | Abdomen | CT, MRI |
BIMCVCovid19 | 16364 | Chest | CT |
BraTS2021 | 5880 | Head | MRI T1, MRI T1Gd, MRI T2, MRI T2-FLAIR |
CC359 | 359 | Head | MRI T1 |
CLDetection2023 | 400 | Head | X-ray |
CRLM | 197 | Abdomen | CT, SEG |
CT_ICH | 75 | Head | CT |
CURVAS | 90 | Abdomen | CT |
CrossMoDA | 484 | Head | MRI T1c, MRI T2hr |
DeepLesion | 20094 | Abdomen, Thorax | CT |
EGD | 3096 | Head | FLAIR, MRI T1, MRI T1GD, MRI T2 |
FLARE2022 | 2100 | Abdomen | CT |
HCP | 1113 | Head | MRI |
KiTS23 | 489 | thorax | CT |
LIDC | 1018 | Chest | CT |
LiTS | 201 | Abdominal | CT |
LiverMedseg | 50 | Chest, Abdomen | CT |
MIDRC | 229 | Thorax | CT |
MOOD | 1358 | Head, Abdominal | MRI, CT |
MSD | 2628 | Chest, Abdominal, Head | CT, CE CT, MRI, MRI FLAIR, MRI T1w, MRI t1gd, MRI T2w, MRI T2, MRI ADC |
MSLUB | 70 | Head | MRI |
Medseg9 | 9 | Chest | CT |
MoscowCancer500 | 979 | Thorax | CT |
MoscowCovid1110 | 1110 | Thorax | CT |
NLST | 26254 | Thorax | CT |
NSCLC | 422 | Thorax | CT |
RSNABreastCancer | 54710 | Thorax | MG |
RibFrac | 660 | Chest | CT |
StanfordCoCa | 1000 | Coronary, Chest | CT |
TBAD | 100 | Chest | CT |
Totalsegmentator | 1204 | Head, Thorax, Abdomen, Pelvis, Legs | CT |
UPENN_GBM | 671 | Head | FLAIR, MRI T1, MRI T1GD, MRI T2, DSC MRI, DTI MRI |
VSSEG | 484 | Head | MRI T1c, MRI T2 |
VerSe | 374 | Thorax, Abdomen | CT |
Check out our docs for a more detailed list of available datasets and their fields.
Install
Just get it from PyPi:
pip install amid
Contribute
Check our contribution guide if you want to add a new dataset to AMID.
Project details
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