amid 0.13.0

Description:

amid 0.13.0

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()
# 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
16335
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


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
155
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
4931
Thorax
CT


NSCLC
422
Thorax
CT


RSNABreastCancer
54710
Thorax
MG


RibFrac
660
Chest
CT


StanfordCoCa
971
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

Or if you want to use version control features:
git clone https://github.com/neuro-ml/amid.git
cd amid && pip install -e .

Contribute
Check our contribution guide if you want to add a new dataset to
AMID.