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.

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.