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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
amid-0.15.0.tar.gz
(62.7 kB
view details)
File details
Details for the file amid-0.15.0.tar.gz.
File metadata
- Download URL: amid-0.15.0.tar.gz
- Upload date:
- Size: 62.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.22
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f3f19a5a4d2d3bdb573ad3495656eda49a0dfe9722062d49d193e9e3acf4bc8f
|
|
| MD5 |
ad1322e176d4e20125d95bbafc2f57e7
|
|
| BLAKE2b-256 |
a5450eb12bfae7e26c74b3fad92094e0558e82b159eb1a44d28cac0050496a21
|