Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation

amos22.zip 24.23GB
Type: Dataset
Tags: computed tomography

Bibtex:
@article{,
title= {Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation},
keywords= {computed tomography},
author= {},
abstract= {AMOS provides 500 CT and 100 MRI scans collected from multi-center, multi-vendor, multi-modality, multi-phase, multi-disease patients, each with voxel-level annotations of 15 abdominal organs, providing challenging examples and test-bed for studying robust segmentation algorithms under diverse targets and scenarios. We further benchmark several state-of-the-art medical segmentation models to evaluate the status of the existing methods on this new challenging dataset. We have made our datasets, benchmark servers, and baselines publicly available, and hope to inspire future research. 


https://zenodo.org/record/7155725},
terms= {},
license= {https://creativecommons.org/licenses/by/4.0/legalcode},
superseded= {},
url= {https://amos22.grand-challenge.org/}
}

Hosted by users:

Send Feedback Start
   0.000005
DB Connect
   0.000240
Lookup hash in DB
   0.000417
Get torrent details
   0.000379
Get torrent details, finished
   0.000467
Get authors
   0.000004
Select authors
   0.000241
Parse bibtex
   0.000452
Write header
   0.000361
get stars
   0.000270
home tab
   0.000252
render right panel
   0.000006
render ads
   0.000043
fetch current hosters
   0.000413
Done