Title
From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge.
Abstract
Automated detection of cancer metastases in lymph nodes has the potential to improve the assessment of prognosis for patients. To enable fair comparison between the algorithms for this purpose, we set up the CAMELYON17 challenge in conjunction with the IEEE International Symposium on Biomedical Imaging 2017 Conference in Melbourne. Over 300 participants registered on the challenge website, of whic...
Year
DOI
Venue
2019
10.1109/TMI.2018.2867350
IEEE Transactions on Medical Imaging
Keywords
Field
DocType
Lymph nodes,Biomedical imaging,Tumors,Metastasis,Pathology,Hospitals
Computer vision,Kappa,Confusion matrix,Medical imaging,Convolutional neural network,Sentinel lymph node,Artificial intelligence,Mathematics,Lymph node,Machine learning,False positive paradox,Test set
Journal
Volume
Issue
ISSN
38
2
0278-0062
Citations 
PageRank 
References 
8
0.47
0
Authors
36