Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge Article Swipe
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Adam E. Flanders
,
Luciano M. Prevedello
,
George Shih
,
Safwan S. Halabi
,
Jayashree Kalpathy–Cramer
,
Robyn L. Ball
,
John Mongan
,
Anouk Stein
,
Felipe Kitamura
,
Matthew P. Lungren
,
Gagandeep Choudhary
,
Lesley Cala
,
Luiz Coelho
,
Monique A. Mogensen
,
Fanny Morón
,
Elka Miller
,
Ichiro Ikuta
,
Vahe M. Zohrabian
,
Olivia McDonnell
,
Christie M. Lincoln
,
Lubdha M. Shah
,
David Joyner
,
Amit Agarwal
,
Ryan K. Lee
,
Jaya Nath
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1148/ryai.2020190211
· OA: W3023284086
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1148/ryai.2020190211
· OA: W3023284086
This dataset is composed of annotations of the five hemorrhage subtypes (subarachnoid, intraventricular, subdural, epidural, and intraparenchymal hemorrhage) typically encountered at brain CT.
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