Distributed deep learning across multisite datasets for generalized CT hemorrhage segmentation

Purpose As deep neural networks achieve more success in the wide field of computer vision, greater emphasis is being placed on the generalizations of these models for production deployment. With sufficiently large training datasets, models can typically avoid overfitting their data; however, for med...

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Veröffentlicht in:	Medical physics (Lancaster) 2020-01, Vol.47 (1), p.89-98
Hauptverfasser:	Remedios, Samuel W., Roy, Snehashis, Bermudez, Camilo, Patel, Mayur B., Butman, John A., Landman, Bennett A., Pham, Dzung L.
Format:	Artikel
Sprache:	eng
Schlagworte:	computed tomography (CT) Deep Learning distributed hemorrhage Hemorrhage - diagnostic imaging Humans Image Processing, Computer-Assisted - methods image segmentation lesion multisite neural network Tomography, X-Ray Computed traumatic brain injury
Online-Zugang:	Volltext
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