Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

We propose a novel attention gate (AG) model for medical image analysis that automatically learns to focus on target structures of varying shapes and sizes. Models trained with AGs implicitly learn to suppress irrelevant regions in an input image while highlighting salient features useful for a spec...

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Detalles Bibliográficos
Autores principales: Schlemper, Jo, Oktay, Ozan, Schaap, Michiel, Heinrich, Mattias, Kainz, Bernhard, Glocker, Ben, Rueckert, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610718/
https://www.ncbi.nlm.nih.gov/pubmed/30802813
http://dx.doi.org/10.1016/j.media.2019.01.012

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610718/
https://www.ncbi.nlm.nih.gov/pubmed/30802813
http://dx.doi.org/10.1016/j.media.2019.01.012

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