Multidimensional Deep Learning Reduces False-Positives in the Automated Detection of Cerebral Aneurysms on Time-Of-Flight Magnetic Resonance Angiography: A Multi-Center Study

Current deep learning-based cerebral aneurysm detection demonstrates high sensitivity, but produces numerous false-positives (FPs), which hampers clinical application of automated detection systems for time-of-flight magnetic resonance angiography. To reduce FPs while maintaining high sensitivity, w...

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Detalles Bibliográficos
Autores principales: Terasaki, Yuki, Yokota, Hajime, Tashiro, Kohei, Maejima, Takuma, Takeuchi, Takashi, Kurosawa, Ryuna, Yamauchi, Shoma, Takada, Akiyo, Mukai, Hiroki, Ohira, Kenji, Ota, Joji, Horikoshi, Takuro, Mori, Yasukuni, Uno, Takashi, Suyari, Hiroki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805516/
https://www.ncbi.nlm.nih.gov/pubmed/35115991
http://dx.doi.org/10.3389/fneur.2021.742126

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805516/
https://www.ncbi.nlm.nih.gov/pubmed/35115991
http://dx.doi.org/10.3389/fneur.2021.742126

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