Improvement of the diagnostic accuracy for intracranial haemorrhage using deep learning–based computer-assisted detection.

Purpose: To elucidate the effect of deep learning–based computer-assisted detection (CAD) on the performance of different-level physicians in detecting intracranial haemorrhage using CT. Methods: A total of 40 head CT datasets (normal, 16; haemorrhagic, 24) were evaluated by 15 physicians (5 board-c...

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Publicado en:	Neuroradiology Vol. 63; no. 5; pp. 713 - 721
Autores principales:	Watanabe, Yoshiyuki, Tanaka, Takahiro, Nishida, Atsushi, Takahashi, Hiroto, Fujiwara, Masahiro, Fujiwara, Takuya, Arisawa, Atsuko, Yano, Hiroki, Tomiyama, Noriyuki, Nakamura, Hajime, Todo, Kenichi, Yoshiya, Kazuhisa
Formato:	diagnostic images research tables/charts Journal Article
Publicado:	Springer Nature May2021
Acceso en línea:	Ver este registro en EBSCOhost