Deep Learning-based Angiogram Generation Model for Cerebral Angiography without Misregistration Artifacts

Background Digital subtraction angiography (DSA) generates an image by subtracting a mask image from a dynamic angiogram. However, patient movement-caused misregistration artifacts can result in unclear DSA images that interrupt procedures. Purpose To train and to validate a deep learning (DL)-based...

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Veröffentlicht in:	Radiology 2021-06, Vol.299 (3), p.203692-681
Hauptverfasser:	Ueda, Daiju, Katayama, Yutaka, Yamamoto, Akira, Ichinose, Tsutomu, Arima, Hironori, Watanabe, Yusuke, Walston, Shannon L, Tatekawa, Hiroyuki, Takita, Hirotaka, Honjo, Takashi, Shimazaki, Akitoshi, Kabata, Daijiro, Ichida, Takao, Goto, Takeo, Miki, Yukio
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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