Deep learning algorithm for detection of aortic dissection on non-contrast-enhanced CT

Objectives To develop a deep learning–based algorithm to detect aortic dissection (AD) and evaluate the diagnostic ability of the algorithm compared with those of radiologists. Methods Included in the study were 170 patients (85 with AD and 85 without AD). An AD detection algorithm was developed usi...

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Veröffentlicht in:	European radiology 2021-02, Vol.31 (2), p.1151-1159
Hauptverfasser:	Hata, Akinori, Yanagawa, Masahiro, Yamagata, Kazuki, Suzuki, Yuuki, Kido, Shoji, Kawata, Atsushi, Doi, Shuhei, Yoshida, Yuriko, Miyata, Tomo, Tsubamoto, Mitsuko, Kikuchi, Noriko, Tomiyama, Noriyuki
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Aneurysm, Dissecting - diagnostic imaging Aorta Aortic dissection Artificial intelligence Artificial neural networks Cardiac Computed tomography Deep Learning Diagnostic Radiology Diagnostic systems Dissection Ground truth Humans Image contrast Image enhancement Imaging Internal Medicine Interventional Radiology Machine learning Medical imaging Medicine Medicine & Public Health Neural networks Neuroradiology Radiologists Radiology Tomography, X-Ray Computed Training Ultrasound
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