Automated classification of hip fractures using deep convolutional neural networks with orthopedic surgeon-level accuracy: ensemble decision-making with antero-posterior and lateral radiographs.

Background and purpose — Deep-learning approaches based on convolutional neural networks (CNNs) are gaining interest in the medical imaging field. We evaluated the diagnostic performance of a CNN to discriminate femoral neck fractures, trochanteric fractures, and non-fracture using antero-posterior...

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Bibliographic Details

Published in:	Acta Orthopaedica Vol. 91; no. 6; pp. 699 - 705
Main Authors:	Yamada, Yutoku, Maki, Satoshi, Kishida, Shunji, Nagai, Haruki, Arima, Junnosuke, Yamakawa, Nanako, Iijima, Yasushi, Shiko, Yuki, Kawasaki, Yohei, Kotani, Toshiaki, Shiga, Yasuhiro, Inage, Kazuhide, Orita, Sumihisa, Eguchi, Yawara, Takahashi, Hiroshi, Yamashita, Takeshi, Minami, Shohei, Ohtori, Seiji
Format:	diagnostic images research tables/charts Journal Article
Published:	Medical Journals Sweden AB Dec2020
Online Access:	View this record in EBSCOhost