Ultrasonic diagnosis of cirrhosis based on preprocessing using pyramid recurrent neural network

Jianming Lu*, Jiang Liu, Xueqin Zhao, Takashi Yahagi

*この研究の対応する著者

研究成果: Article査読

抄録

In this paper, a pyramid recurrent neural network is applied to characterize the hepatic parenchymal diseases in ultrasonic B-scan texture. The cirrhotic parenchymal diseases are classified into four types according to the size of hypoechoic nodular lesions. The B-mode patterns are wavelet transformed, and then the compressed data are fed into a pyramid neural network to diagnose the type of cirrhotic diseases. Compared with the three-layer neural networks, the performance of the proposed pyramid recurrent neural network is improved by a more efficient utilization of lower layers. Simulation results show that the proposed system is suitable for diagnosis of cirrhosis diseases.

本文言語English
ページ(範囲)10-19
ページ数10
ジャーナルElectronics and Communications in Japan, Part II: Electronics (English translation of Denshi Tsushin Gakkai Ronbunshi)
91
7
DOI
出版ステータスPublished - 2008

ASJC Scopus subject areas

  • 物理学および天文学(全般)
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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