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

Jianming Lu, Jiang Liu, Xueqin Zhao, Takashi Yahagi

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 12 1

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

フィンガープリント 「Ultrasonic diagnosis of cirrhosis based on preprocessing using pyramid recurrent neural network」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル