TPUnit neural network and simple ensemble for abnormal shadow detection in lung X-ray images

Asumi Ikeda, Hiroki Yosimura, Maiya Hori, Tadaaki Shimizu, Yoshio Iwai, Satoru Kishida

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

We have constructed systems that detect abnormal areas of lung X-ray images from one-dimensional numeric sequences using neural networks. In these systems, the neural network consists of neurons that use trigonometric polynomials as activation functions, or TPUnit neural networks. The TPunit neural network has a high generalization ability in a smaller number of hidden units. Several TPUnit neural networks are placed in parallel and their outputs are processed as a simple ensemble. ROC curves denoted performance greater than that of previous reports. In addition, the AUC (area under curve) value was 0.9998 and the EER (equal error rate) was 0.5363%. Experimental results indicate that this proposed system is useful for medical imaging diagnosis.

本文言語英語
ホスト出版物のタイトルISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems
ページ285-289
ページ数5
DOI
出版ステータス出版済み - 12 1 2012
外部発表はい
イベント20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012 - Tamsui, New Taipei City, 台湾省、中華民国
継続期間: 11 4 201211 7 2012

出版物シリーズ

名前ISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems

その他

その他20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012
Country台湾省、中華民国
CityTamsui, New Taipei City
Period11/4/1211/7/12

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing

フィンガープリント 「TPUnit neural network and simple ensemble for abnormal shadow detection in lung X-ray images」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