Computer aided diagnosis for pulmonary nodules by shape feature extraction

Kazunori Takei, Noriyasu Homma, Tadashi Ishibashi, Masao Sakai, Makoto Yoshizawa

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

In this paper, we propose a new diagnosis method of pulmonary nodules in CT images to reduce false positive (FP) rate for high true positive (TP) rate conditions. An essential core of the method is to extract two novel and effective features from the raw CT images: One is orientation features of nodules in a region of interest (ROI) extracted by a gabor filter, while the other is variation of CT values of the ROI in the direction along body axis. By using the extracted features, a principal component analysis technic and neural network approaches are then used to discriminate between nodule and non-nodule images. Simulation results show that discrimination performance using the proposed features is extremely improved compared to that of the conventional method.

本文言語English
ホスト出版物のタイトルSICE Annual Conference, SICE 2007
ページ1964-1967
ページ数4
DOI
出版ステータスPublished - 2007 12 1
イベントSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan
継続期間: 2007 9 172007 9 20

出版物シリーズ

名前Proceedings of the SICE Annual Conference

Other

OtherSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
CountryJapan
CityTakamatsu
Period07/9/1707/9/20

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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