Computer aided diagnosis system for pulmonary nodules using hierarchical feature extraction

K. Takei, N. Homma, T. Ishibashi, M. Sakai, M. Yoshizawa, K. Abe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a new diagnosis method of pulmonary nodules in CT images to reduce false positive rate (FP) for a high true positive rate (TP) conditions. An essential core of the method is in its hierarchical feature extraction. In the 1st stage, novel orientation features of nodules in a small region of interest (ROI) are extracted in addition to several conventional features, while a more structural feature of a surrounding area of the ROI is extracted in the 2nd stage. Without the orientation features, when TP was 90%, FP was about 65% and 55% in the 1st and 2nd stage, respectively. On the other hand, using the orientation features, FP was about 15% and only 5% in the 1st and 2nd stages, respectively. These improvement of the discrimination rate clearly demonstrates the effectiveness of the proposed hierarchical method on the nodules diagnosis.

Original languageEnglish
Title of host publicationProceedings of the 12th International Symposium on Artificial Life and Robotics, AROB 12th'07
Pages390-393
Number of pages4
Publication statusPublished - 2007
Event12th International Symposium on Artificial Life and Robotics, AROB 12th'07 - Oita, Japan
Duration: 2007 Jan 252007 Jan 27

Publication series

NameProceedings of the 12th International Symposium on Artificial Life and Robotis, AROB 12th'07

Other

Other12th International Symposium on Artificial Life and Robotics, AROB 12th'07
CountryJapan
CityOita
Period07/1/2507/1/27

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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