Sensitivity improvement of automatic pulmonary nodules detection in chest X-ray CT images

Satoshi Shimoyama, Noriyasu Homma, Tadashi Ishibashi, Makoto Yoshizawa

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

Abstract

In this paper, we develop an automatic detection method of non-isolated pulmonary nodules as a part of computer-aided diagnosis (CAD) system for lung cancers in chest X-ray CT images. An essential core of the method is to separate non-isolated nodules from connecting structures like chest wall and blood vessels. The isolated nodules can be detected more easily by CAD syetems developed previously. To this end, we propose a binarization technique by using two thresholds as a preprocessing for nodule candidates. We evaluate the performance using the receiver operating characteristic (ROC) analysis in clinical chest CT images. The results suggest that detection ability of nonisolated nodules by the proposed method is superior to that by the conventional preprocessing methods.

Original languageEnglish
Title of host publicationProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10
Pages481-484
Number of pages4
Publication statusPublished - 2010
Event15th International Symposium on Artificial Life and Robotics, AROB '10 - Beppu, Oita, Japan
Duration: 2010 Feb 42010 Feb 6

Publication series

NameProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10

Other

Other15th International Symposium on Artificial Life and Robotics, AROB '10
CountryJapan
CityBeppu, Oita
Period10/2/410/2/6

Keywords

  • Computer-aided diagnosis
  • Lung cancer
  • Lung nodule
  • Multiple thresholds
  • X-ray CT

ASJC Scopus subject areas

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

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