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

Noriyasu Homma, Satoshi Shimoyama, Tadashi Ishibashi, Yusuke Kawazumi, Makoto Yoshizawa

研究成果: Article査読

抄録

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

本文言語English
ページ(範囲)526-529
ページ数4
ジャーナルArtificial Life and Robotics
15
4
DOI
出版ステータスPublished - 2010

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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