Skip to main content
Log in

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

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Iinuma T, Tateno Y, Matsumoto T, et al (1992) Preliminary specification of X-ray CT for lung cancer screening (LSCT) and its evaluation on risk-cost-effectiveness (in Japanese). Radiation Med 52(2):182–190

    Google Scholar 

  2. Tateno Y, Iinuma T, Matsumoto T, et al (1990) Development of the X-ray CT for lung cancer examination (in Japanese). New Med Jpn 17(10):28–32

    Google Scholar 

  3. Yamamoto S, Tanaka I, Senda M (1993) Image processing for computer aided diagnosis in the lung cancer screening system by CT (LSCT) (in Japanese). IEICE Trans Inform Syst J76-D2(2):250–260

    Google Scholar 

  4. Miwa T, Kako J, Yamamoto S, et al (1999) Automatic detection of lung cancers in chest CT images by the variable N-Quoit filter (in Japanese). Trans Inst Electron Inform Commun Eng J82-D-II(2):178–187

    Google Scholar 

  5. Homma N, Takei K, Ishibashi T (2008) Combinatorial effect of various features extraction on computer aided detection of pulmonary nodules in X-ray CT images. WSEAS Trans Inform Sci Appl 5(7):1127–1136

    Google Scholar 

  6. Takei K, Homma N, Ishibashi T, et al (2008) Computer aided diagnosis for pulmonary nodules by extracting new shape features from X-ray CT images (in Japanese). Jpn Soc Fuzzy Theory Intell Inform 20(1):108–116

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Noriyasu Homma.

Additional information

This work was presented in part at the 15th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2010

About this article

Cite this article

Homma, N., Shimoyama, S., Ishibashi, T. et al. Sensitivity improvement of automatic pulmonary nodules detection in chest X-ray CT images. Artif Life Robotics 15, 526–529 (2010). https://doi.org/10.1007/s10015-010-0860-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-010-0860-1

Key words

Navigation