Skip to main content

Advertisement

SpringerLink
Log in

Development of a method of automated extraction of biological fingerprints from chest radiographs as preprocessing of patient recognition and identification

  • Published:
Radiological Physics and Technology Aims and scope Submit manuscript

Abstract

This paper describes the development of an automated method of extraction of biological fingerprints (BFs), including detection of image orientation in chest radiographs. The image orientation of a target image was recognized and modified by examination of normalized cross-correlation values between a target image and averaged male and female images with correct image orientation. Templates of BFs were extracted from averaged images. Then, each BF in the target image was extracted from locations that showed the highest cross-correlation value between the template of BF in the averaged image and the corresponding BF in the target image. With our method, 100% (200/200) of image orientations were recognized correctly. If the orientation was recognized as inappropriate, our algorithm modified it into the appropriate chest image orientation. In addition, the BFs automatically extracted from target images were improved. This method would be useful in a preprocessing system for patient recognition and identification.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Morishita J, Watanabe H, Katsuragawa S, Oda N, Sukenobu Y, Okazaki H, Nakata H, Doi K. Investigation of misfiled cases in the PACS environment and a solution to prevent filing errors or chest radiographs. Acad Radiol. 2005;12(1):97–103.

    Article  PubMed  Google Scholar 

  2. Morishita J, Katsuragawa S, Kondo K, Doi K. An automated patient recognition method based on an image-matching technique using previous chest radiographs in the picture archiving and communication system environment. Med Phys. 2001;28(6):1093–7.

    Article  CAS  PubMed  Google Scholar 

  3. Kondo K, Morishita J, Katsuragawa S, Doi K. Development of an automated patient recognition method for chest radiographs using edge enhanced images. Jpn J Radiol Technol. 2003;59(10):1277–84 (in Japanese).

    Article  Google Scholar 

  4. Morishita J, Katsuragawa S, Sasaki Y, Doi K. Potential usefulness of biological fingerprints in chest radiographs for automated patient recognition and identification. Acad Radiol. 2004;11(3):309–15.

    Article  PubMed  Google Scholar 

  5. Toge R, Morishita J, Sasaki Y. Doi K. Computerized image-searching method for finding correct patients for chest radiographs in a PACS server by use of biological fingerprints. Radiol Phys Technol. 2013;6:437–43.

    Article  PubMed  Google Scholar 

  6. Kao EF, Lin WC, Jaw TS, Liu GC, Wu JS, Lee CN. Automated patient identify recognition by analysis of chest radiograph features. Acad Radiol. 2013;20(8):1024–31.

    Article  PubMed  Google Scholar 

  7. Ueda Y, Morishita J, Kudomi S, Ueda K. Usefulness of biological fingerprint in magnetic resonance imaging for patient verification. Med Biol Eng Comput. 2016;54(9):1341–51.

    Article  PubMed  Google Scholar 

  8. Shimizu Y, Matsunobu Y, Morishita J. Evaluation of the usefulness of modified biological fingerprints in chest radiographs for patient recognition and identification. Radiol Phys Technol. 2016;9(2):240–4.

    Article  PubMed  Google Scholar 

  9. Pietka E, Huang HK. Orientation correction for chest images. J Dig Imag. 1992;5:185–9.

    Article  CAS  Google Scholar 

  10. Arimura H, Katsuragawa S, Li Q, Ishida T, Doi K. Development of a computerized method for identifying the posteroanterior and lateral views of chest radiographs by use of a template matching technique. Med Phys. 2002;29(7):1556–61.

    Article  PubMed  Google Scholar 

  11. Nose H, Unno Y, Koike M, Shiraishi J. A simple method for identifying image orientation of chest radiographs by use of the center of gravity of the image. Radiol Phys Technol. 2012;5:207–12.

    Article  PubMed  Google Scholar 

  12. Sasaki Y, Abe K, Tabei M, Katsuragawa S, Kurosaki A, Matsuoka S. Clinical usefulness of temporal subtraction method in screening digital chest radiography with a mobile computed radiography system. Radiol Phys Technol. 2011;4:84–90.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank Yusuke Matsunobu, M.Sc., R.T., Yongsu Yoon, M.Sc., R.T., Keishin Kawamoto, B.Sc., R.T., Shun Tsubaki, B.Sc., R.T., and Hitomi Nakamura, B.Sc., R.T., for useful discussions and comments on this study. We also thank Dr. Yasuo Sasaki (Department of Radiology, Iwate Prefectural Central Hospital) for providing all chest images. The authors are grateful to the editorial assistant of this journal, Mrs. Lanzl, for providing initial and final polishing of our manuscript to improve the readability and English expressions. Also, we are grateful to the Editors and Reviewers for providing useful comments and suggestions on this study.

Author information

Authors and Affiliations

  1. Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan

    Yoichiro Shimizu

  2. Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan

    Junji Morishita

Authors
  1. Yoichiro Shimizu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Junji Morishita
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yoichiro Shimizu.

Ethics declarations

Conflict of interest

All authors have no conflicts of interest to disclose.

Ethical approval

All procedures in studies involving human participants were performed in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was waived by the Institutional Review Board for all images included in the database used in this study.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shimizu, Y., Morishita, J. Development of a method of automated extraction of biological fingerprints from chest radiographs as preprocessing of patient recognition and identification. Radiol Phys Technol 10, 376–381 (2017). https://doi.org/10.1007/s12194-017-0400-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12194-017-0400-y

Keywords

Search

Navigation