Preview

Journal of the Russian Universities. Radioelectronics

Advanced search

ENDOSCOPIC IMAGES DIGITAL PROCESSING FOR CLINICAL DECISION SUPPORT SYSTEMS

https://doi.org/10.32603/1993-8985-2018-21-6-54-65

Abstract

The purpose of this research is to create new automatic methods for endoscopic image digital processing, ensuring their high ergonomics and the possibility of effective use in clinical decision support systems. As the result of investigation, the following methods were proposed: the detection and removal of specular highlights; compensation of radial and tangential geometric distortions; the mosaic panorama creation from the input video stream with low level of detail; brightness and contrast enhancement, providing simultaneous successful correction of both dark and bright areas of the image (uneven contrast) without significant underlining of the noise component typical for the existing nonlinear contrasting methods, especially in low-detail image areas; custom color correction based on linear transformation matrix taking into account endoscopic image characteristics and making it possible to customize color palette according to the physician individual preferences. The methods considered were successfully tested on real endoscopic images at the department of innovative medical devices of the Korean Electrotechnological Research Institute. The test results demonstrate their effectiveness and applicability in clinical decision support systems.

About the Authors

Natalya A. Obukhova
Saint Petersburg Electrotechnical University "LETI"
Russian Federation

Natalia A. Obukhova – D.Sc. in Engineering (2009), Professor (2004) of the Department of Television and Video Equipment of Saint-Petersburg Electrotechnical University "LETI". The author of more than 70 scientific publications. Area of expertise: digital image processing; applied television systems.

5, Professor Popov Str., 197376, St. Petersburg




Alexander A. Motyko
Saint Petersburg Electrotechnical University "LETI"
Russian Federation

Alexander A. Motyko – Ph.D. in Engineering (2012), Associate Professor of the Department of Television and Video Equipment of Saint-Petersburg Electrotechnical University "LETI". The author of more than 30 scientific publications. Area of expertise: digital image processing; applied television systems.

5, Professor Popov Str., 197376, St. Petersburg




Alexander A. Pozdeev
Saint Petersburg Electrotechnical University "LETI"
Russian Federation

Alexander A. Pozdeev – Postgraduate Student, Assistant of the Department of Television and Video Equipment of Saint-Petersburg Electrotechnical University "LETI". The author of 10 scientific publications. Area of expertise: digital image processing; applied television systems.

5, Professor Popov Str., 197376, St. Petersburg



References

1. Liedlgruber M., Uhl A. Computer-Aided Decision Support Systems for Endoscopy in the Gastrointestinal Tract: A Review. IEEE Reviews in Biomedical Engineering. 2011, vol. 4, pp. 73–88.

2. Münzer B., Schoeffmann K., Böszörmenyi L. Content-Based Processing and Analysis of Endoscopic Images and Videos: A survey. Multimedia Tools and Applications. 2018, vol. 77(1), pp. 1323–1362.

3. Obukhova N., Motyko А. Image Analysis in Clinical Decision Support System. Computer Vision in Control Systems. Springer, 2017, pp. 261–299.

4. Serra J., Salembier P. Mathematical Morphology and Its Applications to Image Processing. Dordrecht, Netherlands: Kluwer Academic Publishers, 1994, 368 p.

5. Shih T., Chang R. C. Digital Inpainting – Survey and Multilayer Image Inpainting Algorithms. Proc of the Third Int’l Conf. on Information Technology and Applications (ICITA 2005), Sydney, Australia, 4–7 July 2005. Piscataway: IEEE, 2005, pp. 15–24.

6. Sethian J. A Fast Marching Level Set Method for Monotonically Advancing Fronts. Proc. of the Natl. Acad. Sci., Washington, 20 Feb. 1996, pp.1591–1595.

7. Walree P. Distortion. Available at: https://web.archive.org/web/20160420093927/http://toothwalker.org:80/optics/distortion.html (accessed 20.12.2018)

8. Hsu C. H., Miaou S. G., Chang F. L. A Distortion Correction Method for Endoscope Images Based on Calibration Patterns and a Simple Mathematic Model for Optical Lens. Biomedical Engineering Applications, Basis & Communications. 2005, vol. 17, pp. 309–318.

9. Harris C., Stephens M. A Combined Corner and Edge Detector. Proc. of the 4th Alvey Vision Conference, Manchester, UK, 1988, pp. 147–151.

10. Hartley R., Zisserman A. Multiple View Geometry in Computer Vision. Cambridge University Press, 2003, 561 p.

11. Obukhova N., Motyko А., Pozdeev A. Modern Methods and Algorithms in Digital Processing of Endoscopic Images. Proc. of Conference of Open Innovations Association FRUCT and ISPIT, Helsinki, Finland, 6-10 Nov. 2017. Piscataway, IEEE, 2017, pp. 260–267.

12. Vonikakis V., Andreadis I. Multi-Scale Image Contrast Enhancement. Proc. of the 10th Intl. Conf. on Control, Automation, Robotics and Vision. Hanoi, Vietnam, 17–20 Dec. 2008. Piscataway: IEEE, 2008, pp. 856–861.

13. Tao L., Asari K. V. An Adaptive and Integrated Neighborhood Dependent Approach for Nonlinear Enhancement of Color Images. SPIE Journal of Electronic Imaging. 2005, vol. 14(4), pp. 1–14.

14. Arigela S., Asari V. A Locally Tuned Nonlinear Technique for Color Image Enhancement. WSEAS Trans. Signal Process. 2008, vol. 4(8), pp. 514–519.

15. Obukhova N. A., Pozdeev A. A. Metod nelineinogo kontrastirovaniya meditsinskikh izobrazhenii [Nonlinear Contrast Method for Medical Images]. Sbornik dokl. 19-i Mezhdunarodnoi konferentsii "Tsifrovaya obrabotka signalov i ee primenenie DSPA-2017" [Proc. of 19th International Conference "Digital Signal Processing and Its Application DSPA-2017"]. 2017, pp 521–524. (In Russian)

16. Li W., Tompson M. S., Xiong Y., Lange H. A New Image Calibration Technique for Colposcopic Images. Medical Imaging 2006: Image Processing. Ed. by Joseph M. Reinhardt, Josien P. W. Pluim. Proc. of SPIE. 2006. Vol. 6144, pp. 227–239.

17. Patent US 8027533 B2, Method of Automated Image Color Calibration, 2008.

18. Wolf S. Color Correction Matrix for Digital Still and Video Imaging Systems. Washington: National Telecommunications and Information Administration, 2003, 20 p.

19. Trust the Colors with Olympus True Color LED. Available at: https://www.olympus-lifescience.com/en/resources/white-papers/true-color-led (accessed 20.12.2018).

20. Obukhova N.A., Motyko A.A. Color Calibration Procedure for Multispectral TV System for Diagnosing Cervix Uterus Oncological Changes. Voprosy radioelektroniki. Seriya: Tekhnika televideniya [Questions Radio Electronics. Television Equipment]. 2015, vol. 4, pp. 149–153. (In Russian)


Review

For citations:


Obukhova N.A., Motyko A.A., Pozdeev A.A. ENDOSCOPIC IMAGES DIGITAL PROCESSING FOR CLINICAL DECISION SUPPORT SYSTEMS. Journal of the Russian Universities. Radioelectronics. 2018;(6):54-65. (In Russ.) https://doi.org/10.32603/1993-8985-2018-21-6-54-65

Views: 802


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1993-8985 (Print)
ISSN 2658-4794 (Online)