Preview

Diagnostic radiology and radiotherapy

Advanced search

Results of clinical application of the color contrasting method of digitalx-rays

https://doi.org/10.22328/2079-5343-2021-12-4-83-98

Abstract

Introduction. Color processing of X-ray images has a long history and initially was directed for improvement of analysis of medical diagnostic images. Purpose — to evaluate the results of clinical application of the method for color contrast enhancement of digital radiographs.
Material and methods. The study was carried out in the X-ray department of the city Mariinsky hospital in St. Petersburg, having installed a computer program on the workstations of the radiologists for carrying out color contrasting of digital radiographs (CCDR). The CCDR program allowed the radiologist to select one of 63 trajectories in 8 colors. Choosing options for coloring, we settled on a warm, cold, full scale, as well as 4 combinations of one color from cold and warm scales with a saturation from 0 to 100%. The CCDR performed 100 digital radiographs of various anatomical areas.We analyzed a variety of colors and their percentage of saturation in terms of optimal transmission of pathological signs of anatomical areas. 27 radiologists assessed the possibilities of CCDR in X-ray diagnostics.
Results. Clinical application of CCDR showed that thanks to this method, tissues of different densities were distinguished in more detail on the X-ray image, since their contours were more expressively emphasized. Pathological symptoms, indistinctly expressed on a black-and-white radiograph, were convincingly reflected in the colorized image, which increased the sensitivity and specificity of the diagnosis. Thanks to color post-processing, it was possible to optimize subtle radiological signs of structural bone changes, traumatic injuries of the ribs, impaired pneumatization of the lungs (infiltration, hypoventilation), pneumo-, hydrothorax, and others. Of the radiologists, 77% considered it important to use CCDR in X-ray diagnostics.
Conclusion. A digital radiograph, contrasted with a color of optimal saturation, has distinct advantages over a traditional blackand-white X-ray image, since it reveals hidden or subtle diagnostic information. The diagnostic efficiency of the method of color contrasting of radiographs is higher than the analysis of black-and-white images up to 13%.To increase the diagnostic capabilities of X-ray diagnostics, it is advisable to include the method of color contrasting in the package of computer post-processing of images, using at least three gamuts in the standard, the saturation of which is 25–50%.The colorized image does not replace black and white, but complements it, resolving the diagnostic doubts of the radiologist.

About the Authors

I. G. Kamyshanskaya
St. Petersburg State University; Mariinsky City Hospita; Maternity hospital № 6 named after professor V. F. Snegirev
Russian Federation

St. Petersburg



V. M. Cheremisin
St. Petersburg State University; Mariinsky City Hospital
Russian Federation

St. Petersburg



References

1. Roentgenograms // Amer. J. Roentgenology, Radium Therapy, and Nuclear Medicine. 1958. Vol. 79, No. 2. Р. 342–347. PMID: 13498226.

2. Bykov R.E., Korkunov Yu.F. Television in medicine and biology. Leningrad: Publishing house Energy, 1968, 224 р. (In Russ.).

3. Miroshnikov M.M., Lisovskii V.A., Filippov E.V. еt al. Iconics in physiology and medicine / еd. by A.M.Ugalevа; USSR Academy of Sciences, Department of Physiology. Leningrad, Science, Leningrad Branch, 1987, 391 р. ((In Russ.).

4. Technical means of medical Introscope. Edited by B.I.Leonova; Moscow: Publishing house Medicine, 1989, 304 р. (In Russ.).

5. Ivanov S.A., Komiak N.I., Mazurov A.I. X-ray television methods for the study of microstructures. Leningrad: Publishing house Mechanical Engineering, 1983, 131 р. (In Russ.).

6. Shi Xie-Qi., Sällström P., Welander U. A color-coding method for radiographic images // Image and Vision Computing. 2002. Vol. 20, pp. 762–767. doi: 10.1016/S0262-8856(02)00045-8.

7. Sanavullah M.Y., Ravindran S. Pseudocolour Image Processing in Digital Mammography // Proceedings of the International Conference on Cognition and Recognition. 2004. Р. 752–758.

8. Shi Xie-Qi., Yoshiura G., Li K., Welander U. Perceptibility curve test for conventional and color-coded radiographs // Dentomaxillofacial Radiology. 2004. Vol. 33, pp. 318–322. https://doi.org/10.1259/dmfr/27372105.

9. Khan M.A.U., Khan R.B., Bilal Sh., Jamil A., Shah M.A. Enhancement of Angiogram Images Using Pseudo Color Processing // Information Technology Journal. 2008. Vol. 7, No. 1. Р. 210–214. doi: 10.3923/itj.2008.210.214.

10. Shi Xie-Qi, Sallstrom P., Welander U. A colorcoding method for radiographic images // Image and Vision Computing. 2002. Vol. 20, No. 11, pp. 761–767. doi: 10.1016/S0262-8856(02)00045-8.

11. Raghuvanshi R.S., Datar A. Composite Pseudocoloring Scheme Using Spiral Method with Ensuring Same Brightness. International Journal of Engineering Trends and Technology, 2013, Vol. 4, No. 7, рр. 2800–2805 (In Russ.).

12. Niuberg N.D. Theoretical foundations of color reproduction. Moscow: Publishing house Soviet science, 1947, 176 р. (In Russ.).

13. Mazurov A.I., Denisov A.K. An effective method of coding radiographs with color. Diagnostic radiology and radiotherapy, 2018, Vol. 9, No. 1, pp. 176–177 (In Russ.).

14. Mazurov A.I., Raevskaya K.A. Lowest colormetric quantum model. See the invisible Collection of scientific papers Issue 3ed. by A.I. Mazurova, Yu.Yu. Mikhailova. St. Petersburg, OOO «St. Petersburg: SRP. „Pavel” VOG», 2017. pp. 36–39 (In Russ.).

15. Mazurov A.I. Parametric colorimetric system FED (E). See the invisible. Collection of scientific papers Issue 3 edited by A.I.Mazurova, Yu.Yu. Mikhailova. St. Petersburg: OOO «SPb. SRP. „Pavel” VOG», 2017, pp. 119–120 (In Russ.).

16. Li G., Engström P.E., Welander U. Measurement accuracy of marginal bone level in digital radiographs with and without color coding // Acta Odontol Scand. 2007. Oct. Vol. 65, No. 5, pp. 254–258. doi: 10.1080/00016350701452089. PMID: 18092199.

17. Moon Suh Park, Jae Yong Byun, Seung Geun Yeo, Ho Yun Lee. Use of Pseudocolor for Detecting Otologic Structures in CT // Theory and Applications of CT Imaging and Analysis. 2011. Р. 205–212. doi: 10.5772/14670.

18. Pelka O, Nensa F, Friedrich C.M. Annotation of enhanced radiographs for medical image retrieval with deep convolutional neural networks // PLOS ONE. 2018. Vol. 13, No. 11. e0206229. doi: 10.1371/journal.pone.0206229.

19. Blinov N.N., Mazurov A.I. Visualization of medical images in color. Medical equipment, 2013, Vol. 281, No. 5, pp. 1–3 (In Russ.).

20. Blinov N.N. Eye and image. Moscow, Medicine, 2004, 320 р.(In Russ.).


Review

For citations:


Kamyshanskaya I.G., Cheremisin V.M. Results of clinical application of the color contrasting method of digitalx-rays. Diagnostic radiology and radiotherapy. 2021;12(4):83-98. (In Russ.) https://doi.org/10.22328/2079-5343-2021-12-4-83-98

Views: 542


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


ISSN 2079-5343 (Print)