| Authors |
Chereshnev Vitaliy Olegovich, student, Tambov State Technical University (106 Sovetskaya street, Tambov, Russia), E-mail: Vitaliy-cha1999@yandex.ru
Frolov Sergey Vladimirovich, doctor of technical sciences, professor, head of sub-department of biomedical engineering, Tambov State Technical University (106 Sovetskaya street, Tambov, Russia), E-mail: sergej.frolov@gmail.com
Potlov Anton Yuryevich, candidate of technical sciences, associate professor, sub-department of biomedical engineering, Tambov State Technical University (106 Sovetskaya street, Tambov, Russia), E-mail: zerner@yandex.ru
Proskurin Sergey Gennadevich, doctor of technical sciences, candidate of physical and mathematical sciences, associate professor, Tambov State Technical University (106 Sovetskaya street, Tambov, Russia), E-mail: spros@tamb.ru
|
| Abstract |
Subject and goals. The paper presents the results of a study in which structural images of an optical coherent tomograph of human biological tissues and blood vessels in vivo. The aim of the study was to analyze the pixels of structural OCT images by calculating the dispersion matrix, constructing gamma distributions and histograms of pixel intensity variability.
Methods. The initial data of biological objects were obtained using an optical coherence tomograph based on a Michelson interferometer with coherence probing depth of about 1–1,5 mm and subjected to computer processing. Histograms of pixels’ distributions of the regions of biological tissue, blood vessel, and air were analyzed and least square approximated by the gamma distribution function with an accuracy of about R2 ~ 0.95. Variances between adjacent A-scans were also calculated, on the basis of which the OCT image variance matrix was also calculated. The dependences of the average intensity of the variance matrix of biological tissue, blood, and vessel regions on the number of averaged A-scans were revealed, what made it possible to determine tissue types. On the basis of the data obtained, image reconstruction algorithms have been developed based on a variance matrix that reflects the processes of backscattering and reflection of photons, as well as gamma distributions, corresponding to histogram distributions of structural images’ pixels of biological tissue, blood vessels, blood and air.
Results. The gamma distributions of areas of biological tissue, blood vessel and air show clear differences in the intensity of the structures. The variance matrix, in turn, shows the regions of backscattering and reflection of photons allowing differentiation of the skin area.
Conclusions. The combination of the advantages of the presented methods made it possible to reconstruct a high-precision OCT image with distinguishable boundaries of the corresponding structures, highlighting the areas of the blood vessel, blood, air, aneurysms and the depth of coherence probing.
|
| Key words |
optical coherence tomography (OCT), digital image processing, variance matrix, speckle structures, photon migration, gamma distribution
|
