OCT lymphangiography based on speckle statistics evaluation

Lev A. Matveev; Valentin Demidov; Marina A. Sirotkina; Dmitry A. Karashtin; Alexander A. Moiseev; Ivan Popov; Alexander A. Sovetsky; Alexander L. Matveyev; Olga Demidova; Grigory V. Gelikonov; Costel Flueraru; Elena V. Zagaynova; Natalia D. Gladkova; Vladimir Y. Zaitsev; I. Alex Vitkin

doi:10.1117/12.2523291

3 June 2019 OCT lymphangiography based on speckle statistics evaluation

Lev A. Matveev, Valentin Demidov, Marina A. Sirotkina, Dmitry A. Karashtin, Alexander A. Moiseev, Ivan Popov, Alexander A. Sovetsky, Alexander L. Matveyev, Olga Demidova, Grigory V. Gelikonov, Costel Flueraru, Elena V. Zagaynova, Natalia D. Gladkova, Vladimir Y. Zaitsev, I. Alex Vitkin

Author Affiliations +

Proceedings Volume 11065, Saratov Fall Meeting 2018: Optical and Nano-Technologies for Biology and Medicine; 1106502 (2019) https://doi.org/10.1117/12.2523291
Event: International Symposium on Optics and Biophotonics VI: Saratov Fall Meeting 2018, 2018, Saratov, Russian Federation

Abstract

We present an optical coherence tomography (OCT) lymphangiography visualization approach based on analysis of speckle statistics. For in-vivo experimentation, normal and tumor tissues are examined in mouse dorsal skin window chamber model. In order to evaluate the speckle statistics, OCT datasets are acquired in 3 spatial and 1 temporal dimensions to be divided then into smaller volumes of interests. In temporal dimension, repeated same-location scanning is performed for simultaneous blood vessel detection through speckle variance processing. Speckle statistics in each volume of interest are tested for similarity to known distributions corresponding either to noise or to tissue. We show that lymphatic vessels could be detected using a specific parameter range of speckle statistics as a filter, to separate the surrounding tissues and blood vessels. The proposed approach does not require numerous post-processing steps that are often used in lymphatic detection methods that are based on low signal amplitude regions (e.g., OCT signal attenuation compensation, inversion, amplitude thresholding etc.). Instead, we use a fast 2-step filtering procedure to reveal lymphatic vessels in imaged tissues.

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Lev A. Matveev, Valentin Demidov, Marina A. Sirotkina, Dmitry A. Karashtin, Alexander A. Moiseev, Ivan Popov, Alexander A. Sovetsky, Alexander L. Matveyev, Olga Demidova, Grigory V. Gelikonov, Costel Flueraru, Elena V. Zagaynova, Natalia D. Gladkova, Vladimir Y. Zaitsev, and I. Alex Vitkin "OCT lymphangiography based on speckle statistics evaluation", Proc. SPIE 11065, Saratov Fall Meeting 2018: Optical and Nano-Technologies for Biology and Medicine, 1106502 (3 June 2019); https://doi.org/10.1117/12.2523291

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