Assessment and removal of additive noise in a complex optical coherence tomography signal based on Doppler variation analysis

Spatial coordinate corrected motion tracking for optical coherence elastography

We investigate a spatial coordinate correction (SCC) method to track motion with high accuracy for optical coherence elastography (OCE). Through SCC, we refer the displacement field tracked by optical coherence tomography (OCT) in the loaded sample to individual material points defined in a fixed coordinate system. SCC allows OCE to perform spatially and temporally unambiguous tracking of displacement and enables accurate mechanical characterization of biological tissue for cancer diagnosis and tumor margin assessment. In this study, we validated the effectiveness of motion tracking based on SCC using experimental OCE data obtained from ex vivo human breast tissues.

Temporally and spatially adaptive Doppler analysis for robust handheld optical coherence elastography

Optical coherence elastography (OCE), a functional extension of optical coherence tomography (OCT), can be used to characterize the mechanical properties of biological tissue. A handheld fiber-optic OCE instrument will allow the clinician to conveniently interrogate the localized mechanical properties of in vivo tissue, leading to better informed clinical decision making. During handheld OCE characterization, the handheld probe is used to compress the sample and the displacement of the sample is quantified by analyzing the OCT signals acquired. However, the motion within the sample inevitably varies in time due to varying hand motion. Moreover, the motion speed depends on spatial location due to the sample deformation. Hence, there is a need for a robust motion tracking method for manual OCE measurement. In this study, we investigate a temporally and spatially adaptive Doppler analysis method. The method described here strategically chooses the time interval (δt) between signals involved in Doppler analysis to track the motion speed v(z,t) that varies temporally and spatially in a deformed sample volume under manual compression. Enabled by temporally and spatially adaptive Doppler analysis, we report the first demonstration of real-time manual OCE characterization of in vivo tissue to the best of our knowledge.