Probabilistic OCT Post-Processing Methods
Néstor Uribe-Patarroyo and his team are pushing the envelope to improve functional and endogenous contrast OCT imaging, independent of instrument platform, with the development of probabilistic post-processing techniques. This work has already resulted unimproved structural and polarization imaging, and there are extensions to multiple functional imaging modalities in the works.
CBORT OCT/OFDI Raw Data Reconstruction
Python Package on Github
CBORT is excited to announce that it has developed an open source Python package for reconstructing raw OCT/OFDI available through GitHub as a general tool for dissemination and education. When coupled with acquisition frameworks, this new package allows for automated processing of raw OCT data into analyzable images with little to no user input.
Layer-based, depth resolved computation of attenuation coefficients and backscattering fractions in tissue using optical coherence tomography
Taylor Cannon, graduate student at CBORT demonstrated an improved, layer-based approach, for calculating depth-resolved attenuation coefficients to improve quantitative OCT imaging.