In vivo microvascular network imaging of the human retina combined with an automatic three-dimensional segmentation method

Microvascular network of the retina plays an important role in diagnosis and monitoring of various retinal diseases. We propose a three-dimensional (3-D) segmentation method with intensity-based Doppler variance (IBDV) based on swept-source optical coherence tomography. The automatic 3-D segmentation method is used to obtain seven surfaces of intraretinal layers. The microvascular network of the retina, which is acquired by the IBDV method, can be divided into six layers. The microvascular network of the six individual layers is visualized, and the morphology and contrast images can be improved by using the segmentation method. This method has potential for earlier diagnosis and precise monitoring in retinal vascular diseases.

Imaging and quantifying Brownian motion of micro- and nanoparticles using phase-resolved Doppler variance optical coherence tomography

Different types and sizes of micro- and nanoparticles have been synthesized and developed for numerous applications. It is crucial to characterize the particle sizes. Traditional dynamic light scattering, a predominant method used to characterize particle size, is unable to provide depth resolved information or imaging functions. Doppler variance optical coherence tomography (OCT) measures the spectral bandwidth of the Doppler frequency shift due to the Brownian motion of the particles utilizing the phase-resolved approach and can provide quantitative information about particle size. Spectral bandwidths of Doppler frequency shifts for various sized particles were quantified and were demonstrated to be inversely proportional to the diameter of the particles. The study demonstrates the phase-resolved Doppler variance spectral domain OCT technique has the potential to be used to investigate the properties of particles in highly scattering media.