The comprehensive architectural analysis of the retinal vasculature would greatly aid with the diagnosis and management of many ocular diseases. Optical coherence tomography angiography (OCTA) is a powerful micrometerlevel resolution, high sensitivity, and potentially large field of view retinal imaging modality that allows assessment of 2D and 3D microvascular networks. However, the quality of retinal OCTA images are often degraded by the noise and poor vascular contrast. Digital image filters are widely used in medical diagnostic to selectively enhance specific local intensity profiles or structures such as vasculatures. Most successful feature enhancement filters employ Hessian matrix and eigen values-based approach. In this paper, we demonstrate the feasibility of multiscale Hessian filters for the enhancement of the OCTA images of a mouse retina. We show that the enhancement filter based on the ratio of Hessian eigenvalues proposed by Jerman et al. (Jerman filter) performs better than the most commonly used Frangi’s method. This improved performance included close-to-uniform response in all vascular structures and enhancement of visibility of vascular structures with non-circular cross-sections. To evaluate and compare performance, different multi-scale Hessian filtering was performed on OCTA images of different inner retina vascular beds of a mouse eye.
Vision is the most important sense organ of human, more than 80% of the information from outside world is acquired by vision. Vision starts at the photoreceptors in the retina capturing the visible light photons. There are two general types of photoreceptors, called rods and cones. Rods allow us to see in dim and dark light, cones allow us to perceive fine visual detail and color. To understand physiology of cones, researchers developed many model organisms that allow them to study in details different aspects of photoreceptors function. Specifically, mice play a central role in basic vision science research. However, one should keep in mind that mice have rod dominant retinas which is different from human cone dominant retinas near fovea.
As one of the consequence in vivo imaging of cones in humans is relatively easy in periphery, and cone mosaic was the first cellular structure that was reported to be seen by optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO), especially with implementation of adaptive optics (AO). However, just recently researchers started to visualize human rods which are smaller than cones [2, 3]. In case of mouse retinal imaging, it is quite the opposite situation. There have been recent reports of imaging rods mosaic [4-6], but up to date no reports on identifying cones in the images. Given that the cones are twice as big as rods in mice, it is very interesting why one can visualize rods but cannot visualize cones.
Speckle in optical coherence tomography (OCT) is a consequence of coherent detection scheme and is often considered as a noise submerging the micro-structures of biological tissue. In this work we present a novel method to suppress the speckle in OCT by introducing random phase shifts using a fully controlled segmented deformable mirror (DM) conjugated with imaging system pupil plane, allowing dynamic control of Point Spread Function (PSF) in the sample. These PSF modulations allow different set of scatters contribute to generation of un-correlated speckles, allowing for efficient suppression of speckle contrast by averaging multiple images. The speckle contrast suppression by the random shapes of deformable mirror was investigated in detail. We further present that the degradation of image intensity and resolution can be mitigated by using only the selected mirror shapes that correspond to the brighter OCT images, while maintains similar speckle suppression effect. Finally, the in vivo mouse retina imaging results demonstrate the capabilities of our method to enhance the visibility of subcellular micro-structures previously hidden behind the speckles.