BreakNet: Discontinuity-Resilient Multi-Scale Transformer Segmentation of Retinal Layers

Visible light optical coherence tomography (vis-OCT) is gaining traction for retinal imaging due to its high resolution and functional capabilities. However, the significant absorption of hemoglobin in the visible light range leads to pronounced shadow artifacts from retinal blood vessels, posing challenges for accurate layer segmentation. In this study, we present BreakNet, a multi-scale Transformer-based segmentation model designed to address boundary discontinuities caused by these shadow artifacts. BreakNet utilizes hierarchical Transformer and convolutional blocks to extract multi-scale global and local feature maps, capturing essential contextual, textural, and edge characteristics. The model incorporates decoder blocks that expand pathwaproys to enhance the extraction of fine details and semantic information, ensuring precise segmentation. Evaluated on rodent retinal images acquired with prototype vis-OCT, BreakNet demonstrated superior performance over state-of-the-art segmentation models, such as TCCT-BP and U-Net, even when faced with limited-quality ground truth data. Our findings indicate that BreakNet has the potential to significantly improve retinal quantification and analysis.

Choroidal vasculature imaging with laser Doppler holography

The choroid is a highly vascularized tissues supplying the retinal pigment epithelium and photoreceptors. Its implication in retinal diseases is gaining increasing interest. However, investigating the anatomy and flow of the choroid remains challenging. Here we show that laser Doppler holography provides high contrast imaging of choroidal vessels in humans, with a spatial resolution comparable to state of the art indocyanine green angiography and optical coherence tomography. Additionally, laser Doppler holography contributes to sort out choroidal arteries and veins by using a power Doppler spectral analysis. We thus demonstrate the potential of laser Doppler holography to improve our understanding of the anatomy and flow of the choroidal vascular network.