Choroid Segmentation

Choroid segmentation involves automatically identifying and measuring the choroid layer in optical coherence tomography (OCT) and other retinal imaging modalities. Current research emphasizes developing accurate, fast, and open-source automated segmentation algorithms, often employing deep learning architectures like U-Nets, often incorporating attention mechanisms to improve performance, particularly in segmenting choroidal vessels. This work aims to improve the objectivity and efficiency of choroid analysis, enabling large-scale studies and potentially facilitating earlier and more accurate diagnosis of various eye diseases and systemic conditions linked to choroidal changes. The availability of open-source tools is accelerating progress and standardization in this field.