English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

When the optic disc is swollen, the visibility of the Bruch's membrane opening (BMO) is often drastically reduced in spectral-domain optical coherence tomography (SD-OCT) volumes. Recent work pro- posed a semi-automated method to segment the BMO using combined information from 2D high-definition raster and 3D volumetric SD-OCT scans; however, manual placement of six landmark points was required. In this work, we propose a fully automated approach to segment the BMO from 2D high-definition and 3D volumetric SD-OCT scans. Using the topographic shape of the internal limiting membrane and textural information near Bruch's membrane, two BMO points are first estimated in the high-definition central B-scan and then registered into the corre- sponding volumetric scan. Utilizing the information from both the high- definition BMO estimates and the standard-definition SD-OCT volume, the cost image was created. A graph-based algorithm with soft shape- based constraints is further applied to segment the BMO contour on the SD-OCT en-face image domain. Using a set of 23 volumes with reason- ably centered raster scans and swelling larger than 14.42 mm 3 , the fully automated approach was significantly more accurate than a traditional approach utilizing information only from the SD-OCT volume (RMS er- ror of 7.18 vs. 21.37 in pixels; p < 0.05) and had only a slightly higher (and not significantly dierent) error than the previously proposed semi- automated approach (RMS error of 7.18 vs. 5.30 in pixels; p = 0.08).

Automated Bruch’s Membrane Opening Segmentation in Cases of Optic Disc Swelling in Combined 2D and 3D SD-OCT Images Using Shape-Prior and Texture Information