Computational modeling of full 3D OCT volumes

Develop computational methods to model entire three-dimensional optical coherence tomography (OCT) volumes holistically, rather than aggregating predictions from individual B-scans, to effectively capture inter-slice spatial structure and avoid the suboptimal performance of slice-wise aggregation approaches.

Background

Existing retinal foundation models such as RETFound primarily operate on 2D OCT slices (often the center B-scan) and can underutilize volumetric context present across the slow-scan dimension. Simple post hoc aggregation of slice-wise predictions does not fully leverage 3D structural continuity and may be suboptimal.

The paper introduces OCTCube, a 3D masked autoencoder-based framework with FlashAttention for efficiency, precisely to address the limitations of 2D-only or slice-aggregation approaches. This open problem highlights the broader methodological need for principled, effective 3D OCT volume modeling beyond naive aggregation.