APTOS-2024 challenge report: Generation of synthetic 3D OCT images from fundus photographs
Journal:
arXiv
Published Date:
Jun 9, 2025
Abstract
Optical Coherence Tomography (OCT) provides high-resolution, 3D, and
non-invasive visualization of retinal layers in vivo, serving as a critical
tool for lesion localization and disease diagnosis. However, its widespread
adoption is limited by equipment costs and the need for specialized operators.
In comparison, 2D color fundus photography offers faster acquisition and
greater accessibility with less dependence on expensive devices. Although
generative artificial intelligence has demonstrated promising results in
medical image synthesis, translating 2D fundus images into 3D OCT images
presents unique challenges due to inherent differences in data dimensionality
and biological information between modalities. To advance generative models in
the fundus-to-3D-OCT setting, the Asia Pacific Tele-Ophthalmology Society
(APTOS-2024) organized a challenge titled Artificial Intelligence-based OCT
Generation from Fundus Images. This paper details the challenge framework
(referred to as APTOS-2024 Challenge), including: the benchmark dataset,
evaluation methodology featuring two fidelity metrics-image-based distance
(pixel-level OCT B-scan similarity) and video-based distance (semantic-level
volumetric consistency), and analysis of top-performing solutions. The
challenge attracted 342 participating teams, with 42 preliminary submissions
and 9 finalists. Leading methodologies incorporated innovations in hybrid data
preprocessing or augmentation (cross-modality collaborative paradigms),
pre-training on external ophthalmic imaging datasets, integration of vision
foundation models, and model architecture improvement. The APTOS-2024 Challenge
is the first benchmark demonstrating the feasibility of fundus-to-3D-OCT
synthesis as a potential solution for improving ophthalmic care accessibility
in under-resourced healthcare settings, while helping to expedite medical
research and clinical applications.
