Test-Time Image Reconstruction for Cross-Device OCT Fingerprint Extraction

Optical coherence tomography (OCT) technology enables imaging of 3D fingerprint structures. Extracting surface and internal fingerprints for identity recognition is possible by processing OCT images with layer segmentation and contour extraction. However, due to domain shift effects, OCT fingerprint extraction models often struggle to perform well across different devices. In this paper, a cross-device OCT fingerprint extraction method based on test-time image reconstruction is proposed. This method simultaneously trains layer segmentation and image reconstruction tasks during training. Additionally, a contour classification task is integrated to ensure the continuity and robustness of the contour extraction results. During the testing phase, image reconstruction is performed on test images, and the shared modules are updated to adapt the layer segmentation and contour classification network to the test domain. The result with the minimum inconsistency during the testing phase is selected as the final prediction. Experiments and comparisons are performed in terms of the distance between the ground truth and the extracted contours.