# Adaptive Curved Slicing for En Face Imaging in Optical Coherence Tomography

## TL;DR

This paper introduces a new method for improving en face imaging in OCT by using curved slicing to reduce interference from strong reflections in thin layers.

## Contribution

The novel approach uses Otsu-based thresholding and polynomial curve fitting to adaptively slice OCT images for better en face visualization.

## Key findings

- The method achieved an FSIM score of 0.7020, outperforming traditional en face OCT with a score of 0.6445.
- It successfully analyzed latent fingerprints on translucent tape, which is challenging for conventional techniques.
- The approach is compatible with other signal processing methods, as shown by ink thickness measurements on thermal-printed labels.

## Abstract

Optical coherence tomography (OCT) employs light to acquire high-resolution 3D images and is widely applied in fields such as ophthalmology and forensic science. A popular technique for visualizing the top view (en face) is to slice it with flat horizontal plane or apply statistical functions along the depth axis. However, when the target appears as a thin layer, strong reflections from other layers can interfere with the target, rendering the flat-plane approach ineffective. We apply Otsu-based thresholding to extract the object’s foreground, then use least squares (with Tikhonov regularization) to fit a polynomial curve that describes the sample’s structural morphology. The surface is then used to obtain the latent fingerprint image and its residues at different depths from a translucent tape, which cannot be analyzed using conventional en face OCT due to strong reflection from the diffusive surface, achieving FSIM of 0.7020 compared to traditional en face of 0.6445. The method is also compatible with other signal processing techniques, as demonstrated by a thermal-printed label ink thickness measurement confirmed by a microscopic image. Our approach empowers OCT to observe targets embedded in samples with arbitrary postures and morphology, and can be easily adapted to various optical imaging technologies.