ArticleBiomedical optics express2016
Segmentation guided registration of wide field-of-view retinal optical coherence tomography volumes.
Article in Biomedical optics express, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Multi-modal and inter-device retinal OCT registration via learning-based feature correspondence.Biomedical optics express · 2026Article
- Volumetric montaging of optical coherence tomography in human retinas.bioRxiv : the preprint server for biology · 2026Article
- Sensor-driven digital motion correction of robotically-aligned optical coherence tomography retinal volumes.Biomedical optics express · 2025Article
- Wide-field OCT volumetric segmentation using semi-supervised CNN and transformer integration.Scientific reports · 2025Article
- Automatic segmentation of layers in chorio-retinal complex using Graph-based method for ultra-speed 1.7 MHz wide field swept source FDML optical coherence tomography.Medical & biological engineering & computing · 2024Article
- Five degrees-of-freedom mechanical arm with remote center of motion (RCM) device for volumetric optical coherence tomography (OCT) retinal imaging.Biomedical optics express · 2024Article
- Automated inter-device 3D OCT image registration using deep learning and retinal layer segmentation.Biomedical optics express · 2023Article
- Higher-order regression three-dimensional motion-compensation method for real-time optical coherence tomography volumetric imaging of the cornea.Journal of biomedical optics · 2022Article
- Robust three-dimensional registration on optical coherence tomography angiography for speckle reduction and visualization.Quantitative imaging in medicine and surgery · 2021Article
- Efficient and high accuracy 3-D OCT angiography motion correction in pathology.Biomedical optics express · 2021Article
- Generating large field of view en-face projection images from intra-acquisition motion compensated volumetric optical coherence tomography data.Biomedical optics express · 2020Article
- Numerical method for axial motion artifact correction in retinal spectral-domain optical coherence tomography.Frontiers of optoelectronics · 2020Article
- Semi-automated registration and segmentation for gingival tissue volume measurement on 3D OCT images.Biomedical optics express · 2020Article
- Spectrally encoded coherence tomography and reflectometry: Simultaneous en face and cross-sectional imaging at 2 gigapixels per second.Journal of biophotonics · 2018Article
- Characterization of Long Working Distance Optical Coherence Tomography for Imaging of Pediatric Retinal Pathology.Translational vision science & technology · 2017Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Patient motion artifacts are often visible in densely sampled or large wide field-of-view (FOV) retinal optical coherence tomography (OCT) volumes. A popular strategy for reducing motion artifacts is to capture two orthogonally oriented volumetric scans. However, due to larger volume sizes, longer acquisition times, and corresponding larger motion artifacts, the registration of wide FOV scans remains a challenging problem. In particular, gaps in data acquisition due to eye motion, such as saccades, can be significant and their modeling becomes critical for successful registration. In this article, we develop a complete computational pipeline for the automatic motion correction and accurate registration of wide FOV orthogonally scanned OCT images of the human retina. The proposed framework utilizes the retinal boundary segmentation as a guide for registration and requires only a minimal transformation of the acquired data to produce a successful registration. It includes saccade detection and correction, a custom version of the optical flow algorithm for dense lateral registration and a linear optimization approach for axial registration. Utilizing a wide FOV swept source OCT system, we acquired retinal volumes of 12 subjects and we provide qualitative and quantitative experimental results to validate the state-of-the-art effectiveness of the proposed technique. The source code corresponding to the proposed algorithm is available online.
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