A Spatiotemporal Model for Precise and Efficient Fully-Automatic 3D Motion Correction in OCT

Ploner S, Chen S, Won J, Husvogt L, Breininger K, Schottenhamml J, Fujimoto J, Maier A (2022)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2022

Journal

Publisher: Springer Science and Business Media Deutschland GmbH

Book Volume: 13432 LNCS

Pages Range: 517-527

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Singapore, SGP

ISBN: 9783031164330

DOI: 10.1007/978-3-031-16434-7_50

Open Access Link: https://arxiv.org/abs/2209.07232

Abstract

Optical coherence tomography (OCT) is a micrometer-scale, volumetric imaging modality that has become a clinical standard in ophthalmology. OCT instruments image by raster-scanning a focused light spot across the retina, acquiring sequential cross-sectional images to generate volumetric data. Patient eye motion during the acquisition poses unique challenges: Non-rigid, discontinuous distortions can occur, leading to gaps in data and distorted topographic measurements. We present a new distortion model and a corresponding fully-automatic, reference-free optimization strategy for computational motion correction in orthogonally raster-scanned, retinal OCT volumes. Using a novel, domain-specific spatiotemporal parametrization of forward-warping displacements, eye motion can be corrected continuously for the first time. Parameter estimation with temporal regularization improves robustness and accuracy over previous spatial approaches. We correct each A-scan individually in 3D in a single mapping, including repeated acquisitions used in OCT angiography protocols. Specialized 3D forward image warping reduces median runtime to < 9 s, fast enough for clinical use. We present a quantitative evaluation on 18 subjects with ocular pathology and demonstrate accurate correction during microsaccades. Transverse correction is limited only by ocular tremor, whereas submicron repeatability is achieved axially (0.51 μ m median of medians), representing a dramatic improvement over previous work. This allows assessing longitudinal changes in focal retinal pathologies as a marker of disease progression or treatment response, and promises to enable multiple new capabilities such as supersampled/super-resolution volume reconstruction and analysis of pathological eye motion occurring in neurological diseases.

Authors with CRIS profile

Involved external institutions

Massachusetts Institute of Technology (MIT) United States (USA) (US)

How to cite

APA:

Ploner, S., Chen, S., Won, J., Husvogt, L., Breininger, K., Schottenhamml, J.,... Maier, A. (2022). A Spatiotemporal Model for Precise and Efficient Fully-Automatic 3D Motion Correction in OCT. In Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 517-527). Singapore, SGP: Springer Science and Business Media Deutschland GmbH.

MLA:

Ploner, Stefan, et al. "A Spatiotemporal Model for Precise and Efficient Fully-Automatic 3D Motion Correction in OCT." Proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, Singapore, SGP Ed. Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li, Springer Science and Business Media Deutschland GmbH, 2022. 517-527.

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