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Surgical biomicroscopy-guided intra-operative optical coherence tomography (iOCT) image super-resolution

Komninos, Charalampos; Pissas, Theodoros; Mekki, Lina; Flores, Blanca; Bloch, Edward; Vercauteren, Tom; Ourselin, Sebastien; ... Bergeles, Christos; + view all (2022) Surgical biomicroscopy-guided intra-operative optical coherence tomography (iOCT) image super-resolution. International Journal of Computer Assisted Radiology and Surgery 10.1007/s11548-022-02603-5. (In press). Green open access

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Abstract

Purpose: Intra-retinal delivery of novel sight-restoring therapies will require the precision of robotic systems accompanied by excellent visualisation of retinal layers. Intra-operative Optical Coherence Tomography (iOCT) provides cross-sectional retinal images in real time but at the cost of image quality that is insufficient for intra-retinal therapy delivery.This paper proposes a super-resolution methodology that improves iOCT image quality leveraging spatiotemporal consistency of incoming iOCT video streams. Methods: To overcome the absence of ground truth high-resolution (HR) images, we first generate HR iOCT images by fusing spatially aligned iOCT video frames. Then, we automatically assess the quality of the HR images on key retinal layers using a deep semantic segmentation model. Finally, we use image-to-image translation models (Pix2Pix and CycleGAN) to enhance the quality of LR images via quality transfer from the estimated HR domain. Results: Our proposed methodology generates iOCT images of improved quality according to both full-reference and no-reference metrics. A qualitative study with expert clinicians also confirms the improvement in the delineation of pertinent layers and in the reduction of artefacts. Furthermore, our approach outperforms conventional denoising filters and the learning-based state-of-the-art. Conclusions: The results indicate that the learning-based methods using the estimated, through our pipeline, HR domain can be used to enhance the iOCT image quality. Therefore, the proposed method can computationally augment the capabilities of iOCT imaging helping this modality support the vitreoretinal surgical interventions of the future.

Type: Article
Title: Surgical biomicroscopy-guided intra-operative optical coherence tomography (iOCT) image super-resolution
Location: Germany
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s11548-022-02603-5
Publisher version: https://doi.org/10.1007/s11548-022-02603-5
Language: English
Additional information: Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Science & Technology, Technology, Life Sciences & Biomedicine, Engineering, Biomedical, Radiology, Nuclear Medicine & Medical Imaging, Surgery, Engineering, iOCT, Image quality assessment, Super-resolution, SPECKLE REDUCTION
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10147377
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