Surgical Biomicroscopy Guided Intra-operative Optical Coherence Tomography (iOCT) Image Super Resolution

Charalampos Komninos*, Theodoros Pissas, Lina Mekki, Blanca Flores, Edward Bloch, Tom Vercauteren, Sebastien Ourselin, Lyndon Da Cruz, Christos Bergeles

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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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. Intraoperative 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.
Original languageEnglish
Pages (from-to)1
Number of pages13
JournalInternational Journal of Computer Assisted Radiology and Surgery
Publication statusAccepted/In press - 9 Mar 2022

Keywords

  • OPTICAL COHERENCE TOMOGRAPHY
  • Super-resolution
  • intra-operative optical coherence tomography

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