Intra-operative OCT (iOCT) Image Quality Enhancement: A Super-Resolution Approach Using High Quality iOCT 3D Scans

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

3 Citations (Scopus)
86 Downloads (Pure)

Abstract

Effective treatment of degenerative retinal diseases will require robot-assisted intraretinal therapy delivery supported by excellent retinal layer visualisation capabilities. Intra-operative Optical Coherence Tomography (iOCT) is an imaging modality which provides real-time, cross-sectional retinal images partially allowing visualisation of the layers where the sight restoring treatments should be delivered. Unfortunately, iOCT systems sacrifice image quality for high frame rates, making the identification of pertinent layers challenging. This paper proposes a Super-Resolution pipeline to enhance the quality of iOCT images leveraging information from iOCT 3D cube scans. We first explore whether 3D iOCT cube scans can indeed be used as high-resolution images by performing Image Quality Assessment. Then, we apply non-rigid image registration to generate partially aligned pairs, and we carry out data augmentation to increase the available training data. Finally, we use CycleGAN to transfer the quality between low-resolution (LR) and high-resolution (HR) domain. Quantitative analysis demonstrates that iOCT quality increases with statistical significance, but a qualitative study with expert clinicians is inconclusive with regards to their preferences.

Original languageEnglish
Title of host publicationOphthalmic Medical Image Analysis - 8th International Workshop, OMIA 2021, Held in Conjunction with MICCAI 2021, Proceedings
EditorsHuazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
PublisherSpringer Science and Business Media Deutschland GmbH
Pages21-31
Number of pages11
ISBN (Print)9783030869991
DOIs
Publication statusPublished - 2021
Event8th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2021 held in conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 - Virtual, Online
Duration: 27 Sept 202127 Sept 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12970 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2021 held in conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021
CityVirtual, Online
Period27/09/202127/09/2021

Keywords

  • Image quality assessment
  • iOCT
  • Super-resolution

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