Automatic quality evaluation as assessment standard for optical coherence tomography

Item Type:	Conference or Workshop Item
Title:	Automatic quality evaluation as assessment standard for optical coherence tomography
Creators Name:	Kauer, J. and Gawlik, K. and Zimmermann, H.G. and Kadas, E.M. and Bereuter, C. and Paul, F. and Brandt, A.U. and Hausser, F. and Beckers, I.
Abstract:	Retinal optical coherence tomography (OCT) is increasingly used for quantifying neuroaxonal damage in diseases of the central nervous system such as multiple sclerosis. High-quality OCT images are essential for accurate intraretinal segmentation and for correct quantification of retinal thickness changes. The quality of OCT images depends largely on the operator and patient compliance. Quality evaluation is time-consuming, and current OCT image quality criteria depend on the experience of the grader and are therefore subjective. The automatic graderindependent real-time feedback system for quality evaluation of retinal OCT images, AQuA, was developed to standardize quality evaluation and data accuracy. It classifies by signal quality, anatomical completeness and segmentation plausibility and has been validated by experienced graders. However, it is currently limited to OCT scans taken with one device from a single vendor. The aim of this work is to improve the capability of the AQuA quality classifier to generalize to new data, by developing a convolutional neural network (CNN), AQuANet. Moreover, this CNN may serve as a basic quality classifier, that can be adapted to specific problems by transfer learning. AQuANet is trained on A-Scan batches with quality labels automatically obtained with AQuA. Thus, a large set of training data of about 13000 A-Scan batches could be used, leading to an accuracy of 99.53%.
Keywords:	Optical Coherence Tomography, Real-Time Feedback, Quality Analysis, Quality Standard
Source:	Proceedings of SPIE
Series Name:	Proceedings of SPIE
Title of Book:	Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVII
ISSN:	0277-786X
Publisher:	International Society for Optics and Photonics (SPIE)
Volume:	10868
Page Range:	1086814
Date:	26 February 2019
Official Publication:	https://doi.org/10.1117/12.2510393

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