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The retina is a layer of nervous tissue at the back of the eye that transduces light into neural signals. This process, called phototransduction, is carried out by rod and cone photoreceptor cells in the back of the retina.
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ROQUS: a retinal OCT quality and usability score.

Guilherme Aresta1, Teresa Araújo1, Georg Faustmann1

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Summary
This summary is machine-generated.

A novel deep learning tool, ROQUS, objectively assesses retinal OCT B-scan quality. This automated metric improves identification of poor-quality scans, aiding clinical research and practice.

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Optical Coherence Tomography (OCT) B-scans are crucial for retinal imaging.
  • Assessing the quality of OCT B-scans is vital for accurate diagnosis and research.
  • Current quality assessment methods can be subjective and time-consuming.

Purpose of the Study:

  • To develop and validate a deep learning-based metric for objective OCT B-scan quality assessment.
  • To evaluate the performance of the proposed metric against existing methods and human experts.
  • To enhance the identification of poor-quality OCT acquisitions for improved clinical utility.

Main Methods:

  • A deep learning model, ROQUS (Retinal OCT Quality Score), was developed using a ranking strategy.
  • The model was trained and tested on diverse datasets, including those with simulated and real acquisition artifacts.
  • Performance was evaluated using Receiver Operating Characteristic Area Under the Curve (ROC-AUC) and inter-rater agreement analysis.

Main Results:

  • ROQUS achieved an ROC-AUC of 0.85 in detecting B-scans with acquisition issues.
  • The metric demonstrated superior performance compared to classical quality assessment metrics.
  • ROQUS showed comparable agreement with human experts in ranking B-scan quality and effectively handled noise and brightness variations.

Conclusions:

  • ROQUS provides an objective and reliable method for assessing retinal OCT B-scan quality.
  • The tool can significantly improve the efficiency and accuracy of identifying suboptimal image acquisitions.
  • Implementation of ROQUS can streamline daily practice and enhance the reliability of clinical research involving OCT data.