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The effect of optical degradation from cataract using a new Deep Learning optical coherence tomography segmentation algorithm

  • Retinal Disorders
  • Published:
Graefe's Archive for Clinical and Experimental Ophthalmology Aims and scope Submit manuscript

Abstract 

Purpose

To assess the validity of the results of a freely available online Deep Learning segmentation tool and its sensitivity to noise introduced by cataract.

Methods

The OCT images were collected with a Spectralis SD-OCT (Heidelberg Engineering, Heidelberg, Germany) as part of normal clinical practice. Data were segmented using a freely available online tool called Relayer (https://www.relayer.online/), based on a cross-platform Deep Learning segmentation architecture specifically adapted for retinal OCT images. The segmentations were read into MATLAB (The MathWorks, Natick, MA, USA) and analyzed.

Results

There was an excellent agreement between the ETDRS measurements obtained from the two algorithms. Upon visual inspection, the segmentation based on Deep Learning obtained with Relayer appeared more accurate except in one case of apparent good quality image showing interrupted segmentations in some of the B-scans.

Conclusion

A freely available online Deep Learning segmentation tool showed good and promising performance in healthy retinas before and after cataract surgery, proving robust to optical degradation of the image from media opacities.

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Author information

Authors and Affiliations

  1. Eye Center, Humanitas Gavazzeni-Castelli, Bergamo, Italy

    Davide Allegrini & Mario R. Romano

  2. Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4Pieve Emanuele, 20072, Milan, Italy

    Raffaele Raimondi, Tania Sorrentino, Domenico Tripepi, Elisa Stradiotto, Francesco Paolo De Rosa & Mario R. Romano

  3. PolitoBIOMed Lab—Biomedical Engineering Lab and Department of Electronics and Telecommunications, Politecnico Di Torino, 10129, Turin, Italy

    Marco Caruso

Authors
  1. Davide Allegrini
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  2. Raffaele Raimondi
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  3. Tania Sorrentino
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  4. Domenico Tripepi
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  5. Elisa Stradiotto
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  6. Marco Caruso
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  7. Francesco Paolo De Rosa
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  8. Mario R. Romano
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Corresponding author

Correspondence to Raffaele Raimondi.

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Allegrini, D., Raimondi, R., Sorrentino, T. et al. The effect of optical degradation from cataract using a new Deep Learning optical coherence tomography segmentation algorithm. Graefes Arch Clin Exp Ophthalmol 262, 431–440 (2024). https://doi.org/10.1007/s00417-023-06261-4

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  • DOI: https://doi.org/10.1007/s00417-023-06261-4

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