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May 9, 2026Recent Advances in Computer Science and Communications

Optical Coherence Tomography Image Layer Segmentation Using AIDriven Techniques – A Review

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Authors

MYMithilesh Kumar Singh YadavNSNagendra Pratap Singh

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Overview

Review compares various image segmentation methods in retinal imaging, indicating a need for standardized evaluation.

Key Points

  • The review aims to analyze and compare traditional and AI-driven techniques for segmenting retinal layers in OCT imaging.
  • Systematic analysis of traditional, machine learning, and deep learning methods for OCT segmentation.
  • Comparative study using publicly available datasets and assessment metrics.
  • Presentation of findings in a dedicated table summarizing methodologies.
  • Deep learning models, especially U-Net variants, outperform classical methods in segmentation accuracy.
  • Most methods show reduced generalization on datasets with varying imaging characteristics.
  • Highlights need for standardized datasets and clinically relevant metrics to improve validation.

Cite This Study

Yadav et al. (2026) studied this question.

synapsesocial.com/papers/69fed153b9154b0b828788cfhttps://doi.org/10.2174/0126662558441195260316054353
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