{
  "abstract": "Purpose\n\nTo develop an automated image processing pipeline to segment retinal arterial walls in a series of adaptive optics ophthalmoscopy (AOO) images, overcoming difficulties related to various quality levels within the series, to accurately evaluate morphometric differences.Methods\n\nWe first assess the quality of AOO images by deep learning in order to select the best quality image in the sequence. Then, we segment this image by combining deep learning and dedicated active contour models. Finally, we segment the other images of the sequence using the best image segmentation as a regularization exploiting the temporal continuity to compensate for lower quality.Results\n\nWe applied the proposed method to flicker series, a challenging use-case given the image quality heterogeneity. The quality assessment method achieves a Spearman correlation coefficient of 0.86, demonstrating very good agreement with the quality ranking established by the medical expert. The automatic segmentation method results in accurate segmentations with a mean root mean square error of 0.5 pixel and 1.8 pixels for the inner and outer borders of the arterial wall, respectively. This leads to accurate and unbiased estimates of the wall to lumen ratio.Conclusions\n\nOur algorithm can be applied as a reliable and useful computer-aided tool to process large time series databases in AOO, and can help experts in longitudinal monitoring applications.Translational relevance\n\nFor the first time, AOO image series can be processed with low supervision to accurately monitor morphometric changes in retinal vascularization.",
  "abstract_shown": true,
  "affiliations": [
    "Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.",
    "Télécom Paris, LTCI, Institut Polytechnique de Paris, Palaiseau, France.",
    "Isep, Institut Supérieur d'Electronique de Paris, Paris, France.",
    "Sorbonne Université, CNRS, LIP6, Paris, France.",
    "Clinical Investigation Center 1423, Quinze-Vingts Hospital, Sorbonne Université, INSERM, Paris, France.",
    "Referral Centre CERVCO at the University Hospital Lariboisière in APHP (University Paris Cité), France."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Alireza Vard"
    },
    {
      "affs": [
        2
      ],
      "name": "Abir Aissa"
    },
    {
      "affs": [
        2
      ],
      "name": "Florence Rossant"
    },
    {
      "affs": [
        3
      ],
      "name": "Isabelle Bloch"
    },
    {
      "affs": [
        4
      ],
      "name": "Daniela Castro-Farias"
    },
    {
      "affs": [
        5
      ],
      "name": "Hugues Chabriat"
    },
    {
      "affs": [
        4
      ],
      "name": "Michel Paques"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9jtchc8aej693.bib",
  "cited_by": 0,
  "doi": "10.1167/tvst.15.10.8",
  "fulltext_url": "https://europepmc.org/articles/PMC13657134",
  "id": "9jtchc8aej693",
  "issns": [
    "2164-2591"
  ],
  "landing_url": "https://europepmc.org/article/MED/42841580",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2741|Retinal Imaging and Analysis"
    ]
  ],
  "openalex": "W7220836893",
  "pdf_url": "https://europepmc.org/articles/PMC13657134?pdf=render",
  "pmcid": "PMC13657134",
  "pmid": "42841580",
  "published": "2026-10-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9jtchc8aej693.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:10Z",
      "native_id": "MED:42841580",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42841580"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Retinal Imaging and Analysis",
      "subfield": "imaging"
    }
  ],
  "title": "Time Series Segmentation in Adaptive Optics Ophthalmoscopy With Application to Flicker-Induced Vasodilation.",
  "title_text": "Time Series Segmentation in Adaptive Optics Ophthalmoscopy With Application to Flicker-Induced Vasodilation.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:10Z",
  "url": "https://research.draconitic.com/paper/9jtchc8aej693",
  "venue": "Translational vision science & technology",
  "versions": []
}