ArticleData in brief2019
Retinal layer parcellation of optical coherence tomography images: Data resource for multiple sclerosis and healthy controls.
Article in Data in brief, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 82 citations in OpenAlex.
- A three-dimensional multi-modal foundation model for optical coherence tomography.Nature biomedical engineering · 2026Article
- Evaluation of classification performance for six types of fundus diseases in OCT images based on multi-source training strategy.Frontiers in medicine · 2026Article
- Ensemble learning-based method for multiple sclerosis screening from retinal OCT images.Medical & biological engineering & computing · 2025Article
- Analyzing Retinal Vessel Morphology in MS Using Interpretable AI on Deep Learning-Segmented IR-SLO Images.Bioengineering (Basel, Switzerland) · 2025Article
- OCT5k: A dataset of multi-disease and multi-graded annotations for retinal layers.Scientific data · 2025Article
- Boundary-Repairing Dual-Path Network for Retinal Layer Segmentation in OCT Image with Pigment Epithelial Detachment.Journal of imaging informatics in medicine · 2024Article
- Addressing fairness issues in deep learning-based medical image analysis: a systematic review.NPJ digital medicine · 2024Review
- HDB-Net: hierarchical dual-branch network for retinal layer segmentation in diseased OCT images.Biomedical optics express · 2024Article
- Exploring Publicly Accessible Optical Coherence Tomography Datasets: A Comprehensive Overview.Diagnostics (Basel, Switzerland) · 2024Review
- Hybrid deep learning and optimal graph search method for optical coherence tomography layer segmentation in diseases affecting the optic nerve.Biomedical optics express · 2024Article
- OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods.Scientific data · 2024Article
- Reproducibility evaluation of the effects of MRI defacing on brain segmentation.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Deep learning network with differentiable dynamic programming for retina OCT surface segmentation.Biomedical optics express · 2023Article
- Longitudinal deep network for consistent OCT layer segmentation.Biomedical optics express · 2023Article
- Exploiting multi-granularity visual features for retinal layer segmentation in human eyes.Frontiers in bioengineering and biotechnology · 2023Article
- Wavelet attention network for the segmentation of layer structures on OCT images.Biomedical optics express · 2022Article
- Intraretinal Layer Segmentation Using Cascaded Compressed U-Nets.Journal of imaging · 2022Article
- Recent Advanced Deep Learning Architectures for Retinal Fluid Segmentation on Optical Coherence Tomography Images.Sensors (Basel, Switzerland) · 2022Review
- Autoencoder based self-supervised test-time adaptation for medical image analysis.Medical image analysis · 2021Article
- Structured layer surface segmentation for retina OCT using fully convolutional regression networks.Medical image analysis · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
This paper presents optical coherence tomography (OCT) images of the human retina and manual delineations of eight retinal layers. The data includes 35 human retina scans acquired on a Spectralis OCT system (Heidelberg Engineering, Heidelberg, Germany), 14 of which are healthy controls (HC) and 21 have a diagnosis of multiple sclerosis (MS). The provided data includes manually delineation of eight retina layers, which were independently reviewed and edited. The data presented in this article was used to validate automatic segmentation algorithms (Lang et al., 2013).
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.