AIMC Topic: Choroid

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iPSC-RPE patch restores photoreceptors and regenerates choriocapillaris in a pig retinal degeneration model.

JCI insight
Dry age-related macular degeneration (AMD) is a leading cause of untreatable vision loss. In advanced cases, retinal pigment epithelium (RPE) cell loss occurs alongside photoreceptor and choriocapillaris degeneration. We hypothesized that an RPE-patc...

Age and gender-related changes in choroidal thickness: Insights from deep learning analysis of swept-source OCT images.

Photodiagnosis and photodynamic therapy
BACKGROUND: The choroid is a vital vascular layer of the eye, essential for maintaining ocular health. Understanding its structural variations, particularly choroidal thickness (CT), is crucial for the early detection of diseases, such as age-related...

Assessment of choroidal vessels in healthy eyes using 3-dimensional vascular maps and a semi-automated deep learning approach.

Scientific reports
To assess the choroidal vessels in healthy eyes using a novel three-dimensional (3D) deep learning approach. In this cross-sectional retrospective study, swept-source OCT 6 × 6 mm scans on Plex Elite 9000 device were obtained. Automated segmentation ...

Applications of Artificial Intelligence in Choroid Visualization for Myopia: A Comprehensive Scoping Review.

Middle East African journal of ophthalmology
Numerous artificial intelligence (AI) models, including deep learning techniques, are being developed to segment choroids in optical coherence tomography (OCT) images. However, there is a need for consensus on which specific models to use, requiring ...

Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To describe choroidal thickness measurements using a sequential deep learning segmentation in adults who received childhood atropine treatment for myopia control.

Evaluation of choroid vascular layer thickness in wet age-related macular degeneration using artificial intelligence.

Photodiagnosis and photodynamic therapy
PURPOSE: To facilitate the assessment of choroid vascular layer thickness in patients with wet age-related macular degeneration (AMD) using artificial intelligence (AI).

Predicting central choroidal thickness from colour fundus photographs using deep learning.

PloS one
The estimation of central choroidal thickness from colour fundus images can improve disease detection. We developed a deep learning method to estimate central choroidal thickness from colour fundus images at a single institution, using independent da...

Distribution and determinants of choroidal vascularity index in healthy eyes from deep-learning choroidal analysis: a population-based SS-OCT study.

The British journal of ophthalmology
AIMS: To quantify the profiles of choroidal vascularity index (CVI) using fully artificial intelligence (AI)-based algorithm applied to swept-source optical coherence tomography (SS-OCT) images and evaluate the determinants of CVI in a population-bas...

Validation of reliability, repeatability and consistency of three-dimensional choroidal vascular index.

Scientific reports
This study aimed to investigate the reliability, repeatability and consistency of choroidal vascularity index (CVI) measurements provided by an artificial intelligence-based software in swept-source optical coherence tomography (SS-OCT) in normal sub...

Quantitative analysis of deep learning-based denoising model efficacy on optical coherence tomography images with different noise levels.

Photodiagnosis and photodynamic therapy
BACKGROUND: To quantitatively evaluate the effectiveness of the Noise2Noise (N2N) model, a deep learning (DL)-based noise reduction algorithm, on enhanced depth imaging-optical coherence tomography (EDI-OCT) images with different noise levels.