Volumetric quantification of choroid and Haller's sublayer using OCT scans: An accurate and unified approach based on stratified smoothing

Ibrahim, Mohammed Nasar; Bashar, Sarforaz Bin; Rasheed, Mohammed Abdul; Selvam, Amrish; Sant, Vrinda; Sahel, José‐Alain; Chhablani, Jay; Vupparaboina, Kiran Kumar; Jana, Soumya

doi:10.1016/j.compmedimag.2022.102086

Cited by 5 publications

(2 citation statements)

References 58 publications

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“…To facilitate the training of GAN models for various tasks involving OCT images, we utilized our previously trained residual encoder-decoder (ResUNet) model to generate choroid masks [29]. Only scans with accurate choroid segmentation, as assessed by an expert grader, were included in the analysis.…”

Section: B Data Preparationmentioning

confidence: 99%

Protecting Privacy While Improving Choroid Layer Segmentation in OCT Images: A GAN-Based Image Synthesis Approach

Vupparaboina,

Bollepalli,

Ibrahim

et al. 2024

Preprint

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Section: B Data Preparationmentioning

confidence: 99%

Protecting Privacy While Improving Choroid Layer Segmentation in OCT Images: A GAN-Based Image Synthesis Approach

Vupparaboina,

Bollepalli,

Ibrahim

et al. 2024

Preprint

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“…Their approach involved a Deeplabv3 variant of ResNet for segmentation, followed by traditional machine learning algorithms for prediction. While the applications of choroidal layer segmentation in research and clinical practice are not yet fully explored, future endeavors may encompass cross-modal registration, volumetric analysis, and real-time evaluation of choroidal boundary characteristics [136], [137]. These avenues promise to advance diagnostics and refine treatment strategies in ophthalmology.…”

Section: ) Segmentation Of Choroid Layermentioning

confidence: 99%

Artificial Intelligence in Choroid Through Optical Coherence Tomography: A Comprehensive Review

Selvam,

Driban,

Ong

et al. 2023

Preprint

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<p>Vision-threatening conditions, such as age-related macular degeneration (AMD) and central serous chorioretinopathy (CSCR), arise from dysfunctions in the highly vascular choroid layer in the eye’s posterior segment. Optical coherence tomography (OCT) images play a crucial role in diagnosing choroidal structural changes in clinical practice. This review emphasizes the significant efforts in developing precise detection, quantification, and automated disease classification of choroidal biomarkers. The rapid progress of artificial intelligence (AI) has triggered transformative breakthroughs across sectors including medical image analysis. Recently, the integration of AI within the diagnosis and treatment of choroidal diseases has captured significant attention. Multiple studies highlight AI’s potential to enhance diagnostic precision and optimize clinical outcomes in this context. The review provides an extensive overview of AI’s current applications in choroidal analysis using OCT imaging. It encompasses a diverse array of algorithms and techniques employed for biomarker detection, such as thickness and vascularity index, and for identifying diseases like AMD and CSCR. The overarching goal of this review is to provide an updated and comprehensive exploration of AI’s impact on the choroid, highlighting its potential, challenges, and role in driving innovation in the field.</p>

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Choroidal biomarkers in age-related macular degeneration

Sadeghi,

Valsecchi,

Rahmanipour

et al. 2024

Survey of Ophthalmology

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Volumetric quantification of choroid and Haller's sublayer using OCT scans: An accurate and unified approach based on stratified smoothing

Cited by 5 publications

References 58 publications

Protecting Privacy While Improving Choroid Layer Segmentation in OCT Images: A GAN-Based Image Synthesis Approach

Protecting Privacy While Improving Choroid Layer Segmentation in OCT Images: A GAN-Based Image Synthesis Approach

Artificial Intelligence in Choroid Through Optical Coherence Tomography: A Comprehensive Review

Choroidal biomarkers in age-related macular degeneration

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