HYAMD High-Resolution Fundus Image Dataset for age related macular degeneration (AMD) Diagnosis

Fuente: arXiv
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Main Authors: Meisel, Meishar, Cohen, Benjamin A., Baskin, Meital, Tiosano, Beatrice, Behar, Joachim A., Berkowitz, Eran
Format: Preprint
Published: 2025
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author Meisel, Meishar
Cohen, Benjamin A.
Baskin, Meital
Tiosano, Beatrice
Behar, Joachim A.
Berkowitz, Eran
author_facet Meisel, Meishar
Cohen, Benjamin A.
Baskin, Meital
Tiosano, Beatrice
Behar, Joachim A.
Berkowitz, Eran
contents The Hillel Yaffe Age Related Macular Degeneration (HYAMD) dataset is a longitudinal collection of 1,560 Digital Fundus Images (DFIs) from 325 patients examined at the Hillel Yaffe Medical Center (Hadera, Israel) between 2021 and 2024. The dataset includes an AMD cohort of 147 patients (aged 54-94) with varying stages of AMD and a control group of 190 diabetic retinopathy (DR) patients (aged 24-92). AMD diagnoses were based on comprehensive clinical ophthalmic evaluations, supported by Optical Coherence Tomography (OCT) and OCT angiography. Non-AMD DFIs were sourced from DR patients without concurrent AMD, diagnosed using macular OCT, fluorescein angiography, and widefield imaging. HYAMD provides gold-standard annotations, ensuring AMD labels were assigned following a full clinical assessment. Images were captured with a DRI OCT Triton (Topcon) camera, offering a 45 deg field of view and 1960 x 1934 pixel resolution. To the best of our knowledge, HYAMD is the first open-access retinal dataset from an Israeli sample, designed to support AMD identification using machine learning models.
format Preprint
id arxiv_https___arxiv_org_abs_2505_04230
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle HYAMD High-Resolution Fundus Image Dataset for age related macular degeneration (AMD) Diagnosis
Meisel, Meishar
Cohen, Benjamin A.
Baskin, Meital
Tiosano, Beatrice
Behar, Joachim A.
Berkowitz, Eran
Image and Video Processing
Tissues and Organs
The Hillel Yaffe Age Related Macular Degeneration (HYAMD) dataset is a longitudinal collection of 1,560 Digital Fundus Images (DFIs) from 325 patients examined at the Hillel Yaffe Medical Center (Hadera, Israel) between 2021 and 2024. The dataset includes an AMD cohort of 147 patients (aged 54-94) with varying stages of AMD and a control group of 190 diabetic retinopathy (DR) patients (aged 24-92). AMD diagnoses were based on comprehensive clinical ophthalmic evaluations, supported by Optical Coherence Tomography (OCT) and OCT angiography. Non-AMD DFIs were sourced from DR patients without concurrent AMD, diagnosed using macular OCT, fluorescein angiography, and widefield imaging. HYAMD provides gold-standard annotations, ensuring AMD labels were assigned following a full clinical assessment. Images were captured with a DRI OCT Triton (Topcon) camera, offering a 45 deg field of view and 1960 x 1934 pixel resolution. To the best of our knowledge, HYAMD is the first open-access retinal dataset from an Israeli sample, designed to support AMD identification using machine learning models.
title HYAMD High-Resolution Fundus Image Dataset for age related macular degeneration (AMD) Diagnosis
topic Image and Video Processing
Tissues and Organs
url https://arxiv.org/abs/2505.04230