Diagnosis of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning

Article Ophthalmology

Automated diagnoses of age-related macular degeneration and polypoidal choroidal vasculopathy using bi-modal deep convolutional neural networks

Zhiyan Xu et al.

Summary: The study aimed to investigate the efficacy of a bi-modality deep convolutional neural network (DCNN) framework for categorising age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) from colour fundus images and optical coherence tomography (OCT) images. The results showed that the bi-modal DCNN demonstrated high accuracy, sensitivity, and specificity in classifying AMD and PCV, outperforming human experts and showing promising prospects in the field of public health.

BRITISH JOURNAL OF OPHTHALMOLOGY (2021)

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Article Ophthalmology

Classification of pachychoroid disease on ultrawide-field indocyanine green angiography using auto-machine learning platform

In Ki Kim et al.

Summary: This study investigated the feasibility of classifying pachychoroid disease on ultra-widefield indocyanine green angiography (UWF ICGA) images using an automated machine-learning platform. The results showed that the performance of the models was comparable to that of retinal specialists and superior to ophthalmic residents.

BRITISH JOURNAL OF OPHTHALMOLOGY (2021)

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Article Ophthalmology

Polypoidal Choroidal Vasculopathy Consensus Nomenclature and Non-Indocyanine Green Angiograph Diagnostic Criteria from the Asia-Pacific Ocular Imaging Society PCV Workgroup

Chui M. Cheung et al.

Summary: A panel of retina specialists developed updated terminology and diagnostic criteria for distinguishing PCV from nAMD based on OCT and color fundus photography findings, achieving high accuracy without the need for ICGA.

OPHTHALMOLOGY (2021)

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Article Multidisciplinary Sciences

Deep learning and ensemble stacking technique for differentiating polypoidal choroidal vasculopathy from neovascular age-related macular degeneration

Yu-Bai Chou et al.

Summary: This study introduces a new artificial intelligence model for differentiating between polypoidal choroidal vasculopathy (PCV) and neovascular age-related macular degeneration (nAMD) by combining different technologies to achieve high accuracy.

SCIENTIFIC REPORTS (2021)

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Article Multidisciplinary Sciences

Distinguishing retinal angiomatous proliferation from polypoidal choroidal vasculopathy with a deep neural network based on optical coherence tomography

Daniel Duck-Jin Hwang et al.

Summary: This study successfully distinguished between RAP and PCV cases in neovascular age-related macular degeneration using a deep learning model, showing high accuracy, sensitivity, and specificity. The novel model performed well in distinguishing between PCV and RAP, demonstrating better diagnostic performance than other models and comparable performance with ophthalmologists.

SCIENTIFIC REPORTS (2021)

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Article Ophthalmology