Automated Region of Interest Selection Improves Deep Learning-Based Segmentation of Hyper-Reflective Foci in Optical Coherence Tomography Images

Automated Region of Interest Selection Improves Deep Learning-Based Segmentation of Hyper-Reflective Foci in Optical Coherence Tomography Images

Hyperreflective foci (HRF) have been associated with retinal disease progression and demonstrated as a negative prognostic biomarker for visual function. Automated segmentation of HRF in retinal optical coherence tomography (OCT) scans can be beneficial to identify the formation and movement of the...

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Bibliographic Details
Main Authors: Sarang Goel, Abhishek Sethi, Maximilian Pfau, Monique Munro, Robison Vernon Paul Chan, Jennifer I. Lim, Joelle Hallak, Minhaj Alam
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Journal of Clinical Medicine
Subjects:
hyperreflective foci
deep learning
segmentation
ophthalmic AI
diabetic retinopathy
age-related macular degeneration
Online Access:https://www.mdpi.com/2077-0383/11/24/7404

Internet

https://www.mdpi.com/2077-0383/11/24/7404

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