About this Research Topic
Advanced ocular imaging has become an essential part of clinical vision care. During the last two decades, imaging tools have dramatically expanded from classic instruments such as slit-lamp photography, fundus photography, and sonography to advanced devices such as scanning laser ophthalmology, optical coherence tomography (OCT), OCT-angiography, and more. Recently, artificial intelligence (AI) has emerged and revolutionized the field of image post-processing and interpretation. More recent ocular imaging technologies, including robotic auto-align eye scanners and interpretable diagnostic AI systems, are under development. Furthermore, using novel techniques to address unmet clinical needs underlines joint efforts and multidisciplinary collaboration among scientists, engineers, and clinicians.
Still, early diagnosis and timely interventions of eye diseases require further development of ocular imaging devices featuring cellular and sub-cellular resolutions, ultra-high speeds, ultra-wide field-of-view, molecular and functional contrasts, and imaging in multimodalities. AI-based image processing methods have demonstrated promising results, yet the possibilities to use AI to process ophthalmic images to aid diagnosis are still under-explored. Moreover, translational studies led by joint efforts between engineers and clinicians need to be further encouraged and enhanced to demonstrate the clinical impact of novel imaging technologies.
This Research Topic will include articles about proof-of-concept ocular imaging technologies and modalities, AI-based imaging processing tools in ophthalmology, and pre-clinical and clinical translation of ocular imaging devices. This Research Topic aims to explore new technologies in the context of eye disease diagnosis and monitoring and to stimulate thinking and debate on an effective clinical translation of new ocular imaging techniques. We welcome the submission of Reviews, Mini-Reviews, Perspectives, and Original Research.
Topics of interest include, but are not limited to, the following fields:
- Artificial Intelligence in ophthalmology
- Advanced ocular imaging methods and devices
- Clinical translation of ocular imaging techniques
Still, early diagnosis and timely interventions of eye diseases require further development of ocular imaging devices featuring cellular and sub-cellular resolutions, ultra-high speeds, ultra-wide field-of-view, molecular and functional contrasts, and imaging in multimodalities. AI-based image processing methods have demonstrated promising results, yet the possibilities to use AI to process ophthalmic images to aid diagnosis are still under-explored. Moreover, translational studies led by joint efforts between engineers and clinicians need to be further encouraged and enhanced to demonstrate the clinical impact of novel imaging technologies.
This Research Topic will include articles about proof-of-concept ocular imaging technologies and modalities, AI-based imaging processing tools in ophthalmology, and pre-clinical and clinical translation of ocular imaging devices. This Research Topic aims to explore new technologies in the context of eye disease diagnosis and monitoring and to stimulate thinking and debate on an effective clinical translation of new ocular imaging techniques. We welcome the submission of Reviews, Mini-Reviews, Perspectives, and Original Research.
Topics of interest include, but are not limited to, the following fields:
- Artificial Intelligence in ophthalmology
- Advanced ocular imaging methods and devices
- Clinical translation of ocular imaging techniques
Keywords: Optical coherence tomography, Retinal imaging, OCT-angiography, Artificial intelligence, Fundus photography, Ophthalmic Imaging Device
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
