Expert-level Automated Biomarker Identification in Optical Coherence Tomography Scans.
Sci Rep
; 9(1): 13605, 2019 09 19.
Article
em En
| MEDLINE
| ID: mdl-31537854
ABSTRACT
In ophthalmology, retinal biological markers, or biomarkers, play a critical role in the management of chronic eye conditions and in the development of new therapeutics. While many imaging technologies used today can visualize these, Optical Coherence Tomography (OCT) is often the tool of choice due to its ability to image retinal structures in three dimensions at micrometer resolution. But with widespread use in clinical routine, and growing prevalence in chronic retinal conditions, the quantity of scans acquired worldwide is surpassing the capacity of retinal specialists to inspect these in meaningful ways. Instead, automated analysis of scans using machine learning algorithms provide a cost effective and reliable alternative to assist ophthalmologists in clinical routine and research. We present a machine learning method capable of consistently identifying a wide range of common retinal biomarkers from OCT scans. Our approach avoids the need for costly segmentation annotations and allows scans to be characterized by biomarker distributions. These can then be used to classify scans based on their underlying pathology in a device-independent way.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Doenças Retinianas
/
Interpretação de Imagem Radiográfica Assistida por Computador
Tipo de estudo:
Diagnostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article