METHODS AND SYSTEMS FOR BIOMARKER PREDICTION USING OPTICAL COHERENCE TOMOGRAPHY

Deep learning methods and systems for detecting biomarkers within optical coherence tomography volumes using such deep learning methods and systems are provided. Embodiments predict the presence or absence of clinically useful biomarkers in OCT images using deep neural networks. L'invention con...

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Bibliographic Details
Main Authors DURMUS, Berkin, CHIANG, Jeffrey, HALPERIN, Eran, AVRAM, Oren, SADDA, SriniVas
Format Patent
LanguageEnglish
French
Published 11.05.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DIAGNOSIS
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
MEDICAL OR VETERINARY SCIENCE
PHYSICS
SURGERY
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Summary:Deep learning methods and systems for detecting biomarkers within optical coherence tomography volumes using such deep learning methods and systems are provided. Embodiments predict the presence or absence of clinically useful biomarkers in OCT images using deep neural networks. L'invention concerne des procédés et des systèmes d'apprentissage profond pour détecter des biomarqueurs à l'intérieur de volumes de tomographie par cohérence optique (OCT) faisant appel à de tels procédés et systèmes d'apprentissage profond. Des modes de réalisation prédisent la présence ou l'absence de biomarqueurs cliniquement utiles dans des images d'OCT à l'aide de réseaux neuronaux profonds.
Bibliography:Application Number: WO2022US79182