Systems and Methods for Automated Image Classification and Segmentation

Optical coherence tomography (OCT) may be used to acquire cross-sectional or volumetric images of any specimen, including biological specimens such as the retina. Additional processing of the OCT data may be performed to generate images of features of interest. In some embodiments, these features ma...

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Bibliographic Details
Main Authors Lee Sieun, Merkur Andrew Brian, Sarunic Marinko Venci, Beg Mirza Faisal, Mammo Zaid, Heisler Morgan Lindsay, Loncaric Sven, Prentasic Pavle, Navajas Eduardo
Format Patent
LanguageEnglish
Published 11.01.2018
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DIAGNOSIS
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
MEDICAL OR VETERINARY SCIENCE
PHYSICS
SURGERY
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Summary:Optical coherence tomography (OCT) may be used to acquire cross-sectional or volumetric images of any specimen, including biological specimens such as the retina. Additional processing of the OCT data may be performed to generate images of features of interest. In some embodiments, these features may be in motion relative to their surroundings, e.g., blood in the retinal vasculature. The proposed invention describes a combination of images acquired by OCT, manual segmentations of these images by experts, and an artificial neural network for the automated segmentation and classification of features in the OCT images. As a specific example, the performance of the systems and methods described herein are presented for the automatic segmentation of blood vessels in images acquired with OCT angiography.
Bibliography:Application Number: US201715642290