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Columbia University’s Data Science Institute Presents:

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Wednesday, April 6 • 2:00pm - 4:30pm
Towards the Automatic Classification of Endomyocardial Tissues for Intracardiac OCT [P9]

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Aiming to establish the relationship between ultrastructure and endomyocardial tissue types, especially diseased tissue, we develop an automated algorithm to segment and classify tissue types from intracardiac OCT images. We segmented the OCT image volumes using a graph searching method. Features are extracted and compared in each segmented region. A probabilistic model of relevance vector machine is developed to classify multiple tissue types such as scar, fibrotic myocardium, normal myocardium, endocardium, and adipose tissue. The algorithm is validated from OCT images obtaining from human heart. The tissue types are classified with a good accuracy and are visualized in three dimensions.

Demo/Poster Presenter
avatar for Yu Gan

Yu Gan

PhD Candidate in Electrical Engineering, Columbia Engineering
Yu Gan is a Ph.D. candidate in the Department of Electrical Engineering at Columbia University. He is a research assistant in the Structure Function Imaging Laboratory under supervision of Dr. Christine Hendon. His research interest involves image processing. He is working towards development of a new  analysis tool for image of optical coherence tomography.

Wednesday April 6, 2016 2:00pm - 4:30pm
Roone Arledge Auditorium Lerner Hall, Columbia University 2920 Broadway, New York, NY 10040

Attendees (2)