Histopathology-Based Deep-Learning Predicts Atherosclerotic Lesions in Intravascular Imaging

Histopathology-Based Deep-Learning Predicts Atherosclerotic Lesions in Intravascular Imaging

Background: Optical coherence tomography is a powerful modality to assess atherosclerotic lesions, but detecting lesions in high-resolution OCT is challenging and requires expert knowledge. Deep-learning algorithms can be used to automatically identify atherosclerotic lesions, facilitating identific...

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Bibliographic Details
Main Authors: Olle Holmberg, Tobias Lenz, Valentin Koch, Aseel Alyagoob, Léa Utsch, Andreas Rank, Emina Sabic, Masaru Seguchi, Erion Xhepa, Sebastian Kufner, Salvatore Cassese, Adnan Kastrati, Carsten Marr, Michael Joner, Philipp Nicol
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-12-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
deep learning
artificial intelligence
intravascular imaging
atherosclerosis
histopathology
optical coherence tomography
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2021.779807/full

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https://www.frontiersin.org/articles/10.3389/fcvm.2021.779807/full

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