Automated comprehensive evaluation of coronary artery plaque in IVOCT using deep learning

Automated comprehensive evaluation of coronary artery plaque in IVOCT using deep learning

Summary: The process of manually characterizing and quantifying coronary artery plaque tissue in intravascular optical coherence tomography (IVOCT) images is both time-consuming and subjective. We have developed a deep learning-based semantic segmentation model (EDA-UNet) designed specifically for c...

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Bibliographic Details
Main Authors: Pengfei Liu, Zang Lu, Wenqing Hou, Kaisaierjiang Kadier, Chunying Cui, Zhengyang Mu, Aikeliyaer Ainiwaer, Xinliang Peng, Gulinuer Wufu, Yitong Ma, Jianguo Dai, Xiang Ma
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:iScience
Subjects:
Artificial intelligence
Cardiovascular medicine
Online Access:http://www.sciencedirect.com/science/article/pii/S2589004225004304
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http://www.sciencedirect.com/science/article/pii/S2589004225004304

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