Automatic segmentation of coronary lumen and external elastic membrane in intravascular ultrasound images using 8-layer U-Net

Abstract Background Intravascular ultrasound (IVUS) is the golden standard in accessing the coronary lesions, stenosis, and atherosclerosis plaques. In this paper, a fully automatic approach by an 8-layer U-Net is developed to segment the coronary artery lumen and the area bounded by external elasti...

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Bibliographic Details
Main Authors: Liang Dong, Wenbing Jiang, Wei Lu, Jun Jiang, Ya Zhao, Xiangfen Song, Xiaochang Leng, Hang Zhao, Jian’an Wang, Changling Li, Jianping Xiang
Format: Article
Language:English
Published: BMC 2021-02-01
Series:BioMedical Engineering OnLine
Subjects:
Online Access:https://doi.org/10.1186/s12938-021-00852-0
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Summary:Abstract Background Intravascular ultrasound (IVUS) is the golden standard in accessing the coronary lesions, stenosis, and atherosclerosis plaques. In this paper, a fully automatic approach by an 8-layer U-Net is developed to segment the coronary artery lumen and the area bounded by external elastic membrane (EEM), i.e., cross-sectional area (EEM-CSA). The database comprises single-vendor and single-frequency IVUS data. Particularly, the proposed data augmentation of MeshGrid combined with flip and rotation operations is implemented, improving the model performance without pre- or post-processing of the raw IVUS images. Results The mean intersection of union (MIoU) of 0.937 and 0.804 for the lumen and EEM-CSA, respectively, were achieved, which exceeded the manual labeling accuracy of the clinician. Conclusion The accuracy shown by the proposed method is sufficient for subsequent reconstruction of 3D-IVUS images, which is essential for doctors’ diagnosis in the tissue characterization of coronary artery walls and plaque compositions, qualitatively and quantitatively.
ISSN:1475-925X