A novel hybrid layer-based encoder–decoder framework for 3D segmentation in congenital heart disease

The segmentation of cardiac anatomy represents a crucial stage in accurate diagnosis and subsequent treatment planning for patients with congenital heart disease (CHD). However, the current deep learning-based segmentation networks are ineffective when applied to 3D medical images of CHD because of...

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Bibliographic Details
Published in:	Scientific reports Vol. 15; no. 1; pp. 11891 - 10
Main Authors:	Zhu, Yaoxi, Li, Hongbo, Cao, Bingxin, Huang, Kun, Liu, Jinping
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 07.04.2025 Nature Publishing Group Nature Portfolio
Subjects:	3D CT image 639/705 692/308 692/4019 Algorithms Cardiac segmentation Cardiovascular disease Cardiovascular diseases Congenital diseases Congenital heart disease Coronary artery disease Deep Learning Heart - diagnostic imaging Heart Defects, Congenital - diagnostic imaging Heart diseases Humanities and Social Sciences Humans Hybrid architectures Image processing Image Processing, Computer-Assisted - methods Imaging, Three-Dimensional - methods multidisciplinary Science Science (multidisciplinary) Deep learning Hybrid architectures Congenital heart disease Cardiac segmentation 3D CT image
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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