A Deep Learning-Based Method for Rapid 3D Whole-Heart Modeling in Congenital Heart Disease

The 3D modeling approach has the potential to enhance the precision of surgical planning and diagnosis for congenital heart disease. Future studies should explore larger datasets and training models for different types of congenital heart disease to validate the model's broad applicability.

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Publication Details

Journal
Cardiology
Published
2024-10-11
DOI
https://doi.org/10.1159/000541980
Citations
5
Primary Topic
Anatomy and Medical Technology
Type
article
Field-Weighted Citation Impact
0.92
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article

A Deep Learning-Based Method for Rapid 3D Whole-Heart Modeling in Congenital Heart Disease

Haiping Huang, Yisheng Wu
5 citations
Cardiology
Anatomy and Medical Technology
0.92
article

A Deep Learning-Based Method for Rapid 3D Whole-Heart Modeling in Congenital Heart Disease

Haiping Huang, Yisheng Wu
article en
5 citations

Abstract

The 3D modeling approach has the potential to enhance the precision of surgical planning and diagnosis for congenital heart disease. Future studies should explore larger datasets and training models for different types of congenital heart disease to validate the model's broad applicability.

CardiologyVol. 150(3)
Zhaoqing University (CN)
Good health and well-being
Openalex Percentile: Top 28%
Anatomy and Medical Technology
0.92
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A Deep Learning-Based Method for Rapid 3D Whole-Heart Modeling in Congenital Heart Disease — Haiping Huang, Yisheng Wu · Cardiology (2024) | TGRS Research Map | TGRS