1
|
Ahn SS, Ta K, Thorn S, Langdon J, Sinusas AJ, Duncan JS. Multi-frame Attention Network for Left Ventricle Segmentation in 3D Echocardiography. Med Image Comput Comput Assist Interv 2021; 12901:348-357. [PMID: 34729554 PMCID: PMC8560213 DOI: 10.1007/978-3-030-87193-2_33] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Echocardiography is one of the main imaging modalities used to assess the cardiovascular health of patients. Among the many analyses performed on echocardiography, segmentation of left ventricle is crucial to quantify the clinical measurements like ejection fraction. However, segmentation of left ventricle in 3D echocardiography remains a challenging and tedious task. In this paper, we propose a multi-frame attention network to improve the performance of segmentation of left ventricle in 3D echocardiography. The multi-frame attention mechanism allows highly correlated spatiotemporal features in a sequence of images that come after a target image to be used to augment the performance of segmentation. Experimental results shown on 51 in vivo porcine 3D+time echocardiography images show that utilizing correlated spatiotemporal features significantly improves the performance of left ventricle segmentation when compared to other standard deep learning-based medical image segmentation models.
Collapse
Affiliation(s)
- Shawn S. Ahn
- Department of Biomedical Engineering, Yale University, New
Haven, CT, USA
| | - Kevinminh Ta
- Department of Biomedical Engineering, Yale University, New
Haven, CT, USA
| | - Stephanie Thorn
- Section of Cardiovascular Medicine, Department of Internal
Medicine, Yale University, New Haven, CT, USA
| | - Jonathan Langdon
- Department of Radiology and Biomedical Imaging, Yale
University, New Haven, CT, USA
| | - Albert J. Sinusas
- Section of Cardiovascular Medicine, Department of Internal
Medicine, Yale University, New Haven, CT, USA,Department of Electrical Engineering, Yale University, New
Haven, CT, USA,Department of Radiology and Biomedical Imaging, Yale
University, New Haven, CT, USA
| | - James S. Duncan
- Department of Biomedical Engineering, Yale University, New
Haven, CT, USA,Department of Electrical Engineering, Yale University, New
Haven, CT, USA,Department of Radiology and Biomedical Imaging, Yale
University, New Haven, CT, USA
| |
Collapse
|