Left-Atrial Segmentation From 3-D Ultrasound Using B-Spline Explicit Active Surfaces With Scale Uncoupling

Area of Science:

• Cardiovascular Imaging
• Medical Image Analysis
• Biomedical Engineering

Background:

• Left atrial (LA) segmentation is crucial for assessing cardiac function, but 3-D ultrasound (US) segmentation remains challenging.
• Existing methods primarily focus on left ventricle (LV) segmentation, with limited attention to the LA.

Purpose of the Study:

• To extend the B-spline explicit active surfaces (BEAS) framework for robust semiautomatic LA segmentation in 3-D US.
• To improve shape adaptability for variable LA structures using B-splines with uncoupled scaling.

Main Methods:

• Developed a modified BEAS framework incorporating B-splines with uncoupled scaling for enhanced shape control.
• Applied the framework for semiautomatic segmentation of the LA endocardium in 20 3-D transthoracic echocardiographic datasets.
• Evaluated segmentation accuracy against manual delineations and derived morphological/functional parameters.

Main Results:

• The modified BEAS framework achieved accurate semiautomatic LA segmentation in 3-D transthoracic US.
• The method demonstrated reliable quantification of LA morphology and function.
• Independent control over smoothness and control points improved support for less regular LA shapes.

Conclusions:

• The enhanced BEAS framework offers a clinically viable tool for accurate LA segmentation and functional assessment using 3-D echocardiography.
• This advancement addresses a gap in 3-D US-based cardiac imaging, particularly for LA analysis.