Detection of the whole myocardium in 2D-echocardiography for multiple orientations using a geometrically constrained...

Area of Science:

• Medical imaging
• Cardiology
• Image analysis

Background:

• Accurate segmentation of the myocardium in echocardiographic images is crucial for diagnosing heart disease.
• Echocardiographic images present significant challenges, including low contrast, speckle noise, signal dropout, and shadows, complicating accurate segmentation.
• Existing methods struggle to reliably segment the entire myocardium, encompassing both endocardial and epicardial contours.

Purpose of the Study:

• To propose a novel method for segmenting the whole myocardium, including both endocardial and epicardial contours, in 2D echocardiographic images.
• To develop a framework capable of segmenting the myocardium across the four main echocardiographic views used in clinical practice.
• To address the inherent difficulties in echocardiographic image segmentation through an advanced level-set model.

Main Methods:

• A level-set model is employed for image segmentation.
• A new shape formulation is introduced to constrain the level-set model, enabling the simultaneous modeling of both endocardial and epicardial contours.
• The proposed method is designed to be applicable to the four primary echocardiographic views utilized in routine clinical settings.

Main Results:

• The developed method successfully segments the entire myocardium, capturing both endocardial and epicardial borders.
• Validation on a dataset of clinical echocardiographic images demonstrates the method's efficacy.
• Performance comparison with expert segmentations indicates a high degree of accuracy and reliability.

Conclusions:

• The proposed level-set model with a novel shape constraint offers an effective solution for segmenting the whole myocardium in challenging 2D echocardiographic images.
• This method demonstrates robustness across the four main clinical views, offering potential for improved diagnostic capabilities in cardiology.
• The validated results suggest that this approach can reliably assist clinicians in the diagnosis and assessment of heart disease through enhanced echocardiographic image analysis.