Feature-adaptive motion tracking of ultrasound image sequences using a deformable mesh

Area of Science:

• Medical imaging
• Biomedical engineering
• Ultrasound technology

Background:

• Ultrasound speckle pattern correlation theoretically enables 2D tissue motion recovery.
• Speckle tracking is challenging due to temporal decorrelation and low signal-to-noise ratio in ultrasound images.

Purpose of the Study:

• To investigate an adaptive deformable mesh for nonrigid tissue motion recovery from ultrasound images.
• To address the ill-posed nature of speckle tracking in ultrasound-based motion analysis.

Main Methods:

• Adaptive allocation of mesh nodes to stable speckle patterns resistant to decorrelation.
• Finite element analysis for manipulating irregular mesh elements.
• A novel deformable block matching algorithm with Lagrange elements for motion vector estimation.
• Regularization of nodal displacements by minimizing mesh strain energy for physically plausible solutions.

Main Results:

• Successful tracking of nonrigid displacement fields demonstrated.
• Algorithm validated using ultrasound images of a tissue phantom and contracting muscle.
• Computer simulations confirmed the algorithm's efficacy.

Conclusions:

• The proposed adaptive deformable mesh effectively recovers nonrigid tissue motion from ultrasound data.
• This method enhances the reliability of ultrasound-based motion tracking by mitigating speckle decorrelation issues.
• The approach offers a robust solution for analyzing tissue dynamics in medical ultrasound applications.