A motion estimation refinement framework for real-time tissue axial strain estimation with freehand ultrasound

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Signal Processing

Background:

• Ultrasound elastography is crucial for diagnosing tissue abnormalities.
• It relies on estimating tissue displacement and strain from RF echo signals.
• Existing methods may have limitations in accuracy and real-time application.

Purpose of the Study:

• To develop and validate a novel motion estimation framework for ultrasound elastography.
• To improve the accuracy and robustness of axial tissue displacement and strain computation.
• To enable real-time elastography on ultrasound machines lacking this functionality.

Main Methods:

• A hybrid approach combining Block Matching Algorithm (BMA) for coarse estimation and Lucas-Kanade optical flow for fine-tuning.
• RF echo signals treated as image intensity with RF samples as pixels.
• A warp-and-refine procedure to iteratively enhance motion estimates with sub-pixel precision.

Main Results:

• The proposed method demonstrated robustness to large motions in simulated data.
• Accurate motion estimation with sub-sample spatial resolution was achieved.
• Successful real-time elastography display and freehand scanning were accomplished on a commercial ultrasound machine.

Conclusions:

• The developed framework offers a high-performance alternative for ultrasound elastography motion estimation.
• It enhances diagnostic capabilities by providing accurate displacement and strain data.
• Potential for further improvement exists through hardware integration of BMA.