Lateral Resolution Improvement in Ultrasound Imaging System using Compressed Sensing: Initial Results

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Compressed Sensing (CS) reduces ultrasound data/acquisition time.
• Previous work introduced Gaussian-based undersampling for Conventional Focused Beamforming (CFB).
• No prior studies utilized CS to reduce active receive elements in CFB.

Purpose of the Study:

• Exploit Gaussian sampling CS for improved lateral resolution (LR) in ultrasound.
• Enhance LR without increasing system complexity or cost.
• Investigate waveatom as a sparsifying basis and analyze performance across different receive apertures.

Main Methods:

• Utilized Gaussian sampling based CS framework with waveatom sparsifying basis.
• Generated simulation data using Field II.
• Acquired experimental data from an in-vitro cyst phantom using a Verasonics V-64 ultrasound scanner.

Main Results:

• Achieved nearly twofold improvement in LR compared to CFB.
• Reported approximately 27% increase in contrast over CFB.
• Demonstrated effectiveness with receive apertures 3-4 times the active aperture size.

Conclusions:

• Proposed CS framework significantly improves ultrasound LR and contrast.
• Enhancements are achieved without increasing system complexity or cost.
• Findings support improved, affordable point-of-care ultrasound systems.