Hexagonal adaptive filtering on compound ultrasound images

Area of Science:

• Medical Imaging
• Image Processing
• Ultrasound Technology

Background:

• Ultrasound imaging is crucial for medical diagnostics.
• Enhancing contrast and signal-to-noise ratio (SNR) in ultrasound images remains a challenge.
• Sub-pixel displacements can degrade image quality.

Purpose of the Study:

• To develop and evaluate a novel method for improving ultrasound image quality.
• To increase the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of ultrasound images.
• To address limitations caused by sub-pixel lateral displacements.

Main Methods:

• Images with sub-pixel lateral displacements were re-sampled using a hexagonal grid.
• Image registration and compounding were performed.
• The compounded images were filtered using a hexagonal adaptive masking filter.
• The method was validated using simulated and breast phantom ultrasound images.

Main Results:

• Significant improvements in signal-to-noise ratio (SNR) were observed: up to 313% in simulated images and 182% in phantom images.
• Contrast-to-noise ratio (CNR) improvements reached 286% in simulated images and 56% in phantom images.
• The hexagonal adaptive masking filter effectively enhanced image quality.

Conclusions:

• The proposed hexagonal resampling, registration, compounding, and filtering approach effectively improves ultrasound image quality.
• This method offers substantial gains in SNR and CNR, crucial for enhanced diagnostic accuracy.
• The technique shows promise for various ultrasound applications, particularly in breast imaging.