Related Experiment Video
Updated: Mar 18, 2026

Clinical Imaging of Microwave Mammography
Published on: November 14, 2025
Full Angle Spatial Compound of ARFI images for breast cancer detection
Nuria González-Salido1, Luis Medina1, Jorge Camacho1
1Department of Ultrasonic Sensors and Technology, ITEFI-CSIC, Madrid, Spain.
Abstract:
Automated ultrasound breast imaging would overcome most of the limitations that precludes conventional hand-held echography to be an effective screening method for breast cancer diagnosis. If a three dimensional (3D) ultrasound dataset is acquired without manual intervention of the technician, repeatability and patient follow-up could be improved. Furthermore, depending on the system configuration, resolution and contrast could be enhanced with regard to conventional echography, improving lesion detectability and evaluation. Having multiple modalities is another major advantage of these automated systems, currently under development by several research groups. Because of their circular structure, some of them include through-transmission measurements that allow constructing speed of sound and attenuation maps, which adds complementary information to the conventional reflectivity B-Mode image. This work addresses the implementation of the Acoustic Radiation Force Impulse (ARFI) imaging technique in a Full Angle Spatial Compound (FASC) automated breast imaging system. It is of particular interest because of the high specificity of ARFI for breast cancer diagnosis, by representing tissue elasticity differences rather than acoustic reflectivity. First, the image formation process is analyzed and a compounding strategy is proposed for ARFI-FASC. Then, experimental results with a prototype system and two gelatin phantoms are presented: Phantom A with a hard inclusion in a soft background, and phantom B with three soft inclusions in a hard background and with three steel needles. It is demonstrated that the full angle composition of ARFI images improves image quality, enhancing Contrast to Noise Ratio (CNR) from 4.9 to 20.6 and 3.6 to 13.5 in phantoms A and B respectively. Furthermore, this CNR increase improved detectability of small structures (needles) with regard to images obtained from a single location, in which image texture masked their presence.

