Research on the influence of breast sound velocity inversion based on ultrasound computed tomography

With the passage of time, breast cancer has overtaken lung cancer to become the most prevalent malignant tumor worldwide, exhibiting both high incidence and mortality rates. If breast cancer is diagnosed at an early stage and treated promptly, the survival rate is over 90%. However, the current diagnostic methods for breast cancer are frequently associated with prolonged examination times, elevated costs, and diminished accuracy rates. In order to address these issues, this paper puts forward a breast sound speed inversion algorithm based on ultrasound computed tomography. The algorithm is based on the principles of medical CT scanning, utilizing inverse operations on signals acquired from multiple angles to reconstruct images of the sound speed distribution within the measured area, thus facilitating the efficient identification and localization of abnormalities within the breast tissue. The specific implementation comprises two stages. Initially, the K-Wave toolbox in MATLAB is employed for ultrasound wave simulation and breast tissue modelling. Subsequently, the SIRT reconstruction algorithm is applied to invert the sound speed images. The findings of the research indicate that the inversion effect is optimal when the number of iterations reaches 40. Furthermore, the study examines the impact of model grid size and transducer count on inversion results, revealing that a grid size of 200×200 and a transducer count of 100 achieve the best balance between computational complexity and inversion accuracy.