B-Mode Ultrasound Imaging System Using Raspberry Pi

Abstract

The B-mode ultrasound imaging represents one of the main imaging methods in medical diagnosis. To improve the quality of generated images, new approaches and techniques for digital signal processing based on hardware and software platforms are being introduced nowadays. This article shows the implementation and evaluation of digital signal processing algorithms on the Raspberry Pi using Python programming language for B-mode image reconstruction. The proposed steps include digital filtering, focusing delay, coherent summation, demodulation with envelope detection, and logarithmic compression. To validate the implemented algorithm, 12-bit sampled data with a frequency of 40 MHz were used. Qualitative and quantitative analyses using the Normalized Root Mean Squared Error (NRMSE) and the Normalized Residual Sum of Squares (NRSS) cost functions show results compatible with the reference model in Matlab and validated in previous studies. All NRMSE results were less than 10% and NRSS results were close to zero, indicating excellent agreement with the reference Matlab model.