Role of ARFI elastography for the diagnosis of breast tumour

Acoustic Radiation Force Impulse (ARFI) imaging is a type of ultrasound elastography used in medicine, particularly for the monitoring and diagnosis of cancers. Medical professionals observe the tissue elasticity of the ARFI equipment for the diagnosis of the cancer. This paper investigates the role of image processing on the ARFI image for the diagnosis of breast tumour. Initially, in the pre-processing stage, Non local means filter is applied to the ARFI image to remove speckle noise and enhance the PSNR value. The Spatial Fuzzy Clustering method and the Level Set Segmentation method had been applied to the filtered ARFI image to extract the features like mean, standard deviation, entropy. It is observed that the deviation of entropy, standard deviation and mean feature values between ARFI and ultrasound images for the benign cases are ± 1.41, ± 11.285 and ± 19.21 and for malignant case it is ± 0.14, ± 6.77 and ± 5.73. The deviation between benign and malignant ARFI images for the entropy, standard deviation and mean are ± 1.35, ± 11.975 and ± 20.69. Hence with the observed deviation in the feature values, it is inferred that the features obtained from the processed image can serve as a best marker for the diagnosis of breast tumour.