Ultrasound (US) imaging proved to be less harmful than the traditional mammography is used for diagnosing breast cancer and this has helped reduce the number of unnecessary biopsies.The most important feature of malignant breast lesion is its infiltrative nature in US images.This infiltrative nature having composed of the frequency components that are adjacent to the lower frequency band contains the local variances that are characterized by Variational Mode Decomposition (VMD).On comparison with the existing decomposition models such as Empirical Mode Decomposition (EMD) and Wavelet Transform (WT) which are known for their limitations like sensitivity to noise and sampling which could only partially be addressed by more mathematical attempts to this decomposition problem, like synchrosqueezing, empirical wavelets or recursive variational decomposition.To overcome these limitations, a non-recursive VMD was selected.In this paper, we have presented an algorithmbased on VMD and a suitable architectureto obtain the infiltrative nature of the malignant breast lesion from the US image.
G. Menon, Dr. Palanisamy T., and Dr. Lavanya R., “Hardware Architecture for Variational Mode Decomposition for Breast Cancer Feature Extraction on Ultrasound Images”, International Journal of Applied Engineering Research, vol. 10, no. 7, pp. 16343-16354, 2015.