Aboofazeli Mohammad, Abolmaesumi Purang, Fichtinger Gabor, Mousavi Parvin
Queen's University, Kingston, ON K7L 3N6, Canada. mohammad@ cs.queensu.ca
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:479-82. doi: 10.1109/IEMBS.2009.5335160.
This paper presents a novel method for tissue characterization using wavelet transform of ultrasound radio frequency (RF) echo signals. We propose the use of multiscale products of wavelet transform sequences of RF echoes to estimate the scatterer distribution in the tissue. The proposed method is based on the fact that when emitted ultrasound beams interact with scatterers in the tissue, backscattered beams contain singularities corresponding to the location of the scatterers. The singularities will exist in multiple scales of wavelet sequences of the echo signals. Therefore, peaks of wavelet transform multiscale products correspond to the location of scatterers. Estimation of scatterer spacing can be used for tissue characterization. The efficacy of the proposed method was validated in RF echo signals of in-vitro human prostate to characterize normal and cancerous tissue. The results confirm that wavelet transform multiscale products of RF echo signals contain tissue typing information that can be used as an effective tool to differentiate normal and cancerous prostate tissue.
本文提出了一种利用超声射频(RF)回波信号的小波变换进行组织特征描述的新方法。我们建议使用RF回波的小波变换序列的多尺度乘积来估计组织中的散射体分布。所提出的方法基于这样一个事实,即当发射的超声束与组织中的散射体相互作用时,反向散射束包含与散射体位置相对应的奇异点。这些奇异点将存在于回波信号小波序列的多个尺度中。因此,小波变换多尺度乘积的峰值对应于散射体的位置。散射体间距的估计可用于组织特征描述。该方法的有效性在体外人前列腺的RF回波信号中得到验证,以表征正常组织和癌组织。结果证实,RF回波信号的小波变换多尺度乘积包含组织分型信息,可作为区分正常和癌性前列腺组织的有效工具。