Tissue Elasticity Estimation from Ultrasonic Waveform Using Fuzzy Inference
Tadashi Kimura, Kouki Nagamune, Syoji Kobashi, Katsuya Kondo, Yutaka Hata, and Kazuhiko Taniguchi*
*KINDEN Co., Ltd.
Proc. of 1st Int. Conf. on Soft Computing and Intelligent Systems,
CD-ROM, (2002)
This paper proposes a fuzzy rule-based approach
to tissue elasticity estimation from ultrasonic waveform. The
purpose of this paper is to estimate automatically small
difference of tissue elasticity whose information is useful for
diagnosing a human body. This estimation method consists of
three steps. The first step extracts characteristic values from
known data of elasticity. In the second step, characteristic
values construct fuzzy membership functions. By doing a fuzzy
inference on these membership functions, the final step can
provide information of elasticity of unknown data. We applied
this method into nine phantoms that have different tissue
elasticity. As a result, the correlation coefficient was 0.779.
The accuracy of this method was higher than the statistical
method.