Calcification Contrast Enhanced Ultrasound Imaging Technique

• Main Authors: Lin, Yu-Ju, 林玉茹
• Other Authors: Li, Meng-Lin
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/26629874967596752120

碩士 === 國立清華大學 === 電機工程學系 === 102 === Calcifications are important indicators of breast cancer. Since there is speckle noise in ultrasound images, it is difficult to detect calcifications from breast gland and fat. In this study, we propose three calcification contrast enhanced ultrasound imaging techniques to improve the contrast of calcifications to other tissues in ultrasound images. From signal view, we utilized the signal characteristics of calcifications in frequency domain, since there is more enormous variation of back scattering magnitude of calcifications than that of other tissues in breast in signal spectrum. We used band pass filter (BPF, method 1) and short-time Fouier transform (STFT, method 2) to enhance contrast of calcifications. From image view, we used speckle factor (SF) imaging to enhance the calcification contrast (method 3). Simulations were performed to verify our idea. We used the Faran model to predict the complex amplitude of echoes from calcifications. We compare amplitudes of calcifications and other tissues between different center frequencies, which represents the contrast. Several frequency are chosen then to enhance the contrast of calcifications to other tissues. The selected frequency sets are employed to design band pass filter and apply short-time Fourier transform for contrast enhanced imaging. In addition, different bandwidth, sliding window size and the size of calcifications are simulated to optimize the contrast. Furthermore, calcifications manifest as isolated strong scatterers in the scattering volume, so the variance become large when we calculate the variance of intensity in a small window. Speckle factor which is defined as the standard deviation divided by the mean of each window is used to form images where the contrast of calcifications is enhanced. The calcifications can be identified via the binary images obtained from the speckle factor images. The best results of the three methods are obtained by speckle factor images. Since the binary images are derived from the speckle factor, the background is clear and the image contrast is the best and all the calcifications of different sizes could be detected precisely. There are more problems to solve in the other two methods. If we modify the signal mapping when using band pass filter and try to enhance the contrast in the method using short-time Fourier transform, the image quality and contrast of calcifications would be improved.