Breast Ultrasound Image Enhancement Method Based on Combination of NSST and Improved Fuzzy
CHEN Yaling1, TONG Ying2, HE Ruiqing2, CAO Xuehong2
1. School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications,
Nanjing Jiangsu 210003, China; 2. School of Information and Communication Engineering, Nanjing Institute of Technology,
Nanjing Jiangsu 211167, China
Abstract：Objective To solve the problem that noise introduced in the acquisition and transmission of breast ultrasound images
may decrease the image quality and affect the early diagnosis of breast cancer, to propose a breast ultrasound image enhancement
method based on non-subsampled shearlet transform (NSST) and improved blur. Methods Firstly, the image contrast was
enhanced by improved fuzzy algorithm. Secondly, the image was decomposed into low-frequency and high-frequency parts by
inverse NSST transformation, the low-frequency part was linearly transformed to adjust the overall contrast of the image, and the
threshold model was used to remove the noise in the high frequency part. Finally, the processed high and low frequency parts were
inversely transformed by NSST to obtain an enhanced image. Using signal to noise ratio (SNR) and contrast to noise ratio (CNR) to
measure the denoising performance of the algorithm, structural similarity, feature similarity and information entropy to measure the
algorithm’s detail retention ability, average gradient to measure the algorithm’s contrast enhancement effect. Results By using the
method presented in this paper, the SNR of enhanced image was 2.108, the CNR was 0.903, the information entropy was 7.363, the
average gradient was 9.439, the structural similarity was 0.939, and the feature similarity was 0.972, all of which were significantly
higher than the adaptive selection of search region for NLM based image denoising, the enhancement algorithm based on NSST
and fuzzy contrast, and the NSST denoising algorithm based on bilateral filtering. Conclusion The image enhancement method can
effectively reduce noise and enhance image contrast under the condition of ensuring the image structure. The research results has
practical value.
陈雅玲1，童莹2，何睿清2，曹雪虹2. 基于NSST与改进模糊的乳腺超声
图像增强方法[J]. 中国医疗设备, 2023, 38(7): 28-33.
CHEN Yaling1, TONG Ying2, HE Ruiqing2, CAO Xuehong2. Breast Ultrasound Image Enhancement Method Based on Combination of NSST and Improved Fuzzy. China Medical Devices, 2023, 38(7): 28-33.
