Classification of Benign and Malignant Breast Tumors Using H-Scan Ultrasound Imaging

Shuicai Wu,Yali Ouyang,Weiwei Wu,Po-Hsiang Tsui,Zhuhuang Zhou

doi:10.3390/diagnostics9040182

Abstract

Breast cancer is one of the most common cancers among women worldwide. Ultrasound imaging has been widely used in the detection and diagnosis of breast tumors. However, due to factors such as limited spatial resolution and speckle noise, classification of benign and malignant breast tumors using conventional B-mode ultrasound still remains a challenging task. H-scan is a new ultrasound technique that images the relative size of acoustic scatterers. However, the feasibility of H-scan ultrasound imaging in the classification of benign and malignant breast tumors has not been investigated. In this paper, we proposed a new method based on H-scan ultrasound imaging to classify benign and malignant breast tumors. Backscattered ultrasound radiofrequency signals of 100 breast tumors were used (48 benign and 52 malignant cases). H-scan ultrasound images were constructed with the radiofrequency signals by matched filtering using Gaussian-weighted Hermite polynomials. Experimental results showed that benign breast tumors had more red components, while malignant breast tumors had more blue components in H-scan ultrasound images. There were significant differences between the RGB channels of H-scan ultrasound images of benign and malignant breast tumors. We conclude H-scan ultrasound imaging can be used as a new method for classifying benign and malignant breast tumors.

Highlights

Breast cancer is one of the most common malignant tumors in the world and the leading cause of death among women [1,2]
3, and those of malignant and H-scan images of benign breast tumors are shown in Figure 3, and those of malignantbreast breast tumors are shown inin
Compared with conventional B-mode ultrasound, H-scan imaging can show the relative size and spatial distribution of different scatterers and more abundant information of breast lesions can be obtained by processing the RF signals and estimating the scatterers in the region ofby interest (ROI)

Summary

Introduction

Breast cancer is one of the most common malignant tumors in the world and the leading cause of death among women [1,2]. Detection and diagnosis of breast cancer is of critical importance. Biopsy serves as the gold standard for diagnosing breast tumors [3]. Biopsy is an invasive histological examination method with poor repeatability, and has the risk of infection and bruising [4]. Less than 30% of the breast tumors are malignant after surgical biopsy [5]. Breast biopsy is usually performed after getting suspicious results from imaging examination. The primary imaging modalities for detecting breast cancer are mammography and ultrasonography [6]. Mammography is usually not suitable in 20–50% of patients with dense breasts [7].

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Discussion

Conclusion