## 1 Introduction  
Breast cancer has become a common cancer that affects females worldwide, which is a significant public health issue, with incidence and mortality rates increasing rapidly since the 1980s [1]. The incidence and modality of breast cancer is 24.2% and 15%, respectively, according to the estimated age-standardized mortality rates (World) in 2018. Furthermore, breast cancer has been the top cancer among females in all ages [2]. However, breast cancer survival has improved since the mid-1970s. The decline in cancer mortality over the past two decades is primarily the result of advances in early detection and treatment, which is reflected in considerable decreases for the breast cancer [3]. Specifically, the death rate dropped 39% from 1989 to 2015 for female breast cancer. Therefore, to reduce the mortality and incidence rate, early screening for breast cancer is critical [4, 5]. Ultrasonography is an essential method for medical imaging. Compared with other imaging techniques, ultrasound is inexpensive, harmless, and enables easy real-time imaging for medical diagnosis [6]. Ultrasound computer tomography (USCT) is an emerging imaging method and a good prospect in the detection of breast cancer [7]. This approach has several advantages for breast cancer screening compared with classical ultrasonography [8]. Ultrasound tomography not only overcomes the reliance on the operator's experience but also has potential clinical benefits, such as comfort, safety, and 3D imaging [9]. The transducer is the key component of the USCT system. With the development of the micro-electro-mechanical system (MEMS), the piezoelectric micromachined ultrasonic transducer (PMUT) has become a potential alternative to classical piezoelectric transducers. The potential benefits of the PMUT are its miniaturized size, excellent consistency, and good performance [10]. Ultrasound produces multi-perspective images with high resolution, allowing the assessment of the morphology, orientation, internal structure, and margins of lesions in both dense glandular structures and predominantly fatty breast tissue [11]. The surrounding tissue, shape, size, number, stiffness, margin contour, and boundary of a lesion are significant factors to consider for its classification [12]. Generally, breast cancer tissue is harder than the adjacent normal breast tissue. This property serves as the basis for some examinations, such as elastography [13]. However, elastography images cannot distinguish between lesions and surrounding tissue when their elasticity properties are the same, and the quality of the elastography image is limited by the depth of a lesion [14]. In our previous work, a breast ultrasound imaging system with the cylindrical motion of the PMUT linear array was developed. Pulse-echo tomography was used to detect the size, location, and contour of a breast mass. Ultrasound energy decreases during the transmission of ultrasonic waves in the body [15], and the degree of ultrasound attenuation depends on the type of the tissue and ultrasound wave [16]. The attenuation coefficients vary among different tissues, and the attenuation is affected by the frequency. The higher the frequency, the greater the attenuation [17]. Ultrasound attenuation occurs during the forward propagation of the body and the return of sound waves. Therefore, the pulse-echo intensity of deep tissue is significantly lower than its initial intensity [18]. The breast is made up of breast glands and other soft tissues without bones, which would cause extensive attenuation and scatter the transmitted signal energy [19]. In order to accurately detect breast masses and obtain more detailed internal characteristic information, the time gain compensation (TGC) technique is frequently used to compensate for ultrasound attenuation [20]. The TGC technique is generally realized by using a hardware circuit, and it needs artificial adjustment of parameters and an operator's intervention [21].