# Classifying Breast Density from Mammogram with Pretrained CNNs and Weighted Average Ensembles
## 1 Introduction  
Artificial intelligence (AI) algorithms have improved and affected every aspect of modern life. In the last two decades, machine learning techniques and computer power have experienced momentous development, leading to an enormous increase in digital data in different fields. These advances have enabled researchers to solve real-world problems in many areas, including the medical image analysis field. Medical imaging was first used in 1895 [1]. Since that time, the devices and quality of medical imaging have continued to evolve. Today, medical imaging is an essential tool for diagnosing and detecting diseases such as cancer [2]. Cancer is a significant public health concern that affects people around the world, and it is the second leading cause of death in the US [3]. Breast cancer is one of the most prevalent cancers that affect women [4], but it can also arise in men [5]. In Saudi Arabia, in 2018, breast cancer was the most common type of cancer, with an incidence rate of 14.8% and a mortality rate of 8.5% [6]. In 2020, breast cancer remained the most common type of cancer in Saudi Arabia. Breast cancer is a disease caused by the abnormal growth of breast cells. Usually, somatic cells divide to produce new cells in an orderly manner. When the cells of a specific part of the body grow and divide out of control, a mass of tissue called a tumor is created. A tumor that consistsof normal cells is benign. When the cells are abnormal and exhibit irregular behavior, it is a malignant or cancerous tumor [7]. Three distinct types of medical imaging are used to diagnose breast cancer. These are mammograms, ultrasound,and magnetic resonance imaging (MRI) [8]. Among the breast imaging techniques, the mammogram is considered the gold standard for detecting and diagnosis [9; 10]. A mammogram is a type of medical imaging that uses a low-dose x-ray system to see inside the tissues of the breast [11]. There are two mammogram imaging modalities: digital and screen-film mammography. Screen-film mammography (SFM) consists of conventional analog mammographic films. SFM often contains various background objects, such as labels and markers, that need to be removed. Digital mammograms are also referred to as FFDM images; FFDM stands for full-field digital mammography. FFDM is the approved version in hospitals today [11]. Moreover, mammogram images can be found in several formats, including LJPG, DICOM, PGM, and TIFF. In the standard view for each breast, two X-ray images must be taken on both sides. Therefore, four images of both breasts must be examined. These four images are called: LEFT_CC, LEFT_MLO, RIGHT_CC, RIGHT_MLO [12; 13]. The craniocaudal (CC) view is taken from above a horizontally compressed breast (head-to-foot picture). The CC view captures the medial portion and as much of the breast's outer lateral region as possible. MedioLateralOblique (MLO) view captures the entire breast and often includes the lymph nodes and the pectoral muscle. Figure 1a,b show examples of the CC and MLO views, and Figure 2 illustrates the angle of each view [14]. Among the breast imaging techniques, the mammogram is considered the gold standard [9; 10].