# Existing and Emerging Breast Cancer Detection Technologies and Its Challenges: A Review
## 2 Existing Breast Cancer Detection Techniques & Technologies
### Microwave Imaging-Based Technology  
Alternative technology has focused on breast cancer detection research involving Microwave Imaging (MI) in the recent decade to overcome the inconvenience, accessibility, high risk, and cost associated with X-rays and MRI [56; 57; 58; 59]. MI is a nonionizing electromagnetic signals imaging technology that uses frequencies ranging from 300 MHz to 30 GHz [60]. MI provides higher and stronger contrast between healthy tissue and tumors, contributing to tumor identification without the risk of ionization effects (safe medical screening tool) [61; 62]. As illustrated in Figure 8, a MI architecture consists of two main components: (i) hardware (antenna) for transmitting and collecting microwave signals that reflect from the breast phantom using Vector Network Analyzer (VNA) or any proper electromagnetic transceiver; (ii) software to rebuild the signals received and stored in a computational tool that contains detection algorithm [63]. The latter uses the power distribution of scattered waves to distinguish between healthy and tumor-containing tissues. MI is a cost-effective procedure since the equipment is often a fraction of the cost of equipment for other diagnostic approaches [64]. The most significant problem is that microwave imaging produces an image with limited spatial resolution [65; 66; 67]. Microwave tomography and radar-based imaging are the two main types of microwave imaging [68; 69]. The tissue-dependent dielectric contrast to reconstruct signals and pictures using tomographic or radar-based imaging techniques is the physical foundation of medical microwave imaging. Relative permittivity and conductivity are used to describe the dielectric characteristics of various tissues [70]. Furthermore, if tumorous, tissue of the same kind will have differing dielectric characteristics. Because of this variation, the interaction of EM signals in various tissues will be different [71]. Varied reconstruction techniques may use this to create an image, in 2D or 3D, that displays additional tissue dielectric characteristics or a tumor's location within the body [72]. For creating the dielectric characteristics of the breast, the tomography method is frequently conducted iteratively and may be represented as a nonlinear inverse problem \begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Modality** & **Sensitivity** & **Specificity** & **Accuracy** & **Advantage** & **Limitations** \\ \hline \multirow{3}{*}{Mammogram} & 67.8\% & 75\% & 70.2\% & Low cost & False positive and negative \\  & (120/177) & (61/81) & (181/258) & Low cost & Lower \\  & & (137/177) & (58/81) & (195/258) & Low cost & Lower \\ \hline \multirow{3}{*}{\begin{tabular}{l} Clinical \\ examination \\ \end{tabular} } & 50.3\% & 92\% & 63.6\% & Easy & A small tumor cant \\  & (89/177) & (75/81) & (164/258) & process & detect \\ \hline \multirow{3}{*}{Ultrasound} & 83\% & 34\% & 67.8\% & Better & Difficult to detect solid \\  & (147/177) & (28/81) & (175/258) & than X-ray & tumor \\ \hline \multirow{3}{*}{\
\begin{tabular}{l} Mammogram \\ and \\ ultrasound, \\ and clinical \\ \end{tabular} } & 91.5\% & 23\% & 70.2\% & Cost & Unwanted compression \\  & (162/177) & (19/81) & (181/258) & effective & compression \\ \cline{1-1}  & 93.2\% & 22\% & 70.9\% & Good & Complex signal \\  & (165/177) & (18/81) & (183/258) & detection & processing \\ \hline \multirow{3}{*}{MRI} & 94.4\% & 26\% & 72.9\% & Provide & Higher cost \\  & (167/177) & (21/81) & (188/258) & high resolution & time \\ \hline \multirow{3}{*}{
\begin{tabular}{l} Mammogram, \\ clinical exam, \\ and MRI \\ \end{tabular} } & 99.4\% & 7\% & 70.5\% & Best & Complex, solution & expensive, \\  & (176/177) & (6/81) & (182/258) & ever found & and time \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of diagnostic performance of different breast tumor detection techniques [46; 54; 55]. that demands enormous processing resources.