## 3 Results and Discussion  
The mice skin containing the tumor region were imaged by the SAM system. The reference phase values were corrected and then compared with the H&E stained image, which is shown in Figure 6. The speed-of-sound properties were measured to distinguish between healthy regions and cancerous tissues. Figure 6 also depicts the microscopic image of H&E stained malignant melanoma and surrounding normal tissues, and their corresponding SAM images, mapped from speed-of-sound values, are displayed. Tissues with cell-rich structures such as follicles, malignant melanoma and epidermis demonstrated higher speed-of-sound values than cell-poor structures such as the hypodermis and dermis tissue. The average values of acoustic velocity from different regions are demonstrated in Table 1 and Figure S5. Similar results have been suggested by [PERSON] et al. [23], indicating that the melanoma cells demonstrate the lowest values of sound speed (1360 \(\pm\) 50 m/s). Figure 5: Phase analysis at the first vertical line and the first horizontal line: (**a**) Phase graphs of the first vertical line; (**b**) Phase graphs of the first horizontal line; (**c**) Speed-of-sound image; (**d**) Illustration of the sample setup with the first horizontal and the first vertical lines. In our imaging study depicted in Figure 6a, each skin tissue was distinguished from surrounding tissues by their different acoustic velocities. In Figure 6b, the areas of malignant melanoma were preferably stained with hematoxylin because of the downregulation of intercellular gap junctions between cancerous cells [24]. The speed-of-sound image in Figure 6a agrees with the microscopic H&E stained image in Figure 6b by exhibiting higher acoustic velocity values. The result in Figure 5c showed a poor correlation with H&E staining in Figure 6b in detecting the cancerous region. The speed of sound in Figure 5c differs from Figure 6a at the location where the reference phase from the plane function and the correction function are different. The magnitude of differences in speed-of-sound value could be explained by Equations 5 and 6. The higher the reference phase extracted from the plane function over the acquired value (in Figure 5a,b), the smaller the value of acoustic velocity in Figure 5c over Figure 6a, and vice versa. This indicates that the accuracy of reference phase extraction in such circumstances plays a crucial role in the result. As tissue characterization by SAM has been developed for a long time, the problems mentioned in the study (slope and fluctuation of the scanning lines) may be solved by hiding techniques or they have been worked around when facing the problems (by replacing a new motor). By taking the practical factors of slope and fluctuation into account, this study could be one step further to improve the accuracy of SAM. With our approach, the corrective function works in cases of the slope of the stage, with and without the fluctuation of the scanning lines. In this study, other noise sources, such as phase noise (called jitter caused by unideal oscillating clocks on the electrical devices) of the digitizer, and the inhomogeneous responses of the transducer, were considered as random noises. The noises could cause fluctuations in the phase of the measured signal. The fluctuations were reduced by averaging five times the sampling of each data point. Table S1 and Figure S6 show the differences of random noise at different frequencies and graphs of the values, respectively. The phase values sampled at frequencies 33 MHz and 88 MHz according to the boundary \begin{table}
\begin{tabular}{c c} \hline
**Tissue Skin Layer** & **Average Speed of Sound (m/s)** \\ \hline Epidermis (D) & 1704 \(\pm\) 43 \\ Hypodermis (C) & 1572 \(\pm\) 17 \\ Muscle (B) & 1727 \(\pm\) 58 \\ Dermis (A) & 1595 \(\pm\) 28 \\ Back skin layer follicle (E) & 1693 \(\pm\) 39 \\ Malignant melanoma (F) & 1719 \(\pm\) 36 \\ \hline \end{tabular}
\end{table} 
Table 1: Average speed of sound.