Meanwhile, it can avoid interferences such as sample color, sample roughness, and autofluorescence. However, when scanning with SECM, it is very difficult to locate the exact position of the area scanned on the sample. For instance, the cancerous sites detected in figure could not be directly linked with their optical microscopic pictures displayed in figure 3b. Moreover, the clarity of the SECM images was not as high as the optical microscopic pictures. Therefore, developing a methodology of integrating both SECM images and optical images could improve the resolution and quality of the images. The quality and resolution of the electrochemical imaging rely on many factors, including the tip's size, the reactivity of the target molecules, the convention when collecting the signals, the vibration interference, and the experience of the experiment operator. If we could fuse the SECM image with an optical microscopic image, the resolution and the tissue boundary might be much clearer, so that the distribution of biomarkers could be investigated more thoroughly. We used a built-in function in Matlab software for wavelet processing to process image fusion. This ready-made function, 'wfusimg', is widely used for merging two images, detect edges or noise elimination. The details of wfsimg are explained in SI-5. Although it is a built-in function, there are a lot of parameters that should be adjusted in the fusion process, including 1) wavelets for processing image fusion; 2) wavelet processing decomposition level;