Moreover, we proposed a new AI-assisted methodology for processing SECM images by taking advantage of Matlab software, merging the optical images and electrochemical images obtained from SECM. Images fused with different parameters were fed into our AI model to select the best images with the highest resolution, obvious cancer boundary, and clear biomarker distribution among thousands of combinations, and the accuracy was 97%.