AI-Assisted Fusion of Scanning Electrochemical Microscopy Images Using Novel Soft Probe
Journal
ACS Measurement Science Au
Journal Volume
2
Journal Issue
6
Start Page
576
End Page
583
ISSN
2694250X
Date Issued
2022
Author(s)
Lin, Yi-Hong
Tsai, Chih-Ning
Chen, Po-Feng
Lin, Yen-Tzu
Darvishi, Sorour
Girault, Hubert H.
Lin, Tung-Yi
Liao, Mei-Yi
Abstract
Scanning electrochemical microscopy (SECM) is one of the scanning probe techniques that has attracted considerable attention because of its ability to interrogate surface morphology or electrochemical reactivity. However, the quality of SECM images generally depends on the sizes of the electrodes and many uncontrollable factors. Furthermore, manipulating fragile glass ultramicroelectrodes and blurred images sometimes frustrate researchers. To overcome the challenges of modern SECM, we developed novel soft gold probes and then established the AI-assisted methodology for image fusion. A novel gold microelectrode probe with high softness was developed to scan fragile samples. The distribution of EGFR (protein biomarker) in oral cancer was investigated. Then, we fused the optical microscopic and SECM images to enhance the image quality using Matlab software. However, thousands of fused images were generated by changing the parameters for image fusion, which is annoying for researchers. Thus, a deep learning model was built to select the best-fused images according to the contrast and clarity of the fused images. Therefore, the quality of the SECM images was improved using a novel soft probe and combining the image fusion technique. In the future, a new scanning probe with AI-assisted fused SECM image processing may be interpreted more preciously and contribute to the early detection of cancers. © 2022 American Chemical Society.
Subjects
artificial intelligence
EGFR
gold soft ultramicroelectrode
image fusion
oral cancer
scanning electrochemical microscopy
SECM
Publisher
American Chemical Society
Type
journal article