AI-Assisted Fusion of Scanning Electrochemical Microscopy Images Using Novel Soft Probe

Yi Hong Lin, Chih Ning Tsai, Po Feng Chen, Yen Tzu Lin, Sorour Darvishi, Hubert H. Girault, Tung Yi Lin, Mei Yi Liao, Tzu En Lin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


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.

Original languageEnglish
Pages (from-to)576-583
Number of pages8
JournalACS Measurement Science Au
Issue number6
StatePublished - 21 Dec 2022


  • artificial intelligence
  • EGFR
  • gold soft ultramicroelectrode
  • image fusion
  • oral cancer
  • scanning electrochemical microscopy
  • SECM


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