Automatic Spot Identification Method for High Throughput Surface Plasmon Resonance Imaging Analysis

• Published in: Biosensors (Basel) Vol. 8; no. 3; p. 85
• Main Authors: Wang, Zhiyou, Huang, Xiaoqing, Cheng, Zhiqiang
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 13.09.2018; MDPI
• Subjects: Accuracy; adaptive threshold binarization; Algorithms; Biosensing Techniques - methods; Data analysis; Defects; High-Throughput Screening Assays - methods; Identification; Image enhancement; Image processing; Image Processing, Computer-Assisted - methods; Limit of Detection; Methods; Nonuniformity; Parallel processing; Protein Array Analysis - methods; Protein arrays; protein microarray; Proteins; Resonance; Software; Surface plasmon resonance; Surface Plasmon Resonance - methods; surface plasmon resonance imaging; Video data; Video Recording - methods; Beijing China; China; adaptive threshold binarization; image enhancement; surface plasmon resonance imaging; protein microarray
• ISSN: 2079-6374; 2079-6374
• DOI: 10.3390/bios8030085

An automatic spot identification method is developed for high throughput surface plasmon resonance imaging (SPRi) analysis. As a combination of video accessing, image enhancement, image processing and parallel processing techniques, the method can identify the spots in SPRi images of the microarray from SPRi video data. In demonstrations of the method, SPRi video data of different protein microarrays were processed by the method. Results show that our method can locate spots in the microarray accurately regardless of the microarray pattern, spot-background contrast, light nonuniformity and spotting defects, but also can provide address information of the spots.