scholarly journals Image Processing of Porous Silicon Microarray in Refractive Index Change Detection

Sensors ◽  
2017 ◽  
Vol 17 (6) ◽  
pp. 1335 ◽  
Author(s):  
Zhiqing Guo ◽  
Zhenhong Jia ◽  
Jie Yang ◽  
Nikola Kasabov ◽  
Chuanxi Li
2016 ◽  
Vol 122 (5) ◽  
Author(s):  
Weirong Chen ◽  
Zhenhong Jia ◽  
Peng Li ◽  
Guodong Lv ◽  
Xiaoyi Lv

2000 ◽  
Vol 76 (15) ◽  
pp. 1990-1992 ◽  
Author(s):  
Morio Takahashi ◽  
Yuichi Toriumi ◽  
Takahiro Matsumoto ◽  
Yasuaki Masumoto ◽  
Nobuyoshi Koshida

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2975
Author(s):  
Ruyong Ren ◽  
Zhenhong Jia ◽  
Jie Yang ◽  
Nikola Kasabov

The gray value method can be used to detect gray value changes of each unit almost parallel to the surface image of PSi (porous silicon) microarrays and indirectly measure the refractive index changes of each unit. However, the speckles of different noise intensities produced by lasers on a porous silicon surface have different effects on the gray value of the measured image. This results in inaccurate results of refractive index changes obtained from the change in gray value. Therefore, it is very important to reduce the influence of speckle noise on measurement results. In this paper, a new algorithm based on the concepts of probability-based nonlocal-means filtering (PNLM), gradient operator, and median filtering is proposed for gray value restoration of porous silicon microarray images. A good linear relationship between gray value change and refractive index change is obtained, which can reduce the influence of speckle noise on the gray value of the PSi microarray image, improving detection accuracy. This means the method based on gray value change detection can be applied to the biological detection of PSi microarray arrays.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Guangzhong Ma ◽  
Runli Liang ◽  
Zijian Wan ◽  
Shaopeng Wang

AbstractQuantification of molecular interactions on a surface is typically achieved via label-free techniques such as surface plasmon resonance (SPR). The sensitivity of SPR originates from the characteristic that the SPR angle is sensitive to the surface refractive index change. Analogously, in another interfacial optical phenomenon, total internal reflection, the critical angle is also refractive index dependent. Therefore, surface refractive index change can also be quantified by measuring the reflectivity near the critical angle. Based on this concept, we develop a method called critical angle reflection (CAR) imaging to quantify molecular interactions on glass surface. CAR imaging can be performed on SPR imaging setups. Through a side-by-side comparison, we show that CAR is capable of most molecular interaction measurements that SPR performs, including proteins, nucleic acids and cell-based detections. In addition, we show that CAR can detect small molecule bindings and intracellular signals beyond SPR sensing range. CAR exhibits several distinct characteristics, including tunable sensitivity and dynamic range, deeper vertical sensing range, fluorescence compatibility, broader wavelength and polarization of light selection, and glass surface chemistry. We anticipate CAR can expand SPR′s capability in small molecule detection, whole cell-based detection, simultaneous fluorescence imaging, and broader conjugation chemistry.


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