.png){kind=icon}
.png){kind=icon}
Return
An automatic multi-thread image segmentation embedded system for surface plasmon resonance sensor
.png){kind=icon}
PRE
AI
DOI：10.1016/j.sna.2018.12.007.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In order to reduce the uncertainties associated with manual selection of regions of interest (ROIs) commonly used in Surface Plasmon Resonance (SPR) imaging system, we proposed and implemented an automatic image segmentation method in an embedded system to facilitate the potential real-time applications. Intuitive marker-controlled watershed algorithm is developed to segment ROIs (reaction, blank, and background regions) from images acquired from an experimental image SPR system. The marker assignment algorithms and pre-processing algorithms are executed in parallel by multi-threading programming on the multi-core embedded system to both real-time and good quality of segmentation. This method exhibited a good robustness in a series of ROIs segmentation test. Furthermore, the intensity response from triplicate detection of glucose standard solutions indicated a good reproducibility of data. The linear range was from 2.5 mg/mL to 20.4 mg/mL, with a correlation coefficient (R-2) of 0.999 and sensitivity of 2.69 a.u./mg/mL. In conclusion, the proposed automatic image segmentation method effectively makes the measurement more precise and simplified. (C) 2018 Elsevier B.V. All rights reserved.
Keywords:
Surface plasmon resonance (SPR)
Optical sensor
Biosensor
Image segmentation
Watershed algorithm
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.9
Papers:
1.5W
Citations:
3.3W