Hardware and Software Contributions for Optimized Detection of Fluorescent Labeled Cytokines

被引：0
|
作者：
Topor, A. [1 ]
Ravariu, C. [1 ]
Babarada, F. [1 ]
Malin, S. [1 ]
Salageanu, A. [2 ]
Caras, I. [2 ]
Manuc, D. [3 ]
Patrichi, B. [3 ]
机构：
[1] ETTI UPB, Bucharest, Romania
[2] Cantacuzino Natl Inst Res & Dev Microbiol & Immun, Splaiul Independentei 103, Bucharest 050096, Romania
[3] Carol Davila Univ Med & Pharm, 37 Dionisie Lupu, Bucharest 020022, Romania
来源：
2017 INTERNATIONAL SEMICONDUCTOR CONFERENCE (CAS), 40TH EDITION | 2017年
关键词：
hardware solution; fluorescence detection; optical transducers; error minimization algorithms; MULTIPLE OBJECT TRACKING; BIODEVICE; OXIDE;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Paper presents hardware improvements, step by step, besides to software refinements for the fluorescent labelled cytokines detection, associated to bacterial meningitis diagnosis. The hardware optimization firstly concerns the implementation of a versatile hardware device with the possibility to obtain the finally best solution. The software refinement includes Monte Carlo combined with denoising algorithms. The logistic curve extracted from fluorescent labelled cytokine images, reduces the error vector from 629 to 2.4, offering the best set of parameters.
引用
收藏
页码：267 / 270
页数：4
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