Evidence map›Paper›PMID 35214261›Full record

ArticleSensors (Basel, Switzerland)2022

Denoising of Fluorescence Image on the Surface of Quantum Dot/Nanoporous Silicon Biosensors.

Yong Liu, Miao Sun, Zhenhong Jia, Jie Yang, Nikola K Kasabov

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yong LiuCollege of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.
Miao SunSchool of Physical Science and Technology, Xinjiang University, Urumqi 830046, China.
Zhenhong JiaCollege of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.
Jie YangInstitute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200400, China.
Nikola K KasabovSchool of Engineering, Computing and Mathematical Sciences, Auckland University of Technology, Auckland 1020, New Zealand.ORCID 0000-0003-4433-7521

Funding

National Key R&D Program of China 2019YFC1606100
6 · The paper itself

Abstract

In the process of biological detection of porous silicon photonic crystals based on quantum dots, the concentration of target organisms can be indirectly measured via the change in the gray value of the fluorescence emitted from the quantum dots in the porous silicon pores before and after the biological reaction on the surface of the device. However, due to the disordered nanostructures in porous silicon and the roughness of the surface, the fluorescence images on the surface contain noise. This paper analyzes the type of noise and its influence on the gray value of fluorescent images. The change in the gray value caused by noise greatly reduces the detection sensitivity. To reduce the influence of noise on the gray value of quantum dot fluorescence images, this paper proposes a denoising method based on gray compression and nonlocal anisotropic diffusion filtering. We used the proposed method to denoise the quantum dot fluorescence image after DNA hybridization in a Bragg structure porous silicon device. The experimental results show that the sensitivity of digital image detection improved significantly after denoising.

Indexed as

Biosensing TechniquesNanoporesQuantum DotsPorositySiliconSiliconbiosensorimage denoisingporous siliconquantum dots

Identifiers

PMID35214261
PMCPMC8962970

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.