An improved peak detection algorithm in mass spectra combining wavelet transform and image segmentation

Deng, Fulong; Li, Hong; Wang, Ruxin; Yue, Hanlu; Zhao, Zhongjun; Duan, Yixiang

doi:10.1016/j.ijms.2021.116601

Cited by 19 publications

(16 citation statements)

References 22 publications

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“…There are many types of peak detection methods, such as the direct peak location, Fourier transform, cumulative sum derivative, curve fitting, devolution, and wavelet transform (CWT) methods ( Deng et al, 2021 ). The direct peak location according to the properties of peak and continuous wavelet transform are two classical methods in traditional methods.…”

Section: Resultsmentioning

confidence: 99%

Deep learning on lateral flow immunoassay for the analysis of detection data

Liu

Du²,

Lin

et al. 2023

Front. Comput. Neurosci.

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Lateral flow immunoassay (LFIA) is an important detection method in vitro diagnosis, which has been widely used in medical industry. It is difficult to analyze all peak shapes through classical methods due to the complexity of LFIA. Classical methods are generally some peak-finding methods, which cannot distinguish the difference between normal peak and interference or noise peak, and it is also difficult for them to find the weak peak. Here, a novel method based on deep learning was proposed, which can effectively solve these problems. The method had two steps. The first was to classify the data by a classification model and screen out double-peaks data, and second was to realize segmentation of the integral regions through an improved U-Net segmentation model. After training, the accuracy of the classification model for validation set was 99.59%, and using combined loss function (WBCE + DSC), intersection over union (IoU) value of segmentation model for validation set was 0.9680. This method was used in a hand-held fluorescence immunochromatography analyzer designed independently by our team. A Ferritin standard curve was created, and the T/C value correlated well with standard concentrations in the range of 0–500 ng/ml (R2 = 0.9986). The coefficients of variation (CVs) were ≤ 1.37%. The recovery rate ranged from 96.37 to 105.07%. Interference or noise peaks are the biggest obstacle in the use of hand-held instruments, and often lead to peak-finding errors. Due to the changeable and flexible use environment of hand-held devices, it is not convenient to provide any technical support. This method greatly reduced the failure rate of peak finding, which can reduce the customer’s need for instrument technical support. This study provided a new direction for the data-processing of point-of-care testing (POCT) instruments based on LFIA.

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Section: Resultsmentioning

confidence: 99%

Deep learning on lateral flow immunoassay for the analysis of detection data

Liu

Du²,

Lin

et al. 2023

Front. Comput. Neurosci.

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“…The Mexican hat wavelet basis function has advantageous properties of simple and rapid calculation. It also has the advantage of baseline deduction in the ridge spectral peak recognition as the second derivative of the Gaussian density function. , The Mexican hat wavelet basis function was therefore used for CWT of the T 2 distribution in this paper, which can be written as The diagram of the Mexican hat wavelet basis function is shown in Figure . It is symmetrical and can effectively avoid phase distortion in the process of CWT.…”

Section: Theory and Methodsmentioning

confidence: 99%

“…It also has the advantage of baseline deduction in the ridge spectral peak recognition as the second derivative of the Gaussian density function. 27,28 The Mexican hat wavelet basis function was therefore used for CWT of the T 2 distribution in this paper, which can be written as…”

Section: Continuous Wavelet Transform Of the T 2 Distributionmentioning

confidence: 99%

Novel Method for Determining Irreducible Water Saturation in a Tight Sandstone Reservoir Based on the Nuclear Magnetic Resonance T₂ Distribution

et al. 2022

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Irreducible water saturation, affecting the productivity of a reservoir, is one of the key parameters for a tight sandstone reservoir. Nuclear magnetic resonance (NMR) logging, detecting the relaxation information on pore fluid with hydrogen nuclei in formation, can be used to distinguish irreducible and movable fluids as a result of their different relaxation information. The irreducible water saturation can be determined by the T 2 cutoff method in the conventional reservoir. However, a tight sandstone reservoir possesses a complex pore structure, and relaxation signals of different pore fluids may overlap in the T 2 distribution. The T 2 cutoff method to determine irreducible water saturation may be a challenge in tight sandstone reservoirs. In this study, a novel T 2-distribution-based method, with the film model assumption, was proposed to determine the irreducible water saturation in tight sandstone reservoirs. The T 2 distribution was transformed by a continuous wavelet transform to obtain the two-dimensional matrix of wavelet coefficients, and the position and shape parameters of the spectral peak at different scales in wavelet space were determined. These parameters were used to construct the Gaussian distribution functions (GDFs) at different scales. The T 2 distribution was decomposed on the basis of the constructed GDFs, and then the optimal decomposition was selected. The irreducible water saturation is determined by the optimal T 2 distribution decomposed. The effectiveness and practicability of the proposed method were validated by numerical simulation, core experimental, and NMR logging data processing.

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“…Wavelet transform [24] A local domain transforms in the air and frequency domains, thus effectively extracting information from a signal and performing multiscale analysis of a function or signal through operational functions such as scaling and translation, solving many problems that cannot be solved by the Fourier transform.…”

Section: Tendingmentioning

confidence: 99%

Adaptive analysis of rapid prediction of coal quality information based on image analysis

Liu

Zhang

2023

International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022)

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Machine vision technology has shown great potential for development and application in the coal heat utilization and coal chemical production process It is important to carry out image analysis-based stability adaptation analysis of coal heat utilization and coal chemical equipment. To further expand its application, this work reviewed the characteristics of different vision sensor systems and image processing algorithms in the process of image acquisition and processing, conducted applicability analysis for rapid prediction of coal quality, presented the current problems and future development trends of image analysis technology in the coal heat utilization and coal chemical production process. It provided theoretical guidance and reference for promoting automation, intelligence, and mechanization in the coal industry.

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An improved peak detection algorithm in mass spectra combining wavelet transform and image segmentation

Cited by 19 publications

References 22 publications

Deep learning on lateral flow immunoassay for the analysis of detection data

Deep learning on lateral flow immunoassay for the analysis of detection data

Novel Method for Determining Irreducible Water Saturation in a Tight Sandstone Reservoir Based on the Nuclear Magnetic Resonance T₂ Distribution

Adaptive analysis of rapid prediction of coal quality information based on image analysis

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An improved peak detection algorithm in mass spectra combining wavelet transform and image segmentation

Cited by 19 publications

References 22 publications

Deep learning on lateral flow immunoassay for the analysis of detection data

Deep learning on lateral flow immunoassay for the analysis of detection data

Novel Method for Determining Irreducible Water Saturation in a Tight Sandstone Reservoir Based on the Nuclear Magnetic Resonance T2 Distribution

Adaptive analysis of rapid prediction of coal quality information based on image analysis

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Product

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Novel Method for Determining Irreducible Water Saturation in a Tight Sandstone Reservoir Based on the Nuclear Magnetic Resonance T₂ Distribution