Diffusion enhancement model and its application in peak detection

被引:5
|
作者
Li, Jun [2 ]
Li, Yuanlu [1 ,2 ]
Zhao, Weijing [2 ]
Jiang, Min [2 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Nanjing 210044, Jiangsu, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Sch Automat, Nanjing 210044, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Smoothing; Nonlinear diffusion; Fractional diffusion; Diffusion enhancement; Peak detection; BASE-LINE CORRECTION; SIGNAL; DIFFERENTIATION; SPECTRUM; STRATEGY;
D O I
10.1016/j.chemolab.2019.04.012
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is a challenge for peak detection algorithms to detect some low-amplitude peaks and overlapped peaks contaminated by noise. Among of existing peak detection algorithms, the continuous wavelet transform (CWT)-based algorithm is the best. When the Mexican Hat wavelet is selected as the mother wavelet, the CWT of a signal is essentially equivalent to using the Gaussian function to smooth the 2nd derivative of the signal. Therefore, a natural idea is to combine the peak enhancement step and peak-preserving diffusion into peak detection process to improve the performance of peak detection. In the proposed algorithm, the Gaussian smoothing in the CWT-based algorithm is replaced with the peak-preserving diffusion filtering. As an assessment of the proposed algorithm, a simulated spectrum with low-amplitude peaks and overlapped peaks was generated and used to test the enhancement performance. Then 100 groups of simulated proteomics data sets in [1] were used to assess the proposed algorithm. In these data sets, the true peaks are known in each spectrum. Thus, the false discovery rate (FDR) is easy to find. Five typical peak detection programs were chosen to compare the proposed algorithm. The FDR and sensitivity is employed to compare the performance of these algorithms. Result shows that the proposed algorithm can improve the performance of peak detection.
引用
收藏
页码:130 / 137
页数:8
相关论文
共 50 条
  • [41] Flame feature model development and its application to flame detection
    Lu, Tai-Fang
    Peng, Chien-Yuan
    Horng, Wen-Bing
    Peng, Jian-Wen
    ICICIC 2006: FIRST INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING, INFORMATION AND CONTROL, VOL 1, PROCEEDINGS, 2006, : 158 - 161
  • [42] Bayesian model combination and its application to cervical cancer detection
    Martinez, Miriam
    Sucar, L. Enrique
    Acosta, H. Gabriel
    Cruz, Nicandro
    ADVANCES IN ARTIFICIAL INTELLIGENCE - IBERAMIA-SBIA 2006, PROCEEDINGS, 2006, 4140 : 622 - 631
  • [43] Improved Snake model and its application in image edge detection
    Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China
    Shu Ju Cai Ji Yu Chu Li, 2008, 2 (153-157):
  • [44] Research on a distributed detection system model and its application in engineering
    Xia Wenyue
    Yuan Haiwen
    PROCEEDINGS OF THE 2016 IEEE 11TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2016, : 774 - 778
  • [45] A Hybrid Model of RST and DST with Its Application in Intrusion Detection
    Ye Qing
    Wu Xiaoping
    Liu Yongqing
    Huang Gaofeng
    2010 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY AND SECURITY INFORMATICS (IITSI 2010), 2010, : 202 - 205
  • [46] Enhancement Factors in Ozone Absorption Based on the Surface Renewal Model and its Application
    程江
    杨卓如
    陈焕钦
    C.H.Kuo
    M.E.Zappi
    Chinese Journal of Chemical Engineering, 2000, (03) : 52 - 56
  • [47] Model Compression by Iterative Pruning with Knowledge Distillation and Its Application to Speech Enhancement
    Wei, Zeyuan
    Li, Hao
    Zhang, Xueliang
    INTERSPEECH 2022, 2022, : 941 - 945
  • [48] Enhancement factors in ozone absorption based on the surface renewal model and its application
    Cheng, J
    Yang, ZR
    Chen, HQ
    Kuo, CH
    Zappi, HE
    CHINESE JOURNAL OF CHEMICAL ENGINEERING, 2000, 8 (03) : 236 - 240
  • [49] APPLICATION OF THE EIKONIX DIFFUSION-MODEL TRANSFORMATION FOR ELECTRO-OPTICAL IMAGE-ENHANCEMENT
    RUDOMEN, B
    LIFF, H
    PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 1981, 271 : 2 - 13
  • [50] Feature Enhancement SSD Algorithm and Its Application in Remote Sensing Images Target Detection
    Shi Wen-xu
    Tan Dai-lun
    Bao Sheng-li
    ACTA PHOTONICA SINICA, 2020, 49 (01)