메뉴 건너뛰기




Volumn 24, Issue 4, 1996, Pages 330-339

Automated particle classification based on digital acquisition and analysis of flow cytometric pulse waveforms

Author keywords

Analog to digital conversion; Classification; Fourier transform; Neural networks; Pulse shape analysis

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; FOURIER TRANSFORMATION; PARTICLE SIZE; PRIORITY JOURNAL;

EID: 0029795593     PISSN: 01964763     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1097-0320(19960801)24:4<330::AID-CYTO4>3.0.CO;2-J     Document Type: Article
Times cited : (23)

References (15)
  • 2
    • 9444250164 scopus 로고
    • An investigation into the feasibility of using neural networks to describe a simple wood decay data set
    • Boddy LW, Morris CW: An investigation into the feasibility of using neural networks to describe a simple wood decay data set. Binary 5:61-64, 1991.
    • (1991) Binary , vol.5 , pp. 61-64
    • Boddy, L.W.1    Morris, C.W.2
  • 3
    • 0003437038 scopus 로고
    • Neural network analysis of flow cytometry data
    • Lloyd D (ed). Springer-Verlag, Berlin
    • Boddy LW, Morris CW: Neural network analysis of flow cytometry data. In: Flow Cytometry in Microbiology, Lloyd D (ed). Springer-Verlag, Berlin, 1993, pp 159-169.
    • (1993) Flow Cytometry in Microbiology , pp. 159-169
    • Boddy, L.W.1    Morris, C.W.2
  • 4
    • 0028203678 scopus 로고
    • Neural network analysis of flow cytometric data for 40 marine phytoplankton species
    • Boddy L, Morris CW, Wilkins MF, Tarran GA, Burkill PH: Neural network analysis of flow cytometric data for 40 marine phytoplankton species. Cytometry 15:283-293, 1994.
    • (1994) Cytometry , vol.15 , pp. 283-293
    • Boddy, L.1    Morris, C.W.2    Wilkins, M.F.3    Tarran, G.A.4    Burkill, P.H.5
  • 5
    • 0024723987 scopus 로고
    • Use of a neural net computer system for analysis of flow cytometric data of phytoplankton populations
    • Frankel DS, Olson RJ, Frankel SL, Chisholm SW: Use of a neural net computer system for analysis of flow cytometric data of phytoplankton populations. Cytometry 10:540-550, 1989.
    • (1989) Cytometry , vol.10 , pp. 540-550
    • Frankel, D.S.1    Olson, R.J.2    Frankel, S.L.3    Chisholm, S.W.4
  • 6
    • 0027544701 scopus 로고
    • Real-time adaptive clustering of flow cytometric data
    • Fu L, Yang M, Braylan R, Benson N: Real-time adaptive clustering of flow cytometric data. Pattern Recognition 26:365-373, 1993.
    • (1993) Pattern Recognition , vol.26 , pp. 365-373
    • Fu, L.1    Yang, M.2    Braylan, R.3    Benson, N.4
  • 7
    • 0025619109 scopus 로고
    • Flow cytometric analysis of plant genomes
    • Methods in Flow Cytometry, Darzynkiewicz Z, Crissman H (eds).
    • Galbraith DW: Flow cytometric analysis of plant genomes. In: Methods in Flow Cytometry, Darzynkiewicz Z, Crissman H (eds). Methods Cell Biol 33:549-562, 1990.
    • (1990) Methods Cell Biol , vol.33 , pp. 549-562
    • Galbraith, D.W.1
  • 10
    • 0023331258 scopus 로고
    • An introduction to computing with neural nets
    • April
    • Lippmann RP: An introduction to computing with neural nets. IEEE ASSP Magazine, April, 1987, pp 4-22.
    • (1987) IEEE ASSP Magazine , pp. 4-22
    • Lippmann, R.P.1
  • 12
    • 0022262848 scopus 로고
    • Automated identification of subpopulations in flow cytometric list mode data using cluster analysis
    • Murphy RF: Automated identification of subpopulations in flow cytometric list mode data using cluster analysis. Cytometry 6:302-309, 1985.
    • (1985) Cytometry , vol.6 , pp. 302-309
    • Murphy, R.F.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.