Detection of leukocytes in contact with the vessel wall from in vivo microscope recordings using a neural network

IEEE Transactions on Biomedical Engineering

Volumn 47, Issue 7, 2000, Pages 941-951

  Egmont Petersen, M ^a   Schreiner, U ^a   Tromp, S C ^b   Lehmann, T M ^a  

^a Department of Biophysics ^*  (Netherlands)

^b MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

Leukocyte detection; Microcirculation; Model based image processing; Nonlinear filtering; Object recognition; Shape characterization; Stochastic model

Indexed keywords

CELLS; IMAGING TECHNIQUES; MATHEMATICAL MODELS; MICROCIRCULATION; NEURAL NETWORKS; NONLINEAR FILTERING; OBJECT RECOGNITION; RANDOM PROCESSES;

LEUKOCYTES; SHAPE CHARACTERIZATION; VIDEO MICROSCOPY;

BLOOD VESSELS;

ANIMAL CELL; ANIMAL TISSUE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BLOOD VESSEL WALL; IMAGING SYSTEM; LEUKOCYTE; MATHEMATICAL ANALYSIS; MICROSCOPY; NONHUMAN; RABBIT; RAT; STOCHASTIC MODEL;

ANIMALS; BIOMEDICAL ENGINEERING; BLOOD VESSELS; CELL ADHESION; IMAGE PROCESSING, COMPUTER-ASSISTED; LEUKOCYTES; MICROSCOPY; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); STOCHASTIC PROCESSES;

EID: 0033931304     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/10.846689     Document Type: Article

References (27)

1. M. G. A. oude Egbrink, G. J. Tangelder, D. W. Slaaf, and R. S. Reneman, "Influence of platelet-vessel wall interactions on leukocyte rolling in vivo." Circ. Res., vol. 70, no. 2, pp. 355-363, 1992.
2. Y. Sato, J. Chen, R. A. Zoroofi, N. Harada, S. Tamura, and T. Shiga, "Automatic extraction and measurement of leukocyte motion in microvessels using spatiotemporal image analysis," IEEE Trans. Biomed. Eng., vol. 44, pp. 225-236, Apr. 1997.
3. J. Hektor, J. Jansen, H. Heidtmann, H. Schmid-Schönbein, and R. Grebe, "A setup for computer-assisted tracking of erthrocytes in microvascular networks," J. Computer-Assisted Microscopy, vol. 9, no. 3, pp. 135-141, 1997.
4. M. Watanabe, Y. Senga, T. Shiga, and S. Miname, "The time-space correlation method for measurement of erythrocyte velocity in microvessels using a CCD linear imaging sensor," Microvasc. Res., vol. 41, pp. 41-46, 1991.
5. C. Y. J. Yip, Y. Aggerwal, K. R. Diller, and S. C. Bovik, "Simultaneous multiple site arteriolar vasomotion measurement using digital image analysis," Microvasc. Res., vol. 41, pp. 73-83, 1991.
6. M. Egmont-Petersen and T. Arts, "Recognition of radiopaque markers in X-ray images using a neural network as nonlinear filter," Pattern Recogn. Lett., vol. 20, no. 5, pp. 521-533, 1999.
7. R. C. Gonsalez and R. E. Woods, Digital Image Processing. Reading, MA: Addison-Wesley, 1992.
8. M. Egmont-Petersen and T. Arts, "Detection of implanted markers in radiographic image sequences," in Aachener Workshop für Bildverarbeitung in der Medizin (Aachen Workshop on Medical Image Processing), T. Lehmann and K. Spitzer, Eds, Germany: Aachen, 1996, pp. 209-214.
9. D. DeKruger and B. R. Hunt, "Image processing and neural networks for recognition of cartographic area features," Pattern Recognition, vol. 27, no. 4, pp. 461-483, 1994.
10. M. Egmont-Petersen and E. Pelikan, "Detection of bone tumours in radiographs using neural networks," Pattern Anal. Applicat., vol. 2, no. 2, pp. 521-533, 1999.
11. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active contour models," Int. J. Comput. Vision, pp. 321-331, 1988.
12. S. Lobregt and M. A. Viergever, "A discrete dynamic contour model," IEEE Trans. Med. Imag., vol. 14, pp. 12-24, Feb. 1995.
13. C. Vieren, F. Cabestaing, and J.-G. Postaire, "Catching moving objects with snakes for motion tracking," Pattern Recogn. Lett., vol. 16, pp. 679-685, 1995.
14. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham, "Active shape models - Their training and application," Comput. Vision Image Understanding, vol. 61, no. 1, pp. 38-59, 1995.
15. A. Califano and R. Mohan, "Multidimensional indexing for recognizing visual shapes," IEEE Trans. Pattern Anal. Machine Intell., vol. 16, pp. 373-392, Apr. 1994.
16. T. M. Cover and P. E. Hart, "Nearest neighbor pattern classification," IEEE Trans. Inform. Theory, vol. IT-13, pp. 21-27, Jan. 1967.
17. K.-I. Funahashi, "On the approximate realization of continuous mappings by neural networks," Neural Networks, vol. 2, pp. 183-192, 1989.
18. K. Hornik, "Approximation capabilities of multilayer feedforward networks," Neural Networks, vol.4, pp. 251-257, 1991.
19. J. D. Villiers and B. Bernard, "Backpropagation neural nets with one and two hidden layers," IEEE Trans. Neural Networks, pp. 136-141, July 1992.
20. M. D. Richard and R. P. Lippmann, "Neural network classifiers estimate bayesian a posteriori probabilities," Neural Computation, vol. 3, pp. 461-483, 1991.
21. T. A. Springer, "Traffic signals for lymphocyte recirculation and leukocyte emigration: The multistep paradigm," Cell, vol. 76, pp. 301-314, 1994.
22. D. W. Slaaf, R. Alewijnse, and H. Wayland, "Use of telescopic imaging in intravital microscopy: A simple solution for conventional microscopes," Int. J. Microcirc.; Clin. Exp., vol. 1, pp. 121-134, 1982.
23. T. Lindeberg and B. M. ter Haar Romeny, "Linear scale-space theory," in Geometry-Driven Diffusion in Computer Vision, B. M. ter Haar Romeny, Ed. Dordrecht, The Netherlands: Kluwer Academic, 1994, ch. 2.
24. B. Jähne, Digital Image Processing. Concepts, Algorithms and Scientific Applications. Berlin, Germany: Springer-Verlag, 1995.
25. D. H. Wolpert and W. G. Macready, "No free lunch theorems for search," The Santa Fe Institute, Santa Fe, NM, Tech. Rep. SFI-95-02-010, 1995.
26. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, "Learning internal representations by error propagation," in Parallel Distributed Processing. Exploration into the Microstructure of Cognition, D. E. Rumelhart and J. L. McClelland, Eds. Cambridge, MA: MIT Press, 1986, vol. 1, pp. 318-364.
27. M. C. Weinstein, H. V. Fineberg, A. S. Elstein, H. S. Frazier, D. Neuhauser, R. R. Neutra, and B. J. McNeil, Clinical Decision Analysis. Philadelpha, PA: Saunders, 1978.