Article reference:

M. Egmont-Petersen, U. Schreiner, S.C. Tromp, T. Lehmann, D.W. Slaaf, T. Arts. "Detection of leukocytes in contact with the vessel wall from in vivo microscope recordings using a neural network," IEEE Transactions on Biomedical Engineering, Vol. 47, No. 7, pp. 941-951, 2000.


Leukocytes play an important role in the host defense as they may travel from the blood stream into the tissue in reacting to inflammatory stimuli. The leukocyte-vessel wall interactions are studied in post capillary vessels by intraviral video microscopy during in vivo animal experiments. Sequences of video images are obtained and digitized with a frame grabber. A method for automatic detection and characterization of leukocytes in the video images is developed. Individual leukocytes are detected using a neural network that is trained with synthetic leukocyte images generated using a novel stochastic model. This model makes it feasible to generate images of leukocytes with different shapes and sizes under various lighting conditions. Experiments indicate that neural networks trained with the synthetic leukocyte images perform better than networks trained with images of manually detected leukocytes. The best performing neural network trained with synthetic leukocyte images resulted in an 18% larger area under the ROC curve than the best performing neural network trained with manually detected leukocytes.

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