IEIE Transactions on Smart Processing and Computing

The Institute of Electronics and Information Engineers (대한전자공학회)
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Efficient Generation of Spatiotemporal Images for Leukocyte Motion Detection in Microvessels

  • Kim, Eung Kyeu (Department of Information and Communication Engineering, Hanbat National University) ;
  • Jang, Byunghyun (Department of Computer and Information Science, School of Engineering, The University of Mississippi / University)
  • Received : 2016.11.29
  • Accepted : 2017.01.24
  • Published : 2017.04.30
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Abstract

This paper presents an efficient method for generating spatiotemporal images in order to detect leukocyte motion in microvessels. Leveraging the constraint that leukocytes move along the contour line of the blood vessel wall, our proposed method efficiently generates spatiotemporal images for leukocyte motion detection. To that end, translational motion caused by in vivo movement is first removed by a template matching method. Second, the blood vessel region is detected by an automatic threshold selection method in order to binarize temporal variance images. Then, the contour of the blood vessel wall is expressed via B-spline function. Finally, using the detected blood vessel wall's contour as an initial curve, the plasma layer for the most accurate position is determined in order to find the spatial axis via snake, and the spatiotemporal images are generated. Experimental results show that the spatiotemporal images are generated effectively through comparison of each step with three images.

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