PMID: 15376590Sep 21, 2004Paper

Level set analysis for leukocyte detection and tracking

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Dipti Prasad MukherjeeScott T Acton

Abstract

We propose a cell detection and tracking solution using image-level sets computed via threshold decomposition. In contrast to existing methods where manual initialization is required to track individual cells, the proposed approach can automatically identify and track multiple cells by exploiting the shape and intensity characteristics of the cells. The capture of the cell boundary is considered as an evolution of a closed curve that maximizes image gradient along the curve enclosing a homogeneous region. An energy functional dependent upon the gradient magnitude along the cell boundary, the region homogeneity within the cell boundary and the spatial overlap of the detected cells is minimized using a variational approach. For tracking between frames, this energy functional is modified considering the spatial and shape consistency of a cell as it moves in the video sequence. The integrated energy functional complements shape-based segmentation with a spatial consistency based tracking technique. We demonstrate that an acceptable, expedient solution of the energy functional is possible through a search of the image-level lines: boundaries of connected components within the level sets obtained by threshold decomposition. The level...Continue Reading

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Jun 29, 2011·Medical & Biological Engineering & Computing·Peter UsenikBoštjan Likar
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