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Green Image
Issue No. 04 - October-December (2007 vol. 14)
ISSN: 1070-986X
pp: 52-62
Wamiq M. Ahmed , Purdue University
Arif Ghafoor , Purdue University
J. Paul Robinson , Purdue University
ABSTRACT
We present a multilayered architecture and spatiotemporal models for searching, retrieving, and analyzing high-throughput biological imaging data. The analysis is divided into low- and high-level processing. At the lower level, we address issues like segmentation, tracking, and object recognition. At the high level, we use finite-state-machine- and Petri-net-based models for spatiotemporal event recognition.
INDEX TERMS
Spatiotemporal modeling, high-throughput imaging, semantic analysis, high-content screening, and image understanding.
CITATION

W. M. Ahmed, J. P. Robinson and A. Ghafoor, "Knowledge Extraction for High-Throughput Biological Imaging," in IEEE MultiMedia, vol. 14, no. , pp. 52-62, 2007.
doi:10.1109/MMUL.2007.77
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