Knowledge Extraction for High-Throughput Biological Imaging

Authors

Wamiq AhmedFollow
Arif Ghafoor
J. Paul Robinson

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.

Keywords

multilayered architecture, spatiotemperal, biological imaging, segmentation, tracking, object recognition, finite state machine, Petri net based models

Date of this Version

2007

Comments

MultiMedia, October-December 2007 (vol. 14 no. 4), pages 52-62.