Cell-Image Learning 2009

All Information Under Review

This workshop is to bring together interdisciplinary researchers to present and discuss emerging challenges and research issues that arise when realizing fully-automated intelligent analysis of cell images due to recent advances in cell imaging capabilities to discover new biological knowledge about cell structure and function.

Dramatic advances in fluorescent probe development, new fluorescence microscope designs to achieve greatly improved temporal and spatial resolution, and significant advances in digital camera and computer technology have enabled increasing use of fluorescence microscopy for quantitative, large scale studies of cell behavior. The high volume and high quality of images resulting from these studies has created and will continue to create many opportunities for computational analysis, especially in the realm of computer vision, machine learning and UAI. Successful results have been reported in the literature on determining sub-cellular phenotypes, understanding cell structure and dynamics, reconstruction of the wiring diagram of neurons, drug discovery and cancer diagnosis. Existing relevant machine learning and UAI techniques include, but are not limited to: classification, clustering, graphical models, graph-theoretic approaches, kernel methods, link analysis, Monte Caro methods, semi-supervised/unsupervised learning and stochastic modeling. However, the focus of this workshop will be on emerging challenges and research issues that arise when realizing fully-automated intelligent analysis of cell images due to recent advances in cell imaging capabilities to discover new biological knowledge about cell structure and function. These issues include, but not limited to, the following: * Feature extraction and selection * Quantification of subtle differences and changes in cell images * Event detection and tracking/ temporal analysis * Multi-classification scaled to hundreds or more classes * Generalization across multiple resolutions and imaging platforms * Reconstruction/modeling of biological networks from cell images/animations Discussions of new issues overlooked in the major conferences will be especially encouraged.

Organizers
 * Robert Murphy (Chair), CMU
 * Chun-Nan Hsu, IIS, Academia Sinica, Taiwan
 * Loris Nanni, University of Bologna, Italy

This CfP was obtained from WikiCFP