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Cell-Image Learning 2009 : ICML-UAI-COLT 2009 Workshop on Automated Interpretation and Modeling of Cell Images

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When Jun 18, 2009 - Jun 18, 2009
Where Montreal, Canada
Submission Deadline May 8, 2009
Notification Due May 16, 2009
Final Version Due Jun 13, 2009
Categories    machine learning   bioinformatics   computer vision   biomedical engineering
 

Call For Papers

DEADLINE EXTENDED!! New deadline: May 8, 2009.

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.

Instructions of Submission
===========================
We encourage the submissions of extended abstract. The suggested abstract length is about 4 pages, following the style of ICML. Submissions are not required to be anonymous. The authors of the accepted abstracts will be allocated between 30 and 40 minutes to present their work (to be determined according to submissions). The abstracts will be made available on this web site. The authors should submit their extended abstract to cellimage.icml (at) gmail.com in pdf by the deadline. An email confirming the reception of the submission will be sent by the organizers.


Program Committee
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* Gaudenz Danuser, Scripps Institute, USA
* Roland Eils, DKFZ, Germany
* Ilya Goldberg, NIH, USA
* Nick Hamilton, U. of Queensland, Australia
* Chun-Nan Hsu, Academia Sinica, Taiwan
* Thouis R. Jones, MIT, USA
* Raphael Maree, U. of Liege, Belgium
* Robert Murphy, CMU, USA
* Loris Nanni, U. of Bologna, Italy
* Karl Rohr, DKFZ, Germany
* Badri Roysam, RPI, USA
* Ge Yang, CMU, USA

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

Confirmed Invited Speakers
===========================
* Roland Eils, DKFZ, Germany
* Yoav Freund, UCSD, USA
* Badri Roysam, RPI, USA
* Eric Xing, CMU, USA
* Thouis R. Jones, MIT, USA
* and more...


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