As for Help XXXXXXX Cancer, later Q2 early Q3 are the indicators for it to start. There was confirmation that for BOINC, there would be public BETA runs, so sign up in My Grid > Beta Testing. Reliable machines will be send jobs for that. The test batches are not massive. Sometimes only 1000 - 2000, but it allows an early peek. Beta's are advised in the Beta Announcement [Read Only] forum.

cheers

A Special Message from Dr. David Foran
June 12, 2007

I would like to restate my gratitude to all of those individuals throughout the World Community Grid who contributed computer cycles to the "Help Defeat Cancer" project. Like most research pursuits our team began the Project with an innovative idea which had firm scientific grounding, but required systematic investigation to determine its validity. In our case, we envisioned a high-throughput analysis approach for characterizing protein expression patterns in imaged tissue specimens which could reliably classify subtypes and stages of disease progression in breast, colon, and head and neck cancer.

World Community Grid provided the HDC project with more than 2, 900 years of computation and enabled us to demonstrate the feasibility of using spectral and spatial signatures to characterize expression patterns in imaged cancer specimens. Furthermore, we have been able demonstrate the fact that the resulting library of signatures is not spatially constrained and can therefore be used to perform analysis at multiple levels of granularity, i.e. at the disc, tissue, and tumor level. During the same time we have developed a new region covariance descriptor which was shown to have superior performance in tumor classification and a segmentation framework that can reliably delineate multiple classes of imaged cells and tissues even when they present with different views, illuminations, and scales.



Leveraging the experimental results gathered during the course of the "Help Defeat Cancer" project we submitted a new grant proposal to the National Institutes of Health for funding consideration entitled, "Image Mining for Comparative Analysis of Expression Patterns in Tissue Microarrays". The central objective of this proposal is to build a deployable, grid-enabled clinical decision support system to enable researchers and physicians to automatically analyze and classify imaged cancer specimens with improved diagnostic and prognostic accuracy. Proof-of-concept for the proposed system was conducted using the core reference library of expression signatures that was generated as part of the HDC project.

We were recently informed that the research proposal that we submitted to NIH scored in the top 3.9 percentile. To test the performance of the new technologies and computational tools developed during the course of the 4 year project, a Grid-enabled, virtual laboratory will be established among strategic sites located at The Cancer Institute of New Jersey (CINJ), Columbia University (CU), the Ohio State University (OSU), Rutgers University (RU), and the University of Pennsylvania School of Medicine (UPenn). The software and underlying technologies developed as part of this project will be made available to investigators throughout the scientific and cancer communities for use in clinical decision support, investigative research and discovery.

Although this phase of the "Help Defeat Cancer" project has come to a close I remain convinced that this is actually just the start of new beginnings. This has already been borne out as we approach the start of the new NIH project and as we begin a new collaboration with scientists at IBM's T.J. Watson Research Center. The central objective of the new project with IBM is to advance our preliminary work in order to develop a set of multi-modality meta-classifiers which can simultaneously assess the salient genomic, proteomic and image-based profiles of patients in order to provide improved accuracy in detection, treatment and therapy planning.
Latest update from The Cancer Institute of New Jersey

June 12, 2007. The CBII research lab has a number of new publications in press.

* Lin Yang, Peter Meer, David J. Foran. Pixel-Wise Multiple Class Segmentation Using Histogram Descriptors Over Mean-Shift Patches. IEEE Proceedings on Computer Vision and Pattern Recognition. Accepted for publication. To be presented at the International Conference to be held in Minneapolis, Minnesota, June, 2007.
* Lin Yang and David J. Foran. A Variational Framework for Partially Occluded Image Segmentation Using Coarse to Fine Shape Alignment and Semi-parametric Density Approximation. IEEE Proceedings on Image Processing. Accepted for publication. To be presented at the International Conference to be held in San Antonio, Texas, September, 2007.
* Lin Yang, Peter Meer, Lauri A. Goodell, Michael D. Feldman, and David J. Foran. High-Throughput Breast Cancer Analysis on the Grid. Proceedings on Medical Image Computing and Computer-Assisted Intervention. Accepted for publication. To be presentated at the International Conference to be held in Brisbane, Australia, October, 2007.
* Bonnie H. Hall, Wenjin Chen, and David J. Foran. A Clinically Motivated 2-Fold Framework for Quantifying and Classifying of Immunohistochemically Stained Specimens.Proceedings on Medical Image Computing and Computer-Assisted Intervention. Accepted for publication. To be presented at the International Conference to be held in Brisbane, Australia, October, 2007.
* Gabriela Niculescu, John L. Nosher, David J. Foran. Non-rigid Registration of the Liver in Consecutive CT Studies for Assessment of Tumor Response to Radiofrequency Ablation. IEEE Proceedings of the Engineering in Medicine and Biology Society. Accepted for publication. To be presentated at the International Conference to be held in Lyon, France, August, 2007.

As for Help XXXXXXX Cancer, later Q2 early Q3 are the indicators for it to start. There was confirmation that for BOINC, there would be public BETA runs, so sign up in My Grid > Beta Testing. Reliable machines will be send jobs for that. The test batches are not massive. Sometimes only 1000 - 2000, but it allows an early peek. Beta's are advised in the Beta Announcement [Read Only] forum.

cheers