Welcome HP-MICCAI / MICCAI-DCI 2011, The Joint Workshop on High Performance and Distributed Computing for Medical Imaging, featured at MICCAI 2011, will be held at September 22nd 2011 in Toronto, Canada. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Final Programme
We proudly present the final programme of the HP-MICCAI/MICCAI-DCI 2011 workshop. Two keynotes are given: Alan C. Evans shows how to use distributed environments for Neuroimaging, and Joel Saltz presents solutions for large-scale pathological data analysis. The oral presentations and poster session encompass latest research on a wide range of medical imaging areas and computer systems. Find the full programme below. For full information about authors and session chairs please see PDF We are looking forward to see you in Toronto!
The programme may change due to unexpected incidents.
Topics The list of topics addressed by this workshop includes, but is not limited to:
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Introduction The proliferation and increased reliance on high-resolution, multimodality biomedical images/videos present significant challenges for a broad spectrum of clinical practitioners and investigators throughout the clinical and research communities. A growing spectrum of new and improved imaging modalities and new image processing techniques can significantly affect diagnostic and prognostic accuracy and facilitates progress in the areas of biomedical research and discovery. However, the impact of these new technologies in both time-critical clinical applications and high-throughput research pursuits depends, in large part, on the speed and reliability with which the imaging data can be visualized, analyzed and interpreted. Conventional serial computation is grossly inadequate and inefficient for managing these increasing amounts of data and the employment of the new advances in medical imaging is often limited by insufficient compute and storage resources.
High-performance computing (HPC) such as multicore/multiprocessor and GPU-based processing, and distributed computing infrastructures (DCIs) such as Grids and Clouds are effective approaches for overcoming such limitations. They allow for significant reduction of computational time for running large experiments and speed-up the development time for new algorithms while increasing the availability of new methods for the research community, and supporting large-scale multi-centric collaborations. The workshop will build on existing collaborative efforts in understanding current trends in HPC/DCI medical imaging research. It will demonstrate and encourage open discussion regarding the current status and latest developments in the field; explore new ideas/motifs and identify the challenges which currently impeded wider adoption of these technologies in image-assisted translational research, clinical intervention and decision-making. The workshop addresses researchers who are already employing HPC/DCI techniques, as well as scientists who are developing data- and compute-intensive imaging applications including multi-data studies, large-scale parameter scans or complex analysis pipelines. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||