NA-MIC National Alliance for Medical Image Computing http

NA-MIC National Alliance for Medical Image Computing http: //na-mic. org NA-MIC Ron Kikinis, M. D. , Professor of Radiology, Harvard Medical School, Director, Surgical Planning Laboratory, Brigham and Women’s Hospital kikinis@bwh. harvard. edu Founding Director, Surgical Planning Laboratory, Brigham and Women’s Hospital Principal Investigator, the National Alliance for Medical Image Computing, and the Neuroimage Analysis Center Research Director, National Center for Image Guided Therapy

National Alliance for Medical Image Computing http: //na-mic. org http: //wiki. na-mic. org/Wiki/index. php/Leadership: Main My research- our research

Medical Image Computing • More image data, more complexity • MIC: Extract relevant information • Algorithms, Tools, Applications Provided by Odonnell, et al. Provided by Kindlmann, et al. Kindlmann, National Alliance for Medical Image Computing http: //na-mic. org Golby, Archip et al. 3

NA-MIC Algorithms • Shape representation and analysis – Multiscale/wavelets – Ensemble-based correspondences & multimodal data – Hypothesis testing • Diffusion MRI – – • Filtering, registration, and tensor estimation Stochastic tractography and optimal paths Tract clustering and atlases Hypothesis testing and validation Segmentation/classification – Shape priors and posterior estimation – Statistical atlases – PDEs and efficient numerical implementations • Functional imaging – Multimodal registration and distortion correction – Statistical analysis, regularization, and networks National Alliance for Medical Image Computing http: //na-mic. org

The NA-MIC Kit Modular set of tools and applications • Interoperable, tested, maintainable, multi-platform components – 3 D Slicer, ITK, VTK, XNAT etc. Free Open Source Software (FOSS) • Cost effective: Reduced duplication • High quality: Openness enables validation, debugging and local control • Lowers barriers for scientific exchange – 3 D Slicer: A Platform for Delivering MIC Technologies to Biomedical Scientist National Alliance for Medical Image Computing http: //na-mic. org

Slicer Use Image Gallery 6 National Alliance for Medical Image Computing http: //na-mic. org

Driving Biological Projects I • 2004 -2007 – Dartmouth/Indiana • Examines DW-MRI and f. MRI data in patients with schizophrenia to determine association with brain activation during memory tasks – Harvard • Uses structural MRI, diffusion-weighted MRI, and f. MRI to study the neural bases of schizophrenia and related psychiatric disorders. – UCI • Investigate the connections between neuroanatomy and schizophrenia. – Toronto • Investigate genetic links in schizophrenia. National Alliance for Medical Image Computing http: //na-mic. org

Driving Biological Projects II • 2007 -2010 – Harvard • Collect high-res DTI, structural and f. MRI data from patients with VCFS and use NAMIC tools to analyse the data. – JHU / Queens • Developing novel systems and procedures for prostate cancer interventions, such as biopsy and needle-based local therapies. – Mind • Evaluation of existing tools and the development new tools within SLICER for the time series analysis of brain lesions in lupus. – UNC • Longitudinal study of early brain development by cortical thickness in autistic children and controls (2 years with follow-up at 4 years). National Alliance for Medical Image Computing http: //na-mic. org

Outreach Self-Training Website 2007 2006 Hands-on Workshops National Alliance for Medical Image Computing http: //na-mic. org 2005

Patient-Specific Finite Element Model Development • • Iowa: Kiran H. Shivanna, Vincent A. Magnotta, Nicole M. Grosland, NA-MIC: Steve Pieper, Curt Lisle • Automate the generation of high quality hexahedral meshes • Inclusion of soft tissues such as cartilage • Automated Segmentation • Validation • Published / Accepted – – • Devries NA, Gassman EE, Kallemeyn NA, Shivanna KH, Magnotta VA, Grosland NM. Validation of phalanx bone threedimensional surface segmentation from computed tomography images using laser scanning. Skeletal Radiol. 2008 Jan; 37(1): 3542. Epub 2007 Oct 25. Gassman EE, Powell SM, Kallemeyn NA, De. Vries NA, Shivanna KH, Magnotta VA, Ramme AJ, Adams BD, Grosland NM, Automated Bony Region Identification Using Artificial Neural Networks: Reliability and Validation Measurements. Skeletal Radiology (accepted / online). Grant funding NIH – – R 21 (EB 001501) R 01 (EB 005973) National Alliance for Medical Image Computing http: //na-mic. org

Measuring Alcohol and Stress Interactions with Structural and Perfusion MRI in Monkeys • • Virginia Tech: Ch. Wyatt, Wake Forrest: J. Daunais NA-MIC: Kilian Pohl, W. Wells • Implement and validate algorithms for: – brain extraction – white-gray matter segmentation – subcortical structure segmentation • Grant funding NIH – R 01 AA 016748 National Alliance for Medical Image Computing http: //na-mic. org

NA-MIC NCBC Collaboration: An Integrated System for Image-Guided Radiofrequency Ablation of Liver Tumors • • Georgetown: Enrique Campos-Nanez, Patrick (Peng) Cheng, Kevin Cleary, Ziv Yaniv NA-MIC: Nobuhiko Hata • Implement and validate algorithms for: – brain extraction – white-gray matter segmentation – subcortical structure segmentation • Grant funding NIH – R 01 CA 124377 National Alliance for Medical Image Computing http: //na-mic. org

External Collaborations • • Funded through a variety of mechanisms PAR-05 -057: BRAINS Morphology and Image Analysis – This project is a funded under a Continued Development and Maintenance of Software grant to PIs Vincent Magnotta, Hans Johnson, Jeremy Bockholt, and Nancy Andreasen at the University of Iowa. The goal of this project is to update the BRAINS image analysis software developed at the University of Iowa. • Vascular Modeling Toolkit • Children's Pediatric Cardiology Collaboration with SCI/SPL/Northeastern – – • NAC, the neuroimage analysis center, is a national resource center. NAC is relying on the NA-MIC kit for its general software environment. The mission of NAC is to develop novel concepts for the analysis of images of the brain and develop and disseminate tools based on those concepts. NA-MIC Collaboration with NCIGT – • The NA-MIC Project is working to make NA-MIC neuroimaging software available through the NITRC web site. Supplemental support is helping to create the Slicer 3 Loadable Modules project so that slicer plugins can be hosted on NITRC, allowing greater scalability for developers and users of Slicer. NA-MIC Collaboration with NAC – • Collaboration with John Triedman, Matt Jolley, Dana Brooks, SCI. NA-MIC Collaboration with NITRC – • Collaboration with Luca Antiga of the Mario Negri Institute, Italy. The National Center for Image Guided Therapy is using the NA-MIC kit as the platform for its software tool development. NA-MIC Collaboration with the Japanese Research and Development Project on Intelligent Surgical Instruments – Intelligent Surgical Instruments Projects uses Open-source software engineering tools developed by NA-MIC, and leverage it to surgical robotics, funded by the Japanese Government National Alliance for Medical Image Computing http: //na-mic. org

Example: Non-rigid Deformation BWH CWM Toward real-time image guided neurosurgery using distributed and grid computing (with Andriy Fedorov, Andriy Kot, Neculai Archip, Peter Black, Olivier Clatz, Alexandra Golby, Ron Kikinis, and Simon K. Warfield. In Proceedings of the 2006 ACM/IEEE Conference on Supercomputing, Tampa, Florida, November 11 - 17, 2006. National of preoperative MRI, f. MRI, DT-MRI, with intra-operative MRI for enhanced visualization and (*) Non-rigid alignment. Alliance for Medical Image Computing navigation In http: //na-mic. org image-guided neurosurgery (with N. Archip, O. Clatz, A. Fedorov, A. Kot, S. Whalen, D. Kacher, F. Jolesz, A. Golby, P. Black, S. Warfield) in Neuro. Image, 35(2): 609 -624, 2007.