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Contents
Introduction (April 2005)
NA-MIC, the National Alliance for Medical Image Computing, is a National Center for Biomedical Computing and is funded through the NIH roadmap initiative . The goal of the roadmap initiative is to develop trans-NIH activities that are beyond the scope of a single NIH institute or center. Although NIBIB is the institute managing NA-MIC, the management team is trans-NIH and the funds come from the office of the director.
NA-MIC exists within an active research environment, with multiple collaborators and multiple sites. This page provides an overview of the major funded research efforts of the NA-MIC participants, and the relationship of this funding to NA-MIC. Of note here, in addition to NAC and BIRN, many of the Core and Site PIs participating in NA-MIC also have major research activities funded by NIH, by non-NIH federal, and by private sources. Below we outline the goals of NA-MIC, NAC, and BIRN to provide examples of the relationship among these grants, and to highlight the factors that clearly differentiate them as separate entities. Finally, as with most research collaborations, the participating researchers in NA-MIC are involved in multiple research studies funded through multiple funding mechanisms, and we are pleased that we are able to bring the expertise and strength of such successful scientists to the NA-MIC goals and objectives.
Executive Summary of NA-MIC Interactions with NAC and BIRN
Note: A one picture version of this summary can be downloaded here: pdf and ppt. A one-page text version of this summary can be downloaded here pdf.
- NA-MIC
- National Level Science, National Level Outreach
- Less than 15% of direct funding stays at BWH
- Large majority of investigators working at sites other than BWH
- Compatible with commonly available equipment and resources
- Core infrastructure that is broadly deployable
- Focus on tool and algorithm development (evolving Cores 1 and 2)
- Platform for national effort to develop image computing software engineering framework
- National Level Science, National Level Outreach
- BIRN
- National Level Science, National Level Outreach
- Multi-site collaborative clinical research
- Focus on image calibration, high-speed networking, grid computing, shared databases and large-scale image repositories
- Adapts and applies algorithms and application software from other efforts
- Platform for NA-MIC
- National Level Science, National Level Outreach
- NAC
- Local Level Science, National Level Outreach
- Close interactions of Local BWH expertise
- Leverage Unique BWH environment and infrastructure
- Custom software
- Develop "pioneering solutions"
- Focus on science questions driven by diverse independent collaboration
- Precursor for some NA-MIC development projects
- Local Level Science, National Level Outreach
The NA-MIC, NAC, and BIRN efforts form a mutually beneficial constellation of research initiatives, each with a distinct area of focus and set of priorities, but sharing a common development vision. There are natural interfaces between these projects where interoperability is necessary, but in reality each project has unique deliverables that rely and build upon components provided by the other efforts. In particular, the Neuroimage Analysis Center, as a P41 BTR resource center, brings together a set of collaborators who work together closely, primarily at a local institutional setting (BWH) in order to develop pioneering solutions and to disseminate the results nationally, as well as to make the equipment and related facilities available to the wider community. In contrast, the BIRN and NA-MIC efforts are national consortia aimed at creating solutions that will be workable across a range of institutional settings and different situations.
Thus the differences in scope between NAC and BIRN, and NA-MIC, allow NAC to push the envelope in areas where it can draw on local expertise and the unique environment at BWH. For example, the diffusion tensor based white matter neuroimaging efforts within NAC make use of custom and rapidly evolving MRI pulse sequences not yet widely available outside of the BWH environment. Accordingly, the analysis of these images relies on custom software optimized for the computer infrastructure available at BWH. NAC is, however, dedicated to making these unique resources available through its outreach activities, though this is not the exclusive focus of the research efforts. In contrast, a focus on outreach activities at the national level must work within the constraints of commonly available equipment and resources in their efforts to develop an infrastructure that is deployable to all sites. The fruitful interplay of pioneering local efforts, with widely reproducible and robust national efforts, informed by the best practices at multiple sites, thus provides a significant strength to the research agenda.
In addition to the differences in scope that differentiate NA-MIC and BIRN from the NAC, the NA-MIC and BIRN national efforts themselves have very different scientific targets. The BIRN efforts are fundamentally infrastructure development projects to enable multi-site collaborative clinical research. In particular, the BIRN testbed efforts are heavily focused on multi-site image calibration, nationwide high speed networking, grid computing, and shared databases and large-scale image repositories. Key technology components from several collaborating P41 sites have been adopted, and extended where needed, by the BIRN testbeds in order to prove the efficacy of the infrastructure. Importantly however, the BIRN efforts do not directly fund the development of new algorithms or the corresponding application software methodology -- they only support the adaptation and utilization of algorithms and software within the BIRN testbeds. In contrast, NA-MIC was specifically conceived to address the need for fundamentally new computer science approaches. In one sense, NA-MIC can be seen as an effort to develop the next generation of image computing algorithms that exist in a complementary relationship to, and build upon, the BIRN infrastructure. This new category of algorithms and software engineering practice relies on the well-curated data repositories and abundant grid computing resources provided by BIRN to address the large-scale population studies needed to extract statistically significant findings in measurements of the subtle effects of disease and treatment response. Thus in the burgeoning field of biomedical computing, it is vital to pursue several distinct research agendas -- such as those followed by NAC, BIRN, and NA-MIC in accordance with the mandates of the NIH programs they serve -- while cooridnating the efforts so that the scientific results work well together and avoid redundancy.
Examples to Illustrate Research Relationships between NAMIC, NAC, and BIRN
As an example for the relation between NAC and NA-MIC, we briefly discuss the efforts in DT-MRI postprocessing. In the DT-MRI core within the NAC, the focus is on developing novel filtering, segmentation, and tractography methods for tensor data analysis. During the past several years the team has been working to filter the data using tensor valued Markov Random Fields and analysis of tracts using Laplacian Eigenmaps. The emphasis here is on techniques that have immediate application to clinical DT-MRI data using 3D Slicer.
This sets this work apart from work performed in NAMIC, where currently the algorithmic cores are working on more theoretical approaches to both tensor and non-tensor diffusion data. One important focus within NAMIC is to derive new statistical methods for quantitative measurements (UNC, Utah) and also to investigate non-Gaussian models such as diffusion Q-Ball imaging (MGH).
The 3D Slicer software itself is used as a component of all three projects, but has very different uses driven by the needs of each project. NAC continues to develop the core functionality of Slicer for use by the broader scientific community and has a mandate to disseminate these results. It has been successful in coordinating and sharing image analysis software for image analysis software developers at BWH and nearby with solutions customized for the local environment. Dissemination, on the whole, has been successful with several thousand registered software downloads. But within NAC this effort is limited by the the number of analysis tools that can be incorporated and the ability to test the software in a wide variety of end-user environments. Slicer is built on ITK/VTK, which is a growing industry standard but is not yet widely accepted and requires significant effort to train developers. NA-MIC provides the support to integrate and disseminate a much larger portfolio of medical image analysis software contributed by developers far beyond the BWH site. The emphasis and funding for robust software engineering, training and dissemination is unique to NA-MIC and ensures that like the NAC software tools, those from other expert labs are widely available to the scientific community within a compatible software engineering framework. Slicer serves as the visualization platform for the BIRN project, for which specific modules are adapted to meet the needs of BIRN researchers. For example, significant developments have been made to support interoperability with the FreeSurfer software from MGH and the LDDMM software from JHU, both critical components of the Morphometry BIRN testbed.
Background Information on NIH Missions for the NCBC, BTR, and BIRN
- Biotechnology Resources (P41)
From NCRR's Biomedical Technology Guidelines
"These BT Centers provide state-of-the-art experimental and computational resources to a wide range of biomedical researchers, particularly those supported by NIH."
- National Centers for Biomedical Computing (U54)
From NIH's description of the NCBC program
"The centers will create innovative software programs and other tools that enable the biomedical community to integrate, analyze, model, simulate, and share data on human health and disease."
- Biomedical Informatics Research Network (BIRN)
From NCRR's description of BIRN goals
"The initial goal is to address the needs of biomedical investigators across the country to effectively share and mine data in a site-independent manner for both basic and clinical research."
FAQ
1. Like NA-MIC, NAC also has driving biological problems?
The short answer is yes, but they are called collaborations. The NCBC's are structured in a way that is very similar to the NCRR biotechnology resources. Both have technical development efforts which are responsive to collaborators' needs. NAC, however, is a national resource center and uses neurosurgery, neurologic imaging and schizophrenia as collaborator projects. In contrast, NA-MIC is a U54 and uses several different schizophrenia projects as driving biological problems. Each of these projects have distinctive goals and questions to be addressed.
2. How is the "pioneering" part different in NA-MIC and NAC, i.e., software vs. equipment or different types of software?
Both NA-MIC and NAC work on the general topic of medical image analysis, but there is no relevant overlap of the scientific personnel in the technical development areas. The specific algorithms that are being researched are very different. Accordingly, the specifics of the core algorithmic science are different.
3. How is the tool and algorithm development in NA-MIC different from pioneering efforts and custom solutions in NAC?
4. How is the software development in NA-MIC different from the developments in NAC.
NA-MIC and NAC both use the VTK and ITK toolkits and Slicer as the application del;ivery platform. NAC software development focuses on the specific NAC applications of MRI neuroimaging. The NA-MIC Engineering Core looks for generlalizations and broadens the impact of algorithms generated by Core 1. Iin addition, Core 2 defines software practices and processes for the Center.
For NA-MIC, the goal is to base the work on a shared engineering infrastructure to enable maximal leverage of the software foundation. NAC aims at enabling local scientists to make the results of their research available on a national scale. NA-MIC is a national alliance of algorithm and software researchers, catering to a national audience.
Major support of the participants in 2004
Each entry represents support of over 150k direct per year with leadership function.
NA-MIC is a truly national alliance. Each of the participating groups has a substantial portfolio of local and non-local activities. NA-MIC both leverages and enables these resources on multiple levels. The previous section discusses this relation in more detail with two examples.
The funding inside NA-MIC is distributed in compliance with the RFA: 50% of the NA-MIC direct funding is distributed in roughly equal parts among the participants of the Algorithm and Engineering cores. 25% is split among the DBP's and the remainder is split among the service, dissemination, training, and leadership cores.
Role in NA-MIC | PI | Grant | Grant Number | Agency |
---|---|---|---|---|
Leadership | ||||
BWH | Kikinis | Neuroimaging Analysis Center | P41 RR013218 | NCRR |
MR Guided Therapy | PO1 CA67165 | NCI | ||
Virtual Soldier Phase 1 | A02-600124005 | DARPA | ||
Image Guided Technology | n/a | CIMIT | ||
Morphometry BIRN | U24 RR021382 | NCRR | ||
BWH | Wong | Bioinformatics Research Center | n/a | HCNR |
Time-lapse Microscopy Cellular Analysis | 5R01 LM008696 | NLM | ||
Algorithms | ||||
MIT | Grimson | ERC Center for Medical Robotics and Computer-Assisted Interventional Systems and Technology | 8810-27499 | NSF |
MGH | DKennedy | Anatomic Morphologic Analysis of MR Brain Images | 5R01 NS34189 | NINDS |
Neuroanatomy of Adult ADHD | 5R01 MH62152 | NIMH | ||
Affective & Conative Changes in Alcoholism | 3R37AA007112-1551 | BU | ||
Validating High-Field Functional & Structural MR | ?? | USArmy | ||
Neuroimaging Neuroinformatics Training Program | 1 K12 MH069281 A01 | USArmy | ||
U of Utah | Whitaker | Dynamic MRI for myocardial perfusion and viability | R01 EB000177 | NIBIB |
Assembling Visible Neurons for Simulations | 10218584 | NIMH | ||
Geometric Surface Processing Tools for Analysis of Biological Data | EIA 0313268 | NSF | ||
Virtual Parts Engineering Research Center | DAAD19-01-1-0013 | ARO | ||
Hybrid Modeling for Geometric Design, Estimation, and Analysis | CCR-0310705 | NSF | ||
High Resolution MR Angiography | 2R01 HL048223-11 A1 | NHLBI | ||
UNC | Gerig | Medical Image Presentation MIP: Structural Image Analysis and Medical Uses | P01 CA47982-11 | NIBIB |
Prospective Studies of the Pathogenesis of Schizophrenia | P50 MH064065-01A1 | NIMH | ||
GATech | Tannenbaum | Atmospheric propagation of high energy lasers: modeling, simulation, tracking | 0205-G-DB083 | AFOSR |
Geometric variational methods for computer vision | DAAD19-02-1-0378 | ARO | ||
Active vision control systems for complex adversarial 3-D environments | F49620-03-1-0401 | MURI | ||
Statistical and variational methods for problems in visual control | F49620-05-0017 | AFOSR | ||
Engineering | ||||
GE | Lorensen | Virtual Soldier | W81XWH-04-2-0012 | DARPA |
UCLA | Toga | Computational Anatomy and Multidimensional Modeling/BIRNs | 5 P41 RR013642 | NCRR |
Computational Biology from Genotype to Phenotype | 1 P20 MH065166 | NIMH | ||
A Multidimensional Alzheimer’s Disease Brain Atlas | 5 R01 LM005639 | NLM | ||
Characteristics of Perfusion Related Cortical Signals | 2 R01 MH52083 | NIMH | ||
A Probabilistic Reference System for the Human Brain | 9 P01 EB001955 | NIBIB | ||
UCSD | Ellisman | IVEM and Image Analysis Resource (NCMIR) | 5P41 RR04050-16 | NCRR |
Biomedical Imaging Research Network – Coordinating Center (BIRN-CC) | 1R24 RR019701-01 | NCRR | ||
Dynamics of Membrane Organization at Nodes of Ranvier | 5R01 NS14718-21 | NINDS | ||
National Partnership for Advanced Computational Infrastructure (NPACI) | ASC 97-5249 | NSF | ||
3D Cell-Centered Neuronal Database | 9R01 DA016602-07 | NIDA | ||
Kitware | Schroeder | Insight Toolkit (ITK): Image Processing Tools for the Visible Human Project | N01-LM-9-3532 | NLM |
Visualizing Arbitrary Basis Functions for Advanced Engineering Analysis and Simulation (SBIR) | DMI-0128453 | NSF | ||
Simulation-Based Medical Planning for Cardiovascular Disease | 0205741 | NSF | ||
Scalable Grid Technologies for Visualization Services (SBIR) | DE-FG02-03ER83692 | DOE | ||
Software Toolkit for Image Guided Surgery (STTR) | 2 R42 EB000374-02 | NBIB | ||
System Technology for the Insight Toolkit ITK | NLM RFP 04-101/VMS | NLM | ||
Micro-to-Macro Multimodality Atlas Formation (STTR) | 1 R41 EB004737-01 | NBIB | ||
3D Widgets for Segmentation and Registration | NLM 04-177/CYC | NLM | ||
The Insight Journal: an Open Access Repository for Technical Papers related to the Insight Toolkit | NLM 04-177/CYC | NLM | ||
The Visual Database: Portable, XML-Based Middleware For Media Representation, Interaction and Exchange (SBIR) | DMI-0450513 | NSF | ||
Isomics | Pieper | Neuroimaging Analysis Center | P41 RR13218 | NCRR |
Virtual Soldier Phase I | BAA 03-02 | DARPA | ||
Morphometry BIRN | U24 RR021382 | NCRR | ||
Driving Biological Projects | ||||
VA/Harvard | Shenton | Computerized Image Analyses of MR Scans in Schizophrenia | 2R01 MH50740 | NIMH |
NeuroImaging Studies of Schizophrenia | n/a | VA | ||
Neurophysiological Studies of Schizophrenia | RO1 MH40799-09 | NIMH | ||
Clinical Symptoms & Brain Abnormalities in Schizophrenia | K05 MH70047 | NIMH | ||
MR Brain Diffusion Tensor Imaging in Schizophrenia | n/a | VA | ||
UCI | Potkin | Transdisciplinary Imaging Genetics Center | RR20837 | PHS |
Genetic and Neuropathological Abnormalities in Neuropsychiatric and Neurological Disorders | PNDRF28409 | Pretzker Foundation | ||
Functional Imaging Research in Schizophrenia Testbed: Biomedical Informatics Research Network (BIRN) | M01-RR000827 | NCRR | ||
Neuropathological and Genetic Abnormalities in Depression | MH60398 | NIMH | ||
Morphometry Biomedical Informatics Research Network (mBIRN) | MGH36106 | NCRR | ||
Dartmouth | Saykin | Neural Mechanisms of Chemotherapy-Induced Cognitive Disorder | R01 CA101318 | NCI |
Memory Circuitry in Mild Cognitive Impairment and Early Alzheimer's Disease | R01 AG19771 | NIA | ||
Cognitive Effects of Cancer Chemotherapy | R01 CA87845-03 | NCI | ||
Dopaminergic modulation of working memory in TBI: An fMRI study | R01 NS40472 | NINDS | ||
Catecholaminergic Modulation of Working Memory in TBI | R01 H133G000136 | NIDRR | ||
IDM: Data Management of Protected Information for Data Sharing and Collaboration | 00308229 | NSF | ||
A System for Data Integration and Pattern Discovery in Multimodal, Spatio-temporal Data | 0312629 | NSF | ||
U of Toronto | JKennedy | Genetics of Childhood Onset Depression: Relationship to Psychological Measures | P01 MH056193-08 | NIH |
Supplement to Risk Factors in Childhood-Onset Depression | P01 MH56193-03S1 | NIH | ||
Service | ||||
Kitware | Schroeder | See above | ||
Training | ||||
MGH | Gollub | Morphometry BIRN | R24 RR 012382 | NCRR |
MGH General Clinical Research Center | 5MO1-RR001066 | NCRR | ||
MIND Institute | n/a | DoD | ||
Dissemination | ||||
Isomics | Pieper | See above |