National Alliance for Medical Image Computing (NA-MIC) has matured into the national biomedical computing infrastructure for medical image analysis that we envisioned at the start of our first funding cycle six years ago. Through this alliance, we have demonstrated that coordinated innovation in algorithms, software engineering, and outreach processes can enable innovation in biomedical research to address a range of clinical needs. As in the first cycle, Brigham &Women's Hospital (BWH), acting as the prime contractor, has put together a stellar group of experts in both computer science and biomedical sciences consisting of 13 leading institutions across the country and 18 PIs. The Computer Science Core, addressing algorithms and software engineering, work to implement solutions for Core 2 (Driving Biological Projects or DBPs). Core 3 provides technology service. Core 4 provides training and Core 5 provides dissemination of the NA-MIC deliverables. Core 6 (or Admin Core) will coordinate between various Cores, institutions and the science and finance and project management aspects. As per the RFA, Core IA and IB together constitute 50% of our proposed budget and Core 2 constitutes 25%, while Cores 3-6 constitute 25%. All four DBPs address personalized medicine: adapting radiotherapy to accommodate patient changes;guiding cardiac catheters for targeted ablation;assessing consequences of brain trauma;and predicting future neurodegeneration and treatment response from genetic, clinical, and imaging biomarkers. Building on powerful accepted technologies, our deliverable, the NA-MIC Kit, consists of software, documentation, methodology, license policy, training materials, and data. This free open-source software (FOSS) platform features novel image analysis algorithms, smooth interoperability between its components, ease of integration with third party software, and multi-pronged outreach mechanisms to facilitate end use, thus supporting basic science.

Public Health Relevance

The overarching topic of this competitive renewal is the use of medical image computing for enabling personalized medicine. Computer science and biomedical experts collaborate as part of this project to put immediately usable tools with free open-source software (FOSS) license so that others may extend the goal of using medical imaging for personalized medicine.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZRG1-BST-K (52))
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Pai, Vinay Manjunath
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Brigham and Women's Hospital
United States
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Wachinger, Christian; Brennan, Matthew; Sharp, Greg C et al. (2017) Efficient Descriptor-Based Segmentation of Parotid Glands With Nonlocal Means. IEEE Trans Biomed Eng 64:1492-1502
Norton, Isaiah; Essayed, Walid Ibn; Zhang, Fan et al. (2017) SlicerDMRI: Open Source Diffusion MRI Software for Brain Cancer Research. Cancer Res 77:e101-e103
Sadeghi, Neda; Gilmore, John H; Gerig, Guido (2017) Twin-singleton developmental study of brain white matter anatomy. Hum Brain Mapp 38:1009-1024
Veni, Gopalkrishna; Elhabian, Shireen Y; Whitaker, Ross T (2017) ShapeCut: Bayesian surface estimation using shape-driven graph. Med Image Anal 40:11-29
Irimia, Andrei; Goh, Sheng-Yang Matthew; Wade, Adam C et al. (2017) Traumatic Brain Injury Severity, Neuropathophysiology, and Clinical Outcome: Insights from Multimodal Neuroimaging. Front Neurol 8:530
Ghayoor, Ali; Vaidya, Jatin G; Johnson, Hans J (2017) Robust automated constellation-based landmark detection in human brain imaging. Neuroimage :
Swanson, Meghan R; Wolff, Jason J; Elison, Jed T et al. (2017) Splenium development and early spoken language in human infants. Dev Sci 20:
Hong, Sungmin; Fishbaugh, James; Rezanejad, Morteza et al. (2017) Subject-Specific Longitudinal Shape Analysis by Coupling Spatiotemporal Shape Modeling with Medial Analysis. Proc SPIE Int Soc Opt Eng 10133:
Wolff, Jason J; Swanson, Meghan R; Elison, Jed T et al. (2017) Neural circuitry at age 6 months associated with later repetitive behavior and sensory responsiveness in autism. Mol Autism 8:8
Hazlett, Heather Cody; Gu, Hongbin; Munsell, Brent C et al. (2017) Early brain development in infants at high risk for autism spectrum disorder. Nature 542:348-351

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