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Medical-image Analysis and Statistical Interpretation Lab

‘JIST’

Figure 1 Workflow framework.

Performance Management of High Performance Computing for Medical Image Processing in Amazon Web Services

Feb. 27, 2016—Shunxing Bao, Stephen M. Damon, Bennett A. Landman, Aniruddha Gokhale. “Performance Management of High Performance Computing for Medical Image Processing in Amazon Web Services.” In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2016. Oral presentation. Full Text: https://www.ncbi.nlm.nih.gov/pubmed/?term=Performance+Management+of+High+Performance+Computing+for+Medical+Image+Processing+in+Amazon+Web+Services Abstract Adopting high performance cloud computing for medical image processing is a popular...

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Overview of the need for accurate estimates in high performance medical imaging. Complex multi-stage imaging layouts need to provide accurate estimations of their resource requirements in order to leverage high performance computing resources. The upper-right inlay shows histograms of the runtime for a single software module (“File Collection Efficient Registration”) on datasets acquired on 21 individuals

Resource Estimation in High Performance Medical Image Computing

Oct. 31, 2014—Rueben Banalagay, Kelsie J. Covington, D.Mitch Wilkes, Bennett A. Landman. “Resource Estimation in High Performance Medical Image Computing.” Neuroinformatics. 2014 Oct;12(4):563-73. † PMC4381797 Full Text: https://www.ncbi.nlm.nih.gov/pubmed/24906466 Abstract Medical imaging analysis processes often involve the concatenation of many steps (e.g., multi-stage scripts) to integrate and realize advancements from image acquisition, image processing, and computational analysis. With the...

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Next Generation of the JAVA Image Science Toolkit (JIST) Visualization and Validation

Aug. 1, 2012—Bo Li, Frederick Bryan, Bennett A. Landman, “Next Generation of the JAVA Image Science Toolkit (JIST) Visualization and Validation.” Insight Journal. August 2012. P 874 PMC4181667 Full text: https://www.ncbi.nlm.nih.gov/pubmed/25285310 Abstract Modern medical imaging analyses often involve the concatenation of multiple steps, and neuroimaging analysis is no exception. The Java Image Science Toolkit (JIST) has provided a...

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MIPAV (A) automatically detects the presence of the Plug-In Selector and provides a menu item to open the tool. The Plug-In Selector interface lists all detected plug-ins according to their programmer specified hierarchy (B). Once selected from this menu, a programmatically generated GUI appears for any tool (C) which can operate on any image accessible to MIPAV.

The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

Mar. 31, 2010—Blake C. Lucas, John A. Bogovic, Aaron Carass, Pierre-Loius Bazin, Jerry L. Prince, and Bennett A. Landman, “The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software”, Neuroinformatics. 8(1):5-17.(2010) PMC2860951 Full text: https://www.ncbi.nlm.nih.gov/pubmed/20077162 Abstract Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and...

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