Neuroimaging analysis supports clinicians in the diagnosis of neurological diseases by extracting information from digital images. Due to the large number of images generated by new devices (e.g. PET ones), there is a...
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Neuroimaging analysis supports clinicians in the diagnosis of neurological diseases by extracting information from digital images. Due to the large number of images generated by new devices (e.g. PET ones), there is a lot of effort in defining computer-basedtools to analyze and classify (brain) radiological images. Statistical tools, such as SPM (for Statistical Parametric Mapping), are largely used by physicians for image analysis. Nevertheless, large datasets analysis requires repetitive steps, due to the lack of automatic procedures. E.g. SPM requires human intervention during long and complex steps. We here present a tool, called AutoSPET (for Automatic SPM analysis for PET images), which allows to perform SPM analyses on large sets of PET images. It works as a meta-component orchestrating interactions with SPM, Matlab and with SPM plugins via a unified user interface. AutoSPET has been tested with real clinical datasets and it is publicly available as an official SPM plugin on the SPM website.
In this demonstration we present MYOLAP, a java-based tool that allows OLAP analyses to be personalized and enhanced by expressing "soft" query constraints in the form of user preferences. MYOLAP is based on...
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ISBN:
(纸本)9781424489589
In this demonstration we present MYOLAP, a java-based tool that allows OLAP analyses to be personalized and enhanced by expressing "soft" query constraints in the form of user preferences. MYOLAP is based on a novel preference algebra and a preference evaluation algorithm specifically devised for the OLAP domain. Preferences are formulated either visually or through an extension of the MDX language, and user interaction with the results is mediated by a visual graph-like structure that shows better-than relationships between different sets of data. The demonstration will show how analysis sessions can benefit from coupling ad-hoc preference constructors with the classical OLAP operators, and in particular how MYOLAP supports users in expressing preference queries, analyzing their results, and navigating datacubes.
This article presents a software tool for music composition known as DSP. Developed by the Norwegian Network for Technology, Acoustics, and Music (NOTAM) to address the limitations of existing commercial solutions, DS...
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This article presents a software tool for music composition known as DSP. Developed by the Norwegian Network for Technology, Acoustics, and Music (NOTAM) to address the limitations of existing commercial solutions, DSP is a java-based tool that combines digital signal processing, composition, and tutorial materials into one package that can run in any browser on any computer platform. DSP is freely available for download on the Web (http://***/***). This article discusses the challenges of teaching music composition, computer-based music composition solutions to address these challenges, and the educational model, algorithms, implementation, release, and future enhancements of DSP
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