on the network level Flexibility and modularity Module toolbox. We are actively developing this app and have additional features lined up.1 Felix Ritter, MeVis Research Bremen, Germany Introduction to MeVisLab Visual Programming Image Processing / VIsualization Examples VTK / ITK Integration MeVisLab SDK Features GUI Scripting 2Ģ Innovation in clinical medical imaging requires close communication between Clinical users Prototyping Researchers Developers Prototyping serves as a common language! 3 MeVisLab is: Medical Image Processing and Visualization Platform Research and Development Tool Rapid Application Prototyping Environment Cross-platform (Windows, Mac OS X, Linux) Free for non-commercial usage 4ģ Amira Analyze AVS Express IBM Data Explorer/OpenDX Khoros/VisQuest LONI SCIRun 5 C++ Graphical Scripting Research and development in MeVisLab on the module level Powerful toolbox libraries Efficient Interfaces. Email CSV of datasets you've entered or edited.Print variable summaries and analysis results.Email PDFs and CSVs of variable summaries and analysis results.Current version limited to 100,000 rows and 500 columns to be conservative about performance.Put as many filters as you want on each analysis to focus in on the part of your data you're interested inĪccepts data input in the following formats:.Results are given in statistical terms and also in plain english.Calculate squares, logs, and other commonly used transformation for use in your regressions and correlations Explain how one numerical variable varies by a combination of other numerical variables (linear and logistic regression).See how two numerical variables vary with each other (correlation).See the distribution of a numerical variables broken down by levels of a categorical variable, including one-way ANOVA, box plot, and density plot.Two way frequency tables of what values categorical variables take, including phi and Cramer's V statistics.Hypothesis tests of means and proportions.Variables can be numerical, categorical, or date / time.Get key stats on each variable and see a graph of its distribution.Apply filters to zero in on the rows that interest you. Import data files (csv, txt, xls, xlsx).Get plain english explanations.ĭata Explorer makes the world of data analysis accessible to the rest of us. Use industry standard statistical techniques without being a stats expert. Find patterns within and between variables.

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