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Mango – short for Multi-image Analysis GUI – is a viewer for medical research images. It provides analysis tools and a user interface to navigate image volumes. Versions. There are three versions of Mango, each geared for a different platform: Mango – Desktop – Mac OS X, Windows, and Linux
Mango supports several image layouts within a viewer. The default layout for tomographic images has three orthogonal 2-D section images, one as a large view and the other two as smaller views (Figure 3). By default the larger view displays an axial section (x-y) and the two smaller views display coronal (x-z) and sagittal (y-z) views.
Volume Rendered Images. Volume rendering provides a variety of viewing options for voxel-based images using a technique called ray tracing. A ray is a straight-line path through the object perpendicular to the display plane. Each pixel in the display has an associated ray.
Images can be selected and previewed with this tool. [Alt][o] is the keyboard shortcut for this option. See Image Browser for more information. Open Raw Image. Images which lack a recognized file header, can be opened here. See the Open Raw Image section. Add New Image. New images can be generated using this option. See the Add New Image section.
Download Mango. Download Papaya. Download iMango. Plugins. Download plugins for Mango. Sample Data. A sample image can be downloaded here.
To reset saved info for all images, select the Reset All Defaults option in Settings. Transform.
The processing schema is similar to how Mango performs other multi-image operations such as copying an ROI from one image and pasting it into another. In image coordinate mode images are aligned according to row, col, slice, time = 0,0,0,0. In world coordinate mode images are aligned according to x, y, z, t = 0,0,0,0.
Similarly, increasing row number is anterior to posterior (toward '-y') and increasing slice number is superior to inferior (toward '-z'). In Mango all images are represented internally using a single 'standard' orientation. This simplifies image processing since all images will have identical col, row, slice order.
this + other(1) + other(2) [adds three images together] (this - meanROI(r)) / sdROI(r) [subtracts the mean of the red ROI from each voxel and divides by the standard deviation] col * row * slice [creates a gradient based on the voxel indices] this >= 100 [thresholds the image at 100]
The surface-based volume calculation is faster than voxel counting in voxel-base images. Volumes from surfaces and paired ROIs in voxel-based images are slightly different (1-2%). This is due in part to how surfaces are thresholded, possible differences in connectivity rules used during surface synthesis, and differences due to decimation (reduction of number of triangles) when finalizing the surface model.
