Vivid E9, LCD, Floating Keyboard, Ergonomically Designed, 40% Lighter than many other console units, Nice Workflow with Keystrokes
•Customizable Scan Assist and Scan Assist Pro to acquire images in a pre-defined sequence and significantly reduce keystrokes and exam time.
•Multidimensional imaging so you can capture bi- or tri-plane images in a single beat.
•Auto-Align for 4D views that feature automatic positioning and orientation of the left ventricle.
•Multi-Slice Imaging that provides a live imaging mode with choices of viewing 5, 7, 9 or 12 slices for simultaneous acquisition and assessment.
•Dynamic Multi-Slice to help ensure continuous visualization of the same cardiac structures throughout the heart cycle.
Advanced 4D Quantification
4D Auto LVQ: A mesh-based surface-tracking model, the 4D Auto
LVQ quantification tool provides you with a graphical output of pure 4D volume data. Utilizing temporal data, it delivers more reproducible results that are less prone to artifacts and variable heart rhythms for automatic volume and ejection fractions.
4D LV Mass: Using the above mentioned mesh-based surface tracking model, by adding the epicardial border, an LV Mass and an LV Mass Index is derived from the same data set.
4D Strain: As an extension to the 4D LV Mass tool, both global and regional strain values are calculated based upon a spatial speckle tracking algorithm. The end result is presented in a Strain Bull’s Eye
plot accompanied by Time-Strain curves and Cut Planes for
enhanced visual tracking assessment.
4D Views provides you with“one-touch” options to view images such as
4-chamber, 2-chamber, APLAX, mitral valve, septum and aortic valve.
After an automatic alignment, it takes the full volume acquisition data set and, with the touch of a button, automatically crops away the volume to instantly deliver the view you want. 4D Views helps eliminate the manual cropping and cutting of conventional 3D workflow—a time-consuming process that’s difficult to teach and learn.
4D Virtual Store
This innovative feature helps reduce the size of patient studies by using image pointers to refer back to the original full-volume data set,
rather than saving multiple large data sets for every new crop view or measurement.
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