CIBC:Seg3D2:User Suggestions
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User Suggestions
Preferences
Suggestion
It would be nice if at least these settings were configurable at a per user granularity:
- View Mode: for example, many of them set it to a Single View for a lot of their work
- View Content: for example, they usually set it to Axial cut
- Grid Lines: they usually don't use the gridlines, except in special cases
- Data View: they usually set it so that the posterior is on the bottom, they pointed out that they set this in a way that it only changes the view, not the data... changing the data messes up later steps in their process (apparently there are 2 ways to change this in the current Seg3D, one modifies the data, the other doesn't)
- Fat Label Lines: they usually turn this off
- Auto save: they usually turn this on
- Zoom level: they said they usually have to adjust the zoom level every time they open Seg3D - I'm not sure how data dependent this adjustment is, but it might be helpful to save the last zoom level used
- Customize View Labels: some users may want to use names other than axial, coronal and sagittal
Reaction
- Concerning the viewing options: You can set the default the view mode in the preferences. We will add the option to select which mode to start in as well in the preferences. Also the preferences are per user and hence conform to this suggestion. Default grid lines can be set in the preferences as well.
- The new version will keep the option to change (flip) the view axis visually, but not change the data. The arrow buttons at the bottom of a viewer control this behavior. Label lines can be controlled per label and one can set the default for each new label in the preferences.
- There is a new autosave mode, that will generate a new session. It has now the option to actually save when you stop interacting with the data, so it is less annoying. It will as well only save differentials, which should speed up auto saving
- Concerning Zoom levels, I am not sure how to adjust that automatically. The data will be "auto viewed" by default when the first dataset is loaded to ensure it is in a proper scale. This should take care of it.
- Custom labels have not yet been implemented, this is not hard, but has a low priority currently.
--Jeroen