I have to train an image of 512x512x100 and I want to resize it, i saw a similar post by @donbibi129 , can anyone post the solution, I found scipy ndimage.zoom can do the same, but it is taking longer times..
I work with medical images daily and resizing can mean different things to different people. It could possibly mean:
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Cropping out a sub-volume from within the full image volume
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Making the full volume take up a larger or smaller space (would likely require resampling and interpolation)
There isn't necessarily a one size fits all solution. Do all of the medical images have the identical voxel spacing and is that spacing isometric? This is a key consideration for how you can handle the data while preserving its relation to anatomical space.
I'm happy to try and help, but I just want to be sure I understand what you're trying to achieve.
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