In general, these multiple low-resolution acquisitions are not well suited for any 3D processing, so the best would be to acquire proper 3D volume, with as isotropic spacing (cubic voxel shape) as possible.
You may try to find toolkits that can create an isotropic super-resolution image from multiple low-resolution sweeps, but this is a difficult image reconstruction problem, so there are no standard solutions. Have a look at this post Import volume by projections for info on a toolkit that might be usable.
You may also try to use your volumes for segmentation one by one (since you can swap the master volume any time): Create a high-resolution isotropic volume from any of the input volumes, using Crop volume module. Then create a segmentation node using this isotropic volume as master volume. After this you can switch between master volumes - the segmentation node’s internal binary labelmap representation will remain high-resolution and isotropic. For example, you can segment the structure of interest based on one image, then switch master volume and make adjustments in the segmentation as needed. Unfortunately, this is a manual, iterative process.