Unfortunately the maximum number of labels that is supported in the volume visualization with labeled data is 128 due to implementation specifics when labeled data is overlaid with volume data.
If in your case, these 1000+ labels are not unique and are instance labels of the same category and if it is possible to visualize this volume as a binary mask, you can consider the following workaround:
1) In "volumeSegmenter", solve and visualize the problem as a binary segmentation problem instead of a multi-class segmentation problem. This will involve two classes: true = active particles, false = background.
2) "regionprops3" accepts a logical 3-D array as input, so the result of the segmentation solved in 1) can be fed directly into "regionprops3" for downstream processing. "regionprops3" will compute the individual true regions within the input volumetric binary image as part of the region analysis computation.
Hope this helps!