[saltcured]

Yes, I think you are talking about light-sheet microscopy. This tries to illuminate a thin layer and then images with a 2D sensor like in a normal digital camera. This is often a monochrome sensor, and extra metadata records what kind of optical filters were in place. A multi-channel image would then have separate planes captured with different optical band-pass filters. You need metadata to know how a set of planes relate to each other, whether shifting through space or changing filters or just measuring the same configuration again at different time points.

There are also confocal "laser-scanning" microscopes which effectively illuminate a single point in space and image with what is effectively a single monochrome pixel sensor. In this case, the raw signal is pretty much a time series like you might imagine with digital audio. You need metadata to tell you how the optics were being shifted around, to interpret each sample as representing a point in space at a particular time and with what filters.

Normally, the first round of interpretation is done during the initial file save, packing measurements into a file format that still expects planar, rectangular pixel arrays with a regular grid spacing for the neighboring pixels. You pretend the whole image plane was captured at a time point, but it was really measured sequentially somewhat like a cathode-ray tube displays an image one pixel at a time. A session might produce many such planes, and metadata is still needed to understand whether these planes represent the same plane observed over time and/or parallel planes spanning a volume and/or different channels of the same plane.

On the other end of the spectrum, there are slide scanners which image a much larger stage area by shifting around a 2D camera and taking many overlapping images. So a 2048x2048 sensor might be used to produce a 100,000 x 60,000 pixel image plane. Each sub-image would record its position within the stage area and these do not necessarily line up at precise multiples of image pixels. There might also be gaps where the scanner first detects the overall shape of specimen(s) on the slide and then plans a set of images to cover the specimen while skipping over the background area. This sparsity saves time for imaging as well as storage and transfer times by skipping empty areas.