Fluorescence stitching

Regular readers of this blog will have noticed that I post about large image acquisition and stitching a lot. Partly this is due to demand from users of our facility who want to acquire images of tissue sections. In particular, there’s a lot of demand for imaging fluorescently-labeled mouse brain sections. There doesn’t seem to be a readily available slide scanner at UCSF, so I’ve been trying to come up with some easy methods for acquiring these images. I’ve been working on developing an easy workflow for doing tiled image acquisition and image stitching in Micro-Manager.

Recently, I’ve found that the Grid/Collection stitching plugin in FIJI works well for stitching images acquired in Micro-Manager. Because Micro-Manager saves its images in the OME-TIFF format, they include the coordinates that each image was acquired at. ┬áThis makes stitching the images pretty easy, because the stitcher knows exactly where each image came from. Because of this, acquiring tiled images in Micro-Manager and stitching them is seamless – simply use the create grid function in Micro-Manager to acquire the images and then open and stitch them using Grid/Collection stitching. I’ve written up a full description of how to do this on the NIC Wiki, along with some details about other stitching programs we’ve looked at.

Micro-Manager also includes a plugin for flat-field correcting images, but it doesn’t allow different flat-field images for different channels. On our microscope, there is some variation in shading from image to image, so I’ve put together a plugin that allows different flat-field correction images for different channels. This plugin has been submitted to Micro-Manager and should be available in future releases.

Putting this all together, here’s a fluorescence image of a kidney section, composed of 180 individual 3-color images. It took 3.5 min to acquire using the high speed scanning system I’ve posted about before and 11 min to stitch on a dual quad-core Xeon with 32 GB of RAM. The flat-fielding isn’t perfect, but I hope to improve that soon.