Alignment with sub-pixel accuracy for images of multi-modality microscopes using automatic calibration

A biological specimen is often imaged with various imaging modalities, and it is crucial that such images are well aligned to best reveal physiological structures and functions of the specimen for in-depth analyses. In this paper, we present a methodology for automatic calibration of multiple optical imaging modalities within the x-y detector plane using a custom chrome-on-glass target and an automatic and accurate registration algorithm. The target contains lines crossing at random angles, and our method of registration is based on the alignment of salient features extracted from the lines within the individual images. Once spatial relationships are found between the various detectors and applied to the resultant images, no further registration is required for all static samples, and the registered images serve as the starting point for registration of dynamic samples, where the remaining misalignment is caused by sample movement. We have validated our algorithm with 40 inter-modal and 30 intra-modal image pairs, and the success rates are 95 and 100%, respectively, with sub-pixel accuracy. This methodology is widely applicable to any multi-modal microscope that combines a number of imaging modalities on a common platform assuming images of the target can be obtained.