Correlative microscopy (CM) integrates multiple imaging modalities, including X-ray, light, and electron microscopy, on the same sample. This approach allows for the acquisition of images at varying scales and resolutions, which can be complemented by additional analytical techniques such as elemental dispersive spectroscopy (EDS). By merging these diverse data types—structural, chemical, and functional—CM provides a comprehensive depiction of samples, thereby enhancing our understanding of complex biological systems and leading to more accurate and detailed insights.
Here, we outline two versatile correlative microscopy workflows applied to paraffin sections and reprocessed formalin fixed, paraffin embedded human tissues for investigation by X-ray, light, electron and volume microscopy techniques. By doing so, we reveal the wealth of information retained by these samples that may be used in both clinical and research settings. Additionally, we explore conventional and contemporary AI-driven approaches for image processing, segmentation and quantification, to fully extract the abundance of information embedded within biological samples.