TIRL: Automated Non-Linear Registration of Stand-Alone Histological Sections to Whole-Brain MRI

Istvan Huszar, MD Presenter
Nuffield Department of Clinical Neurosciences
Oxford, Oxfordshire 
United Kingdom
Software Demonstrations 
Advanced MRI methods are sensitive to tissue properties at much finer scales than the resolution of a clinical MRI scan. Consequently, it is of great interest what the MRI signal can reveal about the healthy tissue microstructure, and how it is affected by disease. Conversely, most existing biophysical models concern healthy conditions, and radiological findings in patients are rarely followed up by post-mortem histological validation, leaving the radiological and histopathological understanding of human neurodegeneration detached. Bridging the gap requires precise alignment between MRI and histology that so far has been predominantly addressed for serial sections. However, the costs of this technique are prohibitively high to take disease heterogeneity into account by studying a multitude of brains. Here we report a customisable image registration platform to automate the alignment of conventional small-slide histological sections to whole-brain post-mortem MRI as an alternative.