Kavli Affiliate: Michael Miller, Menno Witter
| Authors: Kaitlin Stouffer, Menno Witter, Daniel Tward and Michael Miller
| Summary:
Reconstructing dense 3D anatomical coordinates from 2D projective measurements has become a central problem in both mouse and human digital pathology. We describe a new family of diffeomorphic mapping technologies called Projective LDDMM which generate diffeomorphic mappings of dense human MRI atlases at tissue scales onto sparse measurements at micron scales associated with histological and more general optical imaging modalities. We solve the problem of dense mapping surjectively onto histological sections by incorporating new technologies for crossing modalities that use non-linear scattering transforms to represent multiple radiomic-like textures at micron scales and incorporating a Gaussian mixture-model framework for modelling tears and distortions associated to each section. We highlight the significance of our method for enabling integration of imaging data across scales with the incorporation of tau digital pathology measures and MRI, as relevant in the development of biomarkers for neurodegenerative diseases in digital pathology, such as Alzheimer’s disease.