  Neuroimaging to neuropathology correlation (NTNC) promises to enable the
transfer of microscopic signatures of pathology to in vivo imaging with MRI,
ultimately enhancing clinical care. NTNC traditionally requires a volumetric
MRI scan, acquired either ex vivo or a short time prior to death.
Unfortunately, ex vivo MRI is difficult and costly, and recent premortem scans
of sufficient quality are seldom available. To bridge this gap, we present
methodology to 3D reconstruct and segment full brain image volumes from brain
dissection photographs, which are routinely acquired at many brain banks and
neuropathology departments. The 3D reconstruction is achieved via a joint
registration framework, which uses a reference volume other than MRI. This
volume may represent either the sample at hand (e.g., a surface 3D scan) or the
general population (a probabilistic atlas). In addition, we present a Bayesian
method to segment the 3D reconstructed photographic volumes into 36
neuroanatomical structures, which is robust to nonuniform brightness within and
across photographs. We evaluate our methods on a dataset with 24 brains, using
Dice scores and volume correlations. The results show that dissection
photography is a valid replacement for ex vivo MRI in many volumetric analyses,
opening an avenue for MRI-free NTNC, including retrospective data. The code is
available at https://github.com/htregidgo/DissectionPhotoVolumes.
