The size of the histology dataset (1853 slices; up to 38 000 × 17 500 pixels per slice; maximum file size per single slice ∼2 GB; 1.6 TB of data for the whole heart) created a computational challenge.
For each dataset three slices at three different levels were selected; medial at the level of the right portal vein, cranial above the level of the left portal vein and caudal at the level of the splenic vein.
Subsets of the complete datasets (60 slices, TE/40 ms, 2 mm isotropic resolution, 96×96 matrix, 1680 Hz/pixel) are shown (for full data sets see Fig. S1a-d).
Datasets were slice-timing corrected (SLICETIMER), motion-corrected (MCFLIRT), brain-extracted (BET), registered to MPRAGE BBREGISTERR) and then to the MNI152 atlas (FNIRT), smoothed with a 5 mm FMWH kernel and high-pass filtered (cutoff = 0.008 Hz).
The MDEFT volume dataset with 160 slices and 1-mm slice thickness was standardized to the Talairach stereotactic space (Talairach & Tournoux, 1988).
The standard scan was reconstructed as a volumetric dataset, and a slice was selected every 20 mm starting at the apex of the thorax for the analysis.
Historically, fossil workers visualized slice datasets by constructing physical models (e.g., Sollas 1904; Sollas and Sollas 1914; Jefferies and Lewis 1978).
Just as in optical imaging, where compiling 2D images into a stack creates a 3D dataset; compiling 2D slices into the final printed object creates a 3D part.
Tumor volumes were calculated from multiple MRI slice datasets.
