sub-pixel accuracy was observed for angles ranging between 0-15$^\circ$ or shrinkage of 0-5%. Beyond these conditions, RAPSODI is still able to recover induced rotation and shrinkage, yet with some misalignment as the initial starting conditions are far from the correct solution.

Moreover, the limitations of the registration may be observed when perfect correspondences are lacking between the histopathology and MRI slices ( \[fig:PhantomResults3\]). Not surprising, the landmark and prostate border deviation are as large as $\sim$ 4 pixels (1.6 mm), as these features are not perfectly matching. Yet we can observe the relative stability of the approach for rotations ranging 0-30$^\circ$ and all tested shrinkage factors ranging between 0-30%, as the induced rotation and shrinkage are properly recovered.

[0.24]{}

[0.24]{}

[0.24]{}

[0.24]{}

[0.24]{}

[0.24]{}

Qualitative Results {#qualitative-results .unnumbered}
-------------------

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

[0.31]{}

We applied RAPSODI to register the histopathology slices and T2w MRI in our radical prostatectomy cohorts of 89 patients.  \[fig:ResultsQualitativeC1\] shows the qualitative results for a subject in cohort C1 that had a Dice Coefficient of 0.98 and a Hausdorff distance of 1.75 mm of the prostate border ($\sim$ 4 pixels).  \[fig:ResultsQualitative2\] shows the same slice 