  Augmented Reality (AR) has emerged as a significant advancement in surgical
procedures, offering a solution to the challenges posed by traditional
neuronavigation methods. These conventional techniques often necessitate
surgeons to split their focus between the surgical site and a separate monitor
that displays guiding images. Over the years, many systems have been developed
to register and track the hologram at the targeted locations, each employed its
own evaluation technique. On the other hand, hologram displacement measurement
is not a straightforward task because of various factors such as occlusion,
Vengence-Accomodation Conflict, and unstable holograms in space. In this study,
we explore and classify different techniques for assessing an AR-assisted
neurosurgery system and propose a new technique to systematize the assessment
procedure. Moreover, we conduct a deeper investigation to assess surgeon error
in the pre- and intra-operative phases of the surgery based on the respective
feedback given. We found that although the system can undergo registration and
tracking errors, physical feedback can significantly reduce the error caused by
hologram displacement. However, the lack of visual feedback on the hologram
does not have a significant effect on the user 3D perception.
