One of the key issues in medicine is quality assurance. It is essential to ensure
the quality, consistency and validity of the various diagnostic processes performed.
Today, the reproducibility and quality assurance of the analysis of digitized image
data is an unsolved problem. Our research has focused on the design and development
of functionalities that can be used to greatly increase the verifiability of the evaluation
of digitized medical image data, thereby reducing the number of misdiagnoses. In addition,
our research presents a possible application of eye-tracking to determine the evaluation
status of medical samples. At the beginning of our research, we looked at how eye-tracking
technology is used in medical fields today and investigated the consistency of medical
diagnoses. In our research, we designed and implemented a solution that can determine
the evaluation state of a tomogram-type 3D sample by monitoring physiological and
software parameters while using the software. In addition, our solution described
in this paper is able to capture and reconstruct/replay complete VR diagnoses made
in a 3D environment. This allows the diagnoses made in our system to be shared and
further evaluated. We set up our own equations to quantify the evaluation status of
a given 3D tomogram. At the end of the paper, we summarize our results and compare
them with those of other researchers.
