Quality Assurance of the Whole Slide Image Evaluation in Digital Pathology: State of the Art and Development Results

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.